diff --git a/datahub-web-react/src/app/ingest/source/builder/constants.ts b/datahub-web-react/src/app/ingest/source/builder/constants.ts index 7b7b880069f67..f892f0ed525d2 100644 --- a/datahub-web-react/src/app/ingest/source/builder/constants.ts +++ b/datahub-web-react/src/app/ingest/source/builder/constants.ts @@ -36,6 +36,7 @@ import csvLogo from '../../../../images/csv-logo.png'; import qlikLogo from '../../../../images/qliklogo.png'; import sigmaLogo from '../../../../images/sigmalogo.png'; import sacLogo from '../../../../images/saclogo.svg'; +import cassandraLogo from '../../../../images/cassandralogo.png'; import datahubLogo from '../../../../images/datahublogo.png'; export const ATHENA = 'athena'; @@ -129,6 +130,8 @@ export const SIGMA = 'sigma'; export const SIGMA_URN = `urn:li:dataPlatform:${SIGMA}`; export const SAC = 'sac'; export const SAC_URN = `urn:li:dataPlatform:${SAC}`; +export const CASSANDRA = 'cassandra'; +export const CASSANDRA_URN = `urn:li:dataPlatform:${CASSANDRA}`; export const DATAHUB = 'datahub'; export const DATAHUB_GC = 'datahub-gc'; export const DATAHUB_LINEAGE_FILE = 'datahub-lineage-file'; @@ -175,6 +178,7 @@ export const PLATFORM_URN_TO_LOGO = { [QLIK_SENSE_URN]: qlikLogo, [SIGMA_URN]: sigmaLogo, [SAC_URN]: sacLogo, + [CASSANDRA_URN]: cassandraLogo, [DATAHUB_URN]: datahubLogo, }; diff --git a/datahub-web-react/src/app/ingest/source/builder/sources.json b/datahub-web-react/src/app/ingest/source/builder/sources.json index 9f54fe23631bc..c20869a1c849c 100644 --- a/datahub-web-react/src/app/ingest/source/builder/sources.json +++ b/datahub-web-react/src/app/ingest/source/builder/sources.json @@ -310,5 +310,12 @@ "description": "Import Spaces, Sources, Tables and statistics from Dremio.", "docsUrl": "https://datahubproject.io/docs/metadata-ingestion/", "recipe": "source:\n type: dremio\n config:\n # Coordinates\n hostname: null\n port: null\n #true if https, otherwise false\n tls: true\n\n #For cloud instance\n #is_dremio_cloud: True\n #dremio_cloud_project_id: \n\n #Credentials with personal access token\n authentication_method: PAT\n password: pass\n\n #Or Credentials with basic auth\n #authentication_method: password\n #username: null\n #password: null\n\n stateful_ingestion:\n enabled: true" + }, + { + "urn": "urn:li:dataPlatform:cassandra", + "name": "cassandra", + "displayName": "CassandraDB", + "docsUrl": "https://datahubproject.io/docs/generated/ingestion/sources/cassandra", + "recipe": "source:\n type: cassandra\n config:\n # Credentials for on prem cassandra\n contact_point: localhost\n port: 9042\n username: admin\n password: password\n\n # Or\n # Credentials Astra Cloud\n #cloud_config:\n # secure_connect_bundle: Path to Secure Connect Bundle (.zip)\n # token: Application Token\n\n # Optional Allow / Deny extraction of particular keyspaces.\n keyspace_pattern:\n allow: [.*]\n\n # Optional Allow / Deny extraction of particular tables.\n table_pattern:\n allow: [.*]" } ] diff --git a/datahub-web-react/src/images/cassandralogo.png b/datahub-web-react/src/images/cassandralogo.png new file mode 100644 index 0000000000000..e497dbb6ee76b Binary files /dev/null and b/datahub-web-react/src/images/cassandralogo.png differ diff --git a/metadata-ingestion/docs/sources/cassandra/cassandra_pre.md b/metadata-ingestion/docs/sources/cassandra/cassandra_pre.md new file mode 100644 index 0000000000000..095f4521d09ff --- /dev/null +++ b/metadata-ingestion/docs/sources/cassandra/cassandra_pre.md @@ -0,0 +1,40 @@ +### Setup + +This integration pulls metadata directly from Cassandra databases, including both **DataStax Astra DB** and **Cassandra Enterprise Edition (EE)**. + +You’ll need to have a Cassandra instance or an Astra DB setup with appropriate access permissions. + +#### Steps to Get the Required Information + +1. **Set Up User Credentials**: + + - **For Astra DB**: + - Log in to your Astra DB Console. + - Navigate to **Organization Settings** > **Token Management**. + - Generate an **Application Token** with the required permissions for read access. + - Download the **Secure Connect Bundle** from the Astra DB Console. + - **For Cassandra EE**: + - Ensure you have a **username** and **password** with read access to the necessary keyspaces. + +2. **Permissions**: + + - The user or token must have `SELECT` permissions that allow it to: + - Access metadata in system keyspaces (e.g., `system_schema`) to retrieve information about keyspaces, tables, columns, and views. + - Perform `SELECT` operations on the data tables if data profiling is enabled. + +3. **Verify Database Access**: + - For Astra DB: Ensure the **Secure Connect Bundle** is used and configured correctly. + - For Cassandra Opensource: Ensure the **contact point** and **port** are accessible. + + +:::caution + +When enabling profiling, make sure to set a limit on the number of rows to sample. Profiling large tables without a limit may lead to excessive resource consumption and slow performance. + +::: + +:::note + +For cloud configuration with Astra DB, it is necessary to specify the Secure Connect Bundle path in the configuration. For that reason, use the CLI to ingest metadata into DataHub. + +::: diff --git a/metadata-ingestion/docs/sources/cassandra/cassandra_recipe.yml b/metadata-ingestion/docs/sources/cassandra/cassandra_recipe.yml new file mode 100644 index 0000000000000..78cec5ef4f31c --- /dev/null +++ b/metadata-ingestion/docs/sources/cassandra/cassandra_recipe.yml @@ -0,0 +1,30 @@ +source: + type: "cassandra" + config: + # Credentials for on prem cassandra + contact_point: "localhost" + port: 9042 + username: "admin" + password: "password" + + # Or + # Credentials Astra Cloud + #cloud_config: + # secure_connect_bundle: "Path to Secure Connect Bundle (.zip)" + # token: "Application Token" + + # Optional Allow / Deny extraction of particular keyspaces. + keyspace_pattern: + allow: [".*"] + + # Optional Allow / Deny extraction of particular tables. + table_pattern: + allow: [".*"] + + # Optional + profiling: + enabled: true + profile_table_level_only: true + +sink: + # config sinks diff --git a/metadata-ingestion/docs/transformer/intro.md b/metadata-ingestion/docs/transformer/intro.md index 0a766f7fd747d..85ba42fca4674 100644 --- a/metadata-ingestion/docs/transformer/intro.md +++ b/metadata-ingestion/docs/transformer/intro.md @@ -26,6 +26,8 @@ DataHub provided transformers for dataset are: - [Simple Add Dataset ownership](./dataset_transformer.md#simple-add-dataset-ownership) - [Pattern Add Dataset ownership](./dataset_transformer.md#pattern-add-dataset-ownership) - [Simple Remove Dataset ownership](./dataset_transformer.md#simple-remove-dataset-ownership) +- [Extract Ownership from Tags](./dataset_transformer.md#extract-ownership-from-tags) +- [Clean suffix prefix from Ownership](./dataset_transformer.md#clean-suffix-prefix-from-ownership) - [Mark Dataset Status](./dataset_transformer.md#mark-dataset-status) - [Simple Add Dataset globalTags](./dataset_transformer.md#simple-add-dataset-globaltags) - [Pattern Add Dataset globalTags](./dataset_transformer.md#pattern-add-dataset-globaltags) @@ -33,9 +35,14 @@ DataHub provided transformers for dataset are: - [Set Dataset browsePath](./dataset_transformer.md#set-dataset-browsepath) - [Simple Add Dataset glossaryTerms](./dataset_transformer.md#simple-add-dataset-glossaryterms) - [Pattern Add Dataset glossaryTerms](./dataset_transformer.md#pattern-add-dataset-glossaryterms) +- [Add Dataset globalTags](./dataset_transformer.md#add-dataset-globaltags) - [Pattern Add Dataset Schema Field glossaryTerms](./dataset_transformer.md#pattern-add-dataset-schema-field-glossaryterms) - [Pattern Add Dataset Schema Field globalTags](./dataset_transformer.md#pattern-add-dataset-schema-field-globaltags) - [Simple Add Dataset datasetProperties](./dataset_transformer.md#simple-add-dataset-datasetproperties) - [Add Dataset datasetProperties](./dataset_transformer.md#add-dataset-datasetproperties) - [Simple Add Dataset domains](./dataset_transformer.md#simple-add-dataset-domains) - [Pattern Add Dataset domains](./dataset_transformer.md#pattern-add-dataset-domains) +- [Domain Mapping Based on Tags](./dataset_transformer.md#domain-mapping-based-on-tags) +- [Simple Add Dataset dataProduct ](./dataset_transformer.md#simple-add-dataset-dataproduct) +- [Pattern Add Dataset dataProduct](./dataset_transformer.md#pattern-add-dataset-dataproduct) +- [Add Dataset dataProduct](./dataset_transformer.md#add-dataset-dataproduct) diff --git a/metadata-ingestion/setup.py b/metadata-ingestion/setup.py index 2014d8ca4e4dd..3152d0290ec22 100644 --- a/metadata-ingestion/setup.py +++ b/metadata-ingestion/setup.py @@ -404,6 +404,13 @@ # https://www.elastic.co/guide/en/elasticsearch/client/python-api/current/release-notes.html#rn-7-14-0 # https://github.com/elastic/elasticsearch-py/issues/1639#issuecomment-883587433 "elasticsearch": {"elasticsearch==7.13.4"}, + "cassandra": { + "cassandra-driver>=3.28.0", + # We were seeing an error like this `numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject` + # with numpy 2.0. This likely indicates a mismatch between scikit-learn and numpy versions. + # https://stackoverflow.com/questions/40845304/runtimewarning-numpy-dtype-size-changed-may-indicate-binary-incompatibility + "numpy<2", + }, "feast": { "feast>=0.34.0,<1", "flask-openid>=1.3.0", @@ -660,6 +667,7 @@ "qlik-sense", "sigma", "sac", + "cassandra", ] if plugin for dependency in plugins[plugin] @@ -778,6 +786,7 @@ "qlik-sense = datahub.ingestion.source.qlik_sense.qlik_sense:QlikSenseSource", "sigma = datahub.ingestion.source.sigma.sigma:SigmaSource", "sac = datahub.ingestion.source.sac.sac:SACSource", + "cassandra = datahub.ingestion.source.cassandra.cassandra:CassandraSource", ], "datahub.ingestion.transformer.plugins": [ "pattern_cleanup_ownership = datahub.ingestion.transformer.pattern_cleanup_ownership:PatternCleanUpOwnership", diff --git a/metadata-ingestion/src/datahub/ingestion/source/cassandra/__init__.py b/metadata-ingestion/src/datahub/ingestion/source/cassandra/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra.py b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra.py new file mode 100644 index 0000000000000..6a5236563f48d --- /dev/null +++ b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra.py @@ -0,0 +1,476 @@ +import dataclasses +import json +import logging +from typing import Any, Dict, Iterable, List, Optional + +from datahub.emitter.mce_builder import ( + make_data_platform_urn, + make_dataplatform_instance_urn, + make_dataset_urn_with_platform_instance, + make_schema_field_urn, +) +from datahub.emitter.mcp import MetadataChangeProposalWrapper +from datahub.emitter.mcp_builder import ( + ContainerKey, + add_dataset_to_container, + gen_containers, +) +from datahub.ingestion.api.common import PipelineContext +from datahub.ingestion.api.decorators import ( + SourceCapability, + SupportStatus, + capability, + config_class, + platform_name, + support_status, +) +from datahub.ingestion.api.source import MetadataWorkUnitProcessor +from datahub.ingestion.api.workunit import MetadataWorkUnit +from datahub.ingestion.source.cassandra.cassandra_api import ( + CassandraAPI, + CassandraColumn, + CassandraEntities, + CassandraKeyspace, + CassandraTable, + CassandraView, +) +from datahub.ingestion.source.cassandra.cassandra_config import CassandraSourceConfig +from datahub.ingestion.source.cassandra.cassandra_profiling import CassandraProfiler +from datahub.ingestion.source.cassandra.cassandra_utils import ( + SYSTEM_KEYSPACE_LIST, + CassandraSourceReport, + CassandraToSchemaFieldConverter, +) +from datahub.ingestion.source.common.subtypes import ( + DatasetContainerSubTypes, + DatasetSubTypes, +) +from datahub.ingestion.source.state.stale_entity_removal_handler import ( + StaleEntityRemovalHandler, +) +from datahub.ingestion.source.state.stateful_ingestion_base import ( + StatefulIngestionSourceBase, +) +from datahub.metadata.com.linkedin.pegasus2avro.common import StatusClass +from datahub.metadata.com.linkedin.pegasus2avro.schema import ( + SchemaField, + SchemaMetadata, +) +from datahub.metadata.schema_classes import ( + DataPlatformInstanceClass, + DatasetLineageTypeClass, + DatasetPropertiesClass, + FineGrainedLineageClass, + FineGrainedLineageDownstreamTypeClass, + FineGrainedLineageUpstreamTypeClass, + OtherSchemaClass, + SubTypesClass, + UpstreamClass, + UpstreamLineageClass, + ViewPropertiesClass, +) + +logger = logging.getLogger(__name__) + +PLATFORM_NAME_IN_DATAHUB = "cassandra" + + +class KeyspaceKey(ContainerKey): + keyspace: str + + +@platform_name("Cassandra") +@config_class(CassandraSourceConfig) +@support_status(SupportStatus.INCUBATING) +@capability(SourceCapability.CONTAINERS, "Enabled by default") +@capability(SourceCapability.SCHEMA_METADATA, "Enabled by default") +@capability(SourceCapability.PLATFORM_INSTANCE, "Enabled by default") +@capability( + SourceCapability.DELETION_DETECTION, + "Optionally enabled via `stateful_ingestion.remove_stale_metadata`", + supported=True, +) +class CassandraSource(StatefulIngestionSourceBase): + + """ + This plugin extracts the following: + + - Metadata for tables + - Column types associated with each table column + - The keyspace each table belongs to + """ + + config: CassandraSourceConfig + report: CassandraSourceReport + platform: str + + def __init__(self, ctx: PipelineContext, config: CassandraSourceConfig): + super().__init__(config, ctx) + self.ctx = ctx + self.platform = PLATFORM_NAME_IN_DATAHUB + self.config = config + self.report = CassandraSourceReport() + self.cassandra_api = CassandraAPI(config, self.report) + self.cassandra_data = CassandraEntities() + # For profiling + self.profiler = CassandraProfiler(config, self.report, self.cassandra_api) + + @classmethod + def create(cls, config_dict, ctx): + config = CassandraSourceConfig.parse_obj(config_dict) + return cls(ctx, config) + + def get_platform(self) -> str: + return PLATFORM_NAME_IN_DATAHUB + + def get_workunit_processors(self) -> List[Optional[MetadataWorkUnitProcessor]]: + return [ + *super().get_workunit_processors(), + StaleEntityRemovalHandler.create( + self, self.config, self.ctx + ).workunit_processor, + ] + + def get_workunits_internal( + self, + ) -> Iterable[MetadataWorkUnit]: + if not self.cassandra_api.authenticate(): + return + keyspaces: List[CassandraKeyspace] = self.cassandra_api.get_keyspaces() + for keyspace in keyspaces: + keyspace_name: str = keyspace.keyspace_name + if keyspace_name in SYSTEM_KEYSPACE_LIST: + continue + + if not self.config.keyspace_pattern.allowed(keyspace_name): + self.report.report_dropped(keyspace_name) + continue + + yield from self._generate_keyspace_container(keyspace) + + try: + yield from self._extract_tables_from_keyspace(keyspace_name) + except Exception as e: + self.report.num_tables_failed += 1 + self.report.failure( + message="Failed to extract table metadata for keyspace", + context=keyspace_name, + exc=e, + ) + try: + yield from self._extract_views_from_keyspace(keyspace_name) + except Exception as e: + self.report.num_views_failed += 1 + self.report.failure( + message="Failed to extract view metadata for keyspace ", + context=keyspace_name, + exc=e, + ) + + # Profiling + if self.config.is_profiling_enabled(): + yield from self.profiler.get_workunits(self.cassandra_data) + + def _generate_keyspace_container( + self, keyspace: CassandraKeyspace + ) -> Iterable[MetadataWorkUnit]: + keyspace_container_key = self._generate_keyspace_container_key( + keyspace.keyspace_name + ) + yield from gen_containers( + container_key=keyspace_container_key, + name=keyspace.keyspace_name, + qualified_name=keyspace.keyspace_name, + extra_properties={ + "durable_writes": str(keyspace.durable_writes), + "replication": json.dumps(keyspace.replication), + }, + sub_types=[DatasetContainerSubTypes.KEYSPACE], + ) + + def _generate_keyspace_container_key(self, keyspace_name: str) -> ContainerKey: + return KeyspaceKey( + keyspace=keyspace_name, + platform=self.platform, + instance=self.config.platform_instance, + env=self.config.env, + ) + + # get all tables for a given keyspace, iterate over them to extract column metadata + def _extract_tables_from_keyspace( + self, keyspace_name: str + ) -> Iterable[MetadataWorkUnit]: + self.cassandra_data.keyspaces.append(keyspace_name) + tables: List[CassandraTable] = self.cassandra_api.get_tables(keyspace_name) + for table in tables: + # define the dataset urn for this table to be used downstream + table_name: str = table.table_name + dataset_name: str = f"{keyspace_name}.{table_name}" + + if not self.config.table_pattern.allowed(dataset_name): + self.report.report_dropped(dataset_name) + continue + + self.cassandra_data.tables.setdefault(keyspace_name, []).append(table_name) + self.report.report_entity_scanned(dataset_name, ent_type="Table") + + dataset_urn = make_dataset_urn_with_platform_instance( + platform=self.platform, + name=dataset_name, + env=self.config.env, + platform_instance=self.config.platform_instance, + ) + + # 1. Extract columns from table, then construct and emit the schemaMetadata aspect. + try: + yield from self._extract_columns_from_table( + keyspace_name, table_name, dataset_urn + ) + except Exception as e: + self.report.failure( + message="Failed to extract columns from table", + context=table_name, + exc=e, + ) + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=StatusClass(removed=False), + ).as_workunit() + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=SubTypesClass( + typeNames=[ + DatasetSubTypes.TABLE, + ] + ), + ).as_workunit() + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=DatasetPropertiesClass( + name=table_name, + qualifiedName=f"{keyspace_name}.{table_name}", + description=table.comment, + customProperties={ + "bloom_filter_fp_chance": str(table.bloom_filter_fp_chance), + "caching": json.dumps(table.caching), + "compaction": json.dumps(table.compaction), + "compression": json.dumps(table.compression), + "crc_check_chance": str(table.crc_check_chance), + "dclocal_read_repair_chance": str( + table.dclocal_read_repair_chance + ), + "default_time_to_live": str(table.default_time_to_live), + "extensions": json.dumps(table.extensions), + "gc_grace_seconds": str(table.gc_grace_seconds), + "max_index_interval": str(table.max_index_interval), + "min_index_interval": str(table.min_index_interval), + "memtable_flush_period_in_ms": str( + table.memtable_flush_period_in_ms + ), + "read_repair_chance": str(table.read_repair_chance), + "speculative_retry": str(table.speculative_retry), + }, + ), + ).as_workunit() + + yield from add_dataset_to_container( + container_key=self._generate_keyspace_container_key(keyspace_name), + dataset_urn=dataset_urn, + ) + + if self.config.platform_instance: + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=DataPlatformInstanceClass( + platform=make_data_platform_urn(self.platform), + instance=make_dataplatform_instance_urn( + self.platform, self.config.platform_instance + ), + ), + ).as_workunit() + + # get all columns for a given table, iterate over them to extract column metadata + def _extract_columns_from_table( + self, keyspace_name: str, table_name: str, dataset_urn: str + ) -> Iterable[MetadataWorkUnit]: + column_infos: List[CassandraColumn] = self.cassandra_api.get_columns( + keyspace_name, table_name + ) + schema_fields: List[SchemaField] = list( + CassandraToSchemaFieldConverter.get_schema_fields(column_infos) + ) + if not schema_fields: + self.report.report_warning( + message="Table has no columns, skipping", context=table_name + ) + return + + jsonable_column_infos: List[Dict[str, Any]] = [] + for column in column_infos: + self.cassandra_data.columns.setdefault(table_name, []).append(column) + jsonable_column_infos.append(dataclasses.asdict(column)) + + schema_metadata: SchemaMetadata = SchemaMetadata( + schemaName=table_name, + platform=make_data_platform_urn(self.platform), + version=0, + hash="", + platformSchema=OtherSchemaClass( + rawSchema=json.dumps(jsonable_column_infos) + ), + fields=schema_fields, + ) + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=schema_metadata, + ).as_workunit() + + def _extract_views_from_keyspace( + self, keyspace_name: str + ) -> Iterable[MetadataWorkUnit]: + + views: List[CassandraView] = self.cassandra_api.get_views(keyspace_name) + for view in views: + view_name: str = view.view_name + dataset_name: str = f"{keyspace_name}.{view_name}" + self.report.report_entity_scanned(dataset_name) + dataset_urn: str = make_dataset_urn_with_platform_instance( + platform=self.platform, + name=dataset_name, + env=self.config.env, + platform_instance=self.config.platform_instance, + ) + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=StatusClass(removed=False), + ).as_workunit() + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=SubTypesClass( + typeNames=[ + DatasetSubTypes.VIEW, + ] + ), + ).as_workunit() + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=ViewPropertiesClass( + materialized=True, + viewLogic=view.where_clause, # Use the WHERE clause as view logic + viewLanguage="CQL", # Use "CQL" as the language + ), + ).as_workunit() + + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=DatasetPropertiesClass( + name=view_name, + qualifiedName=f"{keyspace_name}.{view_name}", + description=view.comment, + customProperties={ + "bloom_filter_fp_chance": str(view.bloom_filter_fp_chance), + "caching": json.dumps(view.caching), + "compaction": json.dumps(view.compaction), + "compression": json.dumps(view.compression), + "crc_check_chance": str(view.crc_check_chance), + "include_all_columns": str(view.include_all_columns), + "dclocal_read_repair_chance": str( + view.dclocal_read_repair_chance + ), + "default_time_to_live": str(view.default_time_to_live), + "extensions": json.dumps(view.extensions), + "gc_grace_seconds": str(view.gc_grace_seconds), + "max_index_interval": str(view.max_index_interval), + "min_index_interval": str(view.min_index_interval), + "memtable_flush_period_in_ms": str( + view.memtable_flush_period_in_ms + ), + "read_repair_chance": str(view.read_repair_chance), + "speculative_retry": str(view.speculative_retry), + }, + ), + ).as_workunit() + + try: + yield from self._extract_columns_from_table( + keyspace_name, view_name, dataset_urn + ) + except Exception as e: + self.report.failure( + message="Failed to extract columns from views", + context=view_name, + exc=e, + ) + + # Construct and emit lineage off of 'base_table_name' + # NOTE: we don't need to use 'base_table_id' since table is always in same keyspace, see https://docs.datastax.com/en/cql-oss/3.3/cql/cql_reference/cqlCreateMaterializedView.html#cqlCreateMaterializedView__keyspace-name + upstream_urn: str = make_dataset_urn_with_platform_instance( + platform=self.platform, + name=f"{keyspace_name}.{view.table_name}", + env=self.config.env, + platform_instance=self.config.platform_instance, + ) + fineGrainedLineages = self.get_upstream_fields_of_field_in_datasource( + view_name, dataset_urn, upstream_urn + ) + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=UpstreamLineageClass( + upstreams=[ + UpstreamClass( + dataset=upstream_urn, + type=DatasetLineageTypeClass.VIEW, + ) + ], + fineGrainedLineages=fineGrainedLineages, + ), + ).as_workunit() + + yield from add_dataset_to_container( + container_key=self._generate_keyspace_container_key(keyspace_name), + dataset_urn=dataset_urn, + ) + + if self.config.platform_instance: + yield MetadataChangeProposalWrapper( + entityUrn=dataset_urn, + aspect=DataPlatformInstanceClass( + platform=make_data_platform_urn(self.platform), + instance=make_dataplatform_instance_urn( + self.platform, self.config.platform_instance + ), + ), + ).as_workunit() + + def get_upstream_fields_of_field_in_datasource( + self, table_name: str, dataset_urn: str, upstream_urn: str + ) -> List[FineGrainedLineageClass]: + column_infos = self.cassandra_data.columns.get(table_name, []) + # Collect column-level lineage + fine_grained_lineages = [] + for column_info in column_infos: + source_column = column_info.column_name + if source_column: + fine_grained_lineages.append( + FineGrainedLineageClass( + upstreamType=FineGrainedLineageUpstreamTypeClass.FIELD_SET, + downstreamType=FineGrainedLineageDownstreamTypeClass.FIELD, + downstreams=[make_schema_field_urn(dataset_urn, source_column)], + upstreams=[make_schema_field_urn(upstream_urn, source_column)], + ) + ) + return fine_grained_lineages + + def get_report(self): + return self.report + + def close(self): + self.cassandra_api.close() + super().close() diff --git a/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_api.py b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_api.py new file mode 100644 index 0000000000000..4cf0613762aab --- /dev/null +++ b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_api.py @@ -0,0 +1,325 @@ +from dataclasses import dataclass, field +from typing import Any, Dict, List, Optional + +from cassandra import DriverException, OperationTimedOut +from cassandra.auth import PlainTextAuthProvider +from cassandra.cluster import ( + EXEC_PROFILE_DEFAULT, + Cluster, + ExecutionProfile, + ProtocolVersion, + Session, +) + +from datahub.ingestion.api.source import SourceReport +from datahub.ingestion.source.cassandra.cassandra_config import CassandraSourceConfig + + +@dataclass +class CassandraKeyspace: + keyspace_name: str + durable_writes: bool + replication: Dict + + +@dataclass +class CassandraTable: + keyspace_name: str + table_name: str + bloom_filter_fp_chance: Optional[float] + caching: Optional[Dict[str, str]] + comment: Optional[str] + compaction: Optional[Dict[str, Any]] + compression: Optional[Dict[str, Any]] + crc_check_chance: Optional[float] + dclocal_read_repair_chance: Optional[float] + default_time_to_live: Optional[int] + extensions: Optional[Dict[str, Any]] + gc_grace_seconds: Optional[int] + max_index_interval: Optional[int] + memtable_flush_period_in_ms: Optional[int] + min_index_interval: Optional[int] + read_repair_chance: Optional[float] + speculative_retry: Optional[str] + + +@dataclass +class CassandraColumn: + keyspace_name: str + table_name: str + column_name: str + type: str + clustering_order: Optional[str] + kind: Optional[str] + position: Optional[int] + + +@dataclass +class CassandraView(CassandraTable): + view_name: str + include_all_columns: Optional[bool] + where_clause: str = "" + + +@dataclass +class CassandraEntities: + keyspaces: List[str] = field(default_factory=list) + tables: Dict[str, List[str]] = field( + default_factory=dict + ) # Maps keyspace -> tables + columns: Dict[str, List[CassandraColumn]] = field( + default_factory=dict + ) # Maps tables -> columns + + +# - Referencing system_schema: https://docs.datastax.com/en/cql-oss/3.x/cql/cql_using/useQuerySystem.html#Table3.ColumnsinSystem_SchemaTables-Cassandra3.0 - # +# this keyspace contains details about the cassandra cluster's keyspaces, tables, and columns + + +class CassandraQueries: + # get all keyspaces + GET_KEYSPACES_QUERY = "SELECT * FROM system_schema.keyspaces" + # get all tables for a keyspace + GET_TABLES_QUERY = "SELECT * FROM system_schema.tables WHERE keyspace_name = %s" + # get all columns for a table + GET_COLUMNS_QUERY = "SELECT * FROM system_schema.columns WHERE keyspace_name = %s AND table_name = %s" + # get all views for a keyspace + GET_VIEWS_QUERY = "SELECT * FROM system_schema.views WHERE keyspace_name = %s" + # Row Count + ROW_COUNT = 'SELECT COUNT(*) AS row_count FROM {}."{}"' + # Column Count + COLUMN_COUNT = "SELECT COUNT(*) AS column_count FROM system_schema.columns WHERE keyspace_name = '{}' AND table_name = '{}'" + + +class CassandraAPI: + def __init__(self, config: CassandraSourceConfig, report: SourceReport): + self.config = config + self.report = report + self._cassandra_session: Optional[Session] = None + + def authenticate(self) -> bool: + """Establish a connection to Cassandra and return the session.""" + try: + if self.config.cloud_config: + cloud_config = self.config.cloud_config + cluster_cloud_config = { + "connect_timeout": cloud_config.connect_timeout, + "use_default_tempdir": True, + "secure_connect_bundle": cloud_config.secure_connect_bundle, + } + profile = ExecutionProfile(request_timeout=cloud_config.request_timeout) + auth_provider = PlainTextAuthProvider( + "token", + cloud_config.token, + ) + cluster = Cluster( + cloud=cluster_cloud_config, + auth_provider=auth_provider, + execution_profiles={EXEC_PROFILE_DEFAULT: profile}, + protocol_version=ProtocolVersion.V4, + ) + + self._cassandra_session = cluster.connect() + return True + if self.config.username and self.config.password: + auth_provider = PlainTextAuthProvider( + username=self.config.username, password=self.config.password + ) + cluster = Cluster( + [self.config.contact_point], + port=self.config.port, + auth_provider=auth_provider, + load_balancing_policy=None, + ) + else: + cluster = Cluster( + [self.config.contact_point], + port=self.config.port, + load_balancing_policy=None, + ) + + self._cassandra_session = cluster.connect() + return True + except OperationTimedOut as e: + self.report.failure( + message="Failed to Authenticate", context=f"{str(e.errors)}", exc=e + ) + return False + except DriverException as e: + self.report.failure(message="Failed to Authenticate", exc=e) + return False + except Exception as e: + self.report.failure(message="Failed to authenticate to Cassandra", exc=e) + return False + + def get(self, query: str, parameters: Optional[List] = []) -> List: + if not self._cassandra_session: + return [] + + resp = self._cassandra_session.execute(query, parameters) + return resp + + def get_keyspaces(self) -> List[CassandraKeyspace]: + """Fetch all keyspaces.""" + try: + keyspaces = self.get(CassandraQueries.GET_KEYSPACES_QUERY) + keyspace_list = [ + CassandraKeyspace( + keyspace_name=row.keyspace_name, + durable_writes=row.durable_writes, + replication=dict(row.replication), + ) + for row in keyspaces + ] + return keyspace_list + except DriverException as e: + self.report.warning( + message="Failed to fetch keyspaces", context=f"{str(e)}", exc=e + ) + return [] + except Exception as e: + self.report.warning(message="Failed to fetch keyspaces", exc=e) + return [] + + def get_tables(self, keyspace_name: str) -> List[CassandraTable]: + """Fetch all tables for a given keyspace.""" + try: + tables = self.get(CassandraQueries.GET_TABLES_QUERY, [keyspace_name]) + table_list = [ + CassandraTable( + keyspace_name=row.keyspace_name, + table_name=row.table_name, + bloom_filter_fp_chance=row.bloom_filter_fp_chance, + caching=dict(row.caching), + comment=row.comment, + compaction=dict(row.compaction), + compression=dict(row.compression), + crc_check_chance=row.crc_check_chance, + dclocal_read_repair_chance=row.dclocal_read_repair_chance, + default_time_to_live=row.default_time_to_live, + extensions=dict(row.extensions), + gc_grace_seconds=row.gc_grace_seconds, + max_index_interval=row.max_index_interval, + memtable_flush_period_in_ms=row.memtable_flush_period_in_ms, + min_index_interval=row.min_index_interval, + read_repair_chance=row.read_repair_chance, + speculative_retry=row.speculative_retry, + ) + for row in tables + ] + return table_list + except DriverException as e: + self.report.warning( + message="Failed to fetch tables for keyspace", + context=f"{str(e)}", + exc=e, + ) + return [] + except Exception as e: + self.report.warning( + message="Failed to fetch tables for keyspace", + context=f"{keyspace_name}", + exc=e, + ) + return [] + + def get_columns(self, keyspace_name: str, table_name: str) -> List[CassandraColumn]: + """Fetch all columns for a given table.""" + try: + column_infos = self.get( + CassandraQueries.GET_COLUMNS_QUERY, [keyspace_name, table_name] + ) + column_list = [ + CassandraColumn( + keyspace_name=row.keyspace_name, + table_name=row.table_name, + column_name=row.column_name, + clustering_order=row.clustering_order, + kind=row.kind, + position=row.position, + type=row.type, + ) + for row in column_infos + ] + return column_list + except DriverException as e: + self.report.warning( + message="Failed to fetch columns for table", context=f"{str(e)}", exc=e + ) + return [] + except Exception as e: + self.report.warning( + message="Failed to fetch columns for table", + context=f"{keyspace_name}.{table_name}", + exc=e, + ) + return [] + + def get_views(self, keyspace_name: str) -> List[CassandraView]: + """Fetch all views for a given keyspace.""" + try: + views = self.get(CassandraQueries.GET_VIEWS_QUERY, [keyspace_name]) + view_list = [ + CassandraView( + table_name=row.base_table_name, + keyspace_name=row.keyspace_name, + view_name=row.view_name, + bloom_filter_fp_chance=row.bloom_filter_fp_chance, + caching=dict(row.caching), + comment=row.comment, + compaction=dict(row.compaction), + compression=dict(row.compression), + crc_check_chance=row.crc_check_chance, + dclocal_read_repair_chance=row.dclocal_read_repair_chance, + default_time_to_live=row.default_time_to_live, + extensions=dict(row.extensions), + gc_grace_seconds=row.gc_grace_seconds, + include_all_columns=row.include_all_columns, + max_index_interval=row.max_index_interval, + memtable_flush_period_in_ms=row.memtable_flush_period_in_ms, + min_index_interval=row.min_index_interval, + read_repair_chance=row.read_repair_chance, + speculative_retry=row.speculative_retry, + where_clause=row.where_clause, + ) + for row in views + ] + return view_list + except DriverException as e: + self.report.warning( + message="Failed to fetch views for keyspace", context=f"{str(e)}", exc=e + ) + return [] + except Exception as e: + self.report.warning( + message="Failed to fetch views for keyspace", + context=f"{keyspace_name}", + exc=e, + ) + return [] + + def execute(self, query: str, limit: Optional[int] = None) -> List: + """Fetch stats for cassandra""" + try: + if not self._cassandra_session: + return [] + if limit: + query = query + f" LIMIT {limit}" + result_set = self._cassandra_session.execute(query).all() + return result_set + except DriverException as e: + self.report.warning( + message="Failed to fetch stats for keyspace", context=str(e), exc=e + ) + return [] + except Exception: + self.report.warning( + message="Failed to fetch stats for keyspace", + context=f"{query}", + ) + return [] + + def close(self): + """Close the Cassandra session.""" + if self._cassandra_session: + self._cassandra_session.shutdown() diff --git a/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_config.py b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_config.py new file mode 100644 index 0000000000000..340bdb68aa458 --- /dev/null +++ b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_config.py @@ -0,0 +1,111 @@ +from typing import Optional + +from pydantic import Field + +from datahub.configuration.common import AllowDenyPattern, ConfigModel +from datahub.configuration.source_common import ( + EnvConfigMixin, + PlatformInstanceConfigMixin, +) +from datahub.ingestion.source.ge_profiling_config import GEProfilingBaseConfig +from datahub.ingestion.source.state.stale_entity_removal_handler import ( + StatefulStaleMetadataRemovalConfig, +) +from datahub.ingestion.source.state.stateful_ingestion_base import ( + StatefulIngestionConfigBase, +) +from datahub.ingestion.source_config.operation_config import is_profiling_enabled + +# - Referencing https://docs.datastax.com/en/cql-oss/3.x/cql/cql_using/useQuerySystem.html#Table3.ColumnsinSystem_SchemaTables-Cassandra3.0 - # +# this keyspace contains details about the cassandra cluster's keyspaces, tables, and columns +SYSTEM_SCHEMA_KEYSPACE_NAME = "system_schema" + +# Reference: +# https://docs.datastax.com/en/astra-db-serverless/databases/python-driver.html +# https://docs.datastax.com/en/astra-db-serverless/databases/python-driver.html#production-configuration + + +class CassandraCloudConfig(ConfigModel): + """ + Configuration for connecting to DataStax Astra DB in the cloud. + """ + + token: str = Field( + description="The Astra DB application token used for authentication.", + ) + + secure_connect_bundle: str = Field( + description="File path to the Secure Connect Bundle (.zip) used for a secure connection to DataStax Astra DB.", + ) + + connect_timeout: int = Field( + default=600, + description="Timeout in seconds for establishing new connections to Cassandra.", + ) + + request_timeout: int = Field( + default=600, description="Timeout in seconds for individual Cassandra requests." + ) + + +class CassandraSourceConfig( + PlatformInstanceConfigMixin, StatefulIngestionConfigBase, EnvConfigMixin +): + """ + Configuration for connecting to a Cassandra or DataStax Astra DB source. + """ + + contact_point: str = Field( + default="localhost", + description="Domain or IP address of the Cassandra instance (excluding port).", + ) + + port: int = Field( + default=9042, description="Port number to connect to the Cassandra instance." + ) + + username: Optional[str] = Field( + default=None, + description=f"Username credential with read access to the {SYSTEM_SCHEMA_KEYSPACE_NAME} keyspace.", + ) + + password: Optional[str] = Field( + default=None, + description="Password credential associated with the specified username.", + ) + + cloud_config: Optional[CassandraCloudConfig] = Field( + default=None, + description="Configuration for cloud-based Cassandra, such as DataStax Astra DB.", + ) + + keyspace_pattern: AllowDenyPattern = Field( + default=AllowDenyPattern.allow_all(), + description="Regex patterns to filter keyspaces for ingestion.", + ) + + table_pattern: AllowDenyPattern = Field( + default=AllowDenyPattern.allow_all(), + description="Regex patterns to filter keyspaces.tables for ingestion.", + ) + + stateful_ingestion: Optional[StatefulStaleMetadataRemovalConfig] = Field( + default=None, + description="Configuration for stateful ingestion and stale metadata removal.", + ) + + # Profiling + profile_pattern: AllowDenyPattern = Field( + default=AllowDenyPattern.allow_all(), + description="Regex patterns for tables to profile", + ) + + profiling: GEProfilingBaseConfig = Field( + default=GEProfilingBaseConfig(), + description="Configuration for profiling", + ) + + def is_profiling_enabled(self) -> bool: + return self.profiling.enabled and is_profiling_enabled( + self.profiling.operation_config + ) diff --git a/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_profiling.py b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_profiling.py new file mode 100644 index 0000000000000..d8ab62f1d6d91 --- /dev/null +++ b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_profiling.py @@ -0,0 +1,296 @@ +import logging +import time +from concurrent.futures import ThreadPoolExecutor, as_completed +from dataclasses import dataclass, field +from typing import Any, Dict, Iterable, List, Optional + +import numpy as np +from cassandra.util import OrderedMapSerializedKey, SortedSet + +from datahub.emitter.mce_builder import make_dataset_urn_with_platform_instance +from datahub.emitter.mcp import MetadataChangeProposalWrapper +from datahub.ingestion.api.workunit import MetadataWorkUnit +from datahub.ingestion.source.cassandra.cassandra_api import ( + CassandraAPI, + CassandraColumn, + CassandraEntities, + CassandraQueries, +) +from datahub.ingestion.source.cassandra.cassandra_config import CassandraSourceConfig +from datahub.ingestion.source.cassandra.cassandra_utils import CassandraSourceReport +from datahub.ingestion.source_report.ingestion_stage import PROFILING +from datahub.metadata.schema_classes import ( + DatasetFieldProfileClass, + DatasetProfileClass, + QuantileClass, +) + +logger = logging.getLogger(__name__) + + +@dataclass +class ColumnMetric: + col_type: str = "" + values: List[Any] = field(default_factory=list) + null_count: int = 0 + total_count: int = 0 + distinct_count: Optional[int] = None + min: Optional[Any] = None + max: Optional[Any] = None + mean: Optional[float] = None + stdev: Optional[float] = None + median: Optional[float] = None + quantiles: Optional[List[float]] = None + sample_values: Optional[Any] = None + + +@dataclass +class ProfileData: + row_count: Optional[int] = None + column_count: Optional[int] = None + column_metrics: Dict[str, ColumnMetric] = field(default_factory=dict) + + +class CassandraProfiler: + config: CassandraSourceConfig + report: CassandraSourceReport + + def __init__( + self, + config: CassandraSourceConfig, + report: CassandraSourceReport, + api: CassandraAPI, + ) -> None: + self.api = api + self.config = config + self.report = report + + def get_workunits( + self, cassandra_data: CassandraEntities + ) -> Iterable[MetadataWorkUnit]: + for keyspace_name in cassandra_data.keyspaces: + tables = cassandra_data.tables.get(keyspace_name, []) + self.report.set_ingestion_stage(keyspace_name, PROFILING) + with ThreadPoolExecutor( + max_workers=self.config.profiling.max_workers + ) as executor: + future_to_dataset = { + executor.submit( + self.generate_profile, + keyspace_name, + table_name, + cassandra_data.columns.get(table_name, []), + ): table_name + for table_name in tables + } + for future in as_completed(future_to_dataset): + table_name = future_to_dataset[future] + try: + yield from future.result() + except Exception as exc: + self.report.profiling_skipped_other[table_name] += 1 + self.report.failure( + message="Failed to profile for table", + context=f"{keyspace_name}.{table_name}", + exc=exc, + ) + + def generate_profile( + self, + keyspace_name: str, + table_name: str, + columns: List[CassandraColumn], + ) -> Iterable[MetadataWorkUnit]: + dataset_name: str = f"{keyspace_name}.{table_name}" + dataset_urn = make_dataset_urn_with_platform_instance( + platform="cassandra", + name=dataset_name, + env=self.config.env, + platform_instance=self.config.platform_instance, + ) + + if not columns: + self.report.warning( + message="Skipping profiling as no columns found for table", + context=f"{keyspace_name}.{table_name}", + ) + self.report.profiling_skipped_other[table_name] += 1 + return + + if not self.config.profile_pattern.allowed(f"{keyspace_name}.{table_name}"): + self.report.profiling_skipped_table_profile_pattern[keyspace_name] += 1 + logger.info( + f"Table {table_name} in {keyspace_name}, not allowed for profiling" + ) + return + + try: + profile_data = self.profile_table(keyspace_name, table_name, columns) + except Exception as e: + self.report.warning( + message="Profiling Failed", + context=f"{keyspace_name}.{table_name}", + exc=e, + ) + return + + profile_aspect = self.populate_profile_aspect(profile_data) + + if profile_aspect: + self.report.report_entity_profiled(table_name) + mcp = MetadataChangeProposalWrapper( + entityUrn=dataset_urn, aspect=profile_aspect + ) + yield mcp.as_workunit() + + def populate_profile_aspect(self, profile_data: ProfileData) -> DatasetProfileClass: + field_profiles = [ + self._create_field_profile(column_name, column_metrics) + for column_name, column_metrics in profile_data.column_metrics.items() + ] + return DatasetProfileClass( + timestampMillis=round(time.time() * 1000), + rowCount=profile_data.row_count, + columnCount=profile_data.column_count, + fieldProfiles=field_profiles, + ) + + def _create_field_profile( + self, field_name: str, field_stats: ColumnMetric + ) -> DatasetFieldProfileClass: + quantiles = field_stats.quantiles + return DatasetFieldProfileClass( + fieldPath=field_name, + uniqueCount=field_stats.distinct_count, + nullCount=field_stats.null_count, + min=str(field_stats.min) if field_stats.min else None, + max=str(field_stats.max) if field_stats.max else None, + mean=str(field_stats.mean) if field_stats.mean else None, + median=str(field_stats.median) if field_stats.median else None, + stdev=str(field_stats.stdev) if field_stats.stdev else None, + quantiles=[ + QuantileClass(quantile=str(0.25), value=str(quantiles[0])), + QuantileClass(quantile=str(0.75), value=str(quantiles[1])), + ] + if quantiles + else None, + sampleValues=field_stats.sample_values + if field_stats.sample_values + else None, + ) + + def profile_table( + self, keyspace_name: str, table_name: str, columns: List[CassandraColumn] + ) -> ProfileData: + profile_data = ProfileData() + + resp = self.api.execute( + CassandraQueries.ROW_COUNT.format(keyspace_name, table_name) + ) + if resp: + profile_data.row_count = resp[0].row_count + + profile_data.column_count = len(columns) + + if not self.config.profiling.profile_table_level_only: + resp = self.api.execute( + f'SELECT {", ".join([col.column_name for col in columns])} FROM {keyspace_name}."{table_name}"' + ) + profile_data.column_metrics = self._collect_column_data(resp, columns) + + return self._parse_profile_results(profile_data) + + def _parse_profile_results(self, profile_data: ProfileData) -> ProfileData: + for cl_name, column_metrics in profile_data.column_metrics.items(): + if column_metrics.values: + try: + self._compute_field_statistics(column_metrics) + except Exception as e: + self.report.warning( + message="Profiling Failed For Column Stats", + context=cl_name, + exc=e, + ) + raise e + return profile_data + + def _collect_column_data( + self, rows: List[Any], columns: List[CassandraColumn] + ) -> Dict[str, ColumnMetric]: + metrics = {column.column_name: ColumnMetric() for column in columns} + + for row in rows: + for column in columns: + if self._is_skippable_type(column.type): + continue + + value: Any = getattr(row, column.column_name, None) + metric = metrics[column.column_name] + metric.col_type = column.type + + metric.total_count += 1 + if value is None: + metric.null_count += 1 + else: + metric.values.extend(self._parse_value(value)) + + return metrics + + def _is_skippable_type(self, data_type: str) -> bool: + return data_type.lower() in ["timeuuid", "blob", "frozen>"] + + def _parse_value(self, value: Any) -> List[Any]: + if isinstance(value, SortedSet): + return list(value) + elif isinstance(value, OrderedMapSerializedKey): + return list(dict(value).values()) + elif isinstance(value, list): + return value + return [value] + + def _compute_field_statistics(self, column_metrics: ColumnMetric) -> None: + values = column_metrics.values + if not values: + return + + # ByDefault Null count is added + if not self.config.profiling.include_field_null_count: + column_metrics.null_count = 0 + + if self.config.profiling.include_field_distinct_count: + column_metrics.distinct_count = len(set(values)) + + if self.config.profiling.include_field_min_value: + column_metrics.min = min(values) + + if self.config.profiling.include_field_max_value: + column_metrics.max = max(values) + + if values and self._is_numeric_type(column_metrics.col_type): + if self.config.profiling.include_field_mean_value: + column_metrics.mean = round(float(np.mean(values)), 2) + if self.config.profiling.include_field_stddev_value: + column_metrics.stdev = round(float(np.std(values)), 2) + if self.config.profiling.include_field_median_value: + column_metrics.median = round(float(np.median(values)), 2) + if self.config.profiling.include_field_quantiles: + column_metrics.quantiles = [ + float(np.percentile(values, 25)), + float(np.percentile(values, 75)), + ] + + if values and self.config.profiling.include_field_sample_values: + column_metrics.sample_values = [str(v) for v in values[:5]] + + def _is_numeric_type(self, data_type: str) -> bool: + return data_type.lower() in [ + "int", + "counter", + "bigint", + "float", + "double", + "decimal", + "smallint", + "tinyint", + "varint", + ] diff --git a/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_utils.py b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_utils.py new file mode 100644 index 0000000000000..41d4ac7ced603 --- /dev/null +++ b/metadata-ingestion/src/datahub/ingestion/source/cassandra/cassandra_utils.py @@ -0,0 +1,152 @@ +import logging +from dataclasses import dataclass, field +from typing import Dict, Generator, List, Optional, Type + +from datahub.ingestion.source.cassandra.cassandra_api import CassandraColumn +from datahub.ingestion.source.state.stale_entity_removal_handler import ( + StaleEntityRemovalSourceReport, +) +from datahub.ingestion.source_report.ingestion_stage import IngestionStageReport +from datahub.metadata.com.linkedin.pegasus2avro.schema import ( + SchemaField, + SchemaFieldDataType, +) +from datahub.metadata.schema_classes import ( + ArrayTypeClass, + BooleanTypeClass, + BytesTypeClass, + DateTypeClass, + NullTypeClass, + NumberTypeClass, + RecordTypeClass, + StringTypeClass, + TimeTypeClass, +) +from datahub.utilities.lossy_collections import LossyList +from datahub.utilities.stats_collections import TopKDict, int_top_k_dict + +logger = logging.getLogger(__name__) + + +# we always skip over ingesting metadata about these keyspaces +SYSTEM_KEYSPACE_LIST = set( + ["system", "system_auth", "system_schema", "system_distributed", "system_traces"] +) + + +@dataclass +class CassandraSourceReport(StaleEntityRemovalSourceReport, IngestionStageReport): + num_tables_failed: int = 0 + num_views_failed: int = 0 + tables_scanned: int = 0 + views_scanned: int = 0 + entities_profiled: int = 0 + filtered: LossyList[str] = field(default_factory=LossyList) + + def report_entity_scanned(self, name: str, ent_type: str = "View") -> None: + """ + Entity could be a view or a table + """ + if ent_type == "Table": + self.tables_scanned += 1 + elif ent_type == "View": + self.views_scanned += 1 + else: + raise KeyError(f"Unknown entity {ent_type}.") + + def set_ingestion_stage(self, keyspace: str, stage: str) -> None: + self.report_ingestion_stage_start(f"{keyspace}: {stage}") + + # TODO Need to create seperate common config for profiling report + profiling_skipped_other: TopKDict[str, int] = field(default_factory=int_top_k_dict) + profiling_skipped_table_profile_pattern: TopKDict[str, int] = field( + default_factory=int_top_k_dict + ) + + def report_entity_profiled(self, name: str) -> None: + self.entities_profiled += 1 + + def report_dropped(self, ent_name: str) -> None: + self.filtered.append(ent_name) + + +# This class helps convert cassandra column types to SchemaFieldDataType for use by the datahaub metadata schema +class CassandraToSchemaFieldConverter: + # Mapping from cassandra field types to SchemaFieldDataType. + # https://cassandra.apache.org/doc/stable/cassandra/cql/types.html (version 4.1) + _field_type_to_schema_field_type: Dict[str, Type] = { + # Bool + "boolean": BooleanTypeClass, + # Binary + "blob": BytesTypeClass, + # Numbers + "bigint": NumberTypeClass, + "counter": NumberTypeClass, + "decimal": NumberTypeClass, + "double": NumberTypeClass, + "float": NumberTypeClass, + "int": NumberTypeClass, + "smallint": NumberTypeClass, + "tinyint": NumberTypeClass, + "varint": NumberTypeClass, + # Dates + "date": DateTypeClass, + # Times + "duration": TimeTypeClass, + "time": TimeTypeClass, + "timestamp": TimeTypeClass, + # Strings + "text": StringTypeClass, + "ascii": StringTypeClass, + "inet": StringTypeClass, + "timeuuid": StringTypeClass, + "uuid": StringTypeClass, + "varchar": StringTypeClass, + # Records + "geo_point": RecordTypeClass, + # Arrays + "histogram": ArrayTypeClass, + } + + @staticmethod + def get_column_type(cassandra_column_type: str) -> SchemaFieldDataType: + type_class: Optional[ + Type + ] = CassandraToSchemaFieldConverter._field_type_to_schema_field_type.get( + cassandra_column_type + ) + if type_class is None: + logger.warning( + f"Cannot map {cassandra_column_type!r} to SchemaFieldDataType, using NullTypeClass." + ) + type_class = NullTypeClass + + return SchemaFieldDataType(type=type_class()) + + def _get_schema_fields( + self, cassandra_column_infos: List[CassandraColumn] + ) -> Generator[SchemaField, None, None]: + # append each schema field (sort so output is consistent) + for column_info in cassandra_column_infos: + column_name: str = column_info.column_name + cassandra_type: str = column_info.type + + schema_field_data_type: SchemaFieldDataType = self.get_column_type( + cassandra_type + ) + schema_field: SchemaField = SchemaField( + fieldPath=column_name, + nativeDataType=cassandra_type, + type=schema_field_data_type, + description=None, + nullable=True, + recursive=False, + ) + yield schema_field + + @classmethod + def get_schema_fields( + cls, cassandra_column_infos: List[CassandraColumn] + ) -> Generator[SchemaField, None, None]: + converter = cls() + yield from converter._get_schema_fields(cassandra_column_infos) diff --git a/metadata-ingestion/src/datahub/ingestion/source/common/subtypes.py b/metadata-ingestion/src/datahub/ingestion/source/common/subtypes.py index 7271bf6102639..9fbb15500a863 100644 --- a/metadata-ingestion/src/datahub/ingestion/source/common/subtypes.py +++ b/metadata-ingestion/src/datahub/ingestion/source/common/subtypes.py @@ -40,6 +40,7 @@ class DatasetContainerSubTypes(StrEnum): S3_BUCKET = "S3 bucket" GCS_BUCKET = "GCS bucket" ABS_CONTAINER = "ABS container" + KEYSPACE = "Keyspace" # Cassandra class BIContainerSubTypes(StrEnum): diff --git a/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_config.py b/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_config.py index 192ae7cacb8e6..9d6f65b95554e 100644 --- a/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_config.py +++ b/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_config.py @@ -1,9 +1,7 @@ -import datetime import os from typing import List, Literal, Optional import certifi -import pydantic from pydantic import Field, validator from datahub.configuration.common import AllowDenyPattern, ConfigModel @@ -11,7 +9,7 @@ EnvConfigMixin, PlatformInstanceConfigMixin, ) -from datahub.ingestion.source.ge_profiling_config import GEProfilingConfig +from datahub.ingestion.source.ge_profiling_config import GEProfilingBaseConfig from datahub.ingestion.source.state.stale_entity_removal_handler import ( StatefulStaleMetadataRemovalConfig, ) @@ -97,79 +95,15 @@ def validate_password(cls, value, values): return value -class ProfileConfig(GEProfilingConfig): - +class ProfileConfig(GEProfilingBaseConfig): query_timeout: int = Field( default=300, description="Time before cancelling Dremio profiling query" ) - - row_count: bool = True - column_count: bool = True - sample_values: bool = True - - # Below Configs inherited from GEProfilingConfig - # but not used in Dremio so we hide them from docs. include_field_median_value: bool = Field( default=False, hidden_from_docs=True, description="Median causes a number of issues in Dremio.", ) - partition_profiling_enabled: bool = Field(default=True, hidden_from_docs=True) - profile_table_row_count_estimate_only: bool = Field( - default=False, hidden_from_docs=True - ) - query_combiner_enabled: bool = Field(default=True, hidden_from_docs=True) - max_number_of_fields_to_profile: Optional[pydantic.PositiveInt] = Field( - default=None, hidden_from_docs=True - ) - profile_if_updated_since_days: Optional[pydantic.PositiveFloat] = Field( - default=None, hidden_from_docs=True - ) - profile_table_size_limit: Optional[int] = Field( - default=5, - description="Profile tables only if their size is less then specified GBs. If set to `null`, no limit on the size of tables to profile. Supported only in `snowflake` and `BigQuery`", - hidden_from_docs=True, - ) - - profile_table_row_limit: Optional[int] = Field( - default=5000000, - hidden_from_docs=True, - description="Profile tables only if their row count is less then specified count. If set to `null`, no limit on the row count of tables to profile. Supported only in `snowflake` and `BigQuery`", - ) - - partition_datetime: Optional[datetime.datetime] = Field( - default=None, - hidden_from_docs=True, - description="If specified, profile only the partition which matches this datetime. " - "If not specified, profile the latest partition. Only Bigquery supports this.", - ) - use_sampling: bool = Field( - default=True, - hidden_from_docs=True, - description="Whether to profile column level stats on sample of table. Only BigQuery and Snowflake support this. " - "If enabled, profiling is done on rows sampled from table. Sampling is not done for smaller tables. ", - ) - - sample_size: int = Field( - default=10000, - hidden_from_docs=True, - description="Number of rows to be sampled from table for column level profiling." - "Applicable only if `use_sampling` is set to True.", - ) - profile_external_tables: bool = Field( - default=False, - hidden_from_docs=True, - description="Whether to profile external tables. Only Snowflake and Redshift supports this.", - ) - - tags_to_ignore_sampling: Optional[List[str]] = pydantic.Field( - default=None, - hidden_from_docs=True, - description=( - "Fixed list of tags to ignore sampling." - " If not specified, tables will be sampled based on `use_sampling`." - ), - ) class DremioSourceMapping(EnvConfigMixin, PlatformInstanceConfigMixin, ConfigModel): diff --git a/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_profiling.py b/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_profiling.py index 3f25741beec67..5332597ffce9e 100644 --- a/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_profiling.py +++ b/metadata-ingestion/src/datahub/ingestion/source/dremio/dremio_profiling.py @@ -149,11 +149,8 @@ def _build_profile_sql( ) -> str: metrics = [] - if self.config.profiling.row_count: - metrics.append("COUNT(*) AS row_count") - - if self.config.profiling.column_count: - metrics.append(f"{len(columns)} AS column_count") + metrics.append("COUNT(*) AS row_count") + metrics.append(f"{len(columns)} AS column_count") if not self.config.profiling.profile_table_level_only: for column_name, data_type in columns: @@ -239,11 +236,9 @@ def _parse_profile_results( profile: Dict[str, Any] = {"column_stats": {}} result = results[0] if results else {} # We expect only one row of results - if self.config.profiling.row_count: - profile["row_count"] = int(result.get("row_count", 0)) + profile["row_count"] = int(result.get("row_count", 0)) - if self.config.profiling.column_count: - profile["column_count"] = int(result.get("column_count", 0)) + profile["column_count"] = int(result.get("column_count", 0)) for column_name, data_type in columns: safe_column_name = re.sub(r"\W|^(?=\d)", "_", column_name) diff --git a/metadata-ingestion/src/datahub/ingestion/source/ge_profiling_config.py b/metadata-ingestion/src/datahub/ingestion/source/ge_profiling_config.py index 2a9068d3d49d8..8b2443a589b8d 100644 --- a/metadata-ingestion/src/datahub/ingestion/source/ge_profiling_config.py +++ b/metadata-ingestion/src/datahub/ingestion/source/ge_profiling_config.py @@ -19,7 +19,7 @@ logger = logging.getLogger(__name__) -class GEProfilingConfig(ConfigModel): +class GEProfilingBaseConfig(ConfigModel): enabled: bool = Field( default=False, description="Whether profiling should be done." ) @@ -35,15 +35,6 @@ class GEProfilingConfig(ConfigModel): default=None, description="Offset in documents to profile. By default, uses no offset.", ) - report_dropped_profiles: bool = Field( - default=False, - description="Whether to report datasets or dataset columns which were not profiled. Set to `True` for debugging purposes.", - ) - - turn_off_expensive_profiling_metrics: bool = Field( - default=False, - description="Whether to turn off expensive profiling or not. This turns off profiling for quantiles, distinct_value_frequencies, histogram & sample_values. This also limits maximum number of fields being profiled to 10.", - ) profile_table_level_only: bool = Field( default=False, description="Whether to perform profiling at table-level only, or include column-level profiling as well.", @@ -92,6 +83,29 @@ class GEProfilingConfig(ConfigModel): default=True, description="Whether to profile for the sample values for all columns.", ) + + # The default of (5 * cpu_count) is adopted from the default max_workers + # parameter of ThreadPoolExecutor. Given that profiling is often an I/O-bound + # task, it may make sense to increase this default value in the future. + # https://docs.python.org/3/library/concurrent.futures.html#concurrent.futures.ThreadPoolExecutor + max_workers: int = Field( + default=5 * (os.cpu_count() or 4), + description="Number of worker threads to use for profiling. Set to 1 to disable.", + ) + + +class GEProfilingConfig(GEProfilingBaseConfig): + + report_dropped_profiles: bool = Field( + default=False, + description="Whether to report datasets or dataset columns which were not profiled. Set to `True` for debugging purposes.", + ) + + turn_off_expensive_profiling_metrics: bool = Field( + default=False, + description="Whether to turn off expensive profiling or not. This turns off profiling for quantiles, distinct_value_frequencies, histogram & sample_values. This also limits maximum number of fields being profiled to 10.", + ) + field_sample_values_limit: int = Field( default=20, description="Upper limit for number of sample values to collect for all columns.", @@ -126,15 +140,6 @@ class GEProfilingConfig(ConfigModel): "less accurate. Only supported for Postgres and MySQL. ", ) - # The default of (5 * cpu_count) is adopted from the default max_workers - # parameter of ThreadPoolExecutor. Given that profiling is often an I/O-bound - # task, it may make sense to increase this default value in the future. - # https://docs.python.org/3/library/concurrent.futures.html#concurrent.futures.ThreadPoolExecutor - max_workers: int = Field( - default=5 * (os.cpu_count() or 4), - description="Number of worker threads to use for profiling. Set to 1 to disable.", - ) - # The query combiner enables us to combine multiple queries into a single query, # reducing the number of round-trips to the database and speeding up profiling. query_combiner_enabled: bool = Field( diff --git a/metadata-ingestion/tests/integration/cassandra/cassandra_mcps_golden.json b/metadata-ingestion/tests/integration/cassandra/cassandra_mcps_golden.json new file mode 100644 index 0000000000000..1823a218ada2e --- /dev/null +++ b/metadata-ingestion/tests/integration/cassandra/cassandra_mcps_golden.json @@ -0,0 +1,2706 @@ +[ +{ + "entityType": "container", + "entityUrn": "urn:li:container:e88cdfeb0f0ec790300527f9ea34ee05", + "changeType": "UPSERT", + "aspectName": "containerProperties", + "aspect": { + "json": { + "customProperties": { + "platform": "cassandra", + "env": "PROD", + "keyspace": "cass_test_1", + "durable_writes": "True", + "replication": "{\"class\": \"org.apache.cassandra.locator.SimpleStrategy\", \"replication_factor\": \"1\"}" + }, + "name": "cass_test_1", + "qualifiedName": "cass_test_1", + "env": "PROD" + } + }, + "systemMetadata": { + "lastObserved": 1731579516869, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "container", + "entityUrn": "urn:li:container:e88cdfeb0f0ec790300527f9ea34ee05", + "changeType": "UPSERT", + "aspectName": "dataPlatformInstance", + "aspect": { + "json": { + "platform": "urn:li:dataPlatform:cassandra" + } + }, + "systemMetadata": { + "lastObserved": 1731309924399, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "container", + "entityUrn": "urn:li:container:e88cdfeb0f0ec790300527f9ea34ee05", + "changeType": "UPSERT", + "aspectName": "status", + "aspect": { + "json": { + "removed": false + } + }, + "systemMetadata": { + "lastObserved": 1731309924399, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "container", + "entityUrn": "urn:li:container:e88cdfeb0f0ec790300527f9ea34ee05", + "changeType": "UPSERT", + "aspectName": "subTypes", + "aspect": { + "json": { + "typeNames": [ + "Keyspace" + ] + } + }, + "systemMetadata": { + "lastObserved": 1731309924400, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "container", + "entityUrn": "urn:li:container:e88cdfeb0f0ec790300527f9ea34ee05", + "changeType": "UPSERT", + "aspectName": "browsePathsV2", + "aspect": { + "json": { + "path": [] + } + }, + "systemMetadata": { + "lastObserved": 1731309924400, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "dataset", + "entityUrn": "urn:li:dataset:(urn:li:dataPlatform:cassandra,cass_test_1.information,PROD)", + "changeType": "UPSERT", + "aspectName": "schemaMetadata", + "aspect": { + "json": { + "schemaName": "information", + "platform": "urn:li:dataPlatform:cassandra", + "version": 0, + "created": { + "time": 0, + "actor": "urn:li:corpuser:unknown" + }, + "lastModified": { + "time": 0, + "actor": "urn:li:corpuser:unknown" + }, + "hash": "", + "platformSchema": { + "com.linkedin.schema.OtherSchema": { + "rawSchema": "[{\"keyspace_name\": \"cass_test_1\", \"table_name\": \"information\", \"column_name\": \"details\", \"type\": \"text\", \"clustering_order\": \"none\", \"kind\": \"regular\", \"position\": -1}, {\"keyspace_name\": \"cass_test_1\", \"table_name\": \"information\", \"column_name\": \"last_updated\", \"type\": \"timestamp\", \"clustering_order\": \"none\", \"kind\": \"regular\", \"position\": -1}, {\"keyspace_name\": \"cass_test_1\", \"table_name\": \"information\", \"column_name\": \"person_id\", \"type\": \"int\", \"clustering_order\": \"none\", \"kind\": \"partition_key\", \"position\": 0}]" + } + }, + "fields": [ + { + "fieldPath": "details", + "nullable": true, + "type": { + "type": { + "com.linkedin.schema.StringType": {} + } + }, + "nativeDataType": "text", + "recursive": false, + "isPartOfKey": false + }, + { + "fieldPath": "last_updated", + "nullable": true, + "type": { + "type": { + "com.linkedin.schema.TimeType": {} + } + }, + "nativeDataType": "timestamp", + "recursive": false, + "isPartOfKey": false + }, + { + "fieldPath": "person_id", + "nullable": true, + "type": { + "type": { + "com.linkedin.schema.NumberType": {} + } + }, + "nativeDataType": "int", + "recursive": false, + "isPartOfKey": false + } + ] + } + }, + "systemMetadata": { + "lastObserved": 1731591019538, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "dataset", + "entityUrn": "urn:li:dataset:(urn:li:dataPlatform:cassandra,cass_test_1.information,PROD)", + "changeType": "UPSERT", + "aspectName": "status", + "aspect": { + "json": { + "removed": false + } + }, + "systemMetadata": { + "lastObserved": 1731309924405, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "dataset", + "entityUrn": "urn:li:dataset:(urn:li:dataPlatform:cassandra,cass_test_1.information,PROD)", + "changeType": "UPSERT", + "aspectName": "subTypes", + "aspect": { + "json": { + "typeNames": [ + "Table" + ] + } + }, + "systemMetadata": { + "lastObserved": 1731309924405, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "dataset", + "entityUrn": "urn:li:dataset:(urn:li:dataPlatform:cassandra,cass_test_1.information,PROD)", + "changeType": "UPSERT", + "aspectName": "datasetProperties", + "aspect": { + "json": { + "customProperties": { + "bloom_filter_fp_chance": "0.01", + "caching": "{\"keys\": \"ALL\", \"rows_per_partition\": \"NONE\"}", + "compaction": "{\"class\": \"org.apache.cassandra.db.compaction.SizeTieredCompactionStrategy\", \"max_threshold\": \"32\", \"min_threshold\": \"4\"}", + "compression": "{\"chunk_length_in_kb\": \"16\", \"class\": \"org.apache.cassandra.io.compress.LZ4Compressor\"}", + "crc_check_chance": "1.0", + "dclocal_read_repair_chance": "0.0", + "default_time_to_live": "0", + "extensions": "{}", + "gc_grace_seconds": "864000", + "max_index_interval": "2048", + "min_index_interval": "128", + "memtable_flush_period_in_ms": "0", + "read_repair_chance": "0.0", + "speculative_retry": "99p" + }, + "name": "information", + "qualifiedName": "cass_test_1.information", + "description": "", + "tags": [] + } + }, + "systemMetadata": { + "lastObserved": 1731591019540, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "dataset", + "entityUrn": "urn:li:dataset:(urn:li:dataPlatform:cassandra,example_keyspace.all_data_types,PROD)", + "changeType": "UPSERT", + "aspectName": "schemaMetadata", + "aspect": { + "json": { + "schemaName": "all_data_types", + "platform": "urn:li:dataPlatform:cassandra", + "version": 0, + "created": { + "time": 0, + "actor": "urn:li:corpuser:unknown" + }, + "lastModified": { + "time": 0, + "actor": "urn:li:corpuser:unknown" + }, + "hash": "", + "platformSchema": { + "com.linkedin.schema.OtherSchema": { + "rawSchema": "[{\"keyspace_name\": \"example_keyspace\", \"table_name\": \"all_data_types\", \"column_name\": \"ascii_column\", \"type\": \"ascii\", \"clustering_order\": \"none\", \"kind\": \"regular\", \"position\": -1}, {\"keyspace_name\": \"example_keyspace\", \"table_name\": \"all_data_types\", \"column_name\": \"bigint_column\", \"type\": \"bigint\", \"clustering_order\": \"none\", \"kind\": \"regular\", \"position\": -1}, {\"keyspace_name\": \"example_keyspace\", \"table_name\": \"all_data_types\", \"column_name\": \"blob_column\", \"type\": \"blob\", \"clustering_order\": \"none\", \"kind\": \"regular\", \"position\": -1}, {\"keyspace_name\": \"example_keyspace\", \"table_name\": \"all_data_types\", \"column_name\": \"boolean_column\", \"type\": \"boolean\", \"clustering_order\": \"none\", \"kind\": \"regular\", \"position\": -1}, {\"keyspace_name\": \"example_keyspace\", \"table_name\": \"all_data_types\", \"column_name\": 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"lastRunId": "no-run-id-provided" + } +}, +{ + "entityType": "dataset", + "entityUrn": "urn:li:dataset:(urn:li:dataPlatform:cassandra,example_keyspace.shopping_cart,PROD)", + "changeType": "UPSERT", + "aspectName": "datasetProfile", + "aspect": { + "json": { + "timestampMillis": 1731579516925, + "partitionSpec": { + "partition": "FULL_TABLE_SNAPSHOT", + "type": "FULL_TABLE" + }, + "rowCount": 9, + "columnCount": 3, + "fieldProfiles": [ + { + "fieldPath": "item_count", + "uniqueCount": 5, + "nullCount": 4, + "min": "2", + "max": "100", + "mean": "46.4", + "median": "50.0", + "stdev": "38.44", + "sampleValues": [ + "5", + "100", + "75", + "2", + "50" + ] + }, + { + "fieldPath": "last_update_timestamp", + "uniqueCount": 9, + "nullCount": 0, + "min": "2024-11-01 00:00:00", + "max": "2024-11-09 00:00:00", + "sampleValues": [ + "2024-11-08 00:00:00", + "2024-11-06 00:00:00", + "2024-11-02 00:00:00", + "2024-11-03 00:00:00", + "2024-11-05 00:00:00" + ] + }, + { + "fieldPath": "userid", + "uniqueCount": 9, + "nullCount": 0, + "min": "1234", + "max": "9876", + "sampleValues": [ + "1240", + "1238", + "1234", + "1235", + "1237" + ] + } + ] + } + }, + "systemMetadata": { + "lastObserved": 1731579516939, + "runId": "cassandra-test", + "lastRunId": "no-run-id-provided" + } +} +] \ No newline at end of file diff --git a/metadata-ingestion/tests/integration/cassandra/docker-compose.yml b/metadata-ingestion/tests/integration/cassandra/docker-compose.yml new file mode 100644 index 0000000000000..a1a2a3b97d134 --- /dev/null +++ b/metadata-ingestion/tests/integration/cassandra/docker-compose.yml @@ -0,0 +1,38 @@ +version: "1" +services: + test-cassandra: + image: cassandra:latest + container_name: test-cassandra + ports: + - 9042:9042 + volumes: + - ./setup/cassandra.yaml:/etc/cassandra/cassandra.yaml + - ./setup/init_keyspaces.cql:/docker-entrypoint-initdb.d/init_keyspaces.cql + networks: + - testnet + healthcheck: + test: ["CMD-SHELL", "cqlsh -e 'describe keyspaces' || exit 1"] + interval: 10s + timeout: 10s + retries: 10 + + test-cassandra-load-keyspace: + container_name: test-cassandra-load-keyspace + image: cassandra:latest + depends_on: + test-cassandra: + condition: service_healthy + volumes: + - ./setup/init_keyspaces.cql:/init_keyspaces.cql + command: /bin/bash -c "echo loading cassandra keyspace && cqlsh test-cassandra -f init_keyspaces.cql" + deploy: + restart_policy: + condition: on-failure + delay: 5s + max_attempts: 3 + window: 100s + networks: + - testnet + +networks: + testnet: diff --git a/metadata-ingestion/tests/integration/cassandra/setup/cassandra.yaml b/metadata-ingestion/tests/integration/cassandra/setup/cassandra.yaml new file mode 100644 index 0000000000000..2dee71a0b5d1b --- /dev/null +++ b/metadata-ingestion/tests/integration/cassandra/setup/cassandra.yaml @@ -0,0 +1,1827 @@ +# ---------------------------------------------------------------------------------------- # +# NOTE: +# This yaml has been copied from the official Cassandra Docker image: +# (https://github.com/datastax/docker-images/blob/master/config-templates/DSE/6.0.0/cassandra.yaml) +# +# Key interests are in setting the AllowAllNetworkAuthorizer, +# and in enabling materialized view feature. +# ---------------------------------------------------------------------------------------- # + +# Cassandra storage config YAML + +# NOTE: +# See https://cassandra.apache.org/doc/latest/configuration/ for +# full explanations of configuration directives +# /NOTE + +# The name of the cluster. This is mainly used to prevent machines in +# one logical cluster from joining another. +cluster_name: 'Test Cluster' + +# This defines the number of tokens randomly assigned to this node on the ring +# The more tokens, relative to other nodes, the larger the proportion of data +# that this node will store. You probably want all nodes to have the same number +# of tokens assuming they have equal hardware capability. +# +# If you leave this unspecified, Cassandra will use the default of 1 token for legacy compatibility, +# and will use the initial_token as described below. +# +# Specifying initial_token will override this setting on the node's initial start, +# on subsequent starts, this setting will apply even if initial token is set. +# +# See https://cassandra.apache.org/doc/latest/getting_started/production.html#tokens for +# best practice information about num_tokens. +# +num_tokens: 16 + +# Triggers automatic allocation of num_tokens tokens for this node. The allocation +# algorithm attempts to choose tokens in a way that optimizes replicated load over +# the nodes in the datacenter for the replica factor. +# +# The load assigned to each node will be close to proportional to its number of +# vnodes. +# +# Only supported with the Murmur3Partitioner. + +# Replica factor is determined via the replication strategy used by the specified +# keyspace. +# allocate_tokens_for_keyspace: KEYSPACE + +# Replica factor is explicitly set, regardless of keyspace or datacenter. +# This is the replica factor within the datacenter, like NTS. +allocate_tokens_for_local_replication_factor: 3 + +# initial_token allows you to specify tokens manually. While you can use it with +# vnodes (num_tokens > 1, above) -- in which case you should provide a +# comma-separated list -- it's primarily used when adding nodes to legacy clusters +# that do not have vnodes enabled. +# initial_token: + +# May either be "true" or "false" to enable globally +hinted_handoff_enabled: true + +# When hinted_handoff_enabled is true, a black list of data centers that will not +# perform hinted handoff +# hinted_handoff_disabled_datacenters: +# - DC1 +# - DC2 + +# this defines the maximum amount of time a dead host will have hints +# generated. After it has been dead this long, new hints for it will not be +# created until it has been seen alive and gone down again. +# Min unit: ms +max_hint_window: 3h + +# Maximum throttle in KiBs per second, per delivery thread. This will be +# reduced proportionally to the number of nodes in the cluster. (If there +# are two nodes in the cluster, each delivery thread will use the maximum +# rate; if there are three, each will throttle to half of the maximum, +# since we expect two nodes to be delivering hints simultaneously.) +# Min unit: KiB +hinted_handoff_throttle: 1024KiB + +# Number of threads with which to deliver hints; +# Consider increasing this number when you have multi-dc deployments, since +# cross-dc handoff tends to be slower +max_hints_delivery_threads: 2 + +# Directory where Cassandra should store hints. +# If not set, the default directory is $CASSANDRA_HOME/data/hints. +# hints_directory: /var/lib/cassandra/hints + +# How often hints should be flushed from the internal buffers to disk. +# Will *not* trigger fsync. +# Min unit: ms +hints_flush_period: 10000ms + +# Maximum size for a single hints file, in mebibytes. +# Min unit: MiB +max_hints_file_size: 128MiB + +# The file size limit to store hints for an unreachable host, in mebibytes. +# Once the local hints files have reached the limit, no more new hints will be created. +# Set a non-positive value will disable the size limit. +# max_hints_size_per_host: 0MiB + +# Enable / disable automatic cleanup for the expired and orphaned hints file. +# Disable the option in order to preserve those hints on the disk. +auto_hints_cleanup_enabled: false + +# Compression to apply to the hint files. If omitted, hints files +# will be written uncompressed. LZ4, Snappy, and Deflate compressors +# are supported. +#hints_compression: +# - class_name: LZ4Compressor +# parameters: +# - + +# Enable / disable persistent hint windows. +# +# If set to false, a hint will be stored only in case a respective node +# that hint is for is down less than or equal to max_hint_window. +# +# If set to true, a hint will be stored in case there is not any +# hint which was stored earlier than max_hint_window. This is for cases +# when a node keeps to restart and hints are not delivered yet, we would be saving +# hints for that node indefinitely. +# +# Defaults to true. +# +# hint_window_persistent_enabled: true + +# Maximum throttle in KiBs per second, total. This will be +# reduced proportionally to the number of nodes in the cluster. +# Min unit: KiB +batchlog_replay_throttle: 1024KiB + +# Authentication backend, implementing IAuthenticator; used to identify users +# Out of the box, Cassandra provides org.apache.cassandra.auth.{AllowAllAuthenticator, +# PasswordAuthenticator}. +# +# - AllowAllAuthenticator performs no checks - set it to disable authentication. +# - PasswordAuthenticator relies on username/password pairs to authenticate +# users. It keeps usernames and hashed passwords in system_auth.roles table. +# Please increase system_auth keyspace replication factor if you use this authenticator. +# If using PasswordAuthenticator, CassandraRoleManager must also be used (see below) +authenticator: AllowAllAuthenticator + +# Authorization backend, implementing IAuthorizer; used to limit access/provide permissions +# Out of the box, Cassandra provides org.apache.cassandra.auth.{AllowAllAuthorizer, +# CassandraAuthorizer}. +# +# - AllowAllAuthorizer allows any action to any user - set it to disable authorization. +# - CassandraAuthorizer stores permissions in system_auth.role_permissions table. Please +# increase system_auth keyspace replication factor if you use this authorizer. +authorizer: AllowAllAuthorizer + +# Part of the Authentication & Authorization backend, implementing IRoleManager; used +# to maintain grants and memberships between roles. +# Out of the box, Cassandra provides org.apache.cassandra.auth.CassandraRoleManager, +# which stores role information in the system_auth keyspace. Most functions of the +# IRoleManager require an authenticated login, so unless the configured IAuthenticator +# actually implements authentication, most of this functionality will be unavailable. +# +# - CassandraRoleManager stores role data in the system_auth keyspace. Please +# increase system_auth keyspace replication factor if you use this role manager. +role_manager: CassandraRoleManager + +# Network authorization backend, implementing INetworkAuthorizer; used to restrict user +# access to certain DCs +# Out of the box, Cassandra provides org.apache.cassandra.auth.{AllowAllNetworkAuthorizer, +# CassandraNetworkAuthorizer}. +# +# - AllowAllNetworkAuthorizer allows access to any DC to any user - set it to disable authorization. +# - CassandraNetworkAuthorizer stores permissions in system_auth.network_permissions table. Please +# increase system_auth keyspace replication factor if you use this authorizer. +network_authorizer: AllowAllNetworkAuthorizer + +# Depending on the auth strategy of the cluster, it can be beneficial to iterate +# from root to table (root -> ks -> table) instead of table to root (table -> ks -> root). +# As the auth entries are whitelisting, once a permission is found you know it to be +# valid. We default to false as the legacy behavior is to query at the table level then +# move back up to the root. See CASSANDRA-17016 for details. +# traverse_auth_from_root: false + +# Validity period for roles cache (fetching granted roles can be an expensive +# operation depending on the role manager, CassandraRoleManager is one example) +# Granted roles are cached for authenticated sessions in AuthenticatedUser and +# after the period specified here, become eligible for (async) reload. +# Defaults to 2000, set to 0 to disable caching entirely. +# Will be disabled automatically for AllowAllAuthenticator. +# For a long-running cache using roles_cache_active_update, consider +# setting to something longer such as a daily validation: 86400000 +# Min unit: ms +roles_validity: 2000ms + +# Refresh interval for roles cache (if enabled). +# After this interval, cache entries become eligible for refresh. Upon next +# access, an async reload is scheduled and the old value returned until it +# completes. If roles_validity is non-zero, then this must be +# also. +# This setting is also used to inform the interval of auto-updating if +# using roles_cache_active_update. +# Defaults to the same value as roles_validity. +# For a long-running cache, consider setting this to 60000 (1 hour) etc. +# Min unit: ms +# roles_update_interval: 2000ms + +# If true, cache contents are actively updated by a background task at the +# interval set by roles_update_interval. If false, cache entries +# become eligible for refresh after their update interval. Upon next access, +# an async reload is scheduled and the old value returned until it completes. +# roles_cache_active_update: false + +# Validity period for permissions cache (fetching permissions can be an +# expensive operation depending on the authorizer, CassandraAuthorizer is +# one example). Defaults to 2000, set to 0 to disable. +# Will be disabled automatically for AllowAllAuthorizer. +# For a long-running cache using permissions_cache_active_update, consider +# setting to something longer such as a daily validation: 86400000ms +# Min unit: ms +permissions_validity: 2000ms + +# Refresh interval for permissions cache (if enabled). +# After this interval, cache entries become eligible for refresh. Upon next +# access, an async reload is scheduled and the old value returned until it +# completes. If permissions_validity is non-zero, then this must be +# also. +# This setting is also used to inform the interval of auto-updating if +# using permissions_cache_active_update. +# Defaults to the same value as permissions_validity. +# For a longer-running permissions cache, consider setting to update hourly (60000) +# Min unit: ms +# permissions_update_interval: 2000ms + +# If true, cache contents are actively updated by a background task at the +# interval set by permissions_update_interval. If false, cache entries +# become eligible for refresh after their update interval. Upon next access, +# an async reload is scheduled and the old value returned until it completes. +# permissions_cache_active_update: false + +# Validity period for credentials cache. This cache is tightly coupled to +# the provided PasswordAuthenticator implementation of IAuthenticator. If +# another IAuthenticator implementation is configured, this cache will not +# be automatically used and so the following settings will have no effect. +# Please note, credentials are cached in their encrypted form, so while +# activating this cache may reduce the number of queries made to the +# underlying table, it may not bring a significant reduction in the +# latency of individual authentication attempts. +# Defaults to 2000, set to 0 to disable credentials caching. +# For a long-running cache using credentials_cache_active_update, consider +# setting to something longer such as a daily validation: 86400000 +# Min unit: ms +credentials_validity: 2000ms + +# Refresh interval for credentials cache (if enabled). +# After this interval, cache entries become eligible for refresh. Upon next +# access, an async reload is scheduled and the old value returned until it +# completes. If credentials_validity is non-zero, then this must be +# also. +# This setting is also used to inform the interval of auto-updating if +# using credentials_cache_active_update. +# Defaults to the same value as credentials_validity. +# For a longer-running permissions cache, consider setting to update hourly (60000) +# Min unit: ms +# credentials_update_interval: 2000ms + +# If true, cache contents are actively updated by a background task at the +# interval set by credentials_update_interval. If false (default), cache entries +# become eligible for refresh after their update interval. Upon next access, +# an async reload is scheduled and the old value returned until it completes. +# credentials_cache_active_update: false + +# The partitioner is responsible for distributing groups of rows (by +# partition key) across nodes in the cluster. The partitioner can NOT be +# changed without reloading all data. If you are adding nodes or upgrading, +# you should set this to the same partitioner that you are currently using. +# +# The default partitioner is the Murmur3Partitioner. Older partitioners +# such as the RandomPartitioner, ByteOrderedPartitioner, and +# OrderPreservingPartitioner have been included for backward compatibility only. +# For new clusters, you should NOT change this value. +# +partitioner: org.apache.cassandra.dht.Murmur3Partitioner + +# Directories where Cassandra should store data on disk. If multiple +# directories are specified, Cassandra will spread data evenly across +# them by partitioning the token ranges. +# If not set, the default directory is $CASSANDRA_HOME/data/data. +# data_file_directories: +# - /var/lib/cassandra/data + +# Directory were Cassandra should store the data of the local system keyspaces. +# By default Cassandra will store the data of the local system keyspaces in the first of the data directories specified +# by data_file_directories. +# This approach ensures that if one of the other disks is lost Cassandra can continue to operate. For extra security +# this setting allows to store those data on a different directory that provides redundancy. +# local_system_data_file_directory: + +# commit log. when running on magnetic HDD, this should be a +# separate spindle than the data directories. +# If not set, the default directory is $CASSANDRA_HOME/data/commitlog. +# commitlog_directory: /var/lib/cassandra/commitlog + +# Enable / disable CDC functionality on a per-node basis. This modifies the logic used +# for write path allocation rejection (standard: never reject. cdc: reject Mutation +# containing a CDC-enabled table if at space limit in cdc_raw_directory). +cdc_enabled: false + +# CommitLogSegments are moved to this directory on flush if cdc_enabled: true and the +# segment contains mutations for a CDC-enabled table. This should be placed on a +# separate spindle than the data directories. If not set, the default directory is +# $CASSANDRA_HOME/data/cdc_raw. +# cdc_raw_directory: /var/lib/cassandra/cdc_raw + +# Policy for data disk failures: +# +# die +# shut down gossip and client transports and kill the JVM for any fs errors or +# single-sstable errors, so the node can be replaced. +# +# stop_paranoid +# shut down gossip and client transports even for single-sstable errors, +# kill the JVM for errors during startup. +# +# stop +# shut down gossip and client transports, leaving the node effectively dead, but +# can still be inspected via JMX, kill the JVM for errors during startup. +# +# best_effort +# stop using the failed disk and respond to requests based on +# remaining available sstables. This means you WILL see obsolete +# data at CL.ONE! +# +# ignore +# ignore fatal errors and let requests fail, as in pre-1.2 Cassandra +disk_failure_policy: stop + +# Policy for commit disk failures: +# +# die +# shut down the node and kill the JVM, so the node can be replaced. +# +# stop +# shut down the node, leaving the node effectively dead, but +# can still be inspected via JMX. +# +# stop_commit +# shutdown the commit log, letting writes collect but +# continuing to service reads, as in pre-2.0.5 Cassandra +# +# ignore +# ignore fatal errors and let the batches fail +commit_failure_policy: stop + +# Maximum size of the native protocol prepared statement cache +# +# Valid values are either "auto" (omitting the value) or a value greater 0. +# +# Note that specifying a too large value will result in long running GCs and possbily +# out-of-memory errors. Keep the value at a small fraction of the heap. +# +# If you constantly see "prepared statements discarded in the last minute because +# cache limit reached" messages, the first step is to investigate the root cause +# of these messages and check whether prepared statements are used correctly - +# i.e. use bind markers for variable parts. +# +# Do only change the default value, if you really have more prepared statements than +# fit in the cache. In most cases it is not neccessary to change this value. +# Constantly re-preparing statements is a performance penalty. +# +# Default value ("auto") is 1/256th of the heap or 10MiB, whichever is greater +# Min unit: MiB +prepared_statements_cache_size: + +# Maximum size of the key cache in memory. +# +# Each key cache hit saves 1 seek and each row cache hit saves 2 seeks at the +# minimum, sometimes more. The key cache is fairly tiny for the amount of +# time it saves, so it's worthwhile to use it at large numbers. +# The row cache saves even more time, but must contain the entire row, +# so it is extremely space-intensive. It's best to only use the +# row cache if you have hot rows or static rows. +# +# NOTE: if you reduce the size, you may not get you hottest keys loaded on startup. +# +# Default value is empty to make it "auto" (min(5% of Heap (in MiB), 100MiB)). Set to 0 to disable key cache. +# Min unit: MiB +key_cache_size: + +# Duration in seconds after which Cassandra should +# save the key cache. Caches are saved to saved_caches_directory as +# specified in this configuration file. +# +# Saved caches greatly improve cold-start speeds, and is relatively cheap in +# terms of I/O for the key cache. Row cache saving is much more expensive and +# has limited use. +# +# Default is 14400 or 4 hours. +# Min unit: s +key_cache_save_period: 4h + +# Number of keys from the key cache to save +# Disabled by default, meaning all keys are going to be saved +# key_cache_keys_to_save: 100 + +# Row cache implementation class name. Available implementations: +# +# org.apache.cassandra.cache.OHCProvider +# Fully off-heap row cache implementation (default). +# +# org.apache.cassandra.cache.SerializingCacheProvider +# This is the row cache implementation availabile +# in previous releases of Cassandra. +# row_cache_class_name: org.apache.cassandra.cache.OHCProvider + +# Maximum size of the row cache in memory. +# Please note that OHC cache implementation requires some additional off-heap memory to manage +# the map structures and some in-flight memory during operations before/after cache entries can be +# accounted against the cache capacity. This overhead is usually small compared to the whole capacity. +# Do not specify more memory that the system can afford in the worst usual situation and leave some +# headroom for OS block level cache. Do never allow your system to swap. +# +# Default value is 0, to disable row caching. +# Min unit: MiB +row_cache_size: 0MiB + +# Duration in seconds after which Cassandra should save the row cache. +# Caches are saved to saved_caches_directory as specified in this configuration file. +# +# Saved caches greatly improve cold-start speeds, and is relatively cheap in +# terms of I/O for the key cache. Row cache saving is much more expensive and +# has limited use. +# +# Default is 0 to disable saving the row cache. +# Min unit: s +row_cache_save_period: 0s + +# Number of keys from the row cache to save. +# Specify 0 (which is the default), meaning all keys are going to be saved +# row_cache_keys_to_save: 100 + +# Maximum size of the counter cache in memory. +# +# Counter cache helps to reduce counter locks' contention for hot counter cells. +# In case of RF = 1 a counter cache hit will cause Cassandra to skip the read before +# write entirely. With RF > 1 a counter cache hit will still help to reduce the duration +# of the lock hold, helping with hot counter cell updates, but will not allow skipping +# the read entirely. Only the local (clock, count) tuple of a counter cell is kept +# in memory, not the whole counter, so it's relatively cheap. +# +# NOTE: if you reduce the size, you may not get you hottest keys loaded on startup. +# +# Default value is empty to make it "auto" (min(2.5% of Heap (in MiB), 50MiB)). Set to 0 to disable counter cache. +# NOTE: if you perform counter deletes and rely on low gcgs, you should disable the counter cache. +# Min unit: MiB +counter_cache_size: + +# Duration in seconds after which Cassandra should +# save the counter cache (keys only). Caches are saved to saved_caches_directory as +# specified in this configuration file. +# +# Default is 7200 or 2 hours. +# Min unit: s +counter_cache_save_period: 7200s + +# Number of keys from the counter cache to save +# Disabled by default, meaning all keys are going to be saved +# counter_cache_keys_to_save: 100 + +# saved caches +# If not set, the default directory is $CASSANDRA_HOME/data/saved_caches. +# saved_caches_directory: /var/lib/cassandra/saved_caches + +# Number of seconds the server will wait for each cache (row, key, etc ...) to load while starting +# the Cassandra process. Setting this to zero is equivalent to disabling all cache loading on startup +# while still having the cache during runtime. +# Min unit: s +# cache_load_timeout: 30s + +# commitlog_sync may be either "periodic", "group", or "batch." +# +# When in batch mode, Cassandra won't ack writes until the commit log +# has been flushed to disk. Each incoming write will trigger the flush task. +# commitlog_sync_batch_window_in_ms is a deprecated value. Previously it had +# almost no value, and is being removed. +# +# commitlog_sync_batch_window_in_ms: 2 +# +# group mode is similar to batch mode, where Cassandra will not ack writes +# until the commit log has been flushed to disk. The difference is group +# mode will wait up to commitlog_sync_group_window between flushes. +# +# Min unit: ms +# commitlog_sync_group_window: 1000ms +# +# the default option is "periodic" where writes may be acked immediately +# and the CommitLog is simply synced every commitlog_sync_period +# milliseconds. +commitlog_sync: periodic +# Min unit: ms +commitlog_sync_period: 10000ms + +# When in periodic commitlog mode, the number of milliseconds to block writes +# while waiting for a slow disk flush to complete. +# Min unit: ms +# periodic_commitlog_sync_lag_block: + +# The size of the individual commitlog file segments. A commitlog +# segment may be archived, deleted, or recycled once all the data +# in it (potentially from each columnfamily in the system) has been +# flushed to sstables. +# +# The default size is 32, which is almost always fine, but if you are +# archiving commitlog segments (see commitlog_archiving.properties), +# then you probably want a finer granularity of archiving; 8 or 16 MB +# is reasonable. +# Max mutation size is also configurable via max_mutation_size setting in +# cassandra.yaml. The default is half the size commitlog_segment_size in bytes. +# This should be positive and less than 2048. +# +# NOTE: If max_mutation_size is set explicitly then commitlog_segment_size must +# be set to at least twice the size of max_mutation_size +# +# Min unit: MiB +commitlog_segment_size: 32MiB + +# Compression to apply to the commit log. If omitted, the commit log +# will be written uncompressed. LZ4, Snappy, and Deflate compressors +# are supported. +# commitlog_compression: +# - class_name: LZ4Compressor +# parameters: +# - + +# Compression to apply to SSTables as they flush for compressed tables. +# Note that tables without compression enabled do not respect this flag. +# +# As high ratio compressors like LZ4HC, Zstd, and Deflate can potentially +# block flushes for too long, the default is to flush with a known fast +# compressor in those cases. Options are: +# +# none : Flush without compressing blocks but while still doing checksums. +# fast : Flush with a fast compressor. If the table is already using a +# fast compressor that compressor is used. +# table: Always flush with the same compressor that the table uses. This +# was the pre 4.0 behavior. +# +# flush_compression: fast + +# any class that implements the SeedProvider interface and has a +# constructor that takes a Map of parameters will do. +seed_provider: + # Addresses of hosts that are deemed contact points. + # Cassandra nodes use this list of hosts to find each other and learn + # the topology of the ring. You must change this if you are running + # multiple nodes! + - class_name: org.apache.cassandra.locator.SimpleSeedProvider + parameters: + # seeds is actually a comma-delimited list of addresses. + # Ex: ",," + - seeds: "172.18.0.2" + +# For workloads with more data than can fit in memory, Cassandra's +# bottleneck will be reads that need to fetch data from +# disk. "concurrent_reads" should be set to (16 * number_of_drives) in +# order to allow the operations to enqueue low enough in the stack +# that the OS and drives can reorder them. Same applies to +# "concurrent_counter_writes", since counter writes read the current +# values before incrementing and writing them back. +# +# On the other hand, since writes are almost never IO bound, the ideal +# number of "concurrent_writes" is dependent on the number of cores in +# your system; (8 * number_of_cores) is a good rule of thumb. +concurrent_reads: 32 +concurrent_writes: 32 +concurrent_counter_writes: 32 + +# For materialized view writes, as there is a read involved, so this should +# be limited by the less of concurrent reads or concurrent writes. +concurrent_materialized_view_writes: 32 + +# Maximum memory to use for inter-node and client-server networking buffers. +# +# Defaults to the smaller of 1/16 of heap or 128MB. This pool is allocated off-heap, +# so is in addition to the memory allocated for heap. The cache also has on-heap +# overhead which is roughly 128 bytes per chunk (i.e. 0.2% of the reserved size +# if the default 64k chunk size is used). +# Memory is only allocated when needed. +# Min unit: MiB +# networking_cache_size: 128MiB + +# Enable the sstable chunk cache. The chunk cache will store recently accessed +# sections of the sstable in-memory as uncompressed buffers. +# file_cache_enabled: false + +# Maximum memory to use for sstable chunk cache and buffer pooling. +# 32MB of this are reserved for pooling buffers, the rest is used for chunk cache +# that holds uncompressed sstable chunks. +# Defaults to the smaller of 1/4 of heap or 512MB. This pool is allocated off-heap, +# so is in addition to the memory allocated for heap. The cache also has on-heap +# overhead which is roughly 128 bytes per chunk (i.e. 0.2% of the reserved size +# if the default 64k chunk size is used). +# Memory is only allocated when needed. +# Min unit: MiB +# file_cache_size: 512MiB + +# Flag indicating whether to allocate on or off heap when the sstable buffer +# pool is exhausted, that is when it has exceeded the maximum memory +# file_cache_size, beyond which it will not cache buffers but allocate on request. + +# buffer_pool_use_heap_if_exhausted: true + +# The strategy for optimizing disk read +# Possible values are: +# ssd (for solid state disks, the default) +# spinning (for spinning disks) +# disk_optimization_strategy: ssd + +# Total permitted memory to use for memtables. Cassandra will stop +# accepting writes when the limit is exceeded until a flush completes, +# and will trigger a flush based on memtable_cleanup_threshold +# If omitted, Cassandra will set both to 1/4 the size of the heap. +# Min unit: MiB +# memtable_heap_space: 2048MiB +# Min unit: MiB +# memtable_offheap_space: 2048MiB + +# memtable_cleanup_threshold is deprecated. The default calculation +# is the only reasonable choice. See the comments on memtable_flush_writers +# for more information. +# +# Ratio of occupied non-flushing memtable size to total permitted size +# that will trigger a flush of the largest memtable. Larger mct will +# mean larger flushes and hence less compaction, but also less concurrent +# flush activity which can make it difficult to keep your disks fed +# under heavy write load. +# +# memtable_cleanup_threshold defaults to 1 / (memtable_flush_writers + 1) +# memtable_cleanup_threshold: 0.11 + +# Specify the way Cassandra allocates and manages memtable memory. +# Options are: +# +# heap_buffers +# on heap nio buffers +# +# offheap_buffers +# off heap (direct) nio buffers +# +# offheap_objects +# off heap objects +memtable_allocation_type: heap_buffers + +# Limit memory usage for Merkle tree calculations during repairs. The default +# is 1/16th of the available heap. The main tradeoff is that smaller trees +# have less resolution, which can lead to over-streaming data. If you see heap +# pressure during repairs, consider lowering this, but you cannot go below +# one mebibyte. If you see lots of over-streaming, consider raising +# this or using subrange repair. +# +# For more details see https://issues.apache.org/jira/browse/CASSANDRA-14096. +# +# Min unit: MiB +# repair_session_space: + +# Total space to use for commit logs on disk. +# +# If space gets above this value, Cassandra will flush every dirty CF +# in the oldest segment and remove it. So a small total commitlog space +# will tend to cause more flush activity on less-active columnfamilies. +# +# The default value is the smaller of 8192, and 1/4 of the total space +# of the commitlog volume. +# +# commitlog_total_space: 8192MiB + +# This sets the number of memtable flush writer threads per disk +# as well as the total number of memtables that can be flushed concurrently. +# These are generally a combination of compute and IO bound. +# +# Memtable flushing is more CPU efficient than memtable ingest and a single thread +# can keep up with the ingest rate of a whole server on a single fast disk +# until it temporarily becomes IO bound under contention typically with compaction. +# At that point you need multiple flush threads. At some point in the future +# it may become CPU bound all the time. +# +# You can tell if flushing is falling behind using the MemtablePool.BlockedOnAllocation +# metric which should be 0, but will be non-zero if threads are blocked waiting on flushing +# to free memory. +# +# memtable_flush_writers defaults to two for a single data directory. +# This means that two memtables can be flushed concurrently to the single data directory. +# If you have multiple data directories the default is one memtable flushing at a time +# but the flush will use a thread per data directory so you will get two or more writers. +# +# Two is generally enough to flush on a fast disk [array] mounted as a single data directory. +# Adding more flush writers will result in smaller more frequent flushes that introduce more +# compaction overhead. +# +# There is a direct tradeoff between number of memtables that can be flushed concurrently +# and flush size and frequency. More is not better you just need enough flush writers +# to never stall waiting for flushing to free memory. +# +# memtable_flush_writers: 2 + +# Total space to use for change-data-capture logs on disk. +# +# If space gets above this value, Cassandra will throw WriteTimeoutException +# on Mutations including tables with CDC enabled. A CDCCompactor is responsible +# for parsing the raw CDC logs and deleting them when parsing is completed. +# +# The default value is the min of 4096 MiB and 1/8th of the total space +# of the drive where cdc_raw_directory resides. +# Min unit: MiB +# cdc_total_space: 4096MiB + +# When we hit our cdc_raw limit and the CDCCompactor is either running behind +# or experiencing backpressure, we check at the following interval to see if any +# new space for cdc-tracked tables has been made available. Default to 250ms +# Min unit: ms +# cdc_free_space_check_interval: 250ms + +# A fixed memory pool size in MB for for SSTable index summaries. If left +# empty, this will default to 5% of the heap size. If the memory usage of +# all index summaries exceeds this limit, SSTables with low read rates will +# shrink their index summaries in order to meet this limit. However, this +# is a best-effort process. In extreme conditions Cassandra may need to use +# more than this amount of memory. +# Min unit: KiB +index_summary_capacity: + +# How frequently index summaries should be resampled. This is done +# periodically to redistribute memory from the fixed-size pool to sstables +# proportional their recent read rates. Setting to null value will disable this +# process, leaving existing index summaries at their current sampling level. +# Min unit: m +index_summary_resize_interval: 60m + +# Whether to, when doing sequential writing, fsync() at intervals in +# order to force the operating system to flush the dirty +# buffers. Enable this to avoid sudden dirty buffer flushing from +# impacting read latencies. Almost always a good idea on SSDs; not +# necessarily on platters. +trickle_fsync: false +# Min unit: KiB +trickle_fsync_interval: 10240KiB + +# TCP port, for commands and data +# For security reasons, you should not expose this port to the internet. Firewall it if needed. +storage_port: 7000 + +# SSL port, for legacy encrypted communication. This property is unused unless enabled in +# server_encryption_options (see below). As of cassandra 4.0, this property is deprecated +# as a single port can be used for either/both secure and insecure connections. +# For security reasons, you should not expose this port to the internet. Firewall it if needed. +ssl_storage_port: 7001 + +# Address or interface to bind to and tell other Cassandra nodes to connect to. +# You _must_ change this if you want multiple nodes to be able to communicate! +# +# Set listen_address OR listen_interface, not both. +# +# Leaving it blank leaves it up to InetAddress.getLocalHost(). This +# will always do the Right Thing _if_ the node is properly configured +# (hostname, name resolution, etc), and the Right Thing is to use the +# address associated with the hostname (it might not be). If unresolvable +# it will fall back to InetAddress.getLoopbackAddress(), which is wrong for production systems. +# +# Setting listen_address to 0.0.0.0 is always wrong. +# +listen_address: 172.18.0.2 + +# Set listen_address OR listen_interface, not both. Interfaces must correspond +# to a single address, IP aliasing is not supported. +# listen_interface: eth0 + +# If you choose to specify the interface by name and the interface has an ipv4 and an ipv6 address +# you can specify which should be chosen using listen_interface_prefer_ipv6. If false the first ipv4 +# address will be used. If true the first ipv6 address will be used. Defaults to false preferring +# ipv4. If there is only one address it will be selected regardless of ipv4/ipv6. +# listen_interface_prefer_ipv6: false + +# Address to broadcast to other Cassandra nodes +# Leaving this blank will set it to the same value as listen_address +broadcast_address: 172.18.0.2 + +# When using multiple physical network interfaces, set this +# to true to listen on broadcast_address in addition to +# the listen_address, allowing nodes to communicate in both +# interfaces. +# Ignore this property if the network configuration automatically +# routes between the public and private networks such as EC2. +# listen_on_broadcast_address: false + +# Internode authentication backend, implementing IInternodeAuthenticator; +# used to allow/disallow connections from peer nodes. +# internode_authenticator: org.apache.cassandra.auth.AllowAllInternodeAuthenticator + +# Whether to start the native transport server. +# The address on which the native transport is bound is defined by rpc_address. +start_native_transport: true +# port for the CQL native transport to listen for clients on +# For security reasons, you should not expose this port to the internet. Firewall it if needed. +native_transport_port: 9042 +# Enabling native transport encryption in client_encryption_options allows you to either use +# encryption for the standard port or to use a dedicated, additional port along with the unencrypted +# standard native_transport_port. +# Enabling client encryption and keeping native_transport_port_ssl disabled will use encryption +# for native_transport_port. Setting native_transport_port_ssl to a different value +# from native_transport_port will use encryption for native_transport_port_ssl while +# keeping native_transport_port unencrypted. +# native_transport_port_ssl: 9142 +# The maximum threads for handling requests (note that idle threads are stopped +# after 30 seconds so there is not corresponding minimum setting). +# native_transport_max_threads: 128 +# +# The maximum size of allowed frame. Frame (requests) larger than this will +# be rejected as invalid. The default is 16MiB. If you're changing this parameter, +# you may want to adjust max_value_size accordingly. This should be positive and less than 2048. +# Min unit: MiB +# native_transport_max_frame_size: 16MiB + +# The maximum number of concurrent client connections. +# The default is -1, which means unlimited. +# native_transport_max_concurrent_connections: -1 + +# The maximum number of concurrent client connections per source ip. +# The default is -1, which means unlimited. +# native_transport_max_concurrent_connections_per_ip: -1 + +# Controls whether Cassandra honors older, yet currently supported, protocol versions. +# The default is true, which means all supported protocols will be honored. +native_transport_allow_older_protocols: true + +# Controls when idle client connections are closed. Idle connections are ones that had neither reads +# nor writes for a time period. +# +# Clients may implement heartbeats by sending OPTIONS native protocol message after a timeout, which +# will reset idle timeout timer on the server side. To close idle client connections, corresponding +# values for heartbeat intervals have to be set on the client side. +# +# Idle connection timeouts are disabled by default. +# Min unit: ms +# native_transport_idle_timeout: 60000ms + +# When enabled, limits the number of native transport requests dispatched for processing per second. +# Behavior once the limit has been breached depends on the value of THROW_ON_OVERLOAD specified in +# the STARTUP message sent by the client during connection establishment. (See section "4.1.1. STARTUP" +# in "CQL BINARY PROTOCOL v5".) With the THROW_ON_OVERLOAD flag enabled, messages that breach the limit +# are dropped, and an OverloadedException is thrown for the client to handle. When the flag is not +# enabled, the server will stop consuming messages from the channel/socket, putting backpressure on +# the client while already dispatched messages are processed. +# native_transport_rate_limiting_enabled: false +# native_transport_max_requests_per_second: 1000000 + +# The address or interface to bind the native transport server to. +# +# Set rpc_address OR rpc_interface, not both. +# +# Leaving rpc_address blank has the same effect as on listen_address +# (i.e. it will be based on the configured hostname of the node). +# +# Note that unlike listen_address, you can specify 0.0.0.0, but you must also +# set broadcast_rpc_address to a value other than 0.0.0.0. +# +# For security reasons, you should not expose this port to the internet. Firewall it if needed. +rpc_address: 0.0.0.0 + +# Set rpc_address OR rpc_interface, not both. Interfaces must correspond +# to a single address, IP aliasing is not supported. +# rpc_interface: eth1 + +# If you choose to specify the interface by name and the interface has an ipv4 and an ipv6 address +# you can specify which should be chosen using rpc_interface_prefer_ipv6. If false the first ipv4 +# address will be used. If true the first ipv6 address will be used. Defaults to false preferring +# ipv4. If there is only one address it will be selected regardless of ipv4/ipv6. +# rpc_interface_prefer_ipv6: false + +# RPC address to broadcast to drivers and other Cassandra nodes. This cannot +# be set to 0.0.0.0. If left blank, this will be set to the value of +# rpc_address. If rpc_address is set to 0.0.0.0, broadcast_rpc_address must +# be set. +broadcast_rpc_address: 172.18.0.2 + +# enable or disable keepalive on rpc/native connections +rpc_keepalive: true + +# Uncomment to set socket buffer size for internode communication +# Note that when setting this, the buffer size is limited by net.core.wmem_max +# and when not setting it it is defined by net.ipv4.tcp_wmem +# See also: +# /proc/sys/net/core/wmem_max +# /proc/sys/net/core/rmem_max +# /proc/sys/net/ipv4/tcp_wmem +# /proc/sys/net/ipv4/tcp_wmem +# and 'man tcp' +# Min unit: B +# internode_socket_send_buffer_size: + +# Uncomment to set socket buffer size for internode communication +# Note that when setting this, the buffer size is limited by net.core.wmem_max +# and when not setting it it is defined by net.ipv4.tcp_wmem +# Min unit: B +# internode_socket_receive_buffer_size: + +# Set to true to have Cassandra create a hard link to each sstable +# flushed or streamed locally in a backups/ subdirectory of the +# keyspace data. Removing these links is the operator's +# responsibility. +incremental_backups: false + +# Whether or not to take a snapshot before each compaction. Be +# careful using this option, since Cassandra won't clean up the +# snapshots for you. Mostly useful if you're paranoid when there +# is a data format change. +snapshot_before_compaction: false + +# Whether or not a snapshot is taken of the data before keyspace truncation +# or dropping of column families. The STRONGLY advised default of true +# should be used to provide data safety. If you set this flag to false, you will +# lose data on truncation or drop. +auto_snapshot: true + +# Adds a time-to-live (TTL) to auto snapshots generated by table +# truncation or drop (when enabled). +# After the TTL is elapsed, the snapshot is automatically cleared. +# By default, auto snapshots *do not* have TTL, uncomment the property below +# to enable TTL on auto snapshots. +# Accepted units: d (days), h (hours) or m (minutes) +# auto_snapshot_ttl: 30d + +# The act of creating or clearing a snapshot involves creating or removing +# potentially tens of thousands of links, which can cause significant performance +# impact, especially on consumer grade SSDs. A non-zero value here can +# be used to throttle these links to avoid negative performance impact of +# taking and clearing snapshots +snapshot_links_per_second: 0 + +# Granularity of the collation index of rows within a partition. +# Increase if your rows are large, or if you have a very large +# number of rows per partition. The competing goals are these: +# +# - a smaller granularity means more index entries are generated +# and looking up rows withing the partition by collation column +# is faster +# - but, Cassandra will keep the collation index in memory for hot +# rows (as part of the key cache), so a larger granularity means +# you can cache more hot rows +# Min unit: KiB +column_index_size: 64KiB + +# Per sstable indexed key cache entries (the collation index in memory +# mentioned above) exceeding this size will not be held on heap. +# This means that only partition information is held on heap and the +# index entries are read from disk. +# +# Note that this size refers to the size of the +# serialized index information and not the size of the partition. +# Min unit: KiB +column_index_cache_size: 2KiB + +# Number of simultaneous compactions to allow, NOT including +# validation "compactions" for anti-entropy repair. Simultaneous +# compactions can help preserve read performance in a mixed read/write +# workload, by mitigating the tendency of small sstables to accumulate +# during a single long running compactions. The default is usually +# fine and if you experience problems with compaction running too +# slowly or too fast, you should look at +# compaction_throughput first. +# +# concurrent_compactors defaults to the smaller of (number of disks, +# number of cores), with a minimum of 2 and a maximum of 8. +# +# If your data directories are backed by SSD, you should increase this +# to the number of cores. +# concurrent_compactors: 1 + +# Number of simultaneous repair validations to allow. If not set or set to +# a value less than 1, it defaults to the value of concurrent_compactors. +# To set a value greeater than concurrent_compactors at startup, the system +# property cassandra.allow_unlimited_concurrent_validations must be set to +# true. To dynamically resize to a value > concurrent_compactors on a running +# node, first call the bypassConcurrentValidatorsLimit method on the +# org.apache.cassandra.db:type=StorageService mbean +# concurrent_validations: 0 + +# Number of simultaneous materialized view builder tasks to allow. +concurrent_materialized_view_builders: 1 + +# Throttles compaction to the given total throughput across the entire +# system. The faster you insert data, the faster you need to compact in +# order to keep the sstable count down, but in general, setting this to +# 16 to 32 times the rate you are inserting data is more than sufficient. +# Setting this to 0 disables throttling. Note that this accounts for all types +# of compaction, including validation compaction (building Merkle trees +# for repairs). +compaction_throughput: 64MiB/s + +# When compacting, the replacement sstable(s) can be opened before they +# are completely written, and used in place of the prior sstables for +# any range that has been written. This helps to smoothly transfer reads +# between the sstables, reducing page cache churn and keeping hot rows hot +# Set sstable_preemptive_open_interval to null for disabled which is equivalent to +# sstable_preemptive_open_interval_in_mb being negative +# Min unit: MiB +sstable_preemptive_open_interval: 50MiB + +# Starting from 4.1 sstables support UUID based generation identifiers. They are disabled by default +# because once enabled, there is no easy way to downgrade. When the node is restarted with this option +# set to true, each newly created sstable will have a UUID based generation identifier and such files are +# not readable by previous Cassandra versions. At some point, this option will become true by default +# and eventually get removed from the configuration. +uuid_sstable_identifiers_enabled: false + +# When enabled, permits Cassandra to zero-copy stream entire eligible +# SSTables between nodes, including every component. +# This speeds up the network transfer significantly subject to +# throttling specified by entire_sstable_stream_throughput_outbound, +# and entire_sstable_inter_dc_stream_throughput_outbound +# for inter-DC transfers. +# Enabling this will reduce the GC pressure on sending and receiving node. +# When unset, the default is enabled. While this feature tries to keep the +# disks balanced, it cannot guarantee it. This feature will be automatically +# disabled if internode encryption is enabled. +# stream_entire_sstables: true + +# Throttles entire SSTable outbound streaming file transfers on +# this node to the given total throughput in Mbps. +# Setting this value to 0 it disables throttling. +# When unset, the default is 200 Mbps or 24 MiB/s. +# entire_sstable_stream_throughput_outbound: 24MiB/s + +# Throttles entire SSTable file streaming between datacenters. +# Setting this value to 0 disables throttling for entire SSTable inter-DC file streaming. +# When unset, the default is 200 Mbps or 24 MiB/s. +# entire_sstable_inter_dc_stream_throughput_outbound: 24MiB/s + +# Throttles all outbound streaming file transfers on this node to the +# given total throughput in Mbps. This is necessary because Cassandra does +# mostly sequential IO when streaming data during bootstrap or repair, which +# can lead to saturating the network connection and degrading rpc performance. +# When unset, the default is 200 Mbps or 24 MiB/s. +# stream_throughput_outbound: 24MiB/s + +# Throttles all streaming file transfer between the datacenters, +# this setting allows users to throttle inter dc stream throughput in addition +# to throttling all network stream traffic as configured with +# stream_throughput_outbound_megabits_per_sec +# When unset, the default is 200 Mbps or 24 MiB/s. +# inter_dc_stream_throughput_outbound: 24MiB/s + +# Server side timeouts for requests. The server will return a timeout exception +# to the client if it can't complete an operation within the corresponding +# timeout. Those settings are a protection against: +# 1) having client wait on an operation that might never terminate due to some +# failures. +# 2) operations that use too much CPU/read too much data (leading to memory build +# up) by putting a limit to how long an operation will execute. +# For this reason, you should avoid putting these settings too high. In other words, +# if you are timing out requests because of underlying resource constraints then +# increasing the timeout will just cause more problems. Of course putting them too +# low is equally ill-advised since clients could get timeouts even for successful +# operations just because the timeout setting is too tight. + +# How long the coordinator should wait for read operations to complete. +# Lowest acceptable value is 10 ms. +# Min unit: ms +read_request_timeout: 5000ms +# How long the coordinator should wait for seq or index scans to complete. +# Lowest acceptable value is 10 ms. +# Min unit: ms +range_request_timeout: 10000ms +# How long the coordinator should wait for writes to complete. +# Lowest acceptable value is 10 ms. +# Min unit: ms +write_request_timeout: 2000ms +# How long the coordinator should wait for counter writes to complete. +# Lowest acceptable value is 10 ms. +# Min unit: ms +counter_write_request_timeout: 5000ms +# How long a coordinator should continue to retry a CAS operation +# that contends with other proposals for the same row. +# Lowest acceptable value is 10 ms. +# Min unit: ms +cas_contention_timeout: 1000ms +# How long the coordinator should wait for truncates to complete +# (This can be much longer, because unless auto_snapshot is disabled +# we need to flush first so we can snapshot before removing the data.) +# Lowest acceptable value is 10 ms. +# Min unit: ms +truncate_request_timeout: 60000ms +# The default timeout for other, miscellaneous operations. +# Lowest acceptable value is 10 ms. +# Min unit: ms +request_timeout: 10000ms + +# Defensive settings for protecting Cassandra from true network partitions. +# See (CASSANDRA-14358) for details. +# +# The amount of time to wait for internode tcp connections to establish. +# Min unit: ms +# internode_tcp_connect_timeout: 2000ms +# +# The amount of time unacknowledged data is allowed on a connection before we throw out the connection +# Note this is only supported on Linux + epoll, and it appears to behave oddly above a setting of 30000 +# (it takes much longer than 30s) as of Linux 4.12. If you want something that high set this to 0 +# which picks up the OS default and configure the net.ipv4.tcp_retries2 sysctl to be ~8. +# Min unit: ms +# internode_tcp_user_timeout: 30000ms + +# The amount of time unacknowledged data is allowed on a streaming connection. +# The default is 5 minutes. Increase it or set it to 0 in order to increase the timeout. +# Min unit: ms +# internode_streaming_tcp_user_timeout: 300000ms + +# Global, per-endpoint and per-connection limits imposed on messages queued for delivery to other nodes +# and waiting to be processed on arrival from other nodes in the cluster. These limits are applied to the on-wire +# size of the message being sent or received. +# +# The basic per-link limit is consumed in isolation before any endpoint or global limit is imposed. +# Each node-pair has three links: urgent, small and large. So any given node may have a maximum of +# N*3*(internode_application_send_queue_capacity+internode_application_receive_queue_capacity) +# messages queued without any coordination between them although in practice, with token-aware routing, only RF*tokens +# nodes should need to communicate with significant bandwidth. +# +# The per-endpoint limit is imposed on all messages exceeding the per-link limit, simultaneously with the global limit, +# on all links to or from a single node in the cluster. +# The global limit is imposed on all messages exceeding the per-link limit, simultaneously with the per-endpoint limit, +# on all links to or from any node in the cluster. +# +# Min unit: B +# internode_application_send_queue_capacity: 4MiB +# internode_application_send_queue_reserve_endpoint_capacity: 128MiB +# internode_application_send_queue_reserve_global_capacity: 512MiB +# internode_application_receive_queue_capacity: 4MiB +# internode_application_receive_queue_reserve_endpoint_capacity: 128MiB +# internode_application_receive_queue_reserve_global_capacity: 512MiB + + +# How long before a node logs slow queries. Select queries that take longer than +# this timeout to execute, will generate an aggregated log message, so that slow queries +# can be identified. Set this value to zero to disable slow query logging. +# Min unit: ms +slow_query_log_timeout: 500ms + +# Enable operation timeout information exchange between nodes to accurately +# measure request timeouts. If disabled, replicas will assume that requests +# were forwarded to them instantly by the coordinator, which means that +# under overload conditions we will waste that much extra time processing +# already-timed-out requests. +# +# Warning: It is generally assumed that users have setup NTP on their clusters, and that clocks are modestly in sync, +# since this is a requirement for general correctness of last write wins. +# internode_timeout: true + +# Set period for idle state control messages for earlier detection of failed streams +# This node will send a keep-alive message periodically on the streaming's control channel. +# This ensures that any eventual SocketTimeoutException will occur within 2 keep-alive cycles +# If the node cannot send, or timeouts sending, the keep-alive message on the netty control channel +# the stream session is closed. +# Default value is 300s (5 minutes), which means stalled streams +# are detected within 10 minutes +# Specify 0 to disable. +# Min unit: s +# streaming_keep_alive_period: 300s + +# Limit number of connections per host for streaming +# Increase this when you notice that joins are CPU-bound rather that network +# bound (for example a few nodes with big files). +# streaming_connections_per_host: 1 + +# Settings for stream stats tracking; used by system_views.streaming table +# How long before a stream is evicted from tracking; this impacts both historic and currently running +# streams. +# streaming_state_expires: 3d +# How much memory may be used for tracking before evicting session from tracking; once crossed +# historic and currently running streams maybe impacted. +# streaming_state_size: 40MiB +# Enable/Disable tracking of streaming stats +# streaming_stats_enabled: true + +# Allows denying configurable access (rw/rr) to operations on configured ks, table, and partitions, intended for use by +# operators to manage cluster health vs application access. See CASSANDRA-12106 and CEP-13 for more details. +# partition_denylist_enabled: false + +# denylist_writes_enabled: true +# denylist_reads_enabled: true +# denylist_range_reads_enabled: true + +# The interval at which keys in the cache for denylisting will "expire" and async refresh from the backing DB. +# Note: this serves only as a fail-safe, as the usage pattern is expected to be "mutate state, refresh cache" on any +# changes to the underlying denylist entries. See documentation for details. +# Min unit: s +# denylist_refresh: 600s + +# In the event of errors on attempting to load the denylist cache, retry on this interval. +# Min unit: s +# denylist_initial_load_retry: 5s + +# We cap the number of denylisted keys allowed per table to keep things from growing unbounded. Nodes will warn above +# this limit while allowing new denylisted keys to be inserted. Denied keys are loaded in natural query / clustering +# ordering by partition key in case of overflow. +# denylist_max_keys_per_table: 1000 + +# We cap the total number of denylisted keys allowed in the cluster to keep things from growing unbounded. +# Nodes will warn on initial cache load that there are too many keys and be direct the operator to trim down excess +# entries to within the configured limits. +# denylist_max_keys_total: 10000 + +# Since the denylist in many ways serves to protect the health of the cluster from partitions operators have identified +# as being in a bad state, we usually want more robustness than just CL.ONE on operations to/from these tables to +# ensure that these safeguards are in place. That said, we allow users to configure this if they're so inclined. +# denylist_consistency_level: QUORUM + +# phi value that must be reached for a host to be marked down. +# most users should never need to adjust this. +# phi_convict_threshold: 8 + +# endpoint_snitch -- Set this to a class that implements +# IEndpointSnitch. The snitch has two functions: +# +# - it teaches Cassandra enough about your network topology to route +# requests efficiently +# - it allows Cassandra to spread replicas around your cluster to avoid +# correlated failures. It does this by grouping machines into +# "datacenters" and "racks." Cassandra will do its best not to have +# more than one replica on the same "rack" (which may not actually +# be a physical location) +# +# CASSANDRA WILL NOT ALLOW YOU TO SWITCH TO AN INCOMPATIBLE SNITCH +# ONCE DATA IS INSERTED INTO THE CLUSTER. This would cause data loss. +# This means that if you start with the default SimpleSnitch, which +# locates every node on "rack1" in "datacenter1", your only options +# if you need to add another datacenter are GossipingPropertyFileSnitch +# (and the older PFS). From there, if you want to migrate to an +# incompatible snitch like Ec2Snitch you can do it by adding new nodes +# under Ec2Snitch (which will locate them in a new "datacenter") and +# decommissioning the old ones. +# +# Out of the box, Cassandra provides: +# +# SimpleSnitch: +# Treats Strategy order as proximity. This can improve cache +# locality when disabling read repair. Only appropriate for +# single-datacenter deployments. +# +# GossipingPropertyFileSnitch +# This should be your go-to snitch for production use. The rack +# and datacenter for the local node are defined in +# cassandra-rackdc.properties and propagated to other nodes via +# gossip. If cassandra-topology.properties exists, it is used as a +# fallback, allowing migration from the PropertyFileSnitch. +# +# PropertyFileSnitch: +# Proximity is determined by rack and data center, which are +# explicitly configured in cassandra-topology.properties. +# +# Ec2Snitch: +# Appropriate for EC2 deployments in a single Region. Loads Region +# and Availability Zone information from the EC2 API. The Region is +# treated as the datacenter, and the Availability Zone as the rack. +# Only private IPs are used, so this will not work across multiple +# Regions. +# +# Ec2MultiRegionSnitch: +# Uses public IPs as broadcast_address to allow cross-region +# connectivity. (Thus, you should set seed addresses to the public +# IP as well.) You will need to open the storage_port or +# ssl_storage_port on the public IP firewall. (For intra-Region +# traffic, Cassandra will switch to the private IP after +# establishing a connection.) +# +# RackInferringSnitch: +# Proximity is determined by rack and data center, which are +# assumed to correspond to the 3rd and 2nd octet of each node's IP +# address, respectively. Unless this happens to match your +# deployment conventions, this is best used as an example of +# writing a custom Snitch class and is provided in that spirit. +# +# You can use a custom Snitch by setting this to the full class name +# of the snitch, which will be assumed to be on your classpath. +endpoint_snitch: SimpleSnitch + +# controls how often to perform the more expensive part of host score +# calculation +# Min unit: ms +dynamic_snitch_update_interval: 100ms +# controls how often to reset all host scores, allowing a bad host to +# possibly recover +# Min unit: ms +dynamic_snitch_reset_interval: 600000ms +# if set greater than zero, this will allow +# 'pinning' of replicas to hosts in order to increase cache capacity. +# The badness threshold will control how much worse the pinned host has to be +# before the dynamic snitch will prefer other replicas over it. This is +# expressed as a double which represents a percentage. Thus, a value of +# 0.2 means Cassandra would continue to prefer the static snitch values +# until the pinned host was 20% worse than the fastest. +dynamic_snitch_badness_threshold: 1.0 + +# Configure server-to-server internode encryption +# +# JVM and netty defaults for supported SSL socket protocols and cipher suites can +# be replaced using custom encryption options. This is not recommended +# unless you have policies in place that dictate certain settings, or +# need to disable vulnerable ciphers or protocols in case the JVM cannot +# be updated. +# +# FIPS compliant settings can be configured at JVM level and should not +# involve changing encryption settings here: +# https://docs.oracle.com/javase/8/docs/technotes/guides/security/jsse/FIPS.html +# +# **NOTE** this default configuration is an insecure configuration. If you need to +# enable server-to-server encryption generate server keystores (and truststores for mutual +# authentication) per: +# http://download.oracle.com/javase/8/docs/technotes/guides/security/jsse/JSSERefGuide.html#CreateKeystore +# Then perform the following configuration changes: +# +# Step 1: Set internode_encryption= and explicitly set optional=true. Restart all nodes +# +# Step 2: Set optional=false (or remove it) and if you generated truststores and want to use mutual +# auth set require_client_auth=true. Restart all nodes +server_encryption_options: + # On outbound connections, determine which type of peers to securely connect to. + # The available options are : + # none : Do not encrypt outgoing connections + # dc : Encrypt connections to peers in other datacenters but not within datacenters + # rack : Encrypt connections to peers in other racks but not within racks + # all : Always use encrypted connections + internode_encryption: none + # When set to true, encrypted and unencrypted connections are allowed on the storage_port + # This should _only be true_ while in unencrypted or transitional operation + # optional defaults to true if internode_encryption is none + # optional: true + # If enabled, will open up an encrypted listening socket on ssl_storage_port. Should only be used + # during upgrade to 4.0; otherwise, set to false. + legacy_ssl_storage_port_enabled: false + # Set to a valid keystore if internode_encryption is dc, rack or all + keystore: conf/.keystore + keystore_password: cassandra + # Configure the way Cassandra creates SSL contexts. + # To use PEM-based key material, see org.apache.cassandra.security.PEMBasedSslContextFactory + # ssl_context_factory: + # # Must be an instance of org.apache.cassandra.security.ISslContextFactory + # class_name: org.apache.cassandra.security.DefaultSslContextFactory + # Verify peer server certificates + require_client_auth: false + # Set to a valid trustore if require_client_auth is true + truststore: conf/.truststore + truststore_password: cassandra + # Verify that the host name in the certificate matches the connected host + require_endpoint_verification: false + # More advanced defaults: + # protocol: TLS + # store_type: JKS + # cipher_suites: [ + # TLS_ECDHE_ECDSA_WITH_AES_256_GCM_SHA384, TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256, + # TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256, TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA, + # TLS_ECDHE_RSA_WITH_AES_256_CBC_SHA, TLS_RSA_WITH_AES_128_GCM_SHA256, TLS_RSA_WITH_AES_128_CBC_SHA, + # TLS_RSA_WITH_AES_256_CBC_SHA + # ] + +# Configure client-to-server encryption. +# +# **NOTE** this default configuration is an insecure configuration. If you need to +# enable client-to-server encryption generate server keystores (and truststores for mutual +# authentication) per: +# http://download.oracle.com/javase/8/docs/technotes/guides/security/jsse/JSSERefGuide.html#CreateKeystore +# Then perform the following configuration changes: +# +# Step 1: Set enabled=true and explicitly set optional=true. Restart all nodes +# +# Step 2: Set optional=false (or remove it) and if you generated truststores and want to use mutual +# auth set require_client_auth=true. Restart all nodes +client_encryption_options: + # Enable client-to-server encryption + enabled: false + # When set to true, encrypted and unencrypted connections are allowed on the native_transport_port + # This should _only be true_ while in unencrypted or transitional operation + # optional defaults to true when enabled is false, and false when enabled is true. + # optional: true + # Set keystore and keystore_password to valid keystores if enabled is true + keystore: conf/.keystore + keystore_password: cassandra + # Configure the way Cassandra creates SSL contexts. + # To use PEM-based key material, see org.apache.cassandra.security.PEMBasedSslContextFactory + # ssl_context_factory: + # # Must be an instance of org.apache.cassandra.security.ISslContextFactory + # class_name: org.apache.cassandra.security.DefaultSslContextFactory + # Verify client certificates + require_client_auth: false + # Set trustore and truststore_password if require_client_auth is true + # truststore: conf/.truststore + # truststore_password: cassandra + # More advanced defaults: + # protocol: TLS + # store_type: JKS + # cipher_suites: [ + # TLS_ECDHE_ECDSA_WITH_AES_256_GCM_SHA384, TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256, + # TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256, TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA, + # TLS_ECDHE_RSA_WITH_AES_256_CBC_SHA, TLS_RSA_WITH_AES_128_GCM_SHA256, TLS_RSA_WITH_AES_128_CBC_SHA, + # TLS_RSA_WITH_AES_256_CBC_SHA + # ] + +# internode_compression controls whether traffic between nodes is +# compressed. +# Can be: +# +# all +# all traffic is compressed +# +# dc +# traffic between different datacenters is compressed +# +# none +# nothing is compressed. +internode_compression: dc + +# Enable or disable tcp_nodelay for inter-dc communication. +# Disabling it will result in larger (but fewer) network packets being sent, +# reducing overhead from the TCP protocol itself, at the cost of increasing +# latency if you block for cross-datacenter responses. +inter_dc_tcp_nodelay: false + +# TTL for different trace types used during logging of the repair process. +# Min unit: s +trace_type_query_ttl: 1d +# Min unit: s +trace_type_repair_ttl: 7d + +# If unset, all GC Pauses greater than gc_log_threshold will log at +# INFO level +# UDFs (user defined functions) are disabled by default. +# As of Cassandra 3.0 there is a sandbox in place that should prevent execution of evil code. +user_defined_functions_enabled: false + +# Enables scripted UDFs (JavaScript UDFs). +# Java UDFs are always enabled, if user_defined_functions_enabled is true. +# Enable this option to be able to use UDFs with "language javascript" or any custom JSR-223 provider. +# This option has no effect, if user_defined_functions_enabled is false. +scripted_user_defined_functions_enabled: false + +# Enables encrypting data at-rest (on disk). Different key providers can be plugged in, but the default reads from +# a JCE-style keystore. A single keystore can hold multiple keys, but the one referenced by +# the "key_alias" is the only key that will be used for encrypt opertaions; previously used keys +# can still (and should!) be in the keystore and will be used on decrypt operations +# (to handle the case of key rotation). +# +# It is strongly recommended to download and install Java Cryptography Extension (JCE) +# Unlimited Strength Jurisdiction Policy Files for your version of the JDK. +# (current link: http://www.oracle.com/technetwork/java/javase/downloads/jce8-download-2133166.html) +# +# Currently, only the following file types are supported for transparent data encryption, although +# more are coming in future cassandra releases: commitlog, hints +transparent_data_encryption_options: + enabled: false + chunk_length_kb: 64 + cipher: AES/CBC/PKCS5Padding + key_alias: testing:1 + # CBC IV length for AES needs to be 16 bytes (which is also the default size) + # iv_length: 16 + key_provider: + - class_name: org.apache.cassandra.security.JKSKeyProvider + parameters: + - keystore: conf/.keystore + keystore_password: cassandra + store_type: JCEKS + key_password: cassandra + + +##################### +# SAFETY THRESHOLDS # +##################### + +# When executing a scan, within or across a partition, we need to keep the +# tombstones seen in memory so we can return them to the coordinator, which +# will use them to make sure other replicas also know about the deleted rows. +# With workloads that generate a lot of tombstones, this can cause performance +# problems and even exaust the server heap. +# (http://www.datastax.com/dev/blog/cassandra-anti-patterns-queues-and-queue-like-datasets) +# Adjust the thresholds here if you understand the dangers and want to +# scan more tombstones anyway. These thresholds may also be adjusted at runtime +# using the StorageService mbean. +tombstone_warn_threshold: 1000 +tombstone_failure_threshold: 100000 + +# Filtering and secondary index queries at read consistency levels above ONE/LOCAL_ONE use a +# mechanism called replica filtering protection to ensure that results from stale replicas do +# not violate consistency. (See CASSANDRA-8272 and CASSANDRA-15907 for more details.) This +# mechanism materializes replica results by partition on-heap at the coordinator. The more possibly +# stale results returned by the replicas, the more rows materialized during the query. +replica_filtering_protection: + # These thresholds exist to limit the damage severely out-of-date replicas can cause during these + # queries. They limit the number of rows from all replicas individual index and filtering queries + # can materialize on-heap to return correct results at the desired read consistency level. + # + # "cached_replica_rows_warn_threshold" is the per-query threshold at which a warning will be logged. + # "cached_replica_rows_fail_threshold" is the per-query threshold at which the query will fail. + # + # These thresholds may also be adjusted at runtime using the StorageService mbean. + # + # If the failure threshold is breached, it is likely that either the current page/fetch size + # is too large or one or more replicas is severely out-of-sync and in need of repair. + cached_rows_warn_threshold: 2000 + cached_rows_fail_threshold: 32000 + +# Log WARN on any multiple-partition batch size exceeding this value. 5KiB per batch by default. +# Caution should be taken on increasing the size of this threshold as it can lead to node instability. +# Min unit: KiB +batch_size_warn_threshold: 5KiB + +# Fail any multiple-partition batch exceeding this value. 50KiB (10x warn threshold) by default. +# Min unit: KiB +batch_size_fail_threshold: 50KiB + +# Log WARN on any batches not of type LOGGED than span across more partitions than this limit +unlogged_batch_across_partitions_warn_threshold: 10 + +# Log a warning when compacting partitions larger than this value +compaction_large_partition_warning_threshold: 100MiB + +# Log a warning when writing more tombstones than this value to a partition +compaction_tombstone_warning_threshold: 100000 + +# GC Pauses greater than 200 ms will be logged at INFO level +# This threshold can be adjusted to minimize logging if necessary +# Min unit: ms +# gc_log_threshold: 200ms + +# GC Pauses greater than gc_warn_threshold will be logged at WARN level +# Adjust the threshold based on your application throughput requirement. Setting to 0 +# will deactivate the feature. +# Min unit: ms +# gc_warn_threshold: 1000ms + +# Maximum size of any value in SSTables. Safety measure to detect SSTable corruption +# early. Any value size larger than this threshold will result into marking an SSTable +# as corrupted. This should be positive and less than 2GiB. +# Min unit: MiB +# max_value_size: 256MiB + +# ** Impact on keyspace creation ** +# If replication factor is not mentioned as part of keyspace creation, default_keyspace_rf would apply. +# Changing this configuration would only take effect for keyspaces created after the change, but does not impact +# existing keyspaces created prior to the change. +# ** Impact on keyspace alter ** +# When altering a keyspace from NetworkTopologyStrategy to SimpleStrategy, default_keyspace_rf is applied if rf is not +# explicitly mentioned. +# ** Impact on system keyspaces ** +# This would also apply for any system keyspaces that need replication factor. +# A further note about system keyspaces - system_traces and system_distributed keyspaces take RF of 2 or default, +# whichever is higher, and system_auth keyspace takes RF of 1 or default, whichever is higher. +# Suggested value for use in production: 3 +# default_keyspace_rf: 1 + +# Track a metric per keyspace indicating whether replication achieved the ideal consistency +# level for writes without timing out. This is different from the consistency level requested by +# each write which may be lower in order to facilitate availability. +# ideal_consistency_level: EACH_QUORUM + +# Automatically upgrade sstables after upgrade - if there is no ordinary compaction to do, the +# oldest non-upgraded sstable will get upgraded to the latest version +# automatic_sstable_upgrade: false +# Limit the number of concurrent sstable upgrades +# max_concurrent_automatic_sstable_upgrades: 1 + +# Audit logging - Logs every incoming CQL command request, authentication to a node. See the docs +# on audit_logging for full details about the various configuration options. +audit_logging_options: + enabled: false + logger: + - class_name: BinAuditLogger + # audit_logs_dir: + # included_keyspaces: + # excluded_keyspaces: system, system_schema, system_virtual_schema + # included_categories: + # excluded_categories: + # included_users: + # excluded_users: + # roll_cycle: HOURLY + # block: true + # max_queue_weight: 268435456 # 256 MiB + # max_log_size: 17179869184 # 16 GiB + ## archive command is "/path/to/script.sh %path" where %path is replaced with the file being rolled: + # archive_command: + # max_archive_retries: 10 + + +# default options for full query logging - these can be overridden from command line when executing +# nodetool enablefullquerylog +# full_query_logging_options: + # log_dir: + # roll_cycle: HOURLY + # block: true + # max_queue_weight: 268435456 # 256 MiB + # max_log_size: 17179869184 # 16 GiB + ## archive command is "/path/to/script.sh %path" where %path is replaced with the file being rolled: + # archive_command: + ## note that enabling this allows anyone with JMX/nodetool access to run local shell commands as the user running cassandra + # allow_nodetool_archive_command: false + # max_archive_retries: 10 + +# validate tombstones on reads and compaction +# can be either "disabled", "warn" or "exception" +# corrupted_tombstone_strategy: disabled + +# Diagnostic Events # +# If enabled, diagnostic events can be helpful for troubleshooting operational issues. Emitted events contain details +# on internal state and temporal relationships across events, accessible by clients via JMX. +diagnostic_events_enabled: false + +# Use native transport TCP message coalescing. If on upgrade to 4.0 you found your throughput decreasing, and in +# particular you run an old kernel or have very fewer client connections, this option might be worth evaluating. +#native_transport_flush_in_batches_legacy: false + +# Enable tracking of repaired state of data during reads and comparison between replicas +# Mismatches between the repaired sets of replicas can be characterized as either confirmed +# or unconfirmed. In this context, unconfirmed indicates that the presence of pending repair +# sessions, unrepaired partition tombstones, or some other condition means that the disparity +# cannot be considered conclusive. Confirmed mismatches should be a trigger for investigation +# as they may be indicative of corruption or data loss. +# There are separate flags for range vs partition reads as single partition reads are only tracked +# when CL > 1 and a digest mismatch occurs. Currently, range queries don't use digests so if +# enabled for range reads, all range reads will include repaired data tracking. As this adds +# some overhead, operators may wish to disable it whilst still enabling it for partition reads +repaired_data_tracking_for_range_reads_enabled: false +repaired_data_tracking_for_partition_reads_enabled: false +# If false, only confirmed mismatches will be reported. If true, a separate metric for unconfirmed +# mismatches will also be recorded. This is to avoid potential signal:noise issues are unconfirmed +# mismatches are less actionable than confirmed ones. +report_unconfirmed_repaired_data_mismatches: false + +# Having many tables and/or keyspaces negatively affects performance of many operations in the +# cluster. When the number of tables/keyspaces in the cluster exceeds the following thresholds +# a client warning will be sent back to the user when creating a table or keyspace. +# As of cassandra 4.1, these properties are deprecated in favor of keyspaces_warn_threshold and tables_warn_threshold +# table_count_warn_threshold: 150 +# keyspace_count_warn_threshold: 40 + +# configure the read and write consistency levels for modifications to auth tables +# auth_read_consistency_level: LOCAL_QUORUM +# auth_write_consistency_level: EACH_QUORUM + +# Delays on auth resolution can lead to a thundering herd problem on reconnects; this option will enable +# warming of auth caches prior to node completing startup. See CASSANDRA-16958 +# auth_cache_warming_enabled: false + +######################### +# EXPERIMENTAL FEATURES # +######################### + +# Enables materialized view creation on this node. +# Materialized views are considered experimental and are not recommended for production use. +materialized_views_enabled: true + +# Enables SASI index creation on this node. +# SASI indexes are considered experimental and are not recommended for production use. +sasi_indexes_enabled: false + +# Enables creation of transiently replicated keyspaces on this node. +# Transient replication is experimental and is not recommended for production use. +transient_replication_enabled: false + +# Enables the used of 'ALTER ... DROP COMPACT STORAGE' statements on this node. +# 'ALTER ... DROP COMPACT STORAGE' is considered experimental and is not recommended for production use. +drop_compact_storage_enabled: false + +# Whether or not USE is allowed. This is enabled by default to avoid failure on upgrade. +#use_statements_enabled: true + +# When the client triggers a protocol exception or unknown issue (Cassandra bug) we increment +# a client metric showing this; this logic will exclude specific subnets from updating these +# metrics +#client_error_reporting_exclusions: +# subnets: +# - 127.0.0.1 +# - 127.0.0.0/31 + +# Enables read thresholds (warn/fail) across all replicas for reporting back to the client. +# See: CASSANDRA-16850 +# read_thresholds_enabled: false # scheduled to be set true in 4.2 +# When read_thresholds_enabled: true, this tracks the materialized size of a query on the +# coordinator. If coordinator_read_size_warn_threshold is defined, this will emit a warning +# to clients with details on what query triggered this as well as the size of the result set; if +# coordinator_read_size_fail_threshold is defined, this will fail the query after it +# has exceeded this threshold, returning a read error to the user. +# coordinator_read_size_warn_threshold: +# coordinator_read_size_fail_threshold: +# When read_thresholds_enabled: true, this tracks the size of the local read (as defined by +# heap size), and will warn/fail based off these thresholds; undefined disables these checks. +# local_read_size_warn_threshold: +# local_read_size_fail_threshold: +# When read_thresholds_enabled: true, this tracks the expected memory size of the RowIndexEntry +# and will warn/fail based off these thresholds; undefined disables these checks +# row_index_read_size_warn_threshold: +# row_index_read_size_fail_threshold: + +# Guardrail to warn or fail when creating more user keyspaces than threshold. +# The two thresholds default to -1 to disable. +# keyspaces_warn_threshold: -1 +# keyspaces_fail_threshold: -1 +# Guardrail to warn or fail when creating more user tables than threshold. +# The two thresholds default to -1 to disable. +# tables_warn_threshold: -1 +# tables_fail_threshold: -1 +# Guardrail to enable or disable the ability to create uncompressed tables +# uncompressed_tables_enabled: true +# Guardrail to warn or fail when creating/altering a table with more columns per table than threshold. +# The two thresholds default to -1 to disable. +# columns_per_table_warn_threshold: -1 +# columns_per_table_fail_threshold: -1 +# Guardrail to warn or fail when creating more secondary indexes per table than threshold. +# The two thresholds default to -1 to disable. +# secondary_indexes_per_table_warn_threshold: -1 +# secondary_indexes_per_table_fail_threshold: -1 +# Guardrail to enable or disable the creation of secondary indexes +# secondary_indexes_enabled: true +# Guardrail to warn or fail when creating more materialized views per table than threshold. +# The two thresholds default to -1 to disable. +# materialized_views_per_table_warn_threshold: -1 +# materialized_views_per_table_fail_threshold: -1 +# Guardrail to warn about, ignore or reject properties when creating tables. By default all properties are allowed. +# table_properties_warned: [] +# table_properties_ignored: [] +# table_properties_disallowed: [] +# Guardrail to allow/disallow user-provided timestamps. Defaults to true. +# user_timestamps_enabled: true +# Guardrail to allow/disallow GROUP BY functionality. +# group_by_enabled: true +# Guardrail to allow/disallow TRUNCATE and DROP TABLE statements +# drop_truncate_table_enabled: true +# Guardrail to warn or fail when using a page size greater than threshold. +# The two thresholds default to -1 to disable. +# page_size_warn_threshold: -1 +# page_size_fail_threshold: -1 +# Guardrail to allow/disallow list operations that require read before write, i.e. setting list element by index and +# removing list elements by either index or value. Defaults to true. +# read_before_write_list_operations_enabled: true +# Guardrail to warn or fail when querying with an IN restriction selecting more partition keys than threshold. +# The two thresholds default to -1 to disable. +# partition_keys_in_select_warn_threshold: -1 +# partition_keys_in_select_fail_threshold: -1 +# Guardrail to warn or fail when an IN query creates a cartesian product with a size exceeding threshold, +# eg. "a in (1,2,...10) and b in (1,2...10)" results in cartesian product of 100. +# The two thresholds default to -1 to disable. +# in_select_cartesian_product_warn_threshold: -1 +# in_select_cartesian_product_fail_threshold: -1 +# Guardrail to warn about or reject read consistency levels. By default, all consistency levels are allowed. +# read_consistency_levels_warned: [] +# read_consistency_levels_disallowed: [] +# Guardrail to warn about or reject write consistency levels. By default, all consistency levels are allowed. +# write_consistency_levels_warned: [] +# write_consistency_levels_disallowed: [] +# Guardrail to warn or fail when encountering larger size of collection data than threshold. +# At query time this guardrail is applied only to the collection fragment that is being writen, even though in the case +# of non-frozen collections there could be unaccounted parts of the collection on the sstables. This is done this way to +# prevent read-before-write. The guardrail is also checked at sstable write time to detect large non-frozen collections, +# although in that case exceeding the fail threshold will only log an error message, without interrupting the operation. +# The two thresholds default to null to disable. +# Min unit: B +# collection_size_warn_threshold: +# Min unit: B +# collection_size_fail_threshold: +# Guardrail to warn or fail when encountering more elements in collection than threshold. +# At query time this guardrail is applied only to the collection fragment that is being writen, even though in the case +# of non-frozen collections there could be unaccounted parts of the collection on the sstables. This is done this way to +# prevent read-before-write. The guardrail is also checked at sstable write time to detect large non-frozen collections, +# although in that case exceeding the fail threshold will only log an error message, without interrupting the operation. +# The two thresholds default to -1 to disable. +# items_per_collection_warn_threshold: -1 +# items_per_collection_fail_threshold: -1 +# Guardrail to allow/disallow querying with ALLOW FILTERING. Defaults to true. +# allow_filtering_enabled: true +# Guardrail to warn or fail when creating a user-defined-type with more fields in than threshold. +# Default -1 to disable. +# fields_per_udt_warn_threshold: -1 +# fields_per_udt_fail_threshold: -1 +# Guardrail to warn or fail when local data disk usage percentage exceeds threshold. Valid values are in [1, 100]. +# This is only used for the disks storing data directories, so it won't count any separate disks used for storing +# the commitlog, hints nor saved caches. The disk usage is the ratio between the amount of space used by the data +# directories and the addition of that same space and the remaining free space on disk. The main purpose of this +# guardrail is rejecting user writes when the disks are over the defined usage percentage, so the writes done by +# background processes such as compaction and streaming don't fail due to a full disk. The limits should be defined +# accordingly to the expected data growth due to those background processes, so for example a compaction strategy +# doubling the size of the data would require to keep the disk usage under 50%. +# The two thresholds default to -1 to disable. +# data_disk_usage_percentage_warn_threshold: -1 +# data_disk_usage_percentage_fail_threshold: -1 +# Allows defining the max disk size of the data directories when calculating thresholds for +# disk_usage_percentage_warn_threshold and disk_usage_percentage_fail_threshold, so if this is greater than zero they +# become percentages of a fixed size on disk instead of percentages of the physically available disk size. This should +# be useful when we have a large disk and we only want to use a part of it for Cassandra's data directories. +# Valid values are in [1, max available disk size of all data directories]. +# Defaults to null to disable and use the physically available disk size of data directories during calculations. +# Min unit: B +# data_disk_usage_max_disk_size: +# Guardrail to warn or fail when the minimum replication factor is lesser than threshold. +# This would also apply to system keyspaces. +# Suggested value for use in production: 2 or higher +# minimum_replication_factor_warn_threshold: -1 +# minimum_replication_factor_fail_threshold: -1 + +# Startup Checks are executed as part of Cassandra startup process, not all of them +# are configurable (so you can disable them) but these which are enumerated bellow. +# Uncomment the startup checks and configure them appropriately to cover your needs. +# +#startup_checks: +# Verifies correct ownership of attached locations on disk at startup. See CASSANDRA-16879 for more details. +# check_filesystem_ownership: +# enabled: false +# ownership_token: "sometoken" # (overriden by "CassandraOwnershipToken" system property) +# ownership_filename: ".cassandra_fs_ownership" # (overriden by "cassandra.fs_ownership_filename") +# Prevents a node from starting if snitch's data center differs from previous data center. +# check_dc: +# enabled: true # (overriden by cassandra.ignore_dc system property) +# Prevents a node from starting if snitch's rack differs from previous rack. +# check_rack: +# enabled: true # (overriden by cassandra.ignore_rack system property) +# Enable this property to fail startup if the node is down for longer than gc_grace_seconds, to potentially +# prevent data resurrection on tables with deletes. By default, this will run against all keyspaces and tables +# except the ones specified on excluded_keyspaces and excluded_tables. +# check_data_resurrection: +# enabled: false +# file where Cassandra periodically writes the last time it was known to run +# heartbeat_file: /var/lib/cassandra/data/cassandra-heartbeat +# excluded_keyspaces: # comma separated list of keyspaces to exclude from the check +# excluded_tables: # comma separated list of keyspace.table pairs to exclude from the check diff --git a/metadata-ingestion/tests/integration/cassandra/setup/init_keyspaces.cql b/metadata-ingestion/tests/integration/cassandra/setup/init_keyspaces.cql new file mode 100644 index 0000000000000..81e919461a55b --- /dev/null +++ b/metadata-ingestion/tests/integration/cassandra/setup/init_keyspaces.cql @@ -0,0 +1,131 @@ + +CREATE KEYSPACE cass_test_1 WITH REPLICATION = {'class': 'SimpleStrategy', 'replication_factor': 1}; +CREATE KEYSPACE cass_test_2 WITH REPLICATION = {'class': 'SimpleStrategy', 'replication_factor': 1}; + +CREATE TABLE cass_test_1.information ( + person_id int PRIMARY KEY, + last_updated timestamp, + details text +); + +CREATE TABLE cass_test_1.people ( + person_id int PRIMARY KEY, + name text, + email text +); + +CREATE TABLE cass_test_2.tasks ( + task_id int PRIMARY KEY, + last_updated timestamp, + details text, + status text +); + +CREATE MATERIALIZED VIEW cass_test_2.task_status AS +SELECT + task_id, + status +FROM cass_test_2.tasks +WHERE status IS NOT NULL AND task_id IS NOT NULL +PRIMARY KEY (task_id, status); + +-- Create Keyspace with comments +CREATE KEYSPACE IF NOT EXISTS example_keyspace +WITH replication = {'class': 'SimpleStrategy', 'replication_factor': 1}; + +-- Use Keyspace +USE example_keyspace; + +-- Table with non-counter column types +CREATE TABLE IF NOT EXISTS all_data_types ( + id uuid PRIMARY KEY, + ascii_column ascii, + bigint_column bigint, + blob_column blob, + boolean_column boolean, + date_column date, + decimal_column decimal, + double_column double, + float_column float, + inet_column inet, + int_column int, + list_column list, + map_column map, + set_column set, + smallint_column smallint, + text_column text, + time_column time, + timestamp_column timestamp, + timeuuid_column timeuuid, + tinyint_column tinyint, + tuple_column tuple, + uuid_column uuid, + varchar_column varchar, + varint_column varint, + frozen_map_column frozen>, + frozen_list_column frozen>, + frozen_set_column frozen> +) WITH COMMENT = 'Table containing all supported Cassandra data types, excluding counters'; + +-- Separate table for counters +CREATE TABLE IF NOT EXISTS counter_table ( + id uuid PRIMARY KEY, + counter_column counter +) WITH COMMENT = 'Separate table containing only counter column'; + +-- Sample view +CREATE MATERIALIZED VIEW IF NOT EXISTS example_view_1 AS + SELECT id, ascii_column, bigint_column + FROM all_data_types + WHERE id IS NOT NULL AND ascii_column IS NOT NULL + PRIMARY KEY (id, ascii_column) WITH COMMENT = 'Example view definition with id and ascii_column'; + +CREATE MATERIALIZED VIEW IF NOT EXISTS example_view_2 AS + SELECT id, ascii_column, float_column + FROM all_data_types + WHERE id IS NOT NULL AND ascii_column IS NOT NULL + PRIMARY KEY (id, ascii_column) WITH COMMENT = 'Example view definition with id and ascii_column'; + +-- Table created for profilling +CREATE TABLE IF NOT EXISTS shopping_cart ( +userid text PRIMARY KEY, +item_count int, +last_update_timestamp timestamp +); + +-- Insert some data +INSERT INTO shopping_cart +(userid, item_count, last_update_timestamp) +VALUES ('9876', 2, '2024-11-01T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, item_count, last_update_timestamp) +VALUES ('1234', 5, '2024-11-02T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, item_count, last_update_timestamp) +VALUES ('1235', 100, '2024-11-03T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, item_count, last_update_timestamp) +VALUES ('1236', 50, '2024-11-04T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, item_count, last_update_timestamp) +VALUES ('1237', 75, '2024-11-05T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, last_update_timestamp) +VALUES ('1238', '2024-11-06T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, last_update_timestamp) +VALUES ('1239', '2024-11-07T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, last_update_timestamp) +VALUES ('1240', '2024-11-08T00:00:00.000+0000'); + +INSERT INTO shopping_cart +(userid, last_update_timestamp) +VALUES ('1241', '2024-11-09T00:00:00.000+0000'); \ No newline at end of file diff --git a/metadata-ingestion/tests/integration/cassandra/test_cassandra.py b/metadata-ingestion/tests/integration/cassandra/test_cassandra.py new file mode 100644 index 0000000000000..d561308aaad20 --- /dev/null +++ b/metadata-ingestion/tests/integration/cassandra/test_cassandra.py @@ -0,0 +1,53 @@ +import logging +import time + +import pytest + +from datahub.ingestion.run.pipeline import Pipeline +from tests.test_helpers import mce_helpers +from tests.test_helpers.docker_helpers import wait_for_port + +logger = logging.getLogger(__name__) + + +@pytest.mark.integration +def test_cassandra_ingest(docker_compose_runner, pytestconfig, tmp_path): + test_resources_dir = pytestconfig.rootpath / "tests/integration/cassandra" + + with docker_compose_runner( + test_resources_dir / "docker-compose.yml", "cassandra" + ) as docker_services: + wait_for_port(docker_services, "test-cassandra", 9042) + + time.sleep(5) + # Run the metadata ingestion pipeline. + logger.info("Starting the ingestion test...") + pipeline_default_platform_instance = Pipeline.create( + { + "run_id": "cassandra-test", + "source": { + "type": "cassandra", + "config": { + "contact_point": "localhost", + "port": 9042, + "profiling": {"enabled": True}, + }, + }, + "sink": { + "type": "file", + "config": { + "filename": f"{tmp_path}/cassandra_mcps.json", + }, + }, + } + ) + pipeline_default_platform_instance.run() + pipeline_default_platform_instance.raise_from_status() + + # Verify the output. + logger.info("Verifying output.") + mce_helpers.check_golden_file( + pytestconfig, + output_path=f"{tmp_path}/cassandra_mcps.json", + golden_path=test_resources_dir / "cassandra_mcps_golden.json", + ) diff --git a/metadata-ingestion/tests/unit/test_cassandra_source.py b/metadata-ingestion/tests/unit/test_cassandra_source.py new file mode 100644 index 0000000000000..a4ca3a0a9ef3f --- /dev/null +++ b/metadata-ingestion/tests/unit/test_cassandra_source.py @@ -0,0 +1,81 @@ +import json +import logging +import re +from typing import Any, Dict, List, Tuple + +import pytest + +from datahub.ingestion.source.cassandra.cassandra import CassandraToSchemaFieldConverter +from datahub.ingestion.source.cassandra.cassandra_api import CassandraColumn +from datahub.metadata.com.linkedin.pegasus2avro.schema import SchemaField + +logger = logging.getLogger(__name__) + + +def assert_field_paths_are_unique(fields: List[SchemaField]) -> None: + fields_paths = [f.fieldPath for f in fields if re.match(".*[^]]$", f.fieldPath)] + + if fields_paths: + assert len(fields_paths) == len(set(fields_paths)) + + +def assert_field_paths_match( + fields: List[SchemaField], expected_field_paths: List[str] +) -> None: + logger.debug('FieldPaths=\n"' + '",\n"'.join(f.fieldPath for f in fields) + '"') + assert len(fields) == len(expected_field_paths) + for f, efp in zip(fields, expected_field_paths): + assert f.fieldPath == efp + assert_field_paths_are_unique(fields) + + +# TODO: cover one for every item on https://cassandra.apache.org/doc/stable/cassandra/cql/types.html (version 4.1) +schema_test_cases: Dict[str, Tuple[str, List[str]]] = { + "all_types_on_4.1": ( + """{ + "column_infos": [ + {"keyspace_name": "playground", "table_name": "people", "column_name": "birthday", "clustering_order": "none", "column_name_bytes": null, "kind": "regular", "position": -1, "type": "timestamp"}, + {"keyspace_name": "playground", "table_name": "people", "column_name": "email", "clustering_order": "none", "column_name_bytes": null, "kind": "partition_key", "position": 0, "type": "text"}, + {"keyspace_name": "playground", "table_name": "people", "column_name": "name", "clustering_order": "none", "column_name_bytes": null, "kind": "regular", "position": -1, "type": "text"} + ] + }""", + [ + "birthday", + "email", + "name", + ], + ) +} + + +@pytest.mark.parametrize( + "schema, expected_field_paths", + schema_test_cases.values(), + ids=schema_test_cases.keys(), +) +def test_cassandra_schema_conversion( + schema: str, expected_field_paths: List[str] +) -> None: + + schema_dict: Dict[str, List[Any]] = json.loads(schema) + column_infos: List = schema_dict["column_infos"] + + column_list: List[CassandraColumn] = [ + CassandraColumn( + keyspace_name=row["keyspace_name"], + table_name=row["table_name"], + column_name=row["column_name"], + clustering_order=row["clustering_order"], + kind=row["kind"], + position=row["position"], + type=row["type"], + ) + for row in column_infos + ] + actual_fields = list(CassandraToSchemaFieldConverter.get_schema_fields(column_list)) + assert_field_paths_match(actual_fields, expected_field_paths) + + +def test_no_properties_in_mappings_schema() -> None: + fields = list(CassandraToSchemaFieldConverter.get_schema_fields([])) + assert fields == [] diff --git a/metadata-integration/java/as-a-library.md b/metadata-integration/java/as-a-library.md index dea0a2c94545e..907b331b8bd96 100644 --- a/metadata-integration/java/as-a-library.md +++ b/metadata-integration/java/as-a-library.md @@ -67,8 +67,8 @@ MetadataChangeProposalWrapper mcpw = MetadataChangeProposalWrapper.builder() .aspect(new DatasetProperties().setDescription("This is the canonical User profile dataset")) .build(); -// Blocking call using future -Future requestFuture = emitter.emit(mcpw, null).get(); +// Blocking call using Future.get() +MetadataWriteResponse requestFuture = emitter.emit(mcpw, null).get(); // Non-blocking using callback emitter.emit(mcpw, new Callback() { diff --git a/metadata-models/src/main/pegasus/com/linkedin/entitytype/EntityTypeKey.pdl b/metadata-models/src/main/pegasus/com/linkedin/entitytype/EntityTypeKey.pdl index d857c7ff611e3..6a87c3d63cbd9 100644 --- a/metadata-models/src/main/pegasus/com/linkedin/entitytype/EntityTypeKey.pdl +++ b/metadata-models/src/main/pegasus/com/linkedin/entitytype/EntityTypeKey.pdl @@ -7,5 +7,6 @@ record EntityTypeKey { /** * A unique id for an entity type. Usually this will be a unique namespace + entity name. */ + @Searchable = {} id: string } diff --git a/metadata-service/configuration/src/main/resources/bootstrap_mcps/data-platforms.yaml b/metadata-service/configuration/src/main/resources/bootstrap_mcps/data-platforms.yaml index f480ec862bc4e..1625df4a99540 100644 --- a/metadata-service/configuration/src/main/resources/bootstrap_mcps/data-platforms.yaml +++ b/metadata-service/configuration/src/main/resources/bootstrap_mcps/data-platforms.yaml @@ -717,3 +717,13 @@ displayName: Dremio type: QUERY_ENGINE logoUrl: "/assets/platforms/dremiologo.png" +- entityUrn: urn:li:dataPlatform:cassandra + entityType: dataPlatform + aspectName: dataPlatformInfo + changeType: UPSERT + aspect: + datasetNameDelimiter: "." + name: cassandra + displayName: Cassandra + type: KEY_VALUE_STORE + logoUrl: "/assets/platforms/cassandralogo.png"