feat(cli): Adds ability to upload recipes to DataHub's UI

datahub-graphql-core/src/main/java/com/linkedin/datahub/graphql/resolvers/ingest/source/ListIngestionSourcesResolver.java

@@ -4,6 +4,7 @@
 import com.linkedin.common.urn.Urn;
 import com.linkedin.datahub.graphql.QueryContext;
 import com.linkedin.datahub.graphql.exception.AuthorizationException;
+import com.linkedin.datahub.graphql.generated.FacetFilterInput;
 import com.linkedin.datahub.graphql.generated.ListIngestionSourcesInput;
 import com.linkedin.datahub.graphql.generated.ListIngestionSourcesResult;
 import com.linkedin.datahub.graphql.resolvers.ingest.IngestionAuthUtils;
@@ -20,6 +21,7 @@
 import java.util.Collections;
 import java.util.Comparator;
 import java.util.HashSet;
+import java.util.List;
 import java.util.Map;
 import java.util.concurrent.CompletableFuture;
 import java.util.stream.Collectors;
@@ -51,14 +53,16 @@ public CompletableFuture<ListIngestionSourcesResult> get(final DataFetchingEnvir
       final Integer start = input.getStart() == null ? DEFAULT_START : input.getStart();
       final Integer count = input.getCount() == null ? DEFAULT_COUNT : input.getCount();
       final String query = input.getQuery() == null ? DEFAULT_QUERY : input.getQuery();
+      final List<FacetFilterInput> filters = input.getFilters() == null ? Collections.emptyList() : input.getFilters();
 
       return CompletableFuture.supplyAsync(() -> {
         try {
           // First, get all ingestion sources Urns.
           final SearchResult gmsResult = _entityClient.search(
               Constants.INGESTION_SOURCE_ENTITY_NAME,
               query,
-              Collections.emptyMap(),
+              buildFilter(filters, Collections.emptyList()),
+              null,
               start,
               count,
               context.getAuthentication(),

datahub-graphql-core/src/main/resources/ingestion.graphql

@@ -428,6 +428,11 @@ input ListIngestionSourcesInput {
   An optional search query
   """
   query: String
+
+  """
+  Optional Facet filters to apply to the result set
+  """
+  filters: [FacetFilterInput!]
 }
 
 """

datahub-graphql-core/src/test/java/com/linkedin/datahub/graphql/resolvers/ingest/source/ListIngestionSourceResolverTest.java

@@ -19,7 +19,6 @@
 import com.linkedin.metadata.search.SearchResult;
 import com.linkedin.r2.RemoteInvocationException;
 import graphql.schema.DataFetchingEnvironment;
-import java.util.Collections;
 import java.util.HashSet;
 import org.mockito.Mockito;
 import org.testng.annotations.Test;
@@ -30,7 +29,7 @@
 
 public class ListIngestionSourceResolverTest {
 
-  private static final ListIngestionSourcesInput TEST_INPUT = new ListIngestionSourcesInput(0, 20, null);
+  private static final ListIngestionSourcesInput TEST_INPUT = new ListIngestionSourcesInput(0, 20, null, null);
 
   @Test
   public void testGetSuccess() throws Exception {
@@ -44,7 +43,8 @@ public void testGetSuccess() throws Exception {
     Mockito.when(mockClient.search(
         Mockito.eq(Constants.INGESTION_SOURCE_ENTITY_NAME),
         Mockito.eq(""),
-        Mockito.eq(Collections.emptyMap()),
+        Mockito.any(),
+        Mockito.any(),
         Mockito.eq(0),
         Mockito.eq(20),
         Mockito.any(Authentication.class),

docs/cli.md

@@ -92,13 +92,29 @@ Source specific crawlers are provided by plugins and might sometimes need additi
 Usage: datahub [datahub-options] ingest [command-options]
 
 Command Options:
-  -c / --config        Config file in .toml or .yaml format
-  -n / --dry-run       Perform a dry run of the ingestion, essentially skipping writing to sink
-  --preview            Perform limited ingestion from the source to the sink to get a quick preview
-  --preview-workunits  The number of workunits to produce for preview
-  --strict-warnings    If enabled, ingestion runs with warnings will yield a non-zero error code
+  -c / --config             Config file in .toml or .yaml format
+  -n / --dry-run            Perform a dry run of the ingestion, essentially skipping writing to sink
+  --preview                 Perform limited ingestion from the source to the sink to get a quick preview
+  --preview-workunits       The number of workunits to produce for preview
+  --strict-warnings         If enabled, ingestion runs with warnings will yield a non-zero error code
+  --test-source-connection  When set, ingestion will only test the source connection details from the recipe
 ```
 
+#### ingest deploy
+
+The `ingest deploy` command instructs the cli to upload an ingestion recipe to DataHub to be run by DataHub's [UI Ingestion](./ui-ingestion.md).
+This command can also be used to schedule the ingestion while uploading or even to update existing sources.
+
+To schedule a recipe called "test", to run at 5am everyday, London time with the recipe configured in a local `recipe.yaml` file: 
+````shell
+datahub ingest deploy --name "test" --schedule "5 * * * *" --time-zone "Europe/London" -c recipe.yaml
+````
+
+To update an existing recipe please use the `--urn` parameter to specify the id of the recipe to update.
+
+**Note:** Updating a recipe will result in a replacement of the existing options with what was specified in the cli command.
+I.e: Not specifying a schedule in the cli update command will remove the schedule from the recipe to be updated.
+
 ### init
 
 The init command is used to tell `datahub` about where your DataHub instance is located. The CLI will point to localhost DataHub by default.

docs/ui-ingestion.md

@@ -28,6 +28,9 @@ your first **Ingestion Source**.
 
 ### Creating an Ingestion Source
 
+<Tabs>
+  <TabItem value="ui" label="UI" default>
+
 Before ingesting any metadata, you need to create a new Ingestion Source. Start by clicking **+ Create new source**.
 
 ![](./imgs/create-new-ingestion-source-button.png)
@@ -151,6 +154,45 @@ _Pinning the CLI version to version `0.8.23.2`_
 
 Once you're happy with your changes, simply click 'Done' to save. 
 
+   </TabItem>
+   <TabItem value="cli" label="CLI" default>
+
+You can upload and even update recipes using the cli as mentioned in the [cli documentation for uploading ingestion recipes](./cli.md#ingest-deploy).
+An example execution would look something like:
+
+```bash
+datahub ingest deploy --name "My Test Ingestion Source" --schedule "5 * * * *" --time-zone "UTC" -c recipe.yaml
+```
+
+This would create a new recipe with the name `My Test Ingestion Source`. Note that to update an existing recipe, it's `urn` id must be passed as a parameter.
+DataHub supports having multiple recipes with the same name so to distinguish them we use the urn for unique identification.
+
+   </TabItem>
+   <TabItem value="graphql" label="GraphQL" default>
+
+Create ingestion sources using [DataHub's GraphQL API](./api/graphql/overview.md) using the **createIngestionSource** mutation endpoint.
+```graphql
+mutation {
+   createIngestionSource(input: {
+      name: "My Test Ingestion Source",
+      type: "mysql",
+      description: "My ingestion source description",
+      schedule: {interval: "*/5 * * * *", timezone: "UTC"},
+      config: {
+         recipe: "{\"source\":{\"type\":\"mysql\",\"config\":{\"include_tables\":true,\"database\":null,\"password\":\"${MYSQL_PASSWORD}\",\"profiling\":{\"enabled\":false},\"host_port\":null,\"include_views\":true,\"username\":\"${MYSQL_USERNAME}\"}},\"pipeline_name\":\"urn:li:dataHubIngestionSource:f38bd060-4ea8-459c-8f24-a773286a2927\"}",
+         version: "0.8.18",
+         executorId: "mytestexecutor",
+      }
+   })
+}
+```
+
+To update sources, please use the `updateIngestionSource` endpoint. It is almost identical to the create endpoint, only requiring the urn of the source to be updated in addition to the same input as the create endpoint.
+
+**Note**: Recipe must be double quotes escaped
+
+   </TabItem>
+</Tabs>
 
 ### Running an Ingestion Source
 

metadata-ingestion/README.md

@@ -161,6 +161,19 @@ reporting:
       report_recipe: false
 ```
 
+#### Deploying and scheduling ingestion to the UI
+
+The `deploy` subcommand of the `ingest` command tree allows users to upload their recipes and schedule them in the server.
+
+```shell
+datahub ingest deploy -n <user friendly name for ingestion> -c recipe.yaml
+```
+
+By default, no schedule is done unless explicitly configured with the `--schedule` parameter. Timezones are inferred from the system time, can be overriden with `--time-zone` flag.
+```shell
+datahub ingest deploy -n test --schedule "0 * * * *" --time-zone "Europe/London" -c recipe.yaml
+```
+
 ## Transformations
 
 If you'd like to modify data before it reaches the ingestion sinks – for instance, adding additional owners or tags – you can use a transformer to write your own module and integrate it with DataHub. Transformers require extending the recipe with a new section to describe the transformers that you want to run.

metadata-ingestion/setup.py

@@ -412,6 +412,7 @@ def get_long_description():
     "types-termcolor>=1.0.0",
     "types-Deprecated",
     "types-protobuf>=4.21.0.1",
+    "types-tzlocal",
 }
 
 

metadata-ingestion/src/datahub/cli/ingest_cli.py

@@ -4,11 +4,13 @@
 import logging
 import os
 import sys
+import textwrap
 from datetime import datetime
 from typing import Optional
 
 import click
 import click_spinner
+import tzlocal
 from click_default_group import DefaultGroup
 from tabulate import tabulate
 
@@ -21,6 +23,7 @@
     post_rollback_endpoint,
 )
 from datahub.configuration.config_loader import load_config_file
+from datahub.ingestion.graph.client import get_default_graph
 from datahub.ingestion.run.connection import ConnectionManager
 from datahub.ingestion.run.pipeline import Pipeline
 from datahub.telemetry import telemetry
@@ -198,6 +201,156 @@ async def run_ingestion_and_check_upgrade() -> int:
     # don't raise SystemExit if there's no error
 
 
+@ingest.command()
+@upgrade.check_upgrade
+@telemetry.with_telemetry()
+@click.option(
+    "-n",
+    "--name",
+    type=str,
+    help="Recipe Name",
+    required=True,
+)
+@click.option(
+    "-c",
+    "--config",
+    type=click.Path(dir_okay=False),
+    help="Config file in .toml or .yaml format.",
+    required=True,
+)
+@click.option(
+    "--urn",
+    type=str,
+    help="Urn of recipe to update",
+    required=False,
+)
+@click.option(
+    "--executor-id",
+    type=str,
+    default="default",
+    help="Executor id to route execution requests to. Do not use this unless you have configured a custom executor.",
+    required=False,
+)
+@click.option(
+    "--cli-version",
+    type=str,
+    help="Provide a custom CLI version to use for ingestion. By default will use server default.",
+    required=False,
+    default=None,
+)
+@click.option(
+    "--schedule",
+    type=str,
+    help="Cron definition for schedule. If none is provided, ingestion recipe will not be scheduled",
+    required=False,
+    default=None,
+)
+@click.option(
+    "--time-zone",
+    type=str,
+    help=f"Timezone for the schedule. By default uses the timezone of the current system: {tzlocal.get_localzone_name()}.",
+    required=False,
+    default=tzlocal.get_localzone_name(),
+)
+def deploy(
+    name: str,
+    config: str,
+    urn: str,
+    executor_id: str,
+    cli_version: str,
+    schedule: str,
+    time_zone: str,
+) -> None:
+    """
+    Deploy an ingestion recipe to your DataHub instance.
+
+    The urn of the ingestion source will be based on the name parameter in the format:
+    urn:li:dataHubIngestionSource:<name>
+    """
+
+    datahub_graph = get_default_graph()
+
+    pipeline_config = load_config_file(
+        config,
+        allow_stdin=True,
+        resolve_env_vars=False,
+    )
+
+    graphql_query: str
+
+    variables: dict = {
+        "urn": urn,
+        "name": name,
+        "type": pipeline_config["source"]["type"],
+        "schedule": {"interval": schedule, "timezone": time_zone},
+        "recipe": json.dumps(pipeline_config),
+        "executorId": executor_id,
+        "version": cli_version,
+    }
+
+    if urn:
+        if not datahub_graph.exists(urn):
+            logger.error(f"Could not find recipe for provided urn: {urn}")
+            exit()
+        logger.info("Found recipe URN, will update recipe.")
+
+        graphql_query = textwrap.dedent(
+            """
+            mutation updateIngestionSource(
+                $urn: String!,
+                $name: String!,
+                $type: String!,
+                $schedule: UpdateIngestionSourceScheduleInput,
+                $recipe: String!,
+                $executorId: String!
+                $version: String) {
+
+                updateIngestionSource(urn: $urn, input: {
+                    name: $name,
+                    type: $type,
+                    schedule: $schedule,
+                    config: {
+                        recipe: $recipe,
+                        executorId: $executorId,
+                        version: $version,
+                    }
+                })
+            }
+            """
+        )
+    else:
+        logger.info("No URN specified recipe urn, will create a new recipe.")
+        graphql_query = textwrap.dedent(
+            """
+            mutation createIngestionSource(
+                $name: String!,
+                $type: String!,
+                $schedule: UpdateIngestionSourceScheduleInput,
+                $recipe: String!,
+                $executorId: String!,
+                $version: String) {
+
+                createIngestionSource(input: {
+                    type: $type,
+                    schedule: $schedule,
+                    config: {
+                        recipe: $recipe,
+                        executorId: $executorId,
+                        version: $version,
+                    }
+                })
+            }
+            """
+        )
+
+    response = datahub_graph.execute_graphql(graphql_query, variables=variables)
+
+    click.echo(
+        f"✅ Successfully wrote data ingestion source metadata for recipe {name}:"
+    )
+    click.echo(response)
+
+
 def _test_source_connection(report_to: Optional[str], pipeline_config: dict) -> None:
     connection_report = None
     try:

metadata-ingestion/src/datahub/configuration/config_loader.py

@@ -72,6 +72,7 @@ def load_config_file(
     squirrel_original_config: bool = False,
     squirrel_field: str = "__orig_config",
     allow_stdin: bool = False,
+    resolve_env_vars: bool = True,
 ) -> dict:
     config_mech: ConfigurationMechanism
     if allow_stdin and config_file == "-":
@@ -104,7 +105,10 @@ def load_config_file(
 
     config_fp = io.StringIO(raw_config_file)
     raw_config = config_mech.load_config(config_fp)
-    config = resolve_env_variables(raw_config)
+    if resolve_env_vars:
+        config = resolve_env_variables(raw_config)
+    else:
+        config = raw_config
     if squirrel_original_config:
         config[squirrel_field] = raw_config
     return config