diff --git a/.github/codeql/javascript-config.yml b/.github/codeql/javascript-config.yml new file mode 100644 index 00000000..4631b043 --- /dev/null +++ b/.github/codeql/javascript-config.yml @@ -0,0 +1,4 @@ +name: "CodeQL config for Javascript" + +paths: + - frontend/src/** diff --git a/.github/codeql/python-config.yml b/.github/codeql/python-config.yml new file mode 100644 index 00000000..25903f95 --- /dev/null +++ b/.github/codeql/python-config.yml @@ -0,0 +1 @@ +name: "CodeQL config for Python" diff --git a/.github/workflows/codeql-analysis.yml b/.github/workflows/codeql-analysis.yml new file mode 100644 index 00000000..fb76d794 --- /dev/null +++ b/.github/workflows/codeql-analysis.yml @@ -0,0 +1,58 @@ +name: "CodeQL" + +on: + push: + branches: [ main, 'b[0-9].[0-9]+' ] + pull_request: + # The branches below must be a subset of the branches above + branches: [ main, 'b[0-9].[0-9]+' ] + +jobs: + analyze: + name: Analyze + runs-on: ubuntu-latest + permissions: + actions: read + contents: read + security-events: write + + strategy: + fail-fast: false + matrix: + language: [ 'javascript', 'python' ] + # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ] + # Learn more about CodeQL language support at https://git.io/codeql-language-support + + steps: + - name: Checkout repository + uses: actions/checkout@v3 + + # Initializes the CodeQL tools for scanning. + - name: Initialize CodeQL + uses: github/codeql-action/init@v2 + with: + languages: ${{ matrix.language }} + config-file: ./.github/codeql/${{ matrix.language }}-config.yml + # If you wish to specify custom queries, you can do so here or in a config file. + # By default, queries listed here will override any specified in a config file. + # Prefix the list here with "+" to use these queries and those in the config file. + # queries: ./path/to/local/query, your-org/your-repo/queries@main + + # Autobuild attempts to build any compiled languages (C/C++, C#, or Java). + # If this step fails, then you should remove it and run the build manually (see below) + #- name: Autobuild + # uses: github/codeql-action/autobuild@v2 + + # ℹī¸ Command-line programs to run using the OS shell. + # 📚 https://git.io/JvXDl + + # ✏ī¸ If the Autobuild fails above, remove it and uncomment the following three lines + # and modify them (or add more) to build your code if your project + # uses a compiled language + + #- run: | + # make bootstrap + # make release + + - name: Perform CodeQL Analysis + uses: github/codeql-action/analyze@v2 diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml new file mode 100644 index 00000000..bc5c09cf --- /dev/null +++ b/.github/workflows/test.yaml @@ -0,0 +1,47 @@ +name: Python checks + +on: + push: + branches: ["main"] + tags-ignore: ["**"] + pull_request: + +env: + COVERAGE: ${{ github.workspace }}/coverage + +jobs: + build: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ["3.9.20"] + + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python-version }} + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install tox>=4.19 + - name: Check for lint + # Report errors but don't fail until we achieve stability! + continue-on-error: true + run: | + cd backend + tox -e format,isort,lint + - name: Run unit tests + run: | + cd backend + tox -e unit + - name: Add coverage data to conversation + run: cat $COVERAGE/coverage.txt >> $GITHUB_STEP_SUMMARY + - name: Publish coverage data + uses: actions/upload-artifact@v4 + with: + name: Coverage for ${{ github.event.head_commit.id }} + path: ${{ env.COVERAGE }}/html + if-no-files-found: warn + retention-days: 30 diff --git a/backend/app/services/crucible_readme.md b/backend/app/services/crucible_readme.md new file mode 100644 index 00000000..0ac2e71f --- /dev/null +++ b/backend/app/services/crucible_readme.md @@ -0,0 +1,164 @@ +Crucible divides data across a set of OpenSearch (or ElasticSearch) indices, +each with a specific document mapping. CDM index names include a "root" name +(like "run") with a versioned prefix, like "cdmv7dev-run". + +Crucible timestamps are integers in "millisecond-from-the-epoch" format. + +The Crucible CDM hierarchy is roughly: + +- RUN (an instrumented benchmark run) + - TAG (metadata) + - ITERATION (a benchmark interval) + - PARAM (execution parameters) + - SAMPLE + - PERIOD (time range where data is recorded) + - METRIC_DESC (description of a specific recorded metric) + - METRIC_DATA (a specific recorded data point) + +OpenSearch doesn't support the concept of a SQL "join", but many of the indices +contain documents that could be considered a static "join" with parent documents +for convenience. For example, each `iteration` document contains a copy of it's +parent `run` document, while the `period` document contains copies of its parent +`sample`, `iteration`, and `run` documents. This means, for example, that it's +possible to make a single query returning all `period` documents for specific +iteration number of a specific run. + +
+
RUN
this contains the basic information about a performance run, including a + generated UUID, begin and end timestamps, a benchmark name, a user name and + email, the (host/directory) "source" of the indexed data (which is usable on + the controler's local file system), plus host and test harness names.
+
TAG
this contains information about a general purpose "tag" to associate some + arbitrary context with a run, for example software versions, hardware, or + other metadata. This can be considered a SQL JOIN with the run document, + adding a tag UUID, name, and value.
+
ITERATION
this contains basic information about a performance run iteration, + including the iteration UUID, number, the primary (benchmark) metric associated + with the iteration, plus the primary "period" of the iteration, and the + iteration status.
+
PARAM
this defines a key/value pair specifying behavior of the benchmark + script for an iteration. Parameters are iteration-specific, but parameters that + don't vary between iterations are often represented as run parameters.
+
SAMPLE
this contains basic information about a sample of an iteration, + including a sample UUID and sample number, along with a "path" for sample data + and a sample status.
+
PERIOD
this contains basic information about a period during which data is + collected within a sample, including the period UUID, name, and begin and end + timestamps. A set of periods can be "linked" through a "prev_id" field.
+
METRIC_DESC
this contains descriptive data about a specific series + of metric values within a specific period of a run, including the metric UUID, + the metric "class", type, and source, along with a set of "names" (key/value + pairs) defining the metric breakout details that narrow down a specific source and + type. For example source:mpstat, type:Busy-CPU data is broken down by package, cpu, + core, and other breakouts which can be isolated or aggregated for data reporting.
+
METRIC_DATA
this describes a specific data point, sampled over a specified + duration with a fixed begin and end timestamp, plus a floating point value. + Each is tied to a specific metric_desc UUID value. Depending on the varied + semantics of metric_desc breakouts, it's often valid to aggregate these + across a set of relatead metric_desc IDs, based on source and type, for + example to get aggregate CPU load across all modes, cores, or across all + modes within a core. This service allows arbitrary aggregation within a + given metric source and type, but by default will attempt to direct the + caller to specifying a set of breakouts that result in a single metric_desc + ID.
+
+ +The `crucible_svc` allows CPT project APIs to access a Crucible CDM backing +store to find information about runs, tags, params, iterations, samples, +periods, plus various ways to expose and aggregate metric data both for +primary benchmarks and non-periodic tools. + +The `get_runs` API is the primary entry point, returning an object that +supports filtering, sorting, and pagination of the Crucible run data decorated +with useful iteration, tag, and parameter data. + +The metrics data APIs (data, breakouts, summary, and graph) now allow +filtering by the metric "name" data. This allows "drilling down" through +the non-periodic "tool data". For example, IO data is per-disk, CPU +information is broken down by core and package. You can now aggregate +all global data (e.g., total system CPU), or filter by breakout names to +select by CPU, mode (usr, sys, irq), etc. + +For example, to return `Busy-CPU` ("type") graph data from the `mpstat` +("source") tool for system mode on one core, you might query: + +``` +/api/v1/ilab/runs//graph/mpstat::Busy-CPU?name=core=12,package=1,num=77,type=sys +``` + +If you make a `graph`, `data`, or `summary` query that doesn't translate +to a unique metric, and don't select aggregation, you'll get a diagnostic +message identifying possible additional filters. For example, with +`type=sys` removed, that same query will show the available values for +the `type` breakout name: + +``` +{ + "detail": [ + { + "message": "More than one metric (5) probably means you should add filters", + "names": { + "type": [ + "guest", + "irq", + "soft", + "sys", + "usr" + ] + }, + "periods": [] + } + ] +} +``` + +This capability can be used to build an interactive exploratory UI to +allow displaying breakout details. The `get_metrics` API will show all +recorded metrics, along with information the names and values used in +those. Metrics that show "names" with more than one value will need to be +filtered to produce meaningful summaries or graphs. + +You can instead aggregate metrics across breakouts using the `?aggregate` +query parameter, like `GET /api/v1/ilab/runs//graph/mpstat::Busy-CPU?aggregate` +which will aggregate all CPU busy data for the system. + +Normally you'll want to display data based on sample periods, for example the +primary period of an iteration, using `?period=`. This will +implicitly constrain the metric data based on the period ID associated with +the `metric_desc` document *and* the begin/end time period of the selected +periods. Normally, a benchmark will will separate iterations because each is +run with a different parameter value, and the default graph labeling will +look for a set of distinct parameters not used by other iterations: for +example, `mpstat::Busy-CPU (batch-size=16)`. + +The `get_breakouts` API can be used to explore the namespace recorded for that +metric in the specified run. For example, + +``` +GET /api/v1/ilab/runs//breakouts/sar-net::packets-sec?name=direction=rx +{ + "label": "sar-net::packets-sec", + "source": "sar-net", + "type": "packets-sec", + "class": [], + "names": { + "dev": [ + "lo", + "eno12409", + "eno12399" + ], + "type": [ + "physical", + "virtual" + ] + } +} +``` + +The `get_filters` API reports all the tag and param filter tags and +values for the runs. These can be used for the `filters` query parameter +on `get_runs` to restrict the set of runs reported; for example, +`/api/v1/ilab/runs?filter=param:workflow=sdg` shows only runs with the param +arg `workflow` set to the value `sdg`. You can search for a subset of the +string value using the operator "~" instead of "=". For example, +`?filter=param:user~user` will match `user` values of "A user" or "The user". diff --git a/backend/app/services/crucible_svc.py b/backend/app/services/crucible_svc.py new file mode 100644 index 00000000..3d20bd56 --- /dev/null +++ b/backend/app/services/crucible_svc.py @@ -0,0 +1,1965 @@ +"""Service to pull data from a Crucible CDM OpenSearch data store + +A set of helper methods to enable a project API to easily process data from a +Crucible controller's OpenSearch data backend. + +This includes paginated, filtered, and sorted lists of benchmark runs, along +access to the associated Crucible documents such as iterations, samples, and +periods. Metric data can be accessed by breakout names, or aggregated by +breakout subsets or collection periods as either raw data points, statistical +aggregate, or Plotly graph format for UI display. +""" + +from collections import defaultdict +from dataclasses import dataclass +from datetime import datetime, timezone +import logging +import time +from typing import Any, Iterator, Optional, Tuple, Union + +from elasticsearch import AsyncElasticsearch +from fastapi import HTTPException, status +from pydantic import BaseModel + +from app import config + + +class Graph(BaseModel): + """Describe a single graph + + This represents a JSON object provided by a caller through the get_graph + API to describe a specific metric graph. + + The default title (if the field is omitted) is the metric label with a + suffix denoting breakout values selected, any unique parameter values + in a selected iteration, and (if multiple runs are selected in any Graph + list) an indication of the run index. For example, + "mpstat::Busy-CPU [core=2,type=usr] (batch-size=16)". + + Fields: + metric: the metric label, "ilab::train-samples-sec" + aggregate: True to aggregate unspecified breakouts + color: CSS color string ("green" or "#008000") + names: Lock in breakouts + periods: Select metrics for specific test period(s) + run: Override the default run ID from GraphList + title: Provide a title for the graph. The default is a generated title + """ + + metric: str + aggregate: bool = False + color: Optional[str] = None + names: Optional[list[str]] = None + periods: Optional[list[str]] = None + run: Optional[str] = None + title: Optional[str] = None + + +class GraphList(BaseModel): + """Describe a set of overlaid graphs + + This represents a JSON object provided by a caller through the get_graph + API to introduce a set of constrained metrics to be graphed. The "run + ID" here provides a default for the embedded Graph objects, and can be + omitted if all Graph objects specify a run ID. (This is most useful to + select a set of graphs all for a single run ID.) + + Fields: + run: Specify the (default) run ID + name: Specify a name for the set of graphs + graphs: a list of Graph objects + """ + + run: Optional[str] = None + name: str + graphs: list[Graph] + + +@dataclass +class Point: + """Graph point + + Record the start & end timestamp and value of a metric data point + """ + + begin: int + end: int + value: float + + +COLOR_NAMES = [ + "black", + "aqua", + "blue", + "fuschia", + "gray", + "green", + "maroon", + "navy", + "olive", + "teal", + "silver", + "lightskyblue", + "mediumspringgreen", + "mistyrose", + "darkgoldenrod", + "cadetblue", + "chocolate", + "coral", + "brown", + "bisque", + "deeppink", + "sienna", +] + + +@dataclass +class Term: + namespace: str + key: str + value: str + + +class Parser: + """Help parsing filter expressions.""" + + def __init__(self, term: str): + """Construct an instance to help parse query parameter expressions + + These consist of a sequence of tokens separated by delimiters. Each + token may be quoted to allow matching against strings with spaces. + + For example, `param:name="A string"` + + Args: + term: A filter expression to parse + """ + self.buffer = term + self.context = term + self.offset = 0 + + def _next_token( + self, delimiters: list[str] = [], optional: bool = False + ) -> Tuple[str, Union[str, None]]: + """Extract the next token from an expression + + Tokens may be quoted; the quotes are removed. for example, the two + expressions `'param':"workflow"='"sdg"'` and `param:workflow:sdg` are + identical. + + Args: + delimiters: a list of delimiter characters + optional: whether the terminating delimiter is optional + + Returns: + A tuple consisting of the token and the delimiter (or None if + parsing reached the end of the expression and the delimiter was + optional) + """ + + @dataclass + class Quote: + open: int + quote: str + + quoted: list[Quote] = [] + next_char = None + token = "" + first_quote = None + for o in range(len(self.buffer)): + next_char = self.buffer[o] + if next_char in delimiters and not quoted: + self.buffer = self.buffer[o + 1 :] + self.offset += o + 1 + break + elif next_char in ('"', "'"): + if o == 0: + first_quote = next_char + if quoted and quoted[-1].quote == next_char: + quoted.pop() + else: + quoted.append(Quote(o, next_char)) + token += next_char + else: + next_char = None + if quoted: + q = quoted[-1] + c = self.context + i = q.open + self.offset + annotated = c[:i] + "[" + c[i] + "]" + c[i + 1 :] + raise HTTPException( + status.HTTP_400_BAD_REQUEST, f"Unterminated quote at {annotated!r}" + ) + + # If delimiters are specified, and not optional, then we didn't + # find one, and that's an error. + if not optional and delimiters: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + f"Missing delimiter from {','.join(delimiters)} after {token!r}", + ) + self.buffer = "" + self.offset = len(self.context) + return (token, next_char) if not first_quote else (token[1:-1], next_char) + + +class CommonParams: + """Help with sorting out parameters + + Parameter values are associated with iterations, but often a set of + parameters is common across all iterations of a run, and that set can + provide useful context. + + This helps to filter out identical parameters across a set of + iterations. + """ + + def __init__(self): + self.common: dict[str, Any] = {} + self.omit = set() + + def add(self, params: dict[str, Any]): + """Add a new iteration into the param set + + Mark all parameter keys which don't appear in all iterations, or which + have different values in at least one iteration, to be omitted from the + merged "common" param set. + + Args: + params: the param dictionary of an iteration + """ + if not self.common: + self.common.update(params) + else: + for k, v in self.common.items(): + if k not in self.omit and (k not in params or v != params[k]): + self.omit.add(k) + + def render(self) -> dict[str, Any]: + """Return a new param set with only common params""" + return {k: v for k, v in self.common.items() if k not in self.omit} + + +class CrucibleService: + """Support convenient generalized access to Crucible data + + This implements access to the "v7" Crucible "Common Data Model" through + OpenSearch queries. + """ + + # OpenSearch massive limit on hits in a single query + BIGQUERY = 262144 + + # Define the 'run' document fields that support general filtering via + # `?filter=:` + # + # TODO: this excludes 'desc', which isn't used by the ilab runs, and needs + # different treatment as it's a text field rather than a term. It's not an + # immediate priority for ilab, but may be important for general use. + RUN_FILTERS = ("benchmark", "email", "name", "source", "harness", "host") + + # Define the keywords for sorting. + DIRECTIONS = ("asc", "desc") + FIELDS = ( + "begin", + "benchmark", + "desc", + "email", + "end", + "harness", + "host", + "id", + "name", + "source", + ) + + # Set up a Logger at class level rather than at each instance creation + formatter = logging.Formatter( + "%(asctime)s %(process)d:%(thread)d %(levelname)s %(module)s:%(lineno)d %(message)s" + ) + handler = logging.StreamHandler() + handler.setFormatter(formatter) + logger = logging.getLogger("CrucibleService") + logger.addHandler(handler) + + def __init__(self, configpath: str = "crucible"): + """Initialize a Crucible CDM (OpenSearch) connection. + + Generally the `configpath` should be scoped, like `ilab.crucible` so + that multiple APIs based on access to distinct Crucible controllers can + coexist. + + Initialization includes making an "info" call to confirm and record the + server response. + + Args: + configpath: The Vyper config path (e.g., "ilab.crucible") + """ + self.cfg = config.get_config() + self.user = self.cfg.get(configpath + ".username") + self.password = self.cfg.get(configpath + ".password") + self.auth = (self.user, self.password) if self.user or self.password else None + self.url = self.cfg.get(configpath + ".url") + self.elastic = AsyncElasticsearch(self.url, basic_auth=self.auth) + self.logger.info("Initializing CDM V7 service to %s", self.url) + + @staticmethod + def _get_index(root: str) -> str: + """Expand the root index name to the full name""" + return "cdmv7dev-" + root + + @staticmethod + def _get(source: dict[str, Any], fields: list[str], default: Optional[Any] = None): + """Safely traverse nested dictionaries with a default value""" + r = source + last_missing = False + for f in fields: + last_missing = f not in r + r = r.get(f, {}) + return default if last_missing else r + + @staticmethod + def _split_list(alist: Optional[list[str]] = None) -> list[str]: + """Split a list of parameters + + For simplicity, the APIs supporting "list" query parameters allow + each element in the list to be a comma-separated list of strings. + For example, ["a", "b", "c"] is logically the same as ["a,b,c"]. + + This method normalizes the second form into first to simplify life for + consumers. + + Args: + alist: list of names or name lists + + Returns: + A simple list of options + """ + l: list[str] = [] + if alist: + for n in alist: + l.extend(n.split(",")) + return l + + @staticmethod + def _normalize_date(value: Optional[Union[int, str, datetime]]) -> int: + """Normalize date parameters + + The Crucible data model stores dates as string representations of an + integer "millseconds-from-epoch" value. To allow flexibility, this + Crucible service allows incoming dates to be specified as ISO-format + strings, as integers, or as the stringified integer. + + That is, "2024-09-12 18:29:35.123000+00:00", "1726165775123", and + 1726165775123 are identical. + + Args: + value: Representation of a date-time value + + Returns: + The integer milliseconds-from-epoch equivalent + """ + try: + if isinstance(value, int): + return value + elif isinstance(value, datetime): + return int(value.timestamp() * 1000.0) + else: + # If it's a stringified int, convert & return; otherwise try + # to decode as a date string. + try: + return int(value) + except ValueError: + pass + d = datetime.fromisoformat(value) + return int(d.timestamp() * 1000.0) + except Exception as e: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + f"Date representation {value} is not valid: {str(e)!r}", + ) + + @classmethod + def _hits( + cls, payload: dict[str, Any], fields: Optional[list[str]] = None + ) -> Iterator[dict[str, Any]]: + """Helper to iterate through OpenSearch query matches + + Iteratively yields the "_source" of each hit. As a convenience, can + yield a sub-object of "_source" ... for example, specifying the + optional "fields" as ["metric_desc", "id"] will yield the equivalent of + hit["_source"]["metric_desc"]["id"] + + Args: + payload: OpenSearch reponse payload + fields: Optional sub-fields of "_source" + + Returns: + Yields each object from the "greatest hits" list + """ + if "hits" not in payload or not isinstance(payload["hits"], dict): + raise HTTPException( + status_code=500, detail=f"Attempt to iterate hits for {payload}" + ) + hits = cls._get(payload, ["hits", "hits"], []) + for h in hits: + source = h["_source"] + yield source if not fields else cls._get(source, fields) + + @classmethod + def _aggs( + cls, payload: dict[str, Any], aggregation: str + ) -> Iterator[dict[str, Any]]: + """Helper to access OpenSearch aggregations + + Iteratively yields the name and value of each aggregation returned + by an OpenSearch query. This can also be used for nested aggregations + by specifying an aggregation object. + + Args: + payload: A JSON dict containing an "aggregations" field + + Returns: + Yields each aggregation from an aggregation bucket list + """ + if "aggregations" not in payload or not isinstance( + payload["aggregations"], dict + ): + raise HTTPException( + status_code=500, + detail=f"Attempt to iterate missing aggregations for {payload}", + ) + aggs = payload["aggregations"] + if aggregation not in aggs or not isinstance(aggs[aggregation], dict): + raise HTTPException( + status_code=500, + detail=f"Attempt to iterate missing aggregation {aggregation!r} for {payload}", + ) + for agg in cls._get(aggs, [aggregation, "buckets"], []): + yield agg + + @staticmethod + def _format_timestamp(timestamp: Union[str, int]) -> str: + """Convert stringified integer milliseconds-from-epoch to ISO date""" + try: + ts = int(timestamp) + except Exception as e: + CrucibleService.logger.warning( + "invalid timestamp %r: %r", timestamp, str(e) + ) + ts = 0 + return str(datetime.fromtimestamp(ts / 1000.00, timezone.utc)) + + @classmethod + def _format_data(cls, data: dict[str, Any]) -> dict[str, Any]: + """Helper to format a "metric_data" object + + Crucible stores the date, duration, and value as strings, so this + converts them to more useful values. The end timestamp is converted + to an ISO date-time string; the duration and value to floating point + numbers. + + Args: + data: a "metric_data" object + + Returns: + A neatly formatted "metric_data" object + """ + return { + "begin": cls._format_timestamp(data["begin"]), + "end": cls._format_timestamp(data["end"]), + "duration": int(data["duration"]) / 1000, + "value": float(data["value"]), + } + + @classmethod + def _format_period(cls, period: dict[str, Any]) -> dict[str, Any]: + """Helper to format a "period" object + + Crucible stores the date values as stringified integers, so this + converts the begin and end timestamps to ISO date-time strings. + + Args: + period: a "period" object + + Returns: + A neatly formatted "period" object + """ + return { + "begin": cls._format_timestamp(timestamp=period["begin"]), + "end": cls._format_timestamp(period["end"]), + "id": period["id"], + "name": period["name"], + } + + @classmethod + def _build_filter_options(cls, filter: Optional[list[str]] = None) -> Tuple[ + Optional[list[dict[str, Any]]], + Optional[list[dict[str, Any]]], + Optional[list[dict[str, Any]]], + ]: + """Build filter terms for tag and parameter filter terms + + Each term has the form ":". Any term + may be quoted: quotes are stripped and ignored. (This is generally only + useful on the to include spaces.) + + We support three namespaces: + param: Match against param index arg/val + tag: Match against tag index name/val + run: Match against run index fields + + We support two operators: + =: Exact match + ~: Partial match + + Args: + filter: list of filter terms like "param:key=value" + + Returns: + A set of OpenSearch filter object lists to detect missing + and matching documents for params, tags, and run fields. For + example, to select param:batch-size=12 results in the + following param filter list: + + [ + {' + dis_max': { + 'queries': [ + { + 'bool': { + 'must': [ + {'term': {'param.arg': 'batch-size'}}, + {'term': {'param.val': '12'}} + ] + } + } + ] + } + } + ] + """ + terms = defaultdict(list) + for term in cls._split_list(filter): + p = Parser(term) + namespace, _ = p._next_token([":"]) + key, operation = p._next_token(["=", "~"]) + value, _ = p._next_token() + if operation == "~": + value = f".*{value}.*" + matcher = "regexp" + else: + matcher = "term" + if namespace in ("param", "tag"): + if namespace == "param": + key_field = "param.arg" + value_field = "param.val" + else: + key_field = "tag.name" + value_field = "tag.val" + terms[namespace].append( + { + "bool": { + "must": [ + {"term": {key_field: key}}, + {matcher: {value_field: value}}, + ] + } + } + ) + elif namespace == "run": + terms[namespace].append({matcher: {f"run.{key}": value}}) + else: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + f"unknown filter namespace {namespace!r}", + ) + param_filter = None + tag_filter = None + if "param" in terms: + param_filter = [{"dis_max": {"queries": terms["param"]}}] + if "tag" in terms: + tag_filter = [{"dis_max": {"queries": terms["tag"]}}] + return param_filter, tag_filter, terms.get("run") + + @classmethod + def _build_name_filters( + cls, namelist: Optional[list[str]] = None + ) -> list[dict[str, Any]]: + """Build filter terms for metric breakout names + + for example, "cpu=10" filters for metric data descriptors where the + breakout name "cpu" exists and has a value of 10. + + Args: + namelist: list of possibly comma-separated list values + + Returns: + A list of filters to match breakout terms + """ + names: list[str] = cls._split_list(namelist) + filters = [] + for e in names: + try: + n, v = e.split("=", maxsplit=1) + except ValueError: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, f"Filter item {e!r} must be '='" + ) + filters.append({"term": {f"metric_desc.names.{n}": v}}) + return filters + + @classmethod + def _build_period_filters( + cls, periodlist: Optional[list[str]] = None + ) -> list[dict[str, Any]]: + """Build period filters + + Generate metric_desc filter terms to match against a list of period IDs. + + Note that not all metric descriptions are periodic, and we don't want + these filters to exclude them -- so the filter will exclude only + documents that have a period and don't match. (That is, we won't drop + any non-periodic metrics. We expect those to be filtered by timestamp + instead.) + + Args: + period: list of possibly comma-separated period IDs + + Returns: + A filter term that requires a period.id match only for metric_desc + documents with a period. + """ + pl: list[str] = cls._split_list(periodlist) + if pl: + return [ + { + "dis_max": { + "queries": [ + {"bool": {"must_not": {"exists": {"field": "period"}}}}, + {"terms": {"period.id": pl}}, + ] + } + } + ] + else: + return [] + + @classmethod + def _build_metric_filters( + cls, + run: str, + metric: str, + names: Optional[list[str]] = None, + periods: Optional[list[str]] = None, + ) -> list[dict[str, Any]]: + """Helper for filtering metric descriptions + + We normally filter by run, metric "label", and optionally by breakout + names and periods. This encapsulates the filter construction. + + Args: + run: run ID + metric: metric label (ilab::sdg-samples-sec) + names: list of "name=value" filters + periods: list of period IDs + + Returns: + A list of OpenSearch filter expressions + """ + msource, mtype = metric.split("::") + return ( + [ + {"term": {"run.id": run}}, + {"term": {"metric_desc.source": msource}}, + {"term": {"metric_desc.type": mtype}}, + ] + + cls._build_name_filters(names) + + cls._build_period_filters(periods) + ) + + @classmethod + def _build_sort_terms(cls, sorters: Optional[list[str]]) -> list[dict[str, Any]]: + """Build sort term list + + Sorters may reference any native `run` index field and must specify + either "asc"(ending) or "desc"(ending) sort order. Any number of + sorters may be combined, like ["name:asc,benchmark:desc", "end:desc"] + + Args: + sorters: list of : sort terms + + Returns: + list of OpenSearch sort terms + """ + if sorters: + sort_terms = [] + for s in sorters: + key, dir = s.split(":", maxsplit=1) + if dir not in cls.DIRECTIONS: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + f"Sort direction {dir!r} must be one of {','.join(cls.DIRECTIONS)}", + ) + if key not in cls.FIELDS: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + f"Sort key {key!r} must be one of {','.join(cls.FIELDS)}", + ) + sort_terms.append({f"run.{key}": {"order": dir}}) + else: + sort_terms = [{"run.begin": {"order": "asc"}}] + return sort_terms + + async def _search( + self, index: str, query: Optional[dict[str, Any]] = None, **kwargs + ) -> dict[str, Any]: + """Issue an OpenSearch query + + Args: + index: The "base" CDM index name, e.g., "run", "metric_desc" + query: An OpenSearch query object + kwargs: Additional OpenSearch parameters + + Returns: + The OpenSearch response payload (JSON dict) + """ + idx = self._get_index(index) + start = time.time() + value = await self.elastic.search(index=idx, body=query, **kwargs) + self.logger.info( + "QUERY on %s took %.3f seconds, hits: %d", + idx, + time.time() - start, + value.get("hits", {}).get("total"), + ) + return value + + async def close(self): + """Close the OpenSearch connection""" + if self.elastic: + await self.elastic.close() + self.elastic = None + + async def search( + self, + index: str, + filters: Optional[list[dict[str, Any]]] = None, + aggregations: Optional[dict[str, Any]] = None, + sort: Optional[list[dict[str, str]]] = None, + source: Optional[str] = None, + size: Optional[int] = None, + offset: Optional[int] = None, + **kwargs, + ) -> dict[str, Any]: + """OpenSearch query helper + + Combine index, filters, aggregations, sort, and pagination options + into an OpenSearch query. + + Args: + index: "root" CDM index name ("run", "metric_desc", ...) + filters: list of JSON dict filter terms {"term": {"name": "value}} + aggregations: list of JSON dict aggregations {"name": {"term": "name"}} + sort: list of JSON dict sort terms ("name": "asc") + size: The number of hits to return; defaults to "very large" + offset: The number of hits to skip, for pagination + kwargs: Additional OpenSearch options + + Returns: + The OpenSearch response + """ + f = filters if filters else [] + query = { + "size": self.BIGQUERY if size is None else size, + "query": {"bool": {"filter": f}}, + } + if sort: + query.update({"sort": sort}) + if source: + query.update({"_source": source}) + if offset: + query.update({"from": offset}) + if aggregations: + query.update({"aggs": aggregations}) + return await self._search(index, query, **kwargs) + + async def _get_metric_ids( + self, + run: str, + metric: str, + namelist: Optional[list[str]] = None, + periodlist: Optional[list[str]] = None, + aggregate: bool = False, + ) -> list[str]: + """Generate a list of matching metric_desc IDs + + Given a specific run and metric name, and a set of breakout filters, + returns a list of metric desc IDs that match. + + If a single ID is required to produce a consistent metric, and the + supplied filters produce more than one without aggregation, raise a + 422 HTTP error (UNPROCESSABLE CONTENT) with a response body showing + the unsatisfied breakouts (name and available values). + + TODO: Instead of either single metric or aggregation across multiple + metrics, we should support "breakouts", which would individually + process (graph, summarize, or list) data for each "loose" breakout + name. E.g., Busy-CPU might list per-core, or per-processor mode. + + Args: + run: run ID + metric: combined metric name (e.g., sar-net::packets-sec) + namelist: a list of breakout filters like "type=physical" + periodlist: a list of period IDs + aggregate: if True, allow multiple metric IDs + + Returns: + A list of matching metric_desc ID value(s) + """ + filters = self._build_metric_filters(run, metric, namelist, periodlist) + metrics = await self.search( + "metric_desc", + filters=filters, + ignore_unavailable=True, + ) + if len(metrics["hits"]["hits"]) < 1: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + ( + f"No matches for {metric}" + f"{('+' + ','.join(namelist) if namelist else '')}" + ), + ) + ids = [h["metric_desc"]["id"] for h in self._hits(metrics)] + if len(ids) < 2 or aggregate: + return ids + + # If we get here, the client asked for breakout data that doesn't + # resolve to a single metric stream, and didn't specify aggregation. + # Offer some help. + names = defaultdict(set) + periods = set() + response = { + "message": f"More than one metric ({len(ids)}) means " + "you should add breakout filters or aggregate." + } + for m in self._hits(metrics): + if "period" in m: + periods.add(m["period"]["id"]) + for n, v in m["metric_desc"]["names"].items(): + names[n].add(v) + + # We want to help filter a consistent summary, so only show those + # breakout names with more than one value. + response["names"] = {n: sorted(v) for n, v in names.items() if v and len(v) > 1} + response["periods"] = sorted(periods) + raise HTTPException( + status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=response + ) + + async def _build_timestamp_range_filters( + self, periods: Optional[list[str]] = None + ) -> list[dict[str, Any]]: + """Create a timestamp range filter + + This extracts the begin and end timestamps from the list of periods and + builds a timestamp filter range to select documents on or after the + earliest begin timestamp and on or before the latest end timestamp. + + Args: + periods: a list of CDM period IDs + + Returns: + Constructs a range filter for the earliest begin timestamp and the + latest end timestamp among the specified periods. + """ + if periods: + ps = self._split_list(periods) + matches = await self.search( + "period", filters=[{"terms": {"period.id": ps}}] + ) + start = None + end = None + name = "" + for h in self._hits(matches): + p = h["period"] + st = p.get("begin") + et = p.get("end") + if not st or not et: + name = ( + f"run {self._get(h, ['run', 'benchmark'])}:" + f"{self._get(h, ['run', 'begin'])}," + f"iteration {self._get(h, ['iteration', 'num'])}," + f"sample {self._get(h, ['sample', 'num'])}" + ) + if st and (not start or st < start): + start = st + if et and (not end or et > end): + end = et + if start is None or end is None: + raise HTTPException( + status.HTTP_422_UNPROCESSABLE_ENTITY, + f"Unable to compute {name!r} time range: the run is missing period timestamps", + ) + return [ + {"range": {"metric_data.begin": {"gte": str(start)}}}, + {"range": {"metric_data.end": {"lte": str(end)}}}, + ] + else: + return [] + + async def _get_run_ids( + self, index: str, filters: Optional[list[dict[str, Any]]] = None + ) -> set[str]: + """Return a set of run IDs matching a filter + + Documents in the specified index must have "run.id" fields. Returns + a set of unique run IDs matched by the filter in the specified index. + + Args: + index: root CDM index name + filters: a list of OpenSearch filter terms + + Returns: + a set of unique run ID values + """ + filtered = await self.search( + index, source="run.id", filters=filters, ignore_unavailable=True + ) + self.logger.debug("HITS: %s", filtered["hits"]["hits"]) + return set([x for x in self._hits(filtered, ["run", "id"])]) + + async def get_run_filters(self) -> dict[str, dict[str, list[str]]]: + """Return possible tag and filter terms + + Return a description of tag and param filter terms meaningful + across all datasets. TODO: we should support date-range and benchmark + filtering. Consider supporting all `run` API filtering, which would + allow adjusting the filter popups to drop options no longer relevant + to a given set. + + { + "param": { + {"gpus": [4", "8"]} + } + } + + Returns: + A two-level JSON dict; the first level is the namespace (param or + tag), the second level key is the param/tag/field name and its value + is the set of values defined for that key. + """ + tags = await self.search( + "tag", + size=0, + aggregations={ + "key": { + "terms": {"field": "tag.name", "size": self.BIGQUERY}, + "aggs": { + "values": {"terms": {"field": "tag.val", "size": self.BIGQUERY}} + }, + } + }, + ignore_unavailable=True, + ) + params = await self.search( + "param", + size=0, + aggregations={ + "key": { + "terms": {"field": "param.arg", "size": self.BIGQUERY}, + "aggs": { + "values": { + "terms": {"field": "param.val", "size": self.BIGQUERY} + } + }, + } + }, + ignore_unavailable=True, + ) + aggs = { + k: {"terms": {"field": f"run.{k}", "size": self.BIGQUERY}} + for k in self.RUN_FILTERS + } + runs = await self.search( + "run", + size=0, + aggregations=aggs, + ) + result = defaultdict(lambda: defaultdict(lambda: set())) + for p in self._aggs(params, "key"): + for v in p["values"]["buckets"]: + result["param"][p["key"]].add(v["key"]) + for t in self._aggs(tags, "key"): + for v in t["values"]["buckets"]: + result["tag"][t["key"]].add(v["key"]) + for name in self.RUN_FILTERS: + for f in self._aggs(runs, name): + result["run"][name].add(f["key"]) + return {s: {k: list(v) for k, v in keys.items()} for s, keys in result.items()} + + async def get_runs( + self, + filter: Optional[list[str]] = None, + start: Optional[Union[int, str, datetime]] = None, + end: Optional[Union[int, str, datetime]] = None, + offset: int = 0, + sort: Optional[list[str]] = None, + size: Optional[int] = None, + **kwargs, + ) -> dict[str, Any]: + """Return matching Crucible runs + + Filtered and sorted list of runs. + + { + "sort": [], + "startDate": "2024-01-01T05:00:00+00:00", + "size": 1, + "offset": 0, + "results": [ + { + "begin": "1722878906342", + "benchmark": "ilab", + "email": "A@email", + "end": "1722880503544", + "id": "4e1d2c3c-b01c-4007-a92d-23a561af2c11", + "name": "\"A User\"", + "source": "node.example.com//var/lib/crucible/run/ilab--2024-08-05_17:17:13_UTC--4e1d2c3c-b01c-4007-a92d-23a561af2c11", + "tags": { + "topology": "none" + }, + "iterations": [ + { + "iteration": 1, + "primary_metric": "ilab::train-samples-sec", + "primary_period": "measurement", + "status": "pass", + "params": { + "cpu-offload-pin-memory": "1", + "model": "/home/models/granite-7b-lab/", + "data-path": "/home/data/training/knowledge_data.jsonl", + "cpu-offload-optimizer": "1", + "nnodes": "1", + "nproc-per-node": "4", + "num-runavg-samples": "2" + } + } + ], + "primary_metrics": [ + "ilab::train-samples-sec" + ], + "status": "pass", + "params": { + "cpu-offload-pin-memory": "1", + "model": "/home/models/granite-7b-lab/", + "data-path": "/home/data/training/knowledge_data.jsonl", + "cpu-offload-optimizer": "1", + "nnodes": "1", + "nproc-per-node": "4", + "num-runavg-samples": "2" + }, + "begin_date": "2024-08-05 17:28:26.342000+00:00", + "end_date": "2024-08-05 17:55:03.544000+00:00" + } + ], + "count": 1, + "total": 15, + "next_offset": 1 + } + + Args: + start: Include runs starting at timestamp + end: Include runs ending no later than timestamp + filter: List of tag/param filter terms (parm:key=value) + sort: List of sort terms (column:) + size: Include up to runs in output + offset: Use size/from pagination instead of search_after + + Returns: + JSON object with "results" list and "housekeeping" fields + """ + + # We need to remove runs which don't match against 'tag' or 'param' + # filter terms. The CDM schema doesn't make it possible to do this in + # one shot. Instead, we run queries against the param and tag indices + # separately, producing a list of run IDs which we'll exclude from the + # final collection. + # + # If there are no matches, we can exit early. (TODO: should this be an + # error, or just a success with an empty list?) + results = {} + filters = [] + sorters = self._split_list(sort) + results["sort"] = sorters + sort_terms = self._build_sort_terms(sorters) + param_filters, tag_filters, run_filters = self._build_filter_options(filter) + if run_filters: + filters.extend(run_filters) + if start or end: + s = None + e = None + if start: + s = self._normalize_date(start) + results["startDate"] = datetime.fromtimestamp( + s / 1000.0, tz=timezone.utc + ).isoformat() + if end: + e = self._normalize_date(end) + results["endDate"] = datetime.fromtimestamp( + e / 1000.0, tz=timezone.utc + ).isoformat() + + if s and e and s > e: + raise HTTPException( + status_code=422, + detail={ + "error": "Invalid date format, start_date must be less than end_date" + }, + ) + cond = {} + if s: + cond["gte"] = str(s) + if e: + cond["lte"] = str(e) + filters.append({"range": {"run.begin": cond}}) + if size: + results["size"] = size + results["offset"] = offset if offset is not None else 0 + + # In order to filter by param or tag values, we need to produce a list + # of matching RUN IDs from each index. We'll then drop any RUN ID that's + # not on both lists. + if tag_filters: + tagids = await self._get_run_ids("tag", tag_filters) + if param_filters: + paramids = await self._get_run_ids("param", param_filters) + + # If it's obvious we can't produce any matches at this point, exit. + if (tag_filters and len(tagids) == 0) or (param_filters and len(paramids) == 0): + results.update({"results": [], "count": 0, "total": 0}) + return results + + hits = await self.search( + "run", + size=size, + offset=offset, + sort=sort_terms, + filters=filters, + **kwargs, + ignore_unavailable=True, + ) + rawiterations = await self.search("iteration", ignore_unavailable=True) + rawtags = await self.search("tag", ignore_unavailable=True) + rawparams = await self.search("param", ignore_unavailable=True) + + iterations = defaultdict(list) + tags = defaultdict(defaultdict) + params = defaultdict(defaultdict) + run_params = defaultdict(list) + + for i in self._hits(rawiterations): + iterations[i["run"]["id"]].append(i["iteration"]) + + # Organize tags by run ID + for t in self._hits(rawtags): + tags[t["run"]["id"]][t["tag"]["name"]] = t["tag"]["val"] + + # Organize params by iteration ID + for p in self._hits(rawparams): + run_params[p["run"]["id"]].append(p) + params[p["iteration"]["id"]][p["param"]["arg"]] = p["param"]["val"] + + runs = {} + for h in self._hits(hits): + run = h["run"] + rid = run["id"] + + # Filter the runs by our tag and param queries + if param_filters and rid not in paramids: + continue + + if tag_filters and rid not in tagids: + continue + + # Collect unique runs: the status is "fail" if any iteration for + # that run ID failed. + runs[rid] = run + run["tags"] = tags.get(rid, {}) + run["iterations"] = [] + run["primary_metrics"] = set() + common = CommonParams() + for i in iterations.get(rid, []): + iparams = params.get(i["id"], {}) + if "status" not in run: + run["status"] = i["status"] + else: + if i["status"] != "pass": + run["status"] = i["status"] + common.add(iparams) + run["primary_metrics"].add(i["primary-metric"]) + run["iterations"].append( + { + "iteration": i["num"], + "primary_metric": i["primary-metric"], + "primary_period": i["primary-period"], + "status": i["status"], + "params": iparams, + } + ) + run["params"] = common.render() + try: + run["begin_date"] = self._format_timestamp(run["begin"]) + run["end_date"] = self._format_timestamp(run["end"]) + except KeyError as e: + self.logger.warning("Missing 'run' key %r in %s", str(e), run) + run["begin_date"] = self._format_timestamp("0") + run["end_date"] = self._format_timestamp("0") + + count = len(runs) + total = hits["hits"]["total"]["value"] + results.update( + { + "results": list(runs.values()), + "count": count, + "total": total, + } + ) + if size and (offset + count < total): + results["next_offset"] = offset + size + return results + + async def get_tags(self, run: str, **kwargs) -> dict[str, str]: + """Return the set of tags associated with a run + + Args: + run: run ID + + Returns: + JSON dict with "tag" keys showing each value + """ + tags = await self.search( + index="tag", + filters=[{"term": {"run.id": run}}], + **kwargs, + ignore_unavailable=True, + ) + return {t["name"]: t["val"] for t in self._hits(tags, ["tag"])} + + async def get_params( + self, run: Optional[str] = None, iteration: Optional[str] = None, **kwargs + ) -> dict[str, dict[str, str]]: + """Return the set of parameters for a run or iteration + + Parameters are technically associated with an iteration, but can be + aggregated for a run. This will return a set of parameters for each + iteration; plus, if a "run" was specified, a filtered list of param + values that are common across all iterations. + + Args: + run: run ID + iteration: iteration ID + kwargs: additional OpenSearch keywords + + Returns: + JSON dict of param values by iteration (plus "common" if by run ID) + """ + if not run and not iteration: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + "A params query requires either a run or iteration ID", + ) + match = {"run.id" if run else "iteration.id": run if run else iteration} + params = await self.search( + index="param", + filters=[{"term": match}], + **kwargs, + ignore_unavailable=True, + ) + response = defaultdict(defaultdict) + for param in self._hits(params): + iter = param["iteration"]["id"] + arg = param["param"]["arg"] + val = param["param"]["val"] + old = self._get(response, [iter, arg]) + if old: + self.logger.warning( + "Duplicate param %s for iteration %s (%r, %r)", arg, iter, old, val + ) + response[iter][arg] = val + + # Filter out all parameter values that don't exist in all or which have + # different values. + if run: + common = CommonParams() + for params in response.values(): + common.add(params) + response["common"] = common.render() + return response + + async def get_iterations(self, run: str, **kwargs) -> list[dict[str, Any]]: + """Return a list of iterations for a run + + Args: + run: run ID + kwargs: additional OpenSearch keywords + + Returns: + A list of iteration documents + """ + iterations = await self.search( + index="iteration", + filters=[{"term": {"run.id": run}}], + sort=[{"iteration.num": "asc"}], + **kwargs, + ignore_unavailable=True, + ) + return [i["iteration"] for i in self._hits(iterations)] + + async def get_samples( + self, run: Optional[str] = None, iteration: Optional[str] = None, **kwargs + ): + """Return a list of samples for a run or iteration + + Args: + run: run ID + iteration: iteration ID + kwargs: additional OpenSearch keywords + + Returns: + A list of sample documents. + """ + if not run and not iteration: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + "A sample query requires either a run or iteration ID", + ) + match = {"run.id" if run else "iteration.id": run if run else iteration} + hits = await self.search( + index="sample", + filters=[{"term": match}], + **kwargs, + ignore_unavailable=True, + ) + samples = [] + for s in self._hits(hits): + sample = s["sample"] + sample["iteration"] = s["iteration"]["num"] + sample["primary_metric"] = s["iteration"]["primary-metric"] + samples.append(sample) + return samples + + async def get_periods( + self, + run: Optional[str] = None, + iteration: Optional[str] = None, + sample: Optional[str] = None, + **kwargs, + ): + """Return a list of periods associated with a run, an iteration, or a + sample + + The "period" document is normalized to represent timestamps using ISO + strings. + + Args: + run: run ID + iteration: iteration ID + sample: sample ID + kwargs: additional OpenSearch parameters + + Returns: + a list of normalized period documents + """ + if not any((run, iteration, sample)): + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + "A period query requires a run, iteration, or sample ID", + ) + match = None + if sample: + match = {"sample.id": sample} + elif iteration: + match = {"iteration.id": iteration} + else: + match = {"run.id": run} + periods = await self.search( + index="period", + filters=[{"term": match}], + sort=[{"period.begin": "asc"}], + **kwargs, + ignore_unavailable=True, + ) + body = [] + for h in self._hits(periods): + period = self._format_period(period=h["period"]) + period["iteration"] = h["iteration"]["num"] + period["sample"] = h["sample"]["num"] + period["primary_metric"] = h["iteration"]["primary-metric"] + period["status"] = h["iteration"]["status"] + body.append(period) + return body + + async def get_metrics_list(self, run: str, **kwargs) -> dict[str, Any]: + """Return a list of metrics available for a run + + Each run may have multiple performance metrics stored. This API allows + retrieving a sorted list of the metrics available for a given run, with + the "names" selection criteria available for each and, for "periodic" + (benchmark) metrics, the defined periods for which data was gathered. + + { + "ilab::train-samples-sec": { + "periods": [{"id": , "name": "measurement"}], + "breakouts": {"benchmark-group" ["unknown"], ...} + }, + "iostat::avg-queue-length": { + "periods": [], + "breakouts": {"benchmark-group": ["unknown"], ...}, + }, + ... + } + + Args: + run: run ID + + Returns: + List of metrics available for the run + """ + hits = await self.search( + index="metric_desc", + filters=[{"term": {"run.id": run}}], + ignore_unavailable=True, + **kwargs, + ) + met = {} + for h in self._hits(hits): + desc = h["metric_desc"] + name = desc["source"] + "::" + desc["type"] + if name in met: + record = met[name] + else: + record = {"periods": [], "breakouts": defaultdict(list)} + met[name] = record + if "period" in h: + record["periods"].append(h["period"]["id"]) + for n, v in desc["names"].items(): + # mimic a set, since the set type doesn't serialize + if v not in record["breakouts"][n]: + record["breakouts"][n].append(v) + return met + + async def get_metric_breakouts( + self, + run: str, + metric: str, + names: Optional[list[str]] = None, + periods: Optional[list[str]] = None, + ) -> dict[str, Any]: + """Help explore available metric breakouts + + Args: + run: run ID + metric: metric label (e.g., "mpstat::Busy-CPU") + names: list of name filters ("cpu=3") + periods: list of period IDs + + Returns: + A description of all breakout names and values, which can be + specified to narrow down metrics returns by the data, summary, and + graph APIs. + + { + "label": "mpstat::Busy-CPU", + "class": [ + "throughput" + ], + "type": "Busy-CPU", + "source": "mpstat", + "breakouts": { + "num": [ + "8", + "72" + ], + "thread": [ + 0, + 1 + ] + } + } + """ + start = time.time() + filters = self._build_metric_filters(run, metric, names, periods) + metric_name = metric + ("" if not names else ("+" + ",".join(names))) + metrics = await self.search( + "metric_desc", + filters=filters, + ignore_unavailable=True, + ) + if len(metrics["hits"]["hits"]) < 1: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, + f"Metric name {metric_name} not found for run {run}", + ) + classes = set() + response = {"label": metric} + breakouts = defaultdict(list) + pl = set() + for m in self._hits(metrics): + desc = m["metric_desc"] + response["type"] = desc["type"] + response["source"] = desc["source"] + if desc.get("class"): + classes.add(desc["class"]) + if "period" in m: + pl.add(m["period"]["id"]) + for n, v in desc["names"].items(): + if v not in breakouts[n]: + breakouts[n].append(v) + # We want to help filter a consistent summary, so only show those + # names with more than one value. + if len(pl) > 1: + response["periods"] = sorted(pl) + response["class"] = sorted(classes) + response["breakouts"] = {n: v for n, v in breakouts.items() if len(v) > 1} + self.logger.info("Processing took %.3f seconds", time.time() - start) + return response + + async def get_metrics_data( + self, + run: str, + metric: str, + names: Optional[list[str]] = None, + periods: Optional[list[str]] = None, + aggregate: bool = False, + ) -> list[Any]: + """Return a list of metric data + + The "aggregate" option allows aggregating various metrics across + breakout streams and periods: be careful, as this is meaningful only if + the breakout streams are sufficiently related. + + Args: + run: run ID + metric: metric label (e.g., "mpstat::Busy-CPU") + names: list of name filters ("cpu=3") + periods: list of period IDs + aggregate: aggregate multiple metric data streams + + Returns: + A sequence of data samples, showing the aggregate sample along with + the duration and end timestamp of each sample interval. + + [ + { + "begin": "2024-08-22 20:03:23.028000+00:00", + "end": "2024-08-22 20:03:37.127000+00:00", + "duration": 14.1, + "value": 9.35271216694379 + }, + { + "begin": "2024-08-22 20:03:37.128000+00:00", + "end": "2024-08-22 20:03:51.149000+00:00", + "duration": 14.022, + "value": 9.405932330557683 + }, + { + "begin": "2024-08-22 20:03:51.150000+00:00", + "end": "2024-08-22 20:04:05.071000+00:00", + "duration": 13.922, + "value": 9.478773265522682 + } + ] + """ + start = time.time() + ids = await self._get_metric_ids( + run, metric, names, periodlist=periods, aggregate=aggregate + ) + + # If we're searching by periods, filter metric data by the period + # timestamp range rather than just relying on the metric desc IDs as + # we also want to filter non-periodic tool data. + filters = [{"terms": {"metric_desc.id": ids}}] + filters.extend(await self._build_timestamp_range_filters(periods)) + + response = [] + + # NOTE -- _get_metric_ids already failed if we found multiple IDs but + # aggregation wasn't specified. + if len(ids) > 1: + # Find the minimum sample interval of the selected metrics + aggdur = await self.search( + "metric_data", + size=0, + filters=filters, + aggregations={"duration": {"stats": {"field": "metric_data.duration"}}}, + ) + if aggdur["aggregations"]["duration"]["count"] > 0: + interval = int(aggdur["aggregations"]["duration"]["min"]) + data = await self.search( + index="metric_data", + size=0, + filters=filters, + aggregations={ + "interval": { + "histogram": { + "field": "metric_data.end", + "interval": interval, + }, + "aggs": {"value": {"sum": {"field": "metric_data.value"}}}, + } + }, + ) + for h in self._aggs(data, "interval"): + response.append( + { + "begin": self._format_timestamp(h["key"] - interval), + "end": self._format_timestamp(h["key"]), + "value": h["value"]["value"], + "duration": interval / 1000.0, + } + ) + else: + data = await self.search("metric_data", filters=filters) + for h in self._hits(data, ["metric_data"]): + response.append(self._format_data(h)) + response.sort(key=lambda a: a["end"]) + self.logger.info("Processing took %.3f seconds", time.time() - start) + return response + + async def get_metrics_summary( + self, + run: str, + metric: str, + names: Optional[list[str]] = None, + periods: Optional[list[str]] = None, + ) -> dict[str, Any]: + """Return a statistical summary of metric data + + Provides a statistical summary of selected data samples. + + Args: + run: run ID + metric: metric label (e.g., "mpstat::Busy-CPU") + names: list of name filters ("cpu=3") + periods: list of period IDs + + Returns: + A statistical summary of the selected metric data + + { + "count": 71, + "min": 0.0, + "max": 0.3296, + "avg": 0.02360704225352113, + "sum": 1.676self.BIGQUERY00000001 + } + """ + start = time.time() + ids = await self._get_metric_ids(run, metric, names, periodlist=periods) + filters = [{"terms": {"metric_desc.id": ids}}] + filters.extend(await self._build_timestamp_range_filters(periods)) + data = await self.search( + "metric_data", + size=0, + filters=filters, + aggregations={"score": {"stats": {"field": "metric_data.value"}}}, + ) + self.logger.info("Processing took %.3f seconds", time.time() - start) + return data["aggregations"]["score"] + + async def _graph_title( + self, + run_id: str, + run_id_list: list[str], + graph: Graph, + params_by_run: dict[str, Any], + periods_by_run: dict[str, Any], + ) -> str: + """Compute a default title for a graph + + Use the period, breakout name selections, run list, and iteration + parameters to construct a meaningful name for a graph. + + For example, "ilab::sdg-samples-sec (batch-size=4) {run 1}", or + "mpstat::Busy-CPU [cpu=4]" + + Args: + run_id: the Crucible run ID + run_id_list: ordered list of run IDs in our list of graphs + graph: the current Graph object + params_by_run: initially empty dict used to cache parameters + periods_by_run: initially empty dict used to cache periods + + Returns: + A string title + """ + names = graph.names + metric = graph.metric + if run_id not in params_by_run: + # Gather iteration parameters outside the loop for help in + # generating useful labels. + all_params = await self.search( + "param", filters=[{"term": {"run.id": run_id}}] + ) + collector = defaultdict(defaultdict) + for h in self._hits(all_params): + collector[h["iteration"]["id"]][h["param"]["arg"]] = h["param"]["val"] + params_by_run[run_id] = collector + else: + collector = params_by_run[run_id] + + if run_id not in periods_by_run: + periods = await self.search( + "period", filters=[{"term": {"run.id": run_id}}] + ) + iteration_periods = defaultdict(set) + for p in self._hits(periods): + iteration_periods[p["iteration"]["id"]].add(p["period"]["id"]) + periods_by_run[run_id] = iteration_periods + else: + iteration_periods = periods_by_run[run_id] + + # We can easily end up with multiple graphs across distinct + # periods or iterations, so we want to be able to provide some + # labeling to the graphs. We do this by looking for unique + # iteration parameters values, since the iteration number and + # period name aren't useful by themselves. + name_suffix = "" + if graph.periods: + iteration = None + for i, pset in iteration_periods.items(): + if set(graph.periods) <= pset: + iteration = i + break + + # If the period(s) we're graphing resolve to a single + # iteration in a run with multiple iterations, then we can + # try to find a unique title suffix based on distinct param + # values for that iteration. + if iteration and len(collector) > 1: + unique = collector[iteration].copy() + for i, params in collector.items(): + if i != iteration: + for p in list(unique.keys()): + if p in params and unique[p] == params[p]: + del unique[p] + if unique: + name_suffix = ( + " (" + ",".join([f"{p}={v}" for p, v in unique.items()]) + ")" + ) + + if len(run_id_list) > 1: + name_suffix += f" {{run {run_id_list.index(run_id) + 1}}}" + + options = (" [" + ",".join(names) + "]") if names else "" + return metric + options + name_suffix + + async def get_metrics_graph(self, graphdata: GraphList) -> dict[str, Any]: + """Return metrics data for a run + + Each run may have multiple performance metrics stored. This API allows + retrieving graphable time-series representation of a metric over the + period of the run, in the format defined by Plotly as configuration + settings plus an x value array and a y value array. + + { + "data": [ + { + "x": [ + "2024-08-27 09:16:27.371000", + ... + ], + "y": [ + 10.23444312132161, + ... + ], + "name": "Metric ilab::train-samples-sec", + "type": "scatter", + "mode": "line", + "marker": {"color": "black"}, + "labels": {"x": "sample timestamp", "y": "samples / second"} + } + ] + "layout": { + "width": 1500, + "yaxis": { + "title": "mpstat::Busy-CPU core=2,package=0,num=112,type=usr", + "color": "black" + } + } + } + + Args: + graphdata: A GraphList object + + Returns: + A Plotly object with layout + """ + start = time.time() + graphlist = [] + default_run_id = graphdata.run + layout: dict[str, Any] = {"width": "1500"} + axes = {} + yaxis = None + cindex = 0 + params_by_run = {} + periods_by_run = {} + + # Construct a de-duped ordered list of run IDs, starting with the + # default. + run_id_list = [] + if default_run_id: + run_id_list.append(default_run_id) + run_id_missing = False + for g in graphdata.graphs: + if g.run: + if g.run not in run_id_list: + run_id_list.append(g.run) + else: + run_id_missing = True + + if run_id_missing and not default_run_id: + raise HTTPException( + status.HTTP_400_BAD_REQUEST, "each graph request must have a run ID" + ) + + for g in graphdata.graphs: + run_id = g.run if g.run else default_run_id + names = g.names + metric: str = g.metric + + # The caller can provide a title for each graph; but, if not, we + # journey down dark overgrown pathways to fabricate a default with + # reasonable context, including unique iteration parameters, + # breakdown selections, and which run provided the data. + if g.title: + title = g.title + else: + title = await self._graph_title( + run_id, run_id_list, g, params_by_run, periods_by_run + ) + + ids = await self._get_metric_ids( + run_id, + metric, + names, + periodlist=g.periods, + aggregate=g.aggregate, + ) + filters = [{"terms": {"metric_desc.id": ids}}] + filters.extend(await self._build_timestamp_range_filters(g.periods)) + y_max = 0.0 + points: list[Point] = [] + + # If we're pulling multiple breakouts, e.g., total CPU across modes + # or cores, we want to aggregate by timestamp interval. Sample + # timstamps don't necessarily align, so the "histogram" aggregation + # normalizes within the interval (based on the minimum actual + # interval duration). + if len(ids) > 1: + # Find the minimum sample interval of the selected metrics + aggdur = await self.search( + "metric_data", + size=0, + filters=filters, + aggregations={ + "duration": {"stats": {"field": "metric_data.duration"}} + }, + ) + if aggdur["aggregations"]["duration"]["count"] > 0: + interval = int(aggdur["aggregations"]["duration"]["min"]) + data = await self.search( + index="metric_data", + size=0, + filters=filters, + aggregations={ + "interval": { + "histogram": { + "field": "metric_data.begin", + "interval": interval, + }, + "aggs": { + "value": {"sum": {"field": "metric_data.value"}} + }, + } + }, + ) + for h in self._aggs(data, "interval"): + begin = int(h["key"]) + end = begin + interval - 1 + points.append(Point(begin, end, float(h["value"]["value"]))) + else: + data = await self.search("metric_data", filters=filters) + for h in self._hits(data, ["metric_data"]): + points.append( + Point(int(h["begin"]), int(h["end"]), float(h["value"])) + ) + + # Sort the graph points by timestamp so that Ploty will draw nice + # lines. We graph both the "begin" and "end" timestamp of each + # sample against the value to more clearly show the sampling + # interval. + x = [] + y = [] + + for p in sorted(points, key=lambda a: a.begin): + x.extend( + [self._format_timestamp(p.begin), self._format_timestamp(p.end)] + ) + y.extend([p.value, p.value]) + y_max = max(y_max, p.value) + + if g.color: + color = g.color + else: + color = COLOR_NAMES[cindex] + cindex += 1 + if cindex >= len(COLOR_NAMES): + cindex = 0 + graphitem = { + "x": x, + "y": y, + "name": title, + "type": "scatter", + "mode": "line", + "marker": {"color": color}, + "labels": { + "x": "sample timestamp", + "y": "samples / second", + }, + } + + # Y-axis scaling and labeling is divided by benchmark label; + # so store each we've created to reuse. (E.g., if we graph + # 5 different mpstat::Busy-CPU periods, they'll share a single + # Y axis.) + if metric in axes: + yref = axes[metric] + else: + if yaxis: + name = f"yaxis{yaxis}" + yref = f"y{yaxis}" + yaxis += 1 + layout[name] = { + "title": metric, + "color": color, + "autorange": True, + "anchor": "free", + "autoshift": True, + "overlaying": "y", + } + else: + name = "yaxis" + yref = "y" + yaxis = 2 + layout[name] = { + "title": metric, + "color": color, + } + axes[metric] = yref + graphitem["yaxis"] = yref + graphlist.append(graphitem) + self.logger.info("Processing took %.3f seconds", time.time() - start) + return {"data": graphlist, "layout": layout} diff --git a/backend/poetry.lock b/backend/poetry.lock index 842e52ae..27112850 100644 --- a/backend/poetry.lock +++ b/backend/poetry.lock @@ -1,100 +1,113 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.5.1 and should not be 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"^3.9" -content-hash = "b61c6117aaf307076a1f0eee6b9177cd1f5accf330cd75a28669c36b4c51ad69" +python-versions = "^3.9.20" +content-hash = "228bb1eab40ca6a1e5329f4c746b7608aaf2c08cc3b4c0d40fe1430e374f8121" diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 984496a1..e04b4859 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -1,13 +1,17 @@ [tool.poetry] name = "openshift_perfscale_api" +packages = [ + { include = "app" } +] version = "0.1.1" description = "python transformer of openshift performance and scale test results" authors = ["mleader "] [tool.poetry.dependencies] -python = "^3.9" +python = "^3.9.20" cryptography = "^3.4.8" pandas = "1.2.4" +numpy = "1.26.4" vyper-config = "1.0.0" semver = "2.13.0" splunk-sdk = "2.0.1" @@ -16,17 +20,84 @@ httptools = "^0.2.0" elasticsearch = "7.13.4" fastapi = "^0.104.1" pydantic = "2.3.0" -uvicorn = "^0.14.0" +uvicorn = "^0.32.0" trio = "^0.18.0" aiohttp = "^3.7.4" httpx = "^0.18.1" orjson = "^3.5.3" atlassian-python-api = "^3.41.9" python-keycloak = "^3.12.0" +pytest = "^8.3.4" +pytest-asyncio = "^0.24" +pytest-cov = "^6.0" +tox = "^4.23.2" [tool.poetry.dev-dependencies] watchgod = "^0.7" +[tool.pytest.ini_options] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" + +[tool.isort] +profile = "black" # black-compatible (e.g., trailing comma) +known_first_party = ["app"] # separate our headers into a section +multi_line_output = 3 # "hanging" indent with dedented paren +force_sort_within_sections = true # don't separate import vs from +order_by_type = false # sort alphabetic regardless of case + +[tool.tox] +requires = ["tox>=4.19"] +env_list = ["unit", "format", "lint", "isort"] + +[tool.tox.env_run_base] +description = "Run test under {base_python}" +base_python = ["python3.9"] +deps = [ + "pytest", + "pytest-asyncio", + "pytest-cov", + "coverage", +] +set_env.COVERAGE = { replace = "env", name = "COVERAGE", default = "/var/tmp/{env:USER}" } +allowlist_externals = ["bash", "echo", "coverage"] +commands = [ + ["echo", "{env:COVERAGE}"], + ["pip", "list"], + ["pytest", "-s", "--cov-branch", "--cov=app", "{posargs}", "tests"], + ["coverage", "html", "--directory={env:COVERAGE}/html"], + ["bash", "-c", "coverage report --format=markdown >{env:COVERAGE}/coverage.txt"], +] + +[tool.tox.env.format] +description = "check code format" +skip_install = true +deps = ["black"] +commands = [["black", "--check", { replace = "posargs", default = ["app", "tests"], extend = true} ]] + +[tool.tox.env.isort] +description = "check order of imports" +skip_install = true +deps = ["isort"] +commands = [["isort", "--check", { replace = "posargs", default = ["app", "tests"], extend = true} ]] + +[tool.tox.env.lint] +description = "check code" +skip_install = true +deps = ["flake8"] +commands = [["flake8", { replace = "posargs", default = ["app", "tests"], extend = true} ]] + +[tool.coverage.run] +branch = true +cover_pylib = true +data_file = "coverage.db" +parallel = true +relative_files = true + +[tool.coverage.report] +include_namespace_packages = true +skip_empty = true + [build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" diff --git a/backend/tests/__init__.py b/backend/tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/backend/tests/fake_elastic.py b/backend/tests/fake_elastic.py new file mode 100644 index 00000000..1b7425c0 --- /dev/null +++ b/backend/tests/fake_elastic.py @@ -0,0 +1,176 @@ +from collections import defaultdict +from dataclasses import dataclass +from typing import Any, Optional, Union + +from elasticsearch import AsyncElasticsearch + + +@dataclass +class Request: + index: str + body: dict[str, Any] + doc_type: Optional[str] = None + params: Optional[Any] = None + headers: Optional[Any] = None + kwargs: Optional[dict[str, Any]] = None + + def __eq__(self, other) -> bool: + iok = self.index == other.index + bok = self.body == other.body + dok = self.doc_type == other.doc_type + pok = self.params == other.params + hok = self.headers == other.headers + + # make empty dict and None match + kok = (not self.kwargs and not other.kwargs) or self.kwargs == other.kwargs + return iok and bok and dok and pok and hok and kok + + +class FakeAsyncElasticsearch(AsyncElasticsearch): + hosts: Union[str, list[str]] + args: dict[str, Any] + closed: bool + requests: list[Request] + + # This fake doesn't try to mimic Opensearch query and aggregation logic: + # instead, the "data" is pre-loaded with a JSON response body that will + # be returned on an "index" match. (This means that any external call we + # need to mock has a single query against any one index!) + data: dict[str, Any] + + def __init__(self, hosts: Union[str, list[str]], **kwargs): + self.hosts = hosts + self.args = kwargs + self.closed = False + self.data = defaultdict(list) + self.requests = [] + + # Testing helpers to manage fake searches + def set_query( + self, + root_index: str, + hit_list: Optional[list[dict[str, Any]]] = None, + aggregations: Optional[dict[str, Any]] = None, + version: int = 7, + repeat: int = 1, + ): + """Add a canned response to an Opensearch query + + The overall response and items in the hit and aggregation lists will be + augmented with the usual boilerplate. + + Multiple returns for a single index can be queued, in order, via + successive calls. To return the same result on multiple calls, specify + a "repeat" value greater than 1. + + Args: + root_index: CDM index name (run, period, etc) + hit_list: list of hit objects to be returned + aggregation_list: list of aggregation objects to return + version: CDM version + repeat: + """ + ver = f"v{version:d}dev" + index = f"cdm{ver}-{root_index}" + hits = [] + if hit_list: + for d in hit_list: + source = d + source["cdm"] = {"ver": ver} + hits.append( + { + "_index": index, + "_id": "random_string", + "_score": 1.0, + "_source": source, + } + ) + aggregate_response = {} + if aggregations: + for agg, val in aggregations.items(): + if isinstance(val, list): + aggregate_response[agg] = { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": val, + } + else: + aggregate_response[agg] = val + response = { + "took": 1, + "timed_out": False, + "_shards": {"total": 1, "successful": 1, "skipped": 0, "failed": 0}, + "hits": { + "total": {"value": len(hits), "relation": "eq"}, + "max_score": 1.0, + "hits": hits, + }, + } + if aggregate_response: + response["aggregations"] = aggregate_response + for c in range(repeat): + self.data[index].append(response) + + # Faked AsyncElasticsearch methods + async def close(self): + self.closed = True + + async def info(self, **kwargs): + pass + + async def ping(self, **kwargs): + return True + + async def search( + self, body=None, index=None, doc_type=None, params=None, headers=None, **kwargs + ): + """Return a canned response to a search query. + + Args: + body: query body + index: Opensearch index name + doc_type: document type (rarely used) + params: Opensearch search parameters (rarely used) + headers: HTTP headers (rarely used) + kwargs: whatever else you might pass to search + + Only the index is used here; to verify the correct Opensearch query + bodies and parameters, the full request is recorded for inspection. + + Return: + A JSON dict with the first canned result for the index, or an error + """ + self.requests.append( + Request( + index=index, + body=body, + doc_type=doc_type, + params=params, + headers=headers, + kwargs=kwargs, + ) + ) + if index in self.data and len(self.data[index]) > 0: + target = self.data[index].pop(0) + return target + return { + "error": { + "root_cause": [ + { + "type": "index_not_found_exception", + "reason": f"no such index [{index}]", + "index": index, + "resource.id": index, + "resource.type": "index_or_alias", + "index_uuid": "_na_", + }, + ], + "type": "index_not_found_exception", + "reason": f"no such index [{index}]", + "index": index, + "resource.id": index, + "resource.type": "index_or_alias", + "index_uuid": "_na_", + }, + "status": 404, + } diff --git a/backend/tests/test_crucible.py b/backend/tests/test_crucible.py new file mode 100644 index 00000000..f5df4afc --- /dev/null +++ b/backend/tests/test_crucible.py @@ -0,0 +1,2090 @@ +from collections import defaultdict +from datetime import datetime, timezone +import json + +from elasticsearch import AsyncElasticsearch +from fastapi import HTTPException +import pytest +from vyper import Vyper + +import app.config +from app.services.crucible_svc import ( + CommonParams, + CrucibleService, + Graph, + GraphList, + Parser, +) +from tests.fake_elastic import FakeAsyncElasticsearch, Request + + +@pytest.fixture +def fake_config(monkeypatch): + """Provide a fake configuration""" + + vyper = Vyper(config_name="ocpperf") + vyper.set("TEST.url", "http://elastic.example.com:9200") + monkeypatch.setattr("app.config.get_config", lambda: vyper) + + +@pytest.fixture +def fake_elastic(monkeypatch, fake_config): + """Replace the actual elastic client with a fake""" + + monkeypatch.setattr( + "app.services.crucible_svc.AsyncElasticsearch", FakeAsyncElasticsearch + ) + + +@pytest.fixture +async def fake_crucible(fake_elastic): + crucible = CrucibleService("TEST") + yield crucible + await crucible.close() + + +class TestParser: + + def test_parse_normal(self): + """Test successful parsing of three terms""" + + t = Parser("foo:bar=x") + assert ("foo", ":") == t._next_token([":", "="]) + assert ("bar", "=") == t._next_token([":", "="]) + assert ("x", None) == t._next_token([":", "="], optional=True) + + def test_parse_missing(self): + """Test exception when a delimiter is missing""" + + t = Parser("foo:bar=x") + assert ("foo", ":") == t._next_token([":", "="]) + assert ("bar", "=") == t._next_token([":", "="]) + with pytest.raises(HTTPException) as e: + t._next_token(delimiters=[":", "="]) + assert 400 == e.value.status_code + assert "Missing delimiter from :,= after 'x'" == e.value.detail + + def test_parse_quoted(self): + """Test acceptance of quoted terms""" + + t = Parser("'foo':\"bar\"='x'") + assert ("foo", ":") == t._next_token([":", "="]) + assert ("bar", "=") == t._next_token([":", "="]) + assert ("x", None) == t._next_token([":", "="], optional=True) + + def test_parse_bad_quoted(self): + """Test detection of badly paired quotes""" + + t = Parser("'foo':'bar\"='x'") + assert ("foo", ":") == t._next_token([":", "="]) + with pytest.raises(HTTPException) as e: + t._next_token([":", "="]) + assert 400 == e.value.status_code + assert "Unterminated quote at '\\'foo\\':\\'bar[\"]=\\'x\\''" == e.value.detail + + +class TestCommonParams: + + def test_one(self): + """Test that we drop unique params""" + + c = CommonParams() + c.add({"one": 1, "two": 2}) + c.add({"one": 1, "three": 3}) + c.add({"one": 1, "two": 5}) + assert {"one": 1} == c.render() + + +class TestList: + + @pytest.mark.parametrize( + "input,output", + ( + (None, []), + (["a"], ["a"]), + (["a", "b"], ["a", "b"]), + (["a,b"], ["a", "b"]), + (["a", "b,c", "d"], ["a", "b", "c", "d"]), + ), + ) + def test_split_empty(self, input, output): + assert output == CrucibleService._split_list(input) + + +class TestFormatters: + + @pytest.mark.parametrize( + "input", + ( + "2024-09-12 18:29:35.123000+00:00", + datetime.fromisoformat("2024-09-12 18:29:35.123000+00:00"), + "1726165775123", + 1726165775123, + ), + ) + def test_normalize_date(self, input): + assert 1726165775123 == CrucibleService._normalize_date(input) + + def test_normalize_date_bad(self): + with pytest.raises(HTTPException) as e: + CrucibleService._normalize_date([]) + assert 400 == e.value.status_code + assert "Date representation [] is not a date string or timestamp" + + @pytest.mark.parametrize( + "input,output", + ( + ("abc", "1970-01-01 00:00:00+00:00"), + ("1726165775123", "2024-09-12 18:29:35.123000+00:00"), + (1726165775123, "2024-09-12 18:29:35.123000+00:00"), + ), + ) + def test_format_timestamp(self, input, output): + assert output == CrucibleService._format_timestamp(input) + + def test_format_data(self): + begin = 1726165775123 + duration = 10244 + raw = { + "begin": str(begin), + "end": str(begin + duration), + "duration": str(duration), + "value": "100.3", + } + expect = { + "begin": "2024-09-12 18:29:35.123000+00:00", + "end": "2024-09-12 18:29:45.367000+00:00", + "duration": 10.244, + "value": 100.3, + } + assert expect == CrucibleService._format_data(raw) + + def test_format_period(self): + raw = { + "begin": "1726165775123", + "end": "1726165785234", + "id": "ABC-123", + "name": "measurement", + } + expect = { + "begin": "2024-09-12 18:29:35.123000+00:00", + "end": "2024-09-12 18:29:45.234000+00:00", + "id": "ABC-123", + "name": "measurement", + } + assert expect == CrucibleService._format_period(raw) + + +class TestHits: + + def test_no_hits(self): + """Expect an exception because 'hits' is missing""" + + with pytest.raises(HTTPException) as e: + for a in CrucibleService._hits({}): + assert f"Unexpected result {type(a)}" + assert 500 == e.value.status_code + assert "Attempt to iterate hits for {}" == e.value.detail + + def test_empty_hits(self): + """Expect successful iteration of no hits""" + + for a in CrucibleService._hits({"hits": {"hits": []}}): + assert f"Unexpected result {a}" + + def test_hits(self): + """Test that iteration through hits works""" + + expected = [{"a": 1}, {"b": 1}] + payload = [{"_source": a} for a in expected] + assert expected == list(CrucibleService._hits({"hits": {"hits": payload}})) + + def test_hits_fields(self): + """Test that iteration through hit fields works""" + + expected = [{"a": 1}, {"b": 1}] + payload = [{"_source": {"f": a, "e": 1}} for a in expected] + assert expected == list( + CrucibleService._hits({"hits": {"hits": payload}}, ["f"]) + ) + + +class TestAggregates: + + def test_no_aggregations(self): + """Expect an exception if the aggregations are missing""" + with pytest.raises(HTTPException) as e: + for a in CrucibleService._aggs({}, "agg"): + assert f"Unexpected result {a}" + assert 500 == e.value.status_code + assert "Attempt to iterate missing aggregations for {}" == e.value.detail + + def test_missing_agg(self): + """Expect an exception if the aggregations are missing""" + + payload = {"aggregations": {}} + with pytest.raises(HTTPException) as e: + for a in CrucibleService._aggs(payload, "agg"): + assert f"Unexpected result {a}" + assert 500 == e.value.status_code + assert ( + f"Attempt to iterate missing aggregation 'agg' for {payload}" + == e.value.detail + ) + + def test_empty_aggs(self): + """Expect successful iteration of no aggregation data""" + + for a in CrucibleService._aggs( + {"aggregations": {"agg": {"buckets": []}}}, "agg" + ): + assert f"Unexpected result {a}" + + def test_aggs(self): + """Test that iteration through aggregations works""" + + expected = [{"key": 1, "doc_count": 2}, {"key": 2, "doc_count": 5}] + payload = { + "hits": {"total": {"value": 0}, "hits": []}, + "aggregations": { + "agg": { + "buckets": [{"key": 1, "doc_count": 2}, {"key": 2, "doc_count": 5}] + } + }, + } + assert expected == list(CrucibleService._aggs(payload, "agg")) + + +class TestFilterBuilders: + + @pytest.mark.parametrize( + "filters,terms", + ( + ( + ["param:v=1", "tag:x='one two'", "run:email='d@e.c'"], + ( + [ + { + "dis_max": { + "queries": [ + { + "bool": { + "must": [ + { + "term": { + "param.arg": "v", + }, + }, + { + "term": { + "param.val": "1", + }, + }, + ], + }, + }, + ], + }, + }, + ], + [ + { + "dis_max": { + "queries": [ + { + "bool": { + "must": [ + { + "term": { + "tag.name": "x", + }, + }, + { + "term": { + "tag.val": "one two", + }, + }, + ], + }, + }, + ], + }, + }, + ], + [ + { + "term": { + "run.email": "d@e.c", + }, + }, + ], + ), + ), + ( + ["param:v~a"], + ( + [ + { + "dis_max": { + "queries": [ + { + "bool": { + "must": [ + { + "term": { + "param.arg": "v", + }, + }, + { + "regexp": { + "param.val": ".*a.*", + }, + }, + ], + }, + }, + ], + }, + }, + ], + None, + None, + ), + ), + ( + ["tag:v~a"], + ( + None, + [ + { + "dis_max": { + "queries": [ + { + "bool": { + "must": [ + { + "term": { + "tag.name": "v", + }, + }, + { + "regexp": { + "tag.val": ".*a.*", + }, + }, + ], + }, + }, + ], + }, + }, + ], + None, + ), + ), + ), + ) + def test_build_filter_options(self, filters, terms): + assert terms == CrucibleService._build_filter_options(filters) + + def test_build_filter_bad_key(self): + with pytest.raises(HTTPException) as e: + CrucibleService._build_filter_options(["foobar:x=y"]) + assert 400 == e.value.status_code + assert "unknown filter namespace 'foobar'" == e.value.detail + + def test_build_name_filters(self): + assert [ + {"term": {"metric_desc.names.name": "1"}} + ] == CrucibleService._build_name_filters(["name=1"]) + + def test_build_name_filters_bad(self): + with pytest.raises(HTTPException) as e: + CrucibleService._build_name_filters(["xya:x"]) + assert 400 == e.value.status_code + assert "Filter item 'xya:x' must be '='" + + @pytest.mark.parametrize("periods", ([], ["10"], ["10", "20"])) + def test_build_period_filters(self, periods): + expected = ( + [] + if not periods + else [ + { + "dis_max": { + "queries": [ + {"bool": {"must_not": {"exists": {"field": "period"}}}}, + {"terms": {"period.id": periods}}, + ] + } + } + ] + ) + assert expected == CrucibleService._build_period_filters(periods) + + @pytest.mark.parametrize( + "term,message", + ( + ( + "foo:asc", + "Sort key 'foo' must be one of begin,benchmark,desc,email,end,harness,host,id,name,source", + ), + ("email:up", "Sort direction 'up' must be one of asc,desc"), + ), + ) + def test_build_sort_filters_error(self, term, message): + with pytest.raises(HTTPException) as exc: + CrucibleService._build_sort_terms([term]) + assert 400 == exc.value.status_code + assert message == exc.value.detail + + @pytest.mark.parametrize( + "sort,terms", + ( + ([], (("run.begin", {"order": "asc"}),)), + (["email:asc"], (("run.email", {"order": "asc"}),)), + ( + ["email:desc", "name:asc"], + (("run.email", {"order": "desc"}), ("run.name", {"order": "asc"})), + ), + ), + ) + def test_build_sort_filters(self, sort, terms): + expected = [{t[0]: t[1]} for t in terms] + assert expected == CrucibleService._build_sort_terms(sort) + + @pytest.mark.parametrize( + "periods,result", + ( + ( + [ + { + "period": { + "id": "one", + "begin": "1733505934677", + "end": "1733507347857", + } + } + ], + [ + {"range": {"metric_data.begin": {"gte": "1733505934677"}}}, + {"range": {"metric_data.end": {"lte": "1733507347857"}}}, + ], + ), + (None, []), + ), + ) + async def test_build_timestamp_filter( + self, fake_crucible: CrucibleService, periods, result + ): + plist = None + if periods: + fake_crucible.elastic.set_query("period", periods) + plist = [p["period"]["id"] for p in periods] + assert result == await fake_crucible._build_timestamp_range_filters(plist) + + @pytest.mark.parametrize( + "period,name", + ( + ({"period": {"id": "one"}}, "run None:None,iteration None,sample None"), + ( + { + "run": {"id": "rid", "benchmark": "test", "begin": "1234"}, + "iteration": {"id": "iid", "num": 1}, + "sample": {"id": "sid", "num": 1}, + "period": {"id": "one", "begin": "5423"}, + }, + "run test:1234,iteration 1,sample 1", + ), + ), + ) + async def test_build_timestamp_filter_bad( + self, fake_crucible: CrucibleService, period, name + ): + fake_crucible.elastic.set_query("period", [period]) + with pytest.raises(HTTPException) as exc: + await fake_crucible._build_timestamp_range_filters(["one"]) + assert 422 == exc.value.status_code + assert ( + f"Unable to compute '{name}' time range: the run is missing period timestamps" + == exc.value.detail + ) + + +class TestCrucible: + + async def test_create(self, fake_crucible): + """Create and close a CrucibleService instance""" + + assert fake_crucible + assert isinstance(fake_crucible, CrucibleService) + assert isinstance(fake_crucible.elastic, AsyncElasticsearch) + assert app.config.get_config().get("TEST.url") == fake_crucible.url + elastic = fake_crucible.elastic + await fake_crucible.close() + assert fake_crucible.elastic is None + assert elastic.closed + + async def test_search_args(self, fake_crucible: CrucibleService): + await fake_crucible.search( + "run", + [{"term": "a"}], + [{"x": {"field": "a"}}], + [{"key": "asc"}], + "run", + 42, + 69, + x=2, + z=3, + ) + assert [ + Request( + "cdmv7dev-run", + { + "_source": "run", + "aggs": [ + { + "x": { + "field": "a", + }, + }, + ], + "from": 69, + "query": { + "bool": { + "filter": [ + { + "term": "a", + }, + ], + }, + }, + "size": 42, + "sort": [ + { + "key": "asc", + }, + ], + }, + None, + None, + None, + {"x": 2, "z": 3}, + ) + ] == fake_crucible.elastic.requests + + async def test_metric_ids_none(self, fake_crucible): + """A simple query for failure matching metric IDs""" + + fake_crucible.elastic.set_query("metric_desc", []) + with pytest.raises(HTTPException) as e: + await fake_crucible._get_metric_ids("runid", "source::type") + assert 400 == e.value.status_code + assert "No matches for source::type" == e.value.detail + + @pytest.mark.parametrize( + "found,expected,aggregate", + ( + ( + [ + {"metric_desc": {"id": "one-metric"}}, + ], + ["one-metric"], + False, + ), + ( + [ + {"metric_desc": {"id": "one-metric"}}, + ], + ["one-metric"], + True, + ), + ( + [ + {"metric_desc": {"id": "one-metric"}}, + {"metric_desc": {"id": "two-metric"}}, + ], + ["one-metric", "two-metric"], + True, + ), + ), + ) + async def test_metric_ids(self, fake_crucible, found, expected, aggregate): + """A simple query for matching metric IDs""" + + fake_crucible.elastic.set_query("metric_desc", found) + assert expected == await fake_crucible._get_metric_ids( + "runid", + "source::type", + aggregate=aggregate, + ) + + @pytest.mark.parametrize( + "found,message", + ( + ( + [ + {"metric_desc": {"id": "one-metric", "names": {"john": "yes"}}}, + {"metric_desc": {"id": "two-metric", "names": {"john": "no"}}}, + ], + (2, [], {"john": ["no", "yes"]}), + ), + ( + [ + { + "period": {"id": "p1"}, + "metric_desc": {"id": "three-metric", "names": {"john": "yes"}}, + }, + {"metric_desc": {"id": "four-metric", "names": {"fred": "why"}}}, + { + "period": {"id": "p2"}, + "metric_desc": {"id": "five-metric", "names": {"john": "sure"}}, + }, + {"metric_desc": {"id": "six-metric", "names": {"john": "maybe"}}}, + ], + (4, ["p1", "p2"], {"john": ["maybe", "sure", "yes"]}), + ), + ), + ) + async def test_metric_ids_unproc(self, fake_crucible, found, message): + """Test matching metric IDs with lax criteria""" + + fake_crucible.elastic.set_query("metric_desc", found) + with pytest.raises(HTTPException) as exc: + await fake_crucible._get_metric_ids( + "runid", + "source::type", + aggregate=False, + ) + assert 422 == exc.value.status_code + assert { + "message": f"More than one metric ({message[0]}) means you should add breakout filters or aggregate.", + "periods": message[1], + "names": message[2], + } == exc.value.detail + + async def test_run_filters(self, fake_crucible): + """Test aggregations + + This is the "simplest" aggregation-based query, but we need to define + fake aggregations for the tag, param, and run indices. + """ + + fake_crucible.elastic.set_query( + "tag", + aggregations={ + "key": [ + { + "key": "topology", + "doc_count": 25, + "values": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [], + }, + }, + { + "key": "accelerator", + "doc_count": 19, + "values": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + {"key": "A100", "doc_count": 5}, + {"key": "L40S", "doc_count": 2}, + ], + }, + }, + { + "key": "project", + "doc_count": 19, + "values": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + {"key": "rhelai", "doc_count": 1}, + {"key": "rhosai", "doc_count": 2}, + ], + }, + }, + ] + }, + ) + fake_crucible.elastic.set_query( + "param", + aggregations={ + "key": [ + { + "key": "bucket", + "doc_count": 25, + "values": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [{"key": 200, "doc_count": 30}], + }, + }, + ] + }, + ) + fake_crucible.elastic.set_query( + "run", + aggregations={ + "begin": [{"key": 123456789, "doc_count": 1}], + "benchmark": [{"key": "ilab", "doc_count": 25}], + "desc": [], + "email": [ + {"key": "me@example.com", "doc_count": 10}, + {"key": "you@example.com", "doc_count": 15}, + ], + "end": [{"key": 1234, "doc_count": 10}], + "harness": [], + "host": [ + {"key": "one.example.com", "doc_count": 5}, + {"key": "two.example.com", "doc_count": 20}, + ], + "id": [], + "name": [], + "source": [], + }, + ) + filters = await fake_crucible.get_run_filters() + + # Array ordering is not reliable, so we need to sort + assert sorted(filters.keys()) == ["param", "run", "tag"] + assert sorted(filters["tag"].keys()) == ["accelerator", "project"] + assert sorted(filters["param"].keys()) == ["bucket"] + assert sorted(filters["run"].keys()) == ["benchmark", "email", "host"] + assert sorted(filters["tag"]["accelerator"]) == ["A100", "L40S"] + assert sorted(filters["param"]["bucket"]) == [200] + assert sorted(filters["run"]["benchmark"]) == ["ilab"] + assert sorted(filters["run"]["email"]) == ["me@example.com", "you@example.com"] + assert sorted(filters["run"]["host"]) == ["one.example.com", "two.example.com"] + + async def test_get_run_ids(self, fake_crucible: CrucibleService): + """_get_run_ids + + This is just straightline code coverage as there's no point in mocking + the filters. + """ + fake_crucible.elastic.set_query( + "period", + [{"run": {"id": "one"}}, {"run": {"id": "two"}}, {"run": {"id": "three"}}], + ) + assert {"one", "two", "three"} == await fake_crucible._get_run_ids( + "period", [{"term": {"period.name": "measurement"}}] + ) + + async def test_get_runs_none(self, fake_crucible: CrucibleService): + """Test run summary""" + fake_crucible.elastic.set_query("run", []) + fake_crucible.elastic.set_query("iteration", []) + fake_crucible.elastic.set_query("tag", []) + fake_crucible.elastic.set_query("param", []) + assert { + "count": 0, + "offset": 0, + "results": [], + "sort": [], + "total": 0, + } == await fake_crucible.get_runs() + + async def test_get_runs_time_reverse(self, fake_crucible: CrucibleService): + """Test run summary""" + fake_crucible.elastic.set_query("run", []) + fake_crucible.elastic.set_query("iteration", []) + fake_crucible.elastic.set_query("tag", []) + fake_crucible.elastic.set_query("param", []) + with pytest.raises(HTTPException) as exc: + await fake_crucible.get_runs(start="2025-01-01", end="2024-01-01") + assert 422 == exc.value.status_code + assert { + "error": "Invalid date format, start_date must be less than end_date" + } == exc.value.detail + + @pytest.mark.parametrize( + "args,miss,notag,noparam", + ( + ({}, False, False, False), + ({"size": 2, "offset": 1}, False, False, False), + ({"start": "2024-01-01"}, False, False, False), + ({"end": "2024-02-01"}, False, False, False), + ({"start": "2024-01-01", "end": "2025-01-01"}, False, False, False), + ({"sort": ["end:desc"]}, False, False, False), + ( + {"filter": ["tag:a=42", "param:z=xyzzy", "run:benchmark=test"]}, + False, + False, + False, + ), + ({"filter": ["tag:a=42", "param:z=xyzzy"]}, True, False, False), + ({"filter": ["tag:a=42", "param:z=xyzzy"]}, False, True, False), + ({"filter": ["tag:a=42", "param:z=xyzzy"]}, False, False, True), + ), + ) + async def test_get_runs_queries( + self, args, miss, notag, noparam, fake_crucible: CrucibleService + ): + """Test processing of various query parameters + + Note, this isn't really testing "behavior" of the filters, which is all + in Opensearch, just the CPT service's handling of the query parameters. + + TBD: This should really verify the generated Opensearch query filters, + although that's mostly covered by earlier tests. + """ + runs = [ + {"run": {"id": "r1", "begin": "0", "end": "5000", "benchmark": "test"}}, + ] + if miss: + # Add additional runs which will be rejected by filters + runs.extend( + [ + { + "run": { + "id": "r2", + "begin": "110", + "end": "7000", + "benchmark": "test", + } + }, + { + "run": { + "id": "r3", + "begin": "110", + "end": "6000", + "benchmark": "test", + } + }, + ] + ) + fake_crucible.elastic.set_query("run", runs) + fake_crucible.elastic.set_query( + "iteration", + [ + { + "run": {"id": "r1"}, + "iteration": { + "id": "i1", + "num": 1, + "primary-period": "tp", + "primary-metric": "src::tst1", + "status": "pass", + }, + }, + { + "run": {"id": "r1"}, + "iteration": { + "id": "i2", + "num": 2, + "primary-period": "tp", + "primary-metric": "src::tst2", + "status": "pass", + }, + }, + { + "run": {"id": "r1"}, + "iteration": { + "id": "i3", + "num": 3, + "primary-period": "tp", + "primary-metric": "src::tst1", + "status": "fail", + }, + }, + ], + ) + + if notag: + tags = [] + else: + tags = [ + {"run": {"id": "r1"}, "tag": {"name": "a", "val": 42}}, + {"run": {"id": "r2"}, "tag": {"name": "a", "val": 42}}, + ] + fake_crucible.elastic.set_query("tag", tags, repeat=2) + + if noparam: + params = [] + else: + params = [ + { + "run": {"id": "r1"}, + "iteration": {"id": "i1"}, + "param": {"arg": "b", "val": "cde"}, + }, + { + "run": {"id": "r1"}, + "iteration": {"id": "i1"}, + "param": {"arg": "z", "val": "xyzzy"}, + }, + { + "run": {"id": "r3"}, + "iteration": {"id": "i1"}, + "param": {"arg": "z", "val": "xyzzy"}, + }, + { + "run": {"id": "r1"}, + "iteration": {"id": "i2"}, + "param": {"arg": "b", "val": "cde"}, + }, + { + "run": {"id": "r1"}, + "iteration": {"id": "i2"}, + "param": {"arg": "x", "val": "plugh"}, + }, + ] + fake_crucible.elastic.set_query("param", params, repeat=2) + expected = { + "count": 1, + "offset": 0, + "results": [ + { + "begin": "0", + "begin_date": "1970-01-01 00:00:00+00:00", + "benchmark": "test", + "end": "5000", + "end_date": "1970-01-01 00:00:05+00:00", + "id": "r1", + "iterations": [ + { + "iteration": 1, + "params": defaultdict( + None, + { + "b": "cde", + "z": "xyzzy", + }, + ), + "primary_metric": "src::tst1", + "primary_period": "tp", + "status": "pass", + }, + { + "iteration": 2, + "params": defaultdict( + None, + { + "b": "cde", + "x": "plugh", + }, + ), + "primary_metric": "src::tst2", + "primary_period": "tp", + "status": "pass", + }, + { + "iteration": 3, + "params": {}, + "primary_metric": "src::tst1", + "primary_period": "tp", + "status": "fail", + }, + ], + "params": {}, + "primary_metrics": {"src::tst1", "src::tst2"}, + "status": "fail", + "tags": defaultdict(None, {"a": 42}), + }, + ], + "sort": [], + "total": 1, + } + if notag or noparam: + expected["results"] = [] + expected["count"] = 0 + expected["total"] = 0 + else: + if miss: + expected["total"] = 3 + if "size" in args: + expected["size"] = args["size"] + if args.get("offset"): + expected["offset"] = args["offset"] + if args.get("start"): + expected["startDate"] = ( + datetime.fromisoformat(args["start"]) + .astimezone(tz=timezone.utc) + .isoformat() + ) + if args.get("end"): + expected["endDate"] = ( + datetime.fromisoformat(args["end"]) + .astimezone(tz=timezone.utc) + .isoformat() + ) + if args.get("sort"): + expected["sort"] = args["sort"] + assert expected == await fake_crucible.get_runs(**args) + + async def test_get_tags(self, fake_crucible: CrucibleService): + """Get tags for a run ID""" + fake_crucible.elastic.set_query( + "tag", + [ + {"run": {"id": "one"}, "tag": {"name": "a", "val": 123}}, + {"run": {"id": "one"}, "tag": {"name": "b", "val": "hello"}}, + {"run": {"id": "one"}, "tag": {"name": "c", "val": False}}, + ], + ) + assert {"a": 123, "b": "hello", "c": False} == await fake_crucible.get_tags( + "one" + ) + + async def test_get_params_none(self, fake_crucible: CrucibleService): + """Test error when neither run nor iteration is specified""" + with pytest.raises(HTTPException) as exc: + await fake_crucible.get_params() + assert 400 == exc.value.status_code + assert ( + "A params query requires either a run or iteration ID" == exc.value.detail + ) + + async def test_get_params_run(self, fake_crucible: CrucibleService): + """Get parameters for a run""" + params = [ + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "a", "val": 10}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "b", "val": 5}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "c", "val": "val"}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid2"}, + "param": {"arg": "a", "val": 7}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid2"}, + "param": {"arg": "c", "val": "val"}, + }, + ] + fake_crucible.elastic.set_query("param", params) + assert { + "common": {"c": "val"}, + "iid1": {"a": 10, "b": 5, "c": "val"}, + "iid2": {"a": 7, "c": "val"}, + } == await fake_crucible.get_params("rid") + + async def test_get_params_iteration(self, fake_crucible: CrucibleService): + """Get parameters for an iteration""" + params = [ + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "a", "val": 10}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "b", "val": 5}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "c", "val": "val"}, + }, + ] + fake_crucible.elastic.set_query("param", params) + assert { + "iid1": {"a": 10, "b": 5, "c": "val"} + } == await fake_crucible.get_params(None, "iid1") + + async def test_get_params_iteration_dup(self, fake_crucible: CrucibleService): + """Cover an obscure log warning case""" + params = [ + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "a", "val": 10}, + }, + { + "run": {"id": "rid"}, + "iteration": {"id": "iid1"}, + "param": {"arg": "a", "val": 5}, + }, + ] + fake_crucible.elastic.set_query("param", params) + assert {"iid1": {"a": 5}} == await fake_crucible.get_params(None, "iid1") + + async def test_get_iterations(self, fake_crucible: CrucibleService): + """Get iterations for a run ID""" + iterations = [ + { + "id": "one", + "num": 1, + "path": None, + "primary_metric": "test::metric1", + "primary_period": "measurement", + "status": "pass", + }, + { + "id": "two", + "num": 2, + "path": None, + "primary_metric": "test::metric2", + "primary_period": "measurement", + "status": "pass", + }, + { + "id": "three", + "num": 3, + "path": None, + "primary_metric": "test::metric1", + "primary_period": "measurement", + "status": "pass", + }, + ] + fake_crucible.elastic.set_query( + "iteration", + [ + { + "run": {"id": "one"}, + "iteration": i, + } + for i in iterations + ], + ) + assert iterations == await fake_crucible.get_iterations("one") + + async def test_get_samples_none(self, fake_crucible: CrucibleService): + """Test error when neither run nor iteration is specified""" + with pytest.raises(HTTPException) as exc: + await fake_crucible.get_samples() + assert 400 == exc.value.status_code + assert ( + "A sample query requires either a run or iteration ID" == exc.value.detail + ) + + @pytest.mark.parametrize("ids", (("one", None), (None, 1))) + async def test_get_samples(self, fake_crucible: CrucibleService, ids): + """Get samples for a run ID""" + samples = [ + { + "num": "1", + "path": None, + "id": "one", + "status": "pass", + "primary_metric": "pm", + "primary_period": "m", + "iteration": 1, + }, + { + "id": "two", + "num": "2", + "path": None, + "status": "pass", + "primary_metric": "pm", + "primary_period": "m", + "iteration": 1, + }, + { + "id": "three", + "num": "3", + "path": None, + "status": "pass", + "primary_metric": "pm", + "primary_period": "m", + "iteration": 1, + }, + ] + fake_crucible.elastic.set_query( + "sample", + [ + { + "run": {"id": "one"}, + "iteration": { + "primary-metric": "pm", + "primary-period": "m", + "num": 1, + }, + "sample": s, + } + for s in samples + ], + ) + assert samples == await fake_crucible.get_samples(*ids) + + async def test_get_periods_none(self, fake_crucible: CrucibleService): + """Test error when neither run, iteration, nor sample is specified""" + with pytest.raises(HTTPException) as exc: + await fake_crucible.get_periods() + assert 400 == exc.value.status_code + assert ( + "A period query requires a run, iteration, or sample ID" == exc.value.detail + ) + + @pytest.mark.parametrize( + "ids", (("one", None, None), (None, 1, None), (None, None, 1)) + ) + async def test_get_periods(self, fake_crucible: CrucibleService, ids): + """Get samples for a run ID""" + periods = [ + { + "begin": "2024-12-05 21:16:31.046000+00:00", + "end": "2024-12-05 21:40:31.166000+00:00", + "id": "306C8A78-B352-11EF-8E37-AD212D0A0B9F", + "name": "measurement", + "iteration": 1, + "sample": 1, + "primary_metric": "ilab::sdg-samples-sec", + "status": "pass", + } + ] + fake_crucible.elastic.set_query( + "period", + [ + { + "run": {"id": "one"}, + "iteration": { + "primary-metric": p["primary_metric"], + "primary-period": "measurement", + "num": 1, + "status": p["status"], + }, + "sample": {"num": 1, "status": p["status"], "path": None}, + "period": { + "id": p["id"], + "name": p["name"], + "begin": str( + int(datetime.fromisoformat(p["begin"]).timestamp() * 1000) + ), + "end": str( + int(datetime.fromisoformat(p["end"]).timestamp() * 1000) + ), + "primary-metric": p["primary_metric"], + "status": p["status"], + }, + } + for p in periods + ], + ) + assert periods == await fake_crucible.get_periods(*ids) + + async def test_get_metrics_list(self, fake_crucible: CrucibleService): + """Get samples for a run ID""" + metrics = { + "source1::type1": { + "periods": [], + "breakouts": {"name1": ["value1", "value2"]}, + }, + "source1::type2": {"periods": ["p1", "p2"], "breakouts": {}}, + } + query = [ + { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "names": {"name1": "value1"}, + }, + }, + { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "names": {"name1": "value1"}, + }, + }, + { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "names": {"name1": "value2"}, + }, + }, + { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "names": {"name1": "value2"}, + }, + }, + { + "run": {"id": "one"}, + "period": {"id": "p1"}, + "metric_desc": {"source": "source1", "type": "type2", "names": {}}, + }, + { + "run": {"id": "one"}, + "period": {"id": "p2"}, + "metric_desc": {"source": "source1", "type": "type2", "names": {}}, + }, + ] + fake_crucible.elastic.set_query("metric_desc", query) + result = await fake_crucible.get_metrics_list("one") + + # NOTE: the method returns a defaultdict, which doesn't compare to a + # dict but "in the real world" serializes the same: so we just + # serialize and deserialize to mimic the actual API behavior. + result = json.loads(json.dumps(result)) + assert metrics == result + + async def test_get_metric_breakout_none(self, fake_crucible: CrucibleService): + """Test error when the metric isn't found""" + fake_crucible.elastic.set_query("metric_desc", []) + with pytest.raises(HTTPException) as exc: + await fake_crucible.get_metric_breakouts( + "one", metric="source1::type1", names=[], periods=[] + ) + assert 400 == exc.value.status_code + assert "Metric name source1::type1 not found for run one" == exc.value.detail + + @pytest.mark.parametrize("period", (True, False)) + async def test_get_metric_breakout(self, period, fake_crucible: CrucibleService): + """Get samples for a run ID""" + metrics = { + "label": "source1::type1", + "class": ["classless", "classy"], + "type": "type1", + "source": "source1", + "breakouts": {"name1": ["value1", "value2"]}, + } + md1 = { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "class": "classy", + "names": {"name1": "value1"}, + }, + } + md2 = { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "names": {"name1": "value2"}, + }, + } + if period: + metrics["periods"] = ["p1", "p2"] + md1["period"] = {"id": "p1"} + md2["period"] = {"id": "p2"} + query = [ + md1, + md2, + { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "class": "classless", + "names": {"name1": "value1"}, + }, + }, + { + "run": {"id": "one"}, + "metric_desc": { + "source": "source1", + "type": "type1", + "names": {"name1": "value2"}, + }, + }, + ] + fake_crucible.elastic.set_query("metric_desc", query) + result = await fake_crucible.get_metric_breakouts( + "one", metric="source1::type1", names=[], periods=[] + ) + + # NOTE: the method returns a defaultdict, which doesn't compare to a + # dict but "in the real world" serializes the same: so we just + # serialize and deserialize to mimic the actual API behavior. + result = json.loads(json.dumps(result)) + assert metrics == result + + async def test_metrics_data_one_noagg(self, fake_crucible: CrucibleService): + """Return data samples for a single metric""" + + fake_crucible.elastic.set_query( + "metric_desc", + [{"metric_desc": {"id": "one-metric", "names": {}}}], + ) + fake_crucible.elastic.set_query( + "metric_data", + [ + { + "metric_desc": {"id": "one-metric"}, + "metric_data": { + "begin": "1726165775123", + "end": "1726165789213", + "duration": 14100, + "value": 9.35271216694379, + }, + }, + { + "metric_desc": {"id": "one-metric"}, + "metric_data": { + "begin": "1726165790000", + "end": "1726165804022", + "duration": 14022, + "value": 9.405932330557683, + }, + }, + ], + ) + expected = [ + { + "begin": "2024-09-12 18:29:35.123000+00:00", + "duration": 14.1, + "end": "2024-09-12 18:29:49.213000+00:00", + "value": 9.35271216694379, + }, + { + "begin": "2024-09-12 18:29:50+00:00", + "duration": 14.022, + "end": "2024-09-12 18:30:04.022000+00:00", + "value": 9.405932330557683, + }, + ] + assert expected == await fake_crucible.get_metrics_data("runid", "source::type") + assert fake_crucible.elastic.requests == [ + Request( + "cdmv7dev-metric_desc", + { + "query": { + "bool": { + "filter": [ + { + "term": { + "run.id": "runid", + }, + }, + { + "term": { + "metric_desc.source": "source", + }, + }, + { + "term": { + "metric_desc.type": "type", + }, + }, + ], + }, + }, + "size": 262144, + }, + kwargs={"ignore_unavailable": True}, + ), + Request( + "cdmv7dev-metric_data", + { + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": [ + "one-metric", + ], + }, + }, + ], + }, + }, + "size": 262144, + }, + ), + ] + + @pytest.mark.parametrize("count", (0, 2)) + async def test_metrics_data_agg(self, count, fake_crucible): + """Return data samples for aggregated metrics""" + + fake_crucible.elastic.set_query( + "metric_desc", + [ + {"metric_desc": {"id": "one-metric", "names": {}}}, + {"metric_desc": {"id": "two-metric", "names": {}}}, + ], + ) + fake_crucible.elastic.set_query( + "metric_data", + aggregations={ + "duration": { + "count": count, + "min": 14022, + "max": 14100, + "avg": 14061, + "sum": 28122, + } + }, + ) + if count: + fake_crucible.elastic.set_query( + "metric_data", + aggregations={ + "interval": [ + {"key": 1726165789213, "value": {"value": 9.35271216694379}}, + {"key": 1726165804022, "value": {"value": 9.405932330557683}}, + ] + }, + ) + expected = [ + { + "begin": "2024-09-12 18:29:35.191000+00:00", + "duration": 14.022, + "end": "2024-09-12 18:29:49.213000+00:00", + "value": 9.35271216694379, + }, + { + "begin": "2024-09-12 18:29:50+00:00", + "duration": 14.022, + "end": "2024-09-12 18:30:04.022000+00:00", + "value": 9.405932330557683, + }, + ] + else: + expected = [] + assert expected == await fake_crucible.get_metrics_data( + "r1", "source::type", aggregate=True + ) + expected_requests = [ + Request( + "cdmv7dev-metric_desc", + { + "query": { + "bool": { + "filter": [ + { + "term": { + "run.id": "r1", + }, + }, + { + "term": { + "metric_desc.source": "source", + }, + }, + { + "term": { + "metric_desc.type": "type", + }, + }, + ], + }, + }, + "size": 262144, + }, + kwargs={"ignore_unavailable": True}, + ), + Request( + "cdmv7dev-metric_data", + { + "aggs": { + "duration": { + "stats": { + "field": "metric_data.duration", + }, + }, + }, + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": [ + "one-metric", + "two-metric", + ], + }, + }, + ], + }, + }, + "size": 0, + }, + ), + ] + if count: + expected_requests.append( + Request( + "cdmv7dev-metric_data", + { + "aggs": { + "interval": { + "aggs": { + "value": { + "sum": { + "field": "metric_data.value", + }, + }, + }, + "histogram": { + "field": "metric_data.end", + "interval": 14022, + }, + }, + }, + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": [ + "one-metric", + "two-metric", + ], + }, + }, + ], + }, + }, + "size": 0, + }, + ), + ) + assert fake_crucible.elastic.requests == expected_requests + + async def test_metrics_summary(self, fake_crucible: CrucibleService): + """Return data summary for a metrics""" + + fake_crucible.elastic.set_query( + "metric_desc", + [ + {"metric_desc": {"id": "one-metric", "names": {"a": "1"}}}, + ], + ) + expected = { + "count": 5, + "min": 9.35271216694379, + "max": 9.405932330557683, + "avg": 9.379322249, + "sum": 18.758644498, + } + fake_crucible.elastic.set_query("metric_data", aggregations={"score": expected}) + assert expected == await fake_crucible.get_metrics_summary( + "runid", "one-metric::type", ["a=1"] + ) + assert fake_crucible.elastic.requests == [ + Request( + "cdmv7dev-metric_desc", + { + "query": { + "bool": { + "filter": [ + { + "term": { + "run.id": "runid", + }, + }, + { + "term": { + "metric_desc.source": "one-metric", + }, + }, + { + "term": { + "metric_desc.type": "type", + }, + }, + {"term": {"metric_desc.names.a": "1"}}, + ], + }, + }, + "size": 262144, + }, + kwargs={"ignore_unavailable": True}, + ), + Request( + "cdmv7dev-metric_data", + { + "aggs": {"score": {"stats": {"field": "metric_data.value"}}}, + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": [ + "one-metric", + ], + }, + }, + ], + }, + }, + "size": 0, + }, + ), + ] + + @pytest.mark.parametrize( + "runs,param_idx,periods,period_idx,title", + ( + ([], 0, [], 0, "source::type"), + (["r2", "r1"], 0, [], 0, "source::type {run 2}"), + ([], 0, ["p1"], 0, "source::type (n=42)"), + ([], 1, ["p1"], 1, "source::type"), + ([], 1, ["p1"], 2, "source::type"), + ), + ) + async def test_graph_title_no_query( + self, + runs, + param_idx, + periods, + period_idx, + title, + fake_crucible: CrucibleService, + ): + """Test generation of default metric titles""" + + param_runs = [ + {"r1": {"i1": {"n": "42"}, "i2": {"n": "31"}}}, + {"r1": {"i1": {"n": "42"}, "i2": {"n": "42"}}}, + ][param_idx] + period_runs = [ + {"r1": {"i1": {"p1"}, "i2": {"p2"}}}, + {"r1": {"i1": {"p1"}}}, + {"r1": {"i1": {"p2"}}}, + ][period_idx] + name = await fake_crucible._graph_title( + "r1", + runs, + Graph(metric="source::type", periods=periods), + param_runs, + period_runs, + ) + assert name == title + + async def test_graph_title_query(self, fake_crucible: CrucibleService): + """Test generation of default metric titles""" + + param_runs = {} + period_runs = {} + fake_crucible.elastic.set_query( + "param", + [ + { + "run": {"id": "r1"}, + "iteration": {"id": "i1"}, + "param": {"arg": "a", "val": "1"}, + }, + ], + ) + fake_crucible.elastic.set_query( + "period", + [ + { + "run": {"id": "r1"}, + "iteration": {"id": "i1"}, + "period": {"id": "p1"}, + }, + ], + ) + name = await fake_crucible._graph_title( + "r1", + [], + Graph(metric="source::type"), + param_runs, + period_runs, + ) + assert name == "source::type" + assert fake_crucible.elastic.requests == [ + Request( + "cdmv7dev-param", + { + "query": { + "bool": { + "filter": [ + { + "term": { + "run.id": "r1", + }, + }, + ], + }, + }, + "size": 262144, + }, + ), + Request( + "cdmv7dev-period", + { + "query": { + "bool": { + "filter": [ + { + "term": { + "run.id": "r1", + }, + }, + ], + }, + }, + "size": 262144, + }, + ), + ] + + async def test_metrics_graph_norun(self, fake_crucible: CrucibleService): + with pytest.raises(HTTPException) as exc: + await fake_crucible.get_metrics_graph( + GraphList( + name="graph", + graphs=[Graph(metric="source::type", aggregate=True, title="test")], + ) + ) + assert exc.value.status_code == 400 + assert exc.value.detail == "each graph request must have a run ID" + + @pytest.mark.parametrize("count", (0, 2)) + async def test_metrics_graph(self, count, fake_crucible: CrucibleService): + """Return graph for aggregated metrics""" + + metrics = [{"metric_desc": {"id": "one-metric", "names": {}}}] + if count: + metrics.append({"metric_desc": {"id": "two-metric", "names": {}}}) + fake_crucible.elastic.set_query( + "metric_data", + aggregations={ + "duration": { + "count": count, + "min": 14022, + "max": 14100, + "avg": 14061, + "sum": 28122, + } + }, + ) + fake_crucible.elastic.set_query( + "metric_data", + aggregations={ + "interval": [ + {"key": 1726165789213, "value": {"value": 9.35271216694379}}, + {"key": 1726165804022, "value": {"value": 9.405932330557683}}, + ] + }, + ) + expected = { + "data": [ + { + "labels": { + "x": "sample timestamp", + "y": "samples / second", + }, + "marker": { + "color": "black", + }, + "mode": "line", + "name": "test", + "type": "scatter", + "x": [ + "2024-09-12 18:29:49.213000+00:00", + "2024-09-12 18:30:03.234000+00:00", + "2024-09-12 18:30:04.022000+00:00", + "2024-09-12 18:30:18.043000+00:00", + ], + "y": [ + 9.35271216694379, + 9.35271216694379, + 9.405932330557683, + 9.405932330557683, + ], + "yaxis": "y", + }, + ], + "layout": { + "width": "1500", + "yaxis": { + "color": "black", + "title": "source::type", + }, + }, + } + else: + expected = { + "data": [ + { + "labels": { + "x": "sample timestamp", + "y": "samples / second", + }, + "marker": { + "color": "black", + }, + "mode": "line", + "name": "test", + "type": "scatter", + "x": [ + "2024-09-12 18:29:49.213000+00:00", + "2024-09-12 18:29:50.213000+00:00", + "2024-09-12 18:30:04.022000+00:00", + "2024-09-12 18:30:05.022000+00:00", + ], + "y": [ + 9.35271216694379, + 9.35271216694379, + 9.405932330557683, + 9.405932330557683, + ], + "yaxis": "y", + }, + ], + "layout": { + "width": "1500", + "yaxis": { + "color": "black", + "title": "source::type", + }, + }, + } + fake_crucible.elastic.set_query( + "metric_data", + [ + { + "metric_data": { + "begin": "1726165789213", + "end": "1726165790213", + "value": 9.35271216694379, + } + }, + { + "metric_data": { + "begin": "1726165804022", + "end": "1726165805022", + "value": 9.405932330557683, + } + }, + ], + ) + fake_crucible.elastic.set_query("metric_desc", metrics) + + assert expected == await fake_crucible.get_metrics_graph( + GraphList( + run="r1", + name="graph", + graphs=[Graph(metric="source::type", aggregate=True, title="test")], + ) + ) + expected_requests = [ + Request( + "cdmv7dev-metric_desc", + { + "query": { + "bool": { + "filter": [ + { + "term": { + "run.id": "r1", + }, + }, + { + "term": { + "metric_desc.source": "source", + }, + }, + { + "term": { + "metric_desc.type": "type", + }, + }, + ], + }, + }, + "size": 262144, + }, + kwargs={"ignore_unavailable": True}, + ), + ] + if count: + expected_requests.extend( + [ + Request( + "cdmv7dev-metric_data", + { + "aggs": { + "duration": { + "stats": { + "field": "metric_data.duration", + }, + }, + }, + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": [ + "one-metric", + "two-metric", + ], + }, + }, + ], + }, + }, + "size": 0, + }, + ), + Request( + "cdmv7dev-metric_data", + { + "aggs": { + "interval": { + "aggs": { + "value": { + "sum": { + "field": "metric_data.value", + }, + }, + }, + "histogram": { + "field": "metric_data.begin", + "interval": 14022, + }, + }, + }, + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": [ + "one-metric", + "two-metric", + ], + }, + }, + ], + }, + }, + "size": 0, + }, + ), + ] + ) + else: + expected_requests.append( + Request( + "cdmv7dev-metric_data", + { + "query": { + "bool": { + "filter": [ + { + "terms": { + "metric_desc.id": ["one-metric"], + }, + }, + ], + }, + }, + "size": 262144, + }, + ), + ) + assert fake_crucible.elastic.requests == expected_requests