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Support spans count metrics#19293

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serena-ruan merged 3 commits intotrace-metricsfrom
spans_count_metrics
Dec 17, 2025
Merged

Support spans count metrics#19293
serena-ruan merged 3 commits intotrace-metricsfrom
spans_count_metrics

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@serena-ruan serena-ruan commented Dec 9, 2025 •
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Install mlflow from this PR

# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/19293/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/19293/merge#subdirectory=libs/skinny

For Databricks, use the following command:

%sh curl -LsSf https://raw.githubusercontent.com/mlflow/mlflow/HEAD/dev/install-skinny.sh | sh -s pull/19293/merge

Related Issues/PRs

#xxx

What changes are proposed in this pull request?

Support COUNT on spans.
Refactor the utils a bit so we can reuse the function for traces view & spans view, since the main structure is the same and the only difference is what tables to join and columns to fetch.

How is this PR tested?

  • Existing unit/integration tests
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Does this PR require documentation update?

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  • Yes. I've updated:
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  • area/tracking: Tracking Service, tracking client APIs, autologging
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
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  • area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
  • area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
  • area/prompts: MLflow prompt engineering features, prompt templates, and prompt management
  • area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
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  • rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
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  • rn/feature - A new user-facing feature worth mentioning in the release notes
  • rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
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@github-actions github-actions bot added the rn/none List under Small Changes in Changelogs. label Dec 9, 2025
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github-actions bot commented Dec 9, 2025 •
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@serena-ruan serena-ruan force-pushed the spans_count_metrics branch 3 times, most recently from 71fd561 to 9da86ff Compare December 12, 2025 07:03
@serena-ruan serena-ruan changed the base branch from query_trace_tokens to trace-metrics December 16, 2025 05:30
@serena-ruan
spans count metrics support
94d747f 
Signed-off-by: Serena Ruan <serena.rxy@gmail.com>
@serena-ruan
simplify and fix mssql
baa3bf6 
Signed-off-by: Serena Ruan <serena.rxy@gmail.com>
@harupy harupy requested a review from Copilot December 16, 2025 05:55
Copilot AI reviewed Dec 16, 2025
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Pull request overview

This PR adds support for COUNT aggregation metrics on spans and refactors the metric query utilities to support both traces and spans views using a unified query function.

Key Changes:

  • Added SPANS view type support with COUNT aggregation for the "span" metric grouped by span_type dimension
  • Refactored query_metrics_for_traces_view into a unified query_metrics function that handles both TRACES and SPANS view types
  • Extracted view-specific logic into helper functions (_apply_view_initial_join, _apply_dimension_to_query, _apply_metric_specific_joins, _get_aggregation_column)

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

File Description
tests/store/tracking/test_sqlalchemy_store_query_trace_metrics.py Added comprehensive test coverage for span count metrics including: no dimensions, grouped by span_type, with time intervals, with filters, and across multiple traces
mlflow/store/tracking/utils/sql_trace_metrics_utils.py Refactored metric query logic into view-agnostic functions, added SPANS_METRICS_CONFIGS, updated time bucket expression to handle spans timestamps (nanoseconds), and generalized dimension/aggregation handling
mlflow/store/tracking/sqlalchemy_store.py Simplified query_trace_metrics by replacing view-specific conditional logic with unified query_metrics function call

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B-Step62
B-Step62 reviewed Dec 16, 2025
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mlflow/store/tracking/utils/sql_trace_metrics_utils.py


def query_metrics_for_traces_view(
def query_metrics(
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Shall we separate this into a function to build query and another one to run it and convert result? Since we have many query building logic, it would be easier for us to assert generated query directly rather than having lots of e2e test.

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@serena-ruan serena-ruan Dec 16, 2025 •
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Isn't verifying both more robust? IMO it's more complex that we verify on the query instead of the result, given we have four database engine types to support

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Yeah we want both. The problem is currently we can only have e2e test, where preparing real data for every potential case is cumbersome, then we tend to add less test coverage because it is tedious. Not a blocker, but I think it is more future proof to make it unit-testable especially we will likely to add more filtering logic.

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94d0c38 
Signed-off-by: Serena Ruan <serena.rxy@gmail.com>
@serena-ruan serena-ruan requested a review from B-Step62 December 17, 2025 04:51
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LGTM, https://github.com/mlflow/mlflow/pull/19293/changes#r2622036483 is not a blocker but I recommend addressing this before the e2e test suite becomes too large.

@serena-ruan serena-ruan merged commit 83035bc into trace-metrics Dec 17, 2025
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@serena-ruan serena-ruan deleted the spans_count_metrics branch December 17, 2025 08:16
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