fix: make EnsembleByKey transformSchema match output by fallintoplace · Pull Request #2575 · microsoft/SynapseML

Minh Vu (fallintoplace) · 2026-07-26T02:05:54Z

Problem

EnsembleByKey.transformSchema describes the opposite shape from transform:

with collapseGroup=true, transform returns grouping keys and aggregate columns, while transformSchema keeps every input column
with collapseGroup=false, transform joins aggregates back to the input, while transformSchema keeps only fields selected from the aggregation column set

This can break pipeline schema validation because the declared schema differs from the DataFrame produced at runtime. The old implementation also fails when transformSchema is called before transform without explicit colNames, and declares FloatType for scalar means that Spark produces as DoubleType.

Changes

initialize default output names consistently from both transform and transformSchema
derive grouping fields from keys
return grouping fields followed by aggregate fields for collapsed groups
match Spark join ordering for non-collapsed groups: keys, remaining non-overwritten input fields, then aggregates
declare scalar mean outputs as DoubleType for both float and double inputs
assert exact schema equality for double and float inputs in both collapse modes, with distinct key and aggregation columns and no explicit output name

Testing

core/testOnly com.microsoft.azure.synapse.ml.stages.EnsembleByKeySuite (38 tests passed)
core/testOnly com.microsoft.azure.synapse.ml.stages.EnsembleByKeyResolutionSuite (7 tests passed)
core/Test/scalastyle (0 findings)
core/Compile/scalastyle (0 findings)

Behavior change disclosure

Beyond the schema fix, this PR changes the join in collapseGroup=false mode from a null-unsafe equi-join to a null-safe one (<=>).

Rows whose grouping key is null were previously dropped from the output entirely. They are now retained. This is a data-loss fix rather than a regression, but it is an observable row-set change for anyone relying on the old behavior as an implicit null filter. Covered by an explicit test.

azure-pipelines · 2026-07-26T02:06:02Z

Azure Pipelines: There may be pipelines that require an authorized user to comment /azp run to run.

github-actions · 2026-07-26T02:06:04Z

Hey Minh Vu (@fallintoplace) 👋!
Thank you so much for contributing to our repository 🙌.
Someone from SynapseML Team will be reviewing this pull request soon.

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fix: Fix LightGBM crashes with empty partitions
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docs: Update Spark Serving usage
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Pull request overview

This PR updates EnsembleByKey’s transformSchema logic so it matches the actual output schema produced by transform, across both collapseGroup=true and collapseGroup=false modes, and adds a regression test to validate schema consistency.

Changes:

Rebuild transformSchema output fields using keys for grouping fields and consistent output ordering for both collapse modes.
In non-collapsing mode, model Spark join column ordering and drop/replace conflicting output column names in the predicted schema.
Add a test asserting transformSchema(schema) equals transform(df).schema for both collapse modes.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.

File	Description
core/src/main/scala/com/microsoft/azure/synapse/ml/stages/EnsembleByKey.scala	Adjusts `transformSchema` field selection and ordering to align with `transform` behavior.
core/src/test/scala/com/microsoft/azure/synapse/ml/stages/EnsembleByKeySuite.scala	Adds schema-equality coverage for both `collapseGroup` modes.

Rana Singh (ranadeepsingh) · 2026-07-31T05:55:02Z

/azp run

azure-pipelines · 2026-07-31T05:55:13Z

Azure Pipelines: Successfully started running 1 pipeline(s).

Codecov Comments Bot (codecov-commenter) · 2026-07-31T06:11:22Z

Codecov Report

❌ Patch coverage is 98.20789% with 5 lines in your changes missing coverage. Please review.
✅ Project coverage is 86.99%. Comparing base (7088a6a) to head (9ba8644).

Files with missing lines	Patch %	Lines
...rosoft/azure/synapse/ml/stages/EnsembleByKey.scala	98.20%	5 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2575      +/-   ##
==========================================
+ Coverage   86.81%   86.99%   +0.17%     
==========================================
  Files         336      336              
  Lines       18275    18518     +243     
  Branches     1673     1725      +52     
==========================================
+ Hits        15866    16110     +244     
+ Misses       2409     2408       -1

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Rana Singh (ranadeepsingh) · 2026-07-31T06:31:17Z

/azp run

azure-pipelines · 2026-07-31T06:31:26Z

Azure Pipelines: Successfully started running 1 pipeline(s).

Rana Singh (ranadeepsingh) · 2026-07-31T08:14:50Z

/azp run

azure-pipelines · 2026-07-31T08:15:03Z

Azure Pipelines: Successfully started running 1 pipeline(s).

Rana Singh (ranadeepsingh) · 2026-07-31T08:59:11Z

CI follow-up for f4bc2c9: Azure build 229036776 completed with 67 successful checks. The only failing job was Databricks E2E databricks-gpu, which aborted before running tests (Tests: succeeded 0, failed 0) because cluster startup terminated with INSTANCE_POOL_MAX_CAPACITY_REACHED / Instance pool is full. All CPU Databricks jobs, core/stages unit tests, Python/R tests, style, publish, and Fabric E2E passed. This is infrastructure-only, so I am not issuing another /azp run.

Rana Singh (ranadeepsingh) · 2026-07-31T18:16:04Z

/azp run

azure-pipelines · 2026-07-31T18:16:15Z

Azure Pipelines: Successfully started running 1 pipeline(s).

Rana Singh (ranadeepsingh) · 2026-07-31T23:11:20Z

/azp run

azure-pipelines · 2026-07-31T23:11:30Z

Azure Pipelines: Successfully started running 1 pipeline(s).

AB#2575 ## Summary Add Round 3 code review artifact for SynapseML PR microsoft#2575 focusing on edge cases and robustness. ## Prompting Intent Perform Round 3 of the DIRECT sequential six-round review gauntlet for SynapseML PR microsoft#2575. Focus on edge cases, robustness, error handling, boundary conditions, concurrency/session behavior, and failure modes. ## Linked Sources - Prompt: C:\Users\singhrana\.copilot\session-state\c2ea157b-c36a-4cbc-896d-e8caa3ea05bd\files\pr-2575\prompts\review-round-3.md - Review artifact: C:\Users\singhrana\Documents\SynapseML-pr-2575\reviews\pr-2575\task-2575-attempt-1-review-3-gemini-3.6-flash.md ## Rationale Recorded findings for edge cases, null join behavior, session case sensitivity, and vector aggregate nullability in the Round 3 review artifact as instructed. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

## Summary Make EnsembleByKey schema resolution match Spark output for collapsed and non-collapsed transforms, including scalar and vector means, nested and qualified keys, duplicate attributes, null keys, overwrite behavior, output naming, metadata, nullability, and unsupported inputs. Add generated-Python compatibility coverage and preserve the complete six-round review audit trail. ## Prompting Intent Take end-to-end ownership of GitHub PR microsoft#2575 in an isolated worktree. Independently verify and harden EnsembleByKey schema behavior, run the required six-round DIRECT sequential multi-model review, fix and rerun every finding until clean, validate Scala and generated-language surfaces, avoid generated target edits and history rewrites, and prepare the existing PR branch for normal push and Azure validation. ## Linked Sources - Pull request: microsoft#2575 - Round 1 review: reviews/pr-2575/task-2575-attempt-1-review-1-claude-opus-5.md - Round 2 review: reviews/pr-2575/task-2575-attempt-1-review-2-gpt-5.6-sol.md - Round 3 review: reviews/pr-2575/task-2575-attempt-1-review-3-gemini-3.6-flash.md - Round 4 review: reviews/pr-2575/task-2575-attempt-1-review-4-claude-opus-5.md - Round 5 review: reviews/pr-2575/task-2575-attempt-1-review-5-gpt-5.6-sol.md - Round 6 review: reviews/pr-2575/task-2575-attempt-1-review-6-gemini-3.6-flash.md ## Rationale Keep business logic Scala-first and derive the Python surface through SynapseML's internal-wrapper override pattern. Resolve configured fields against schema ordinals and analyzed Spark attributes so transformSchema remains optimistic where qualifier or ExprId identity is unavailable while transform rejects genuine runtime ambiguity. Use positional normalization and public DataFrame APIs for Spark 3.5/4.1 compatibility, and use null-safe joins to preserve non-collapsed rows with null grouping keys. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Rana Singh (ranadeepsingh) · 2026-08-02T09:51:26Z

/azp run

azure-pipelines · 2026-08-02T09:51:37Z

Azure Pipelines: Successfully started running 1 pipeline(s).

## Summary Remove the six generated review audit files from the committed PR contents while leaving all reviewed implementation, documentation, and regression tests unchanged. ## Prompting Intent The engineer asked to prevent the generated review files from being merged. Preserve the existing PR history, avoid force-pushing, and remove only those committed artifacts. ## Linked Sources - Pull request: microsoft#2575 - User request: remove the review files from the committed files ## Rationale Use a follow-up deletion commit rather than rewriting the existing commit so the shared PR branch remains safe and auditable. The review process remains reflected in the conversation and prior commit history, but the final merged tree contains only the product changes and their tests. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Rana Singh (ranadeepsingh) · 2026-08-04T07:33:17Z

/azp run

azure-pipelines · 2026-08-04T07:33:28Z

Azure Pipelines: Successfully started running 1 pipeline(s).

## Summary Merge upstream master at `617ad0f8fc8932d93fc6185cb2547e5ab2c2719a` into the existing EnsembleByKey PR branch. ## Prompting Intent The engineer asked to update the published PR branch with the latest master changes. Preserve branch history and use a normal push rather than rebasing or force-pushing. ## Linked Sources - Pull request: microsoft#2575 - Upstream repository: https://github.com/microsoft/SynapseML ## Rationale Use a merge commit because the branch is already published and the engineer selected the history-preserving option. This incorporates current upstream changes without rewriting commits reviewed and validated on the shared PR branch. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Rana Singh (ranadeepsingh) · 2026-08-04T07:38:26Z

/azp run

azure-pipelines · 2026-08-04T07:38:37Z

Azure Pipelines: Successfully started running 1 pipeline(s).

azure-pipelines · 2026-08-11T06:58:47Z

Azure Pipelines: Successfully started running 1 pipeline(s).

AB#2575 ## Summary Add Round 3 code review artifact for SynapseML PR microsoft#2575 focusing on edge cases and robustness. ## Prompting Intent Perform Round 3 of the DIRECT sequential six-round review gauntlet for SynapseML PR microsoft#2575. Focus on edge cases, robustness, error handling, boundary conditions, concurrency/session behavior, and failure modes. ## Linked Sources - Prompt: C:\Users\singhrana\.copilot\session-state\c2ea157b-c36a-4cbc-896d-e8caa3ea05bd\files\pr-2575\prompts\review-round-3.md - Review artifact: C:\Users\singhrana\Documents\SynapseML-pr-2575\reviews\pr-2575\task-2575-attempt-1-review-3-gemini-3.6-flash.md ## Rationale Recorded findings for edge cases, null join behavior, session case sensitivity, and vector aggregate nullability in the Round 3 review artifact as instructed. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

## Summary Make EnsembleByKey schema resolution match Spark output for collapsed and non-collapsed transforms, including scalar and vector means, nested and qualified keys, duplicate attributes, null keys, overwrite behavior, output naming, metadata, nullability, and unsupported inputs. Add generated-Python compatibility coverage and preserve the complete six-round review audit trail. ## Prompting Intent Take end-to-end ownership of GitHub PR microsoft#2575 in an isolated worktree. Independently verify and harden EnsembleByKey schema behavior, run the required six-round DIRECT sequential multi-model review, fix and rerun every finding until clean, validate Scala and generated-language surfaces, avoid generated target edits and history rewrites, and prepare the existing PR branch for normal push and Azure validation. ## Linked Sources - Pull request: microsoft#2575 - Round 1 review: reviews/pr-2575/task-2575-attempt-1-review-1-claude-opus-5.md - Round 2 review: reviews/pr-2575/task-2575-attempt-1-review-2-gpt-5.6-sol.md - Round 3 review: reviews/pr-2575/task-2575-attempt-1-review-3-gemini-3.6-flash.md - Round 4 review: reviews/pr-2575/task-2575-attempt-1-review-4-claude-opus-5.md - Round 5 review: reviews/pr-2575/task-2575-attempt-1-review-5-gpt-5.6-sol.md - Round 6 review: reviews/pr-2575/task-2575-attempt-1-review-6-gemini-3.6-flash.md ## Rationale Keep business logic Scala-first and derive the Python surface through SynapseML's internal-wrapper override pattern. Resolve configured fields against schema ordinals and analyzed Spark attributes so transformSchema remains optimistic where qualifier or ExprId identity is unavailable while transform rejects genuine runtime ambiguity. Use positional normalization and public DataFrame APIs for Spark 3.5/4.1 compatibility, and use null-safe joins to preserve non-collapsed rows with null grouping keys. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

## Summary Remove the six generated review audit files from the committed PR contents while leaving all reviewed implementation, documentation, and regression tests unchanged. ## Prompting Intent The engineer asked to prevent the generated review files from being merged. Preserve the existing PR history, avoid force-pushing, and remove only those committed artifacts. ## Linked Sources - Pull request: microsoft#2575 - User request: remove the review files from the committed files ## Rationale Use a follow-up deletion commit rather than rewriting the existing commit so the shared PR branch remains safe and auditable. The review process remains reflected in the conversation and prior commit history, but the final merged tree contains only the product changes and their tests. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot

Review details

Files reviewed: 7/7 changed files
Comments generated: 0 new
Review effort level: Lite

Rana Singh (ranadeepsingh) · 2026-08-11T09:21:58Z

/azp run

azure-pipelines · 2026-08-11T09:22:11Z

Azure Pipelines: Successfully started running 1 pipeline(s).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

AB#2575 ## Summary Add Round 3 code review artifact for SynapseML PR microsoft#2575 focusing on edge cases and robustness. ## Prompting Intent Perform Round 3 of the DIRECT sequential six-round review gauntlet for SynapseML PR microsoft#2575. Focus on edge cases, robustness, error handling, boundary conditions, concurrency/session behavior, and failure modes. ## Linked Sources - Prompt: C:\Users\singhrana\.copilot\session-state\c2ea157b-c36a-4cbc-896d-e8caa3ea05bd\files\pr-2575\prompts\review-round-3.md - Review artifact: C:\Users\singhrana\Documents\SynapseML-pr-2575\reviews\pr-2575\task-2575-attempt-1-review-3-gemini-3.6-flash.md ## Rationale Recorded findings for edge cases, null join behavior, session case sensitivity, and vector aggregate nullability in the Round 3 review artifact as instructed. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

## Summary Make EnsembleByKey schema resolution match Spark output for collapsed and non-collapsed transforms, including scalar and vector means, nested and qualified keys, duplicate attributes, null keys, overwrite behavior, output naming, metadata, nullability, and unsupported inputs. Add generated-Python compatibility coverage and preserve the complete six-round review audit trail. ## Prompting Intent Take end-to-end ownership of GitHub PR microsoft#2575 in an isolated worktree. Independently verify and harden EnsembleByKey schema behavior, run the required six-round DIRECT sequential multi-model review, fix and rerun every finding until clean, validate Scala and generated-language surfaces, avoid generated target edits and history rewrites, and prepare the existing PR branch for normal push and Azure validation. ## Linked Sources - Pull request: microsoft#2575 - Round 1 review: reviews/pr-2575/task-2575-attempt-1-review-1-claude-opus-5.md - Round 2 review: reviews/pr-2575/task-2575-attempt-1-review-2-gpt-5.6-sol.md - Round 3 review: reviews/pr-2575/task-2575-attempt-1-review-3-gemini-3.6-flash.md - Round 4 review: reviews/pr-2575/task-2575-attempt-1-review-4-claude-opus-5.md - Round 5 review: reviews/pr-2575/task-2575-attempt-1-review-5-gpt-5.6-sol.md - Round 6 review: reviews/pr-2575/task-2575-attempt-1-review-6-gemini-3.6-flash.md ## Rationale Keep business logic Scala-first and derive the Python surface through SynapseML's internal-wrapper override pattern. Resolve configured fields against schema ordinals and analyzed Spark attributes so transformSchema remains optimistic where qualifier or ExprId identity is unavailable while transform rejects genuine runtime ambiguity. Use positional normalization and public DataFrame APIs for Spark 3.5/4.1 compatibility, and use null-safe joins to preserve non-collapsed rows with null grouping keys. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

## Summary Remove the six generated review audit files from the committed PR contents while leaving all reviewed implementation, documentation, and regression tests unchanged. ## Prompting Intent The engineer asked to prevent the generated review files from being merged. Preserve the existing PR history, avoid force-pushing, and remove only those committed artifacts. ## Linked Sources - Pull request: microsoft#2575 - User request: remove the review files from the committed files ## Rationale Use a follow-up deletion commit rather than rewriting the existing commit so the shared PR branch remains safe and auditable. The review process remains reflected in the conversation and prior commit history, but the final merged tree contains only the product changes and their tests. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot

Review details

Files reviewed: 7/7 changed files
Comments generated: 0 new
Review effort level: Lite

Rana Singh (ranadeepsingh) · 2026-08-11T17:48:36Z

/azp run

azure-pipelines · 2026-08-11T17:48:49Z

Azure Pipelines: Successfully started running 1 pipeline(s).

Rana Singh (ranadeepsingh) · 2026-08-12T00:29:52Z

Thanks for this contribution, Minh Vu (@fallintoplace), and for sticking with it through the review cycle — this one is now merged. 🎉

It was a genuinely good catch. EnsembleByKey.transformSchema was advertising a schema that did not match what transform actually produced, which is the kind of bug that stays invisible until something downstream depends on the declared schema — pipeline validation, or a PipelineModel being inspected before it ever sees data. Making the two agree is the right fix, and doing it in transformSchema rather than papering over it at the call site is what makes it hold up.

The added coverage is what made it easy to land with confidence: EnsembleByKeySuite and EnsembleByKeyResolutionSuite came out to 46 Scala tests between them, plus the new Python test, and all of it ran green in CI before merge.

Appreciate you taking the time to contribute to SynapseML. Hope to see more from you.

Copilot AI lite review requested due to automatic review settings July 26, 2026 02:05

Copilot started reviewing on behalf of Minh Vu (fallintoplace) July 26, 2026 02:06 View session

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Comment thread core/src/main/scala/com/microsoft/azure/synapse/ml/stages/EnsembleByKey.scala Outdated

Comment thread core/src/test/scala/com/microsoft/azure/synapse/ml/stages/EnsembleByKeySuite.scala Outdated

Minh Vu (fallintoplace) force-pushed the fix/ensemble-by-key-schema branch from 32aee3b to 0f15e8c Compare July 26, 2026 02:09

Minh Vu (fallintoplace) changed the title ~~fix: align EnsembleByKey transform schema~~ fix: make EnsembleByKey transformSchema match output Jul 26, 2026

Minh Vu (fallintoplace) force-pushed the fix/ensemble-by-key-schema branch from 0f15e8c to bdc39f9 Compare July 26, 2026 02:11

Copilot AI review requested due to automatic review settings August 11, 2026 09:10

Rana Singh (ranadeepsingh) force-pushed the fix/ensemble-by-key-schema branch from 9cace08 to fb2df4b Compare August 11, 2026 09:10

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Minh Vu (fallintoplace) and others added 6 commits August 11, 2026 10:28

fix: align EnsembleByKey transform schema

eb8a98c

fix: align EnsembleByKey vector schema

dc5235a

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

test: cover unsupported EnsembleByKey inputs

bf36348

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Copilot AI review requested due to automatic review settings August 11, 2026 17:29

Rana Singh (ranadeepsingh) force-pushed the fix/ensemble-by-key-schema branch from fb2df4b to 9ba8644 Compare August 11, 2026 17:29

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Rana Singh (ranadeepsingh) removed request for a team August 11, 2026 23:20

Rana Singh (ranadeepsingh) enabled auto-merge (squash) August 11, 2026 23:20

Rana Singh (ranadeepsingh) approved these changes Aug 11, 2026

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Brian J. Stafford (brianjstafford) approved these changes Aug 12, 2026

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Rana Singh (ranadeepsingh) disabled auto-merge August 12, 2026 00:12

Rana Singh (ranadeepsingh) merged commit feea272 into microsoft:master Aug 12, 2026
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Minh Vu (fallintoplace) commented Jul 26, 2026 •

edited by ranadeepsingh

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