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 (9 tests passed)
core/Test/scalastyle (0 findings)
core/Compile/scalastyle (0 findings)

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

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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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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 86.36%. Comparing base (0dfddd3) to head (68f56a1).

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   86.33%   86.36%   +0.02%     
==========================================
  Files         335      335              
  Lines       18007    18250     +243     
  Branches     1658     1696      +38     
==========================================
+ Hits        15546    15761     +215     
- Misses       2461     2489      +28

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

/azp run

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

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

/azp run

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

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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

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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

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## 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 · 2026-08-04T09:19:41Z

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

Rana Singh (ranadeepsingh) · 2026-08-04T10:52:58Z

/azp run

azure-pipelines · 2026-08-04T10:53:09Z

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

Rana Singh (ranadeepsingh) · 2026-08-07T00:33:29Z

/azp run

azure-pipelines · 2026-08-07T00:33:41Z

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

Rana Singh (ranadeepsingh) · 2026-08-07T05:10:16Z

/azp run

azure-pipelines · 2026-08-07T05:10:23Z

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Review details

Suppressed comments (1)

core/src/test/scala/com/microsoft/azure/synapse/ml/stages/EnsembleByKeySuite.scala:745

withSQLConf always restores via spark.conf.set(configName, previousValue), which can (a) throw if the key was unset/nonexistent and (b) permanently convert an unset config into a user override. Other tests in this repo preserve the unset/set state via getOption + unset (e.g., core/src/test/scala/com/microsoft/azure/synapse/ml/recommendation/SARIdentifierSpec.scala:152-181).

  private def withSQLConf[T](configName: String, value: String)(action: => T): T = {
    val previousValue = spark.conf.get(configName)
    spark.conf.set(configName, value)
    try action finally spark.conf.set(configName, previousValue)
  }

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

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>

Rana Singh (ranadeepsingh) · 2026-08-07T07:46:20Z

/azp run

azure-pipelines · 2026-08-07T07:46:32Z

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>

Rana Singh (ranadeepsingh) · 2026-08-07T22:51:21Z

/azp run

azure-pipelines · 2026-08-07T22:51:28Z

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Review details

Suppressed comments (1)

core/src/main/scala/com/microsoft/azure/synapse/ml/stages/EnsembleByKey.scala:276

The comment claims RowOrdering.isOrderable is identical in Spark 3.5 and Spark 4.1, but SynapseML is pinned to Spark 3.5.0 (see build.sbt). Referencing Spark 4.1 here is likely to become misleading over time; it’s clearer to describe this as depending on Spark’s internal catalyst API and needing to stay aligned with the supported Spark version.

  // Spark's GetMapValue casts the requested literal to the map key type and additionally requires
  // that key type to be orderable (TypeUtils.checkForOrderingExpr -> RowOrdering.isOrderable).
  // RowOrdering.isOrderable(DataType) is identical in Spark 3.5 and Spark 4.1, so it is safe here.

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

Rana Singh (ranadeepsingh) · 2026-08-07T22:56:12Z

/azp run

azure-pipelines · 2026-08-07T22:56:30Z

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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

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Rana Singh (ranadeepsingh) force-pushed the fix/ensemble-by-key-schema branch from a8d5521 to 04d48a1 Compare August 7, 2026 07:03

Minh Vu (fallintoplace) and others added 6 commits August 7, 2026 15:40

fix: align EnsembleByKey transform schema

c5261b8

fix: align EnsembleByKey vector schema

b343288

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

test: cover unsupported EnsembleByKey inputs

f0c76ba

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

Copilot AI review requested due to automatic review settings August 7, 2026 22:51

Rana Singh (ranadeepsingh) force-pushed the fix/ensemble-by-key-schema branch from 04d48a1 to 68f56a1 Compare August 7, 2026 22:51

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