chore: slim down tableutils

[tchow-zlai]

Summary

Checklist

• Added Unit Tests
• Covered by existing CI
• Integration tested
• Documentation update

Summary by CodeRabbit

• Refactor
  • Updated the data saving process for enhanced consistency by replacing the legacy unpartitioned saving functionality with a unified method that explicitly handles partition columns.
  • Removed the functionality to save unpartitioned DataFrames, ensuring all saves now require partition column specifications.
• Bug Fixes
  • Removed unnecessary partition checks in tests, streamlining the validation process without impacting overall functionality.
• Tests
  • Updated method calls in tests to reflect changes in how table formats are accessed, ensuring accurate validation of expected outcomes.

[coderabbitai]

Walkthrough

The pull request removes the unpartitioned saving functionality by eliminating the saveUnPartitioned method from the DataframeOps class in Extensions.scala and the insertUnPartitioned method from TableUtils.scala. Call sites in several files were updated to use the new save method with an explicit empty list for partitionColumns. These changes span several modules (including GroupByUpload.scala, StagingQuery.scala, CompareJob.scala, and PartitionRunner.scala) without altering the overall saving logic beyond the method signature replacement.

Changes

File(s)	Change Summary
spark/src/main/scala/ai/chronon/spark/Extensions.scala spark/.../TableUtils.scala	Removed methods related to unpartitioned saving: - saveUnPartitioned in DataframeOps - insertUnPartitioned in TableUtils
spark/src/main/scala/ai/chronon/spark/GroupByUpload.scala spark/src/main/scala/ai/chronon/spark/StagingQuery.scala spark/src/main/scala/ai/chronon/spark/stats/CompareJob.scala spark/src/main/scala/ai/chronon/spark/utils/PartitionRunner.scala	Replaced calls to saveUnPartitioned with the save method, explicitly passing partitionColumns = List.empty

Sequence Diagram(s)

sequenceDiagram
    participant Job
    participant DFops
    participant Writer
    Job->>DFops: save(table, props, partitionColumns=[])
    DFops->>Writer: Write DataFrame with given partition configuration
    Writer-->>DFops: Return write result
    DFops->>Job: Return save confirmation

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Possibly related PRs

• chore: trim tableutils #390: Addresses the replacement of saveUnPartitioned with the new save method across multiple files.
• chore: refactor some existing methods #156: Implements a refactor that standardizes DataFrame saving by adding partitioning parameters.
• chore: refactor creationUtils to not use formatProvider #260: Involves removal of the unpartitioned insertion method from TableUtils, aligning with the current changes.

Suggested Reviewers

• piyush-zlai
• nikhil-zlai
• varant-zlai
• david-zlai

Poem

Code paths pruned with care and flair,
Unpartitioned calls vanish in thin air.
New save steps in with parameters neat,
Guiding our DataFrames in a rhythmical beat.
Lines refactored, processes streamlined too,
A little code magic in all that we do.
Cheers to progress and fixes anew!

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Reviewing files that changed from the base of the PR and between f6d342c and f66a53c.

📒 Files selected for processing (1)

• spark/src/main/scala/ai/chronon/spark/TableUtils.scala (4 hunks)

⏰ Context from checks skipped due to timeout of 90000ms (15)

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• GitHub Check: groupby_tests
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• GitHub Check: streaming_tests
• GitHub Check: spark_tests
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• GitHub Check: scala_compile_fmt_fix

🔇 Additional comments (4)

spark/src/main/scala/ai/chronon/spark/TableUtils.scala (4)

33-33: Import addition looks good.

Added FormatProvider import supports the refactoring changes.

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124-124: Method refactoring LGTM.

Replaced direct format access with the provider pattern.

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160-164: Structured error handling improvement.

Good change to use tableFormatProvider with explicit error messaging.

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184-185: Consistent provider pattern usage.

Matches other refactored locations in the codebase.

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