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@varant-zlai varant-zlai commented Apr 2, 2025

Summary

Adding step days of 1 to source job

Checklist

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

Summary by CodeRabbit

  • New Features
    • Data processing is now handled in daily segments, providing more precise and timely results.
  • Bug Fixes
    • Error messages have been refined to clearly indicate the specific day when a query yields no results, improving clarity during troubleshooting.

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coderabbitai bot commented Apr 2, 2025

Walkthrough

The SourceJob class now processes data by iterating over a date range day by day. For each day, a separate data frame is generated and processed. The error handling has been refined to indicate exactly which day produced zero rows. The logic for adding a time-based column and saving the data frame remains unchanged but operates within the daily loop. The MergeJob class has been updated to include a new parameter for processing data on a per-day basis.

Changes

File(s) Change Summary
spark/.../SourceJob.scala Replaced single data frame processing with a loop over daily steps. Updated error handling to specify the day with zero rows.
spark/.../MergeJob.scala Introduced dayStep parameter in getRightPartsData. Modified run method to process data iteratively for each day step.

Suggested reviewers

  • nikhil-zlai
  • piyush-zlai

Poem

A new loop dawns with each fresh day,
Data frames rise and blaze their way.
Errors now speak the exact date,
In code, clarity does resonate.
Each step a note in our rhythmic display!
Happy coding in every single day!

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Reviewing files that changed from the base of the PR and between 4750b45 and d682ca7.

📒 Files selected for processing (1)
  • spark/src/main/scala/ai/chronon/spark/MergeJob.scala (2 hunks)
🧰 Additional context used
🧬 Code Definitions (1)
spark/src/main/scala/ai/chronon/spark/MergeJob.scala (4)
api/src/main/scala/ai/chronon/api/DataRange.scala (2)
  • PartitionRange (38-128)
  • PartitionRange (130-174)
spark/src/main/scala/ai/chronon/spark/TableUtils.scala (1)
  • scanDf (593-613)
spark/src/main/scala/ai/chronon/spark/Join.scala (1)
  • getRightPartsData (202-216)
api/src/main/scala/ai/chronon/api/RelevantLeftForJoinPart.scala (2)
  • RelevantLeftForJoinPart (15-23)
  • RelevantLeftForJoinPart (25-91)
⏰ Context from checks skipped due to timeout of 90000ms (14)
  • GitHub Check: streaming_tests
  • GitHub Check: analyzer_tests
  • GitHub Check: join_tests
  • GitHub Check: streaming_tests
  • GitHub Check: groupby_tests
  • GitHub Check: analyzer_tests
  • GitHub Check: fetcher_tests
  • GitHub Check: spark_tests
  • GitHub Check: spark_tests
  • GitHub Check: groupby_tests
  • GitHub Check: fetcher_tests
  • GitHub Check: join_tests
  • GitHub Check: scala_compile_fmt_fix
  • GitHub Check: enforce_triggered_workflows
🔇 Additional comments (5)
spark/src/main/scala/ai/chronon/spark/MergeJob.scala (5)

19-19: Added import for day-step processing.

Necessary import to support the new parameter in getRightPartsData.


51-55: Code reformatted for readability.

No functional changes, just improved formatting.


61-87: Implemented day-by-day processing.

Processing data in daily steps reduces shuffle overhead when writing output.

Note: Previous review suggested using Try constructor rather than try-catch.


90-90: Updated method signature to support daily processing.

Method now accepts a day step parameter allowing targeted data retrieval.


96-99: Using dayStep instead of dateRange.

Appropriate modification to use the provided day parameter rather than the full range.


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Actionable comments posted: 0

🧹 Nitpick comments (3)
spark/src/main/scala/ai/chronon/spark/MergeJob.scala (3)

57-58: Potential performance overhead scanning full range for schema.


66-79: Consider refining exception handling and logging the problematic day.


80-81: Check if DataFrame is empty before saving to avoid surprises.

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro (Legacy)

📥 Commits

Reviewing files that changed from the base of the PR and between eb4afea and f6ff906.

📒 Files selected for processing (1)
  • spark/src/main/scala/ai/chronon/spark/MergeJob.scala (2 hunks)
🧰 Additional context used
🧬 Code Definitions (1)
spark/src/main/scala/ai/chronon/spark/MergeJob.scala (3)
api/src/main/scala/ai/chronon/api/DataRange.scala (4)
  • PartitionRange (38-128)
  • PartitionRange (130-174)
  • steps (82-87)
  • shift (99-105)
spark/src/main/scala/ai/chronon/spark/TableUtils.scala (1)
  • scanDf (593-613)
spark/src/main/scala/ai/chronon/spark/BootstrapInfo.scala (3)
  • BootstrapInfo (51-74)
  • BootstrapInfo (76-346)
  • from (80-345)
⏰ Context from checks skipped due to timeout of 90000ms (14)
  • GitHub Check: streaming_tests
  • GitHub Check: streaming_tests
  • GitHub Check: spark_tests
  • GitHub Check: join_tests
  • GitHub Check: analyzer_tests
  • GitHub Check: spark_tests
  • GitHub Check: groupby_tests
  • GitHub Check: groupby_tests
  • GitHub Check: fetcher_tests
  • GitHub Check: fetcher_tests
  • GitHub Check: analyzer_tests
  • GitHub Check: scala_compile_fmt_fix
  • GitHub Check: join_tests
  • GitHub Check: enforce_triggered_workflows
🔇 Additional comments (5)
spark/src/main/scala/ai/chronon/spark/MergeJob.scala (5)

19-19: No issues with the new import.


62-65: Day-by-day iteration looks correct.


85-85: New parameter for daily range retrieval is consistent with the loop.


91-91: Watch for off-by-one errors when shifting day range by -1.


93-93: Leaving day range unshifted looks correct for non-snapshot accuracy.

Comment on lines +67 to +80
val joinedDfTry =
try {
Success(
rightPartsData
.foldLeft(leftDf) { case (partialDf, (rightPart, rightDf)) =>
joinWithLeft(partialDf, rightDf, rightPart)
}
// drop all processing metadata columns
.drop(Constants.MatchedHashes, Constants.TimePartitionColumn))
} catch {
case e: Exception =>
e.printStackTrace()
Failure(e)
}
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Suggested change
val joinedDfTry =
try {
Success(
rightPartsData
.foldLeft(leftDf) { case (partialDf, (rightPart, rightDf)) =>
joinWithLeft(partialDf, rightDf, rightPart)
}
// drop all processing metadata columns
.drop(Constants.MatchedHashes, Constants.TimePartitionColumn))
} catch {
case e: Exception =>
e.printStackTrace()
Failure(e)
}
val joinedDfTry =
Try {
rightPartsData
.foldLeft(leftDf) { case (partialDf, (rightPart, rightDf)) =>
joinWithLeft(partialDf, rightDf, rightPart)
}
// drop all processing metadata columns
.drop(Constants.MatchedHashes, Constants.TimePartitionColumn))
}

@varant-zlai varant-zlai merged commit f5a2d89 into main Apr 2, 2025
17 checks passed
@varant-zlai varant-zlai deleted the vz--add_steps_to_source_job branch April 2, 2025 07:20
kumar-zlai pushed a commit that referenced this pull request Apr 25, 2025
## Summary

Adding step days of 1 to source job

## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update



<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Data processing is now handled in daily segments, providing more
precise and timely results.
- **Bug Fixes**
- Error messages have been refined to clearly indicate the specific day
when a query yields no results, improving clarity during
troubleshooting.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: ezvz <[email protected]>
kumar-zlai pushed a commit that referenced this pull request Apr 29, 2025
## Summary

Adding step days of 1 to source job

## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update



<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Data processing is now handled in daily segments, providing more
precise and timely results.
- **Bug Fixes**
- Error messages have been refined to clearly indicate the specific day
when a query yields no results, improving clarity during
troubleshooting.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: ezvz <[email protected]>
chewy-zlai pushed a commit that referenced this pull request May 15, 2025
## Summary

Adding step days of 1 to source job

## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update



<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Data processing is now handled in daily segments, providing more
precise and timely results.
- **Bug Fixes**
- Error messages have been refined to clearly indicate the specific day
when a query yields no results, improving clarity during
troubleshooting.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: ezvz <[email protected]>
chewy-zlai pushed a commit that referenced this pull request May 15, 2025
## Summary

Adding step days of 1 to source job

## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update



<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Data processing is now handled in daily segments, providing more
precise and timely results.
- **Bug Fixes**
- Error messages have been refined to clearly indicate the specific day
when a query yields no results, improving clarity during
troubleshooting.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: ezvz <[email protected]>
chewy-zlai pushed a commit that referenced this pull request May 16, 2025
## Summary

Adding step days of 1 to source job

## Cheour clientslist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update



<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Data processing is now handled in daily segments, providing more
precise and timely results.
- **Bug Fixes**
- Error messages have been refined to clearly indicate the specific day
when a query yields no results, improving clarity during
troubleshooting.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: ezvz <[email protected]>
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4 participants