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@nikhil-zlai nikhil-zlai commented Feb 5, 2025

Summary

The codebase previously operated under the assumption that partition listing is a cheap operation. It is not the case for GCS Format - partition listing is expensive on GCS external tables.

Checklist

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

Summary by CodeRabbit

  • Bug Fixes

    • Improved error handling to provide clearer messaging when data retrieval issues occur.
  • Refactor

    • Streamlined internal processing for data partitions, resulting in more consistent behavior.
    • Enhanced logging during data scanning for easier troubleshooting.
    • Simplified logic for handling intersected ranges, ensuring consistent definitions.
    • Reduced the volume of test data for improved performance and resource utilization during tests.

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coderabbitai bot commented Feb 5, 2025

Walkthrough

This PR updates two Scala files. In GroupBy.scala, the intersectedRange is now assigned unconditionally using getIntersectedRange, and partition conditions are derived directly from tableUtils.whereClauses. In TableUtils.scala, the partitions method has been refactored to use a try-catch block for partition retrieval, consolidating logging and error handling, with added debug logging to the scanDfBase method.

Changes

File(s) Change Summary
spark/.../GroupBy.scala Removed conditional optional handling of intersectedRange; now obtains it unconditionally and uses tableUtils.whereClauses directly.
spark/.../TableUtils.scala Refactored partitions method to use a try-catch block; consolidated logging for partition details; added enhanced error messaging and logging.

Possibly related PRs

Suggested reviewers

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

Poem

Code now flows with less delay,
Checks removed to clear the way.
Intersected ranges set in stone,
Logging insights on their own.
A streamlined path—code on display! 🚀

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Reviewing files that changed from the base of the PR and between 0055cee and d255ee7.

📒 Files selected for processing (1)
  • spark/src/main/scala/ai/chronon/spark/TableUtils.scala (3 hunks)
⏰ Context from checks skipped due to timeout of 90000ms (3)
  • GitHub Check: scala_compile_fmt_fix
  • GitHub Check: spark_tests
  • GitHub Check: enforce_triggered_workflows
🔇 Additional comments (2)
spark/src/main/scala/ai/chronon/spark/TableUtils.scala (2)

184-207: LGTM! Error handling and logging improvements.

The changes improve error handling by using try-catch and add debug level logging for stacktrace as suggested.


744-778: LGTM! Enhanced logging.

Added detailed logging of scan parameters to improve observability.


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partitions
} catch {
case e: Exception =>
logger.error(s"Failed to get partitions for table $tableName. " +
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Based on the beacon datasets this is what I see when doing the 1st time backfill:

[36m2025/02/06 16:53:58 [m [1;31mERROR [m [32mTableUtils.scala:201 [m - Failed to get partitions for table etsy-zipline-dev.search.search_beacons_listing_actions. Either the table is not partitioned or the table is not reachable.
java.lang.UnsupportedOperationException: No partition column for table etsy-zipline-dev.search.search_beacons_listing_actions found.
at ai.chronon.integrations.cloud_gcp.BigQueryFormat.$anonfun$partitions$2(BigQueryFormat.scala:94) ~[cloud_gcp_lib_deploy.jar:?]
at scala.Option.getOrElse(Option.scala:189) ~[scala-library-2.12.18.jar:?]
at ai.chronon.integrations.cloud_gcp.BigQueryFormat.partitions(BigQueryFormat.scala:94) ~[cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.format.Format.primaryPartitions(Format.scala:27) ~[cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.format.Format.primaryPartitions$(Format.scala:18) ~[cloud_gcp_lib_deploy.jar:?]
at ai.chronon.integrations.cloud_gcp.BigQueryFormat.primaryPartitions(BigQueryFormat.scala:28) ~[cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.TableUtils.partitions(TableUtils.scala:187) [cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.TableUtils.unfilledRanges(TableUtils.scala:579) [cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.GroupBy$.computeBackfill(GroupBy.scala:716) [cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.Driver$GroupByBackfill$.run(Driver.scala:402) [cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.Driver$.main(Driver.scala:936) [cloud_gcp_lib_deploy.jar:?]
at ai.chronon.spark.Driver.main(Driver.scala) [cloud_gcp_lib_deploy.jar:?]
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[?:?]
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:?]
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:?]
at java.base/java.lang.reflect.Method.invoke(Method.java:566) ~[?:?]
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52) [spark-core_2.12-3.5.1.jar:3.5.1]
at [org.apache.spark.deploy.SparkSubmit.org](http://org.apache.spark.deploy.sparksubmit.org/)$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:1032) [spark-core_2.12-3.5.1.jar:3.5.1]
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:194) [spark-core_2.12-3.5.1.jar:3.5.1]
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:217) [spark-core_2.12-3.5.1.jar:3.5.1]
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:91) [spark-core_2.12-3.5.1.jar:3.5.1]
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1124) [spark-core_2.12-3.5.1.jar:3.5.1]
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1133) [spark-core_2.12-3.5.1.jar:3.5.1]
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) [spark-core_2.12-3.5.1.jar:3.5.1]

Should we log the stacktrace at debug level? No strong opinions here

val selects = Option(source.query.selects)
.map(_.toScala.map(keyValue => {
if (keyValue._2.contains(Constants.ChrononRunDs)) {
assert(intersectedRange.isDefined && intersectedRange.get.isSingleDay,
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ooc why remove this?

@tchow-zlai tchow-zlai merged commit 021af72 into main Feb 7, 2025
6 checks passed
@tchow-zlai tchow-zlai deleted the partition_scanning_fix branch February 7, 2025 00:32
@coderabbitai coderabbitai bot mentioned this pull request Mar 21, 2025
4 tasks
@coderabbitai coderabbitai bot mentioned this pull request Apr 18, 2025
4 tasks
kumar-zlai pushed a commit that referenced this pull request Apr 25, 2025
## Summary

The codebase previously operated under the assumption that partition
listing is a cheap operation. It is not the case for GCS Format -
partition listing is expensive on GCS external tables.

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



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

- **Bug Fixes**
- Improved error handling to provide clearer messaging when data
retrieval issues occur.

- **Refactor**
- Streamlined internal processing for data partitions, resulting in more
consistent behavior.
  - Enhanced logging during data scanning for easier troubleshooting.
- Simplified logic for handling intersected ranges, ensuring consistent
definitions.
- Reduced the volume of test data for improved performance and resource
utilization during tests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
kumar-zlai pushed a commit that referenced this pull request Apr 29, 2025
## Summary

The codebase previously operated under the assumption that partition
listing is a cheap operation. It is not the case for GCS Format -
partition listing is expensive on GCS external tables.

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



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

- **Bug Fixes**
- Improved error handling to provide clearer messaging when data
retrieval issues occur.

- **Refactor**
- Streamlined internal processing for data partitions, resulting in more
consistent behavior.
  - Enhanced logging during data scanning for easier troubleshooting.
- Simplified logic for handling intersected ranges, ensuring consistent
definitions.
- Reduced the volume of test data for improved performance and resource
utilization during tests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
chewy-zlai pushed a commit that referenced this pull request May 15, 2025
## Summary

The codebase previously operated under the assumption that partition
listing is a cheap operation. It is not the case for GCS Format -
partition listing is expensive on GCS external tables.

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



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

- **Bug Fixes**
- Improved error handling to provide clearer messaging when data
retrieval issues occur.

- **Refactor**
- Streamlined internal processing for data partitions, resulting in more
consistent behavior.
  - Enhanced logging during data scanning for easier troubleshooting.
- Simplified logic for handling intersected ranges, ensuring consistent
definitions.
- Reduced the volume of test data for improved performance and resource
utilization during tests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
chewy-zlai pushed a commit that referenced this pull request May 15, 2025
## Summary

The codebase previously operated under the assumption that partition
listing is a cheap operation. It is not the case for GCS Format -
partition listing is expensive on GCS external tables.

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



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

- **Bug Fixes**
- Improved error handling to provide clearer messaging when data
retrieval issues occur.

- **Refactor**
- Streamlined internal processing for data partitions, resulting in more
consistent behavior.
  - Enhanced logging during data scanning for easier troubleshooting.
- Simplified logic for handling intersected ranges, ensuring consistent
definitions.
- Reduced the volume of test data for improved performance and resource
utilization during tests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
@coderabbitai coderabbitai bot mentioned this pull request May 16, 2025
4 tasks
chewy-zlai pushed a commit that referenced this pull request May 16, 2025
## Summary

The codebase previously operated under the assumption that partition
listing is a cheap operation. It is not the case for GCS Format -
partition listing is expensive on GCS external tables.

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



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

- **Bug Fixes**
- Improved error handling to provide clearer messaging when data
retrieval issues occur.

- **Refactor**
- Streamlined internal processing for data partitions, resulting in more
consistent behavior.
  - Enhanced logging during data scanning for easier troubleshooting.
- Simplified logic for handling intersected ranges, ensuring consistent
definitions.
- Reduced the volume of test data for improved performance and resource
utilization during tests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
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3 participants