feat: do partition filtering on bq native tables by union individual partitions #690
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Co-authored-by: Thomas Chow <[email protected]>
WalkthroughThe Changes
Sequence Diagram(s)sequenceDiagram
participant Caller
participant BigQueryNative
participant BigQuery
Caller->>BigQueryNative: table(...)
BigQueryNative->>BigQuery: Query partition column
BigQuery-->>BigQueryNative: Partition column name
BigQueryNative->>BigQuery: Query distinct partition values (with filters)
BigQuery-->>BigQueryNative: List of partition values
loop For each partition value
BigQueryNative->>BigQuery: Read data for partition value
BigQuery-->>BigQueryNative: DataFrame for partition
end
BigQueryNative->>Caller: Unioned DataFrame with partition column
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Actionable comments posted: 3
🧹 Nitpick comments (1)
cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala (1)
62-70: Many small reads ⇒ latency; prefer singleIN (…)Looping over partitions issues N BQ jobs.
A single read withWHERE partCol IN ('p1','p2',…)is faster and cheaper.
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cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala(2 hunks)
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cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala (2)
spark/src/main/scala/ai/chronon/spark/catalog/TableUtils.scala (3)
sql(319-347)TableUtils(43-639)TableUtils(641-643)cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/SparkBQUtils.scala (2)
SparkBQUtils(7-24)toTableId(9-16)
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🔇 Additional comments (1)
cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala (1)
64-70: Preserve column type when re-adding partition field
lit(partValue)re-creates the column as STRING; original may beDATE/TIMESTAMP. Consider casting:.withColumn(partColName, lit(partValue).cast(col(partColName).schema))
| val partitionWheres = if (partitionFilters.nonEmpty) s"WHERE ${partitionFilters}" else partitionFilters | ||
| val partitionFormat = TableUtils(sparkSession).partitionFormat | ||
| val dfw = sparkSession.read | ||
| val select = s"SELECT distinct(${partColName}) AS ${internalBQCol} FROM ${bqFriendlyName} ${partitionWheres}" |
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Use DISTINCT … – distinct() is invalid BigQuery SQL
distinct(${partColName}) will ☠️ on BQ.
Replace with the keyword form.
-val select = s"SELECT distinct(${partColName}) AS ${internalBQCol} FROM ${bqFriendlyName} ${partitionWheres}"
+val select = s"SELECT DISTINCT ${partColName} AS ${internalBQCol} FROM ${bqFriendlyName} ${partitionWheres}"📝 Committable suggestion
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| val select = s"SELECT distinct(${partColName}) AS ${internalBQCol} FROM ${bqFriendlyName} ${partitionWheres}" | |
| val select = s"SELECT DISTINCT ${partColName} AS ${internalBQCol} FROM ${bqFriendlyName} ${partitionWheres}" |
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| val selectedParts = sparkSession.read | ||
| .format(bqFormat) | ||
| .option("viewsEnabled", true) | ||
| .option("materializationDataset", bqTableId.getDataset) | ||
| if (isPseudoColumn) { | ||
| val select = s"SELECT ${partColName} AS ${internalBQCol}, * FROM ${bqFriendlyName} ${partitionWheres}" | ||
| logger.info(s"BQ select: ${select}") | ||
| dfw | ||
| .load(select) | ||
| .withColumn(partColName, date_format(col(internalBQCol), partitionFormat)) | ||
| .drop(internalBQCol) | ||
| } else { | ||
| dfw | ||
| .load(s"SELECT * FROM ${bqFriendlyName} ${partitionWheres}") | ||
| } | ||
| .load(select) | ||
| .select(date_format(col(internalBQCol), partitionFormat)) |
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Add missing project option when reading partitions
Reads here omit .option("project", providedProject). Cross-project tables will fail.
val selectedParts = sparkSession.read
.format(bqFormat)
+ .option("project", providedProject)
.option("viewsEnabled", true)
.option("materializationDataset", bqTableId.getDataset)
.load(select)Apply the same when loading each partition below.
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| selectedParts | ||
| .map((partValue) => { | ||
| val pFilter = f"${partColName} = '${partValue}'" | ||
| sparkSession.read | ||
| .format(bqFormat) | ||
| .option("filter", pFilter) | ||
| .load(bqFriendlyName) | ||
| .withColumn(partColName, lit(partValue)) | ||
| }) // todo: make it nullable | ||
| .reduce(_ unionByName _) |
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Guard against empty partition list
reduce throws on Nil.
- .reduce(_ unionByName _)
+ .reduceOption(_ unionByName _)
+ .getOrElse(sparkSession.emptyDataFrame)Co-authored-by: Thomas Chow <[email protected]>
varant-zlai
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Apr 28, 2025
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…partitions (#690) ## Summary - Getting a 403 querying for a range of partitions in bigquery native tables: ``` Response too large to return. Consider specifying a destination table in your job configuration ``` - instead, let's just query individual partitions of data as separate dataframes and union them together. ## Checklist - [ ] Added Unit Tests - [ ] Covered by existing CI - [ ] Integration tested - [ ] Documentation update <!-- av pr metadata This information is embedded by the av CLI when creating PRs to track the status of stacks when using Aviator. Please do not delete or edit this section of the PR. ``` {"parent":"main","parentHead":"","trunk":"main"} ``` --> <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **Bug Fixes** - Improved handling of BigQuery partitioned tables, ensuring more accurate partition filtering and data retrieval. - **Refactor** - Streamlined the process for reading partitioned data from BigQuery, resulting in a clearer and more consistent approach for users working with partitioned tables. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Thomas Chow <[email protected]>
This was referenced Apr 29, 2025
chewy-zlai
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May 15, 2025
…partitions (#690) ## Summary - Getting a 403 querying for a range of partitions in bigquery native tables: ``` Response too large to return. Consider specifying a destination table in your job configuration ``` - instead, let's just query individual partitions of data as separate dataframes and union them together. ## Checklist - [ ] Added Unit Tests - [ ] Covered by existing CI - [ ] Integration tested - [ ] Documentation update <!-- av pr metadata This information is embedded by the av CLI when creating PRs to track the status of stacks when using Aviator. Please do not delete or edit this section of the PR. ``` {"parent":"main","parentHead":"","trunk":"main"} ``` --> <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **Bug Fixes** - Improved handling of BigQuery partitioned tables, ensuring more accurate partition filtering and data retrieval. - **Refactor** - Streamlined the process for reading partitioned data from BigQuery, resulting in a clearer and more consistent approach for users working with partitioned tables. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Thomas Chow <[email protected]>
chewy-zlai
pushed a commit
that referenced
this pull request
May 15, 2025
…partitions (#690) ## Summary - Getting a 403 querying for a range of partitions in bigquery native tables: ``` Response too large to return. Consider specifying a destination table in your job configuration ``` - instead, let's just query individual partitions of data as separate dataframes and union them together. ## Checklist - [ ] Added Unit Tests - [ ] Covered by existing CI - [ ] Integration tested - [ ] Documentation update <!-- av pr metadata This information is embedded by the av CLI when creating PRs to track the status of stacks when using Aviator. Please do not delete or edit this section of the PR. ``` {"parent":"main","parentHead":"","trunk":"main"} ``` --> <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **Bug Fixes** - Improved handling of BigQuery partitioned tables, ensuring more accurate partition filtering and data retrieval. - **Refactor** - Streamlined the process for reading partitioned data from BigQuery, resulting in a clearer and more consistent approach for users working with partitioned tables. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Thomas Chow <[email protected]>
chewy-zlai
pushed a commit
that referenced
this pull request
May 16, 2025
…partitions (#690) ## Summary - Getting a 403 querying for a range of partitions in bigquery native tables: ``` Response too large to return. Consider specifying a destination table in your job configuration ``` - instead, let's just query individual partitions of data as separate dataframes and union them together. ## Cheour clientslist - [ ] Added Unit Tests - [ ] Covered by existing CI - [ ] Integration tested - [ ] Documentation update <!-- av pr metadata This information is embedded by the av CLI when creating PRs to traour clients the status of staour clientss when using Aviator. Please do not delete or edit this section of the PR. ``` {"parent":"main","parentHead":"","trunk":"main"} ``` --> <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **Bug Fixes** - Improved handling of BigQuery partitioned tables, ensuring more accurate partition filtering and data retrieval. - **Refactor** - Streamlined the process for reading partitioned data from BigQuery, resulting in a clearer and more consistent approach for users working with partitioned tables. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Co-authored-by: Thomas Chow <[email protected]>
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Summary
Checklist
Summary by CodeRabbit
Bug Fixes
Refactor