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feat: support pseudocolumns in bigquery native tables #689
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Co-authored-by: Thomas Chow <[email protected]>
WalkthroughThe Changes
Sequence Diagram(s)sequenceDiagram
participant Caller
participant BigQueryNative
participant BigQuery
participant SparkSession
Caller->>BigQueryNative: table(tableName, partitionFilters)
BigQueryNative->>BigQuery: Query INFORMATION_SCHEMA.COLUMNS
BigQuery-->>BigQueryNative: Return partition column info
BigQueryNative->>BigQueryNative: Validate partition column & system-defined flag
alt System-defined partition column
BigQueryNative->>BigQuery: Query table with partition column aliased
BigQuery-->>BigQueryNative: Return data
BigQueryNative->>SparkSession: Format partition column, drop alias
else Not system-defined
BigQueryNative->>BigQuery: Query table with optional WHERE clause
BigQuery-->>BigQueryNative: Return data
end
BigQueryNative-->>Caller: Return DataFrame
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Co-authored-by: Thomas Chow <[email protected]>
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Actionable comments posted: 0
🧹 Nitpick comments (2)
cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala (2)
30-41
: Avoid full collect for a single-row lookup
collect.headOption
materialises the entire INFORMATION_SCHEMA query (one row today, but unbounded in theory). Fetch just the first row to keep driver memory/use low.- .collect - .headOption + .limit(1) + .as[(String, String)] + .headOption // pulls a single row only
58-66
: Duplicate column scan & extra shuffle
SELECT ${partColName} as ${internalBQCol}, *
re-reads the partition column twice, and BigQuery will still transmit both before we drop one.
A lighter pattern:-SELECT ${partColName} as ${internalBQCol}, * FROM +SELECT *, ${partColName} as ${internalBQCol} FROMor BigQuery’s
REPLACE
clause:SELECT * REPLACE(${partColName} AS ${internalBQCol}) FROM ...keeps the payload minimal and sidesteps duplicate-column pitfalls.
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cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala
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🔇 Additional comments (1)
cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala (1)
49-51
:❌ Incorrect review comment
logger
may be undefined here
logger.info
assumes an in-scopelogger
, but this object doesn’t declare one andFormat
doesn’t obviously supply it. Compilation will fail unless another trait injects it.Please verify or add something like:
private val logger = org.slf4j.LoggerFactory.getLogger(getClass)
🏁 Script executed:
#!/bin/bash # Show the definition and signature of BigQueryNative grep -n "class BigQueryNative" -n cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala sed -n '1,50p' cloud_gcp/src/main/scala/ai/chronon/integrations/cloud_gcp/BigQueryNative.scala # Find any Format trait declarations grep -R "trait Format" -n .Length of output: 2716
🏁 Script executed:
#!/bin/bash sed -n '1,200p' spark/src/main/scala/ai/chronon/spark/catalog/Format.scalaLength of output: 2242
Ignore logger undefined warning
The
Format
trait declares@transient protected lazy val logger: Logger = LoggerFactory.getLogger(getClass)so
BigQueryNative
already inheritslogger
. No change needed.Likely an incorrect or invalid review comment.
Co-authored-by: Thomas Chow <[email protected]>
## Summary ## 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 - **Bug Fixes** - Improved handling of BigQuery partitioned tables to correctly identify and process system-defined partition columns. - Enhanced error handling and validation for partition column detection. - Improved logging to provide clearer information about partition columns and their types. <!-- end of auto-generated comment: release notes by coderabbit.ai --> <!-- 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"} ``` --> --------- Co-authored-by: Thomas Chow <[email protected]>
## Summary ## 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 - **Bug Fixes** - Improved handling of BigQuery partitioned tables to correctly identify and process system-defined partition columns. - Enhanced error handling and validation for partition column detection. - Improved logging to provide clearer information about partition columns and their types. <!-- end of auto-generated comment: release notes by coderabbit.ai --> <!-- 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"} ``` --> --------- Co-authored-by: Thomas Chow <[email protected]>
## Summary ## 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 - **Bug Fixes** - Improved handling of BigQuery partitioned tables to correctly identify and process system-defined partition columns. - Enhanced error handling and validation for partition column detection. - Improved logging to provide clearer information about partition columns and their types. <!-- end of auto-generated comment: release notes by coderabbit.ai --> <!-- 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"} ``` --> --------- Co-authored-by: Thomas Chow <[email protected]>
## Summary ## 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 - **Bug Fixes** - Improved handling of BigQuery partitioned tables to correctly identify and process system-defined partition columns. - Enhanced error handling and validation for partition column detection. - Improved logging to provide clearer information about partition columns and their types. <!-- end of auto-generated comment: release notes by coderabbit.ai --> <!-- 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"} ``` --> --------- Co-authored-by: Thomas Chow <[email protected]>
## Summary ## 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 - **Bug Fixes** - Improved handling of BigQuery partitioned tables to correctly identify and process system-defined partition columns. - Enhanced error handling and validation for partition column detection. - Improved logging to provide clearer information about partition columns and their types. <!-- end of auto-generated comment: release notes by coderabbit.ai --> <!-- 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"} ``` --> --------- Co-authored-by: Thomas Chow <[email protected]>
Summary
Checklist
Summary by CodeRabbit