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https://issues.apache.org/jira/browse/SPARK-57460?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Max Gekk updated SPARK-57460:
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Affects Version/s: 4.3.0
(was: 5.0.0)
> Support nanosecond-precision timestamp types in the JDBC datasource
> -------------------------------------------------------------------
>
> Key: SPARK-57460
> URL: https://issues.apache.org/jira/browse/SPARK-57460
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 4.3.0
> Reporter: Max Gekk
> Priority: Major
>
> Umbrella: SPARK-56822 (Timestamps with nanosecond precision).
> Add read and write support for the nanosecond-capable timestamp types
> TIMESTAMP_NTZ(p) and TIMESTAMP_LTZ(p) (p in 7-9) so this datasource reaches
> parity with the microsecond TimestampType / TimestampNTZType. Remove the
> SPARK-57166 rejection guardrail (supportDataType / supportsDataType) once
> read and write are implemented and tested, and update
> FileBasedDataSourceSuite accordingly. Cover precisions 7-9 for both NTZ and
> LTZ.
> Scope (java.sql.Timestamp already carries sub-microsecond getNanos):
> - Spark->JDBC: add nanos cases to JdbcUtils.getCommonJDBCType
> (Types.TIMESTAMP; dialects may emit TIMESTAMP(p) / WITH TIME ZONE).
> - JDBC->Spark: getCatalystType / getTimestampType (map driver TIMESTAMP to
> nanos only when requested via option/dialect, to preserve default microsecond
> behavior).
> - Read: makeGetter builds TimestampNanosVal preserving
> rs.getTimestamp().getNanos().
> - Write: makeSetter sets full nanos.
> - Dialect hooks in JdbcDialects for DBs with explicit TIMESTAMP(p).
> - Guardrail: CreatableRelationProvider.supportsDataType whitelist in
> interfaces.scala.
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