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Posted to issues@spark.apache.org by "Max Gekk (Jira)" <ji...@apache.org> on 2026/06/15 07:56:00 UTC
[jira] [Updated] (SPARK-57455) Support nanosecond-precision timestamp types in the ORC datasource (v1 and v2)
[ https://issues.apache.org/jira/browse/SPARK-57455?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Max Gekk updated SPARK-57455:
-----------------------------
Affects Version/s: 4.3.0
(was: 5.0.0)
> Support nanosecond-precision timestamp types in the ORC datasource (v1 and v2)
> ------------------------------------------------------------------------------
>
> Key: SPARK-57455
> URL: https://issues.apache.org/jira/browse/SPARK-57455
> 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 (core + hive ORC):
> - Type mapping in OrcUtils (orcTypeDescription / toCatalystSchema): TimestampLTZNanosType via native ORC timestamp (seconds+nanos, lossless); TimestampNTZNanosType via ORC LONG with a catalyst attribute.
> - Write: OrcSerializer (preserve sub-microsecond nanos); Hive path via HiveInspectors.wrapperFor.
> - Read non-vectorized: OrcDeserializer.
> - Read vectorized: OrcAtomicColumnVector (build TimestampNanosVal from the scratch java.sql.Timestamp).
> - Guardrails: core OrcFileFormat, v2 OrcTable, hive orc OrcFileFormat.
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