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https://issues.apache.org/jira/browse/SPARK-21422?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-21422:
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Description:
Like Parquet, this issue aims to depend on the latest Apache ORC 1.4 for Apache
Spark 2.3. There are key benefits for now.
- Stability: Apache ORC 1.4.0 has many fixes and we can depend on ORC community
more.
- Maintainability: Reduce the Hive dependency and can remove old legacy code
later.
Later, we can get the following two key benefits by adding new ORCFileFormat in
SPARK-20728, too.
- Usability: User can use ORC data sources without hive module, i.e, -Phive.
- Speed: Use both Spark ColumnarBatch and ORC RowBatch together. This is faster
than the current implementation in Spark.
was:
Like Parquet, this issue aims to depend on the latest Apache ORC 1.4 for Apache
Spark 2.3.
> Depend on Apache ORC 1.4.0
> --------------------------
>
> Key: SPARK-21422
> URL: https://issues.apache.org/jira/browse/SPARK-21422
> Project: Spark
> Issue Type: Bug
> Components: Build
> Affects Versions: 2.3.0
> Reporter: Dongjoon Hyun
>
> Like Parquet, this issue aims to depend on the latest Apache ORC 1.4 for
> Apache Spark 2.3. There are key benefits for now.
> - Stability: Apache ORC 1.4.0 has many fixes and we can depend on ORC
> community more.
> - Maintainability: Reduce the Hive dependency and can remove old legacy code
> later.
> Later, we can get the following two key benefits by adding new ORCFileFormat
> in SPARK-20728, too.
> - Usability: User can use ORC data sources without hive module, i.e, -Phive.
> - Speed: Use both Spark ColumnarBatch and ORC RowBatch together. This is
> faster than the current implementation in Spark.
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