GitHub user dongjoon-hyun opened a pull request:
https://github.com/apache/spark/pull/17924
[SPARK-20682][SQL] Support a new faster ORC data source based on Apache ORC
## What changes were proposed in this pull request?
Since [SPARK-2883](https://issues.apache.org/jira/browse/SPARK-2883),
Apache Spark supports Apache ORC inside `sql/hive` module with Hive dependency.
This issue aims to add a new and faster ORC data source inside `sql/core` and
to replace the old ORC data source eventually. In this issue, the latest Apache
ORC 1.4.0 (released yesterday) is used.
There are four key benefits.
- Speed: Use both Spark `ColumnarBatch` and ORC `RowBatch` together. This
is faster than the current implementation in Spark.
- Stability: Apache ORC 1.4.0 has many fixes and we can depend on ORC
community more.
- Usability: User can use `ORC` data sources without hive module, i.e,
`-Phive`.
- Maintainability: Reduce the Hive dependency and can remove old legacy
code later.
## How was this patch tested?
Pass the Jenkins tests with newly added test suites in `sql/core`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/dongjoon-hyun/spark SPARK-20682
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17924.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17924
----
commit 8bfd4bb4aec6dc3a5e7f41ec8d5c2a25f14ab87b
Author: Dongjoon Hyun <[email protected]>
Date: 2017-04-25T19:30:24Z
[SPARK-20682][SQL] Implement new ORC data source based on Apache ORC
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