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Posted to issues@spark.apache.org by "René X Parra (JIRA)" <ji...@apache.org> on 2014/11/03 23:54:34 UTC
[jira] [Commented] (SPARK-3720) support ORC in spark sql
[ https://issues.apache.org/jira/browse/SPARK-3720?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14195287#comment-14195287 ]
René X Parra commented on SPARK-3720:
-------------------------------------
[~zhazhan] should this JIRA ticket be closed (marked as duplicate) of SPARK-2883 ??
> support ORC in spark sql
> ------------------------
>
> Key: SPARK-3720
> URL: https://issues.apache.org/jira/browse/SPARK-3720
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 1.1.0
> Reporter: wangfei
> Attachments: orc.diff
>
>
> The Optimized Row Columnar (ORC) file format provides a highly efficient way to store data on hdfs.ORC file format has many advantages such as:
> 1 a single file as the output of each task, which reduces the NameNode's load
> 2 Hive type support including datetime, decimal, and the complex types (struct, list, map, and union)
> 3 light-weight indexes stored within the file
> skip row groups that don't pass predicate filtering
> seek to a given row
> 4 block-mode compression based on data type
> run-length encoding for integer columns
> dictionary encoding for string columns
> 5 concurrent reads of the same file using separate RecordReaders
> 6 ability to split files without scanning for markers
> 7 bound the amount of memory needed for reading or writing
> 8 metadata stored using Protocol Buffers, which allows addition and removal of fields
> Now spark sql support Parquet, support ORC provide people more opts.
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