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https://issues.apache.org/jira/browse/SPARK-3720?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14376361#comment-14376361
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Zhan Zhang commented on SPARK-3720:
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[~iward] Since this jiar is duplicated to Spark-2883, we can move the
discussion to that one.
In short, Sparkl-2883 wants to support saveAsOrcFile and orcFile similar to
parquet file support in spark. But due to the underlying api change, the patch
is delayed.
> 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: Fei Wang
> 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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