You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@flink.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/10/16 08:28:00 UTC
[jira] [Commented] (FLINK-9407) Support orc rolling sink writer
[ https://issues.apache.org/jira/browse/FLINK-9407?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16651308#comment-16651308 ]
ASF GitHub Bot commented on FLINK-9407:
---------------------------------------
luyee commented on issue #6075: [FLINK-9407] [hdfs connector] Support orc rolling sink writer
URL: https://github.com/apache/flink/pull/6075#issuecomment-430148205
@zhangminglei does this pr works well ,in production?
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
> Support orc rolling sink writer
> -------------------------------
>
> Key: FLINK-9407
> URL: https://issues.apache.org/jira/browse/FLINK-9407
> Project: Flink
> Issue Type: New Feature
> Components: filesystem-connector
> Reporter: zhangminglei
> Assignee: zhangminglei
> Priority: Major
> Labels: pull-request-available
>
> Currently, we only support {{StringWriter}}, {{SequenceFileWriter}} and {{AvroKeyValueSinkWriter}}. I would suggest add an orc writer for rolling sink.
> Below, FYI.
> I tested the PR and verify the results with spark sql. Obviously, we can get the results of what we had written down before. But I will give more tests in the next couple of days. Including the performance under compression with short checkpoint intervals. And more UTs.
> {code:java}
> scala> spark.read.orc("hdfs://10.199.196.0:9000/data/hive/man/2018-07-06--21")
> res1: org.apache.spark.sql.DataFrame = [name: string, age: int ... 1 more field]
> scala>
> scala> res1.registerTempTable("tablerice")
> warning: there was one deprecation warning; re-run with -deprecation for details
> scala> spark.sql("select * from tablerice")
> res3: org.apache.spark.sql.DataFrame = [name: string, age: int ... 1 more field]
> scala> res3.show(3)
> +-----+---+-------+
> | name|age|married|
> +-----+---+-------+
> |Sagar| 26| false|
> |Sagar| 30| false|
> |Sagar| 34| false|
> +-----+---+-------+
> only showing top 3 rows
> {code}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)