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https://issues.apache.org/jira/browse/FLINK-9407?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zhangminglei updated FLINK-9407:
--------------------------------
Description:
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 written down before. But I will give more tests in the
next couple of days. Including the performance under compression. And more UT
tests.
{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}
was:Currently, we only support {{StringWriter}}, {{SequenceFileWriter}} and
{{AvroKeyValueSinkWriter}}. I would suggest add an orc writer for rolling sink.
> 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: patch-available, 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 written down before. But I will give more tests in the
> next couple of days. Including the performance under compression. And more UT
> tests.
> {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}
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