[
https://issues.apache.org/jira/browse/FLINK-5802?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Zhuoluo Yang updated FLINK-5802:
--------------------------------
Description:
It's important to call hive udf in Flink SQL. A great many udfs were written in
hive since last ten years.
It's really important to reuse the hive udfs. This feature will reduce the cost
of migration and bring more users to flink.
Spark SQL has already supported this function.
https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.4.0/bk_spark-guide/content/calling-udfs.html
The Hive UDFs here include both built-in UDFs and customized UDFs. As many
business logic had been written in UDFs, the customized UDFs are more important
than the built-in UDFs.
Generally, there are three kinds of UDFs in Hive: UDF, UDTF and UDAF.
Here is the document of the Spark SQL:
http://spark.apache.org/docs/latest/sql-programming-guide.html#compatibility-with-apache-hive
Spark code:
https://github.com/apache/spark/blob/master/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
https://github.com/apache/spark/blob/master/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
was:
It's important to call hive udf in Flink SQL. A great many udfs were written in
hive since last ten years.
It's really important to reuse the hive udfs. This feature will reduce the cost
of migration and bring more users to flink.
Spark SQL has already supported this function.
https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.4.0/bk_spark-guide/content/calling-udfs.html
The Hive UDFs here include both built-in UDFs and customized UDFs. As many
business logic had been written in UDFs, the customized UDFs are more important
than the built-in UDFs.
Generally, there are three kinds of UDFs in Hive: UDF, UDTF and UDAF.
Here is the document of the Spark SQL:
http://spark.apache.org/docs/latest/sql-programming-guide.html#compatibility-with-apache-hive
> Flink SQL calling Hive User-Defined Functions
> ---------------------------------------------
>
> Key: FLINK-5802
> URL: https://issues.apache.org/jira/browse/FLINK-5802
> Project: Flink
> Issue Type: New Feature
> Components: Table API & SQL
> Reporter: Zhuoluo Yang
> Labels: features
>
> It's important to call hive udf in Flink SQL. A great many udfs were written
> in hive since last ten years.
> It's really important to reuse the hive udfs. This feature will reduce the
> cost of migration and bring more users to flink.
> Spark SQL has already supported this function.
> https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.4.0/bk_spark-guide/content/calling-udfs.html
> The Hive UDFs here include both built-in UDFs and customized UDFs. As many
> business logic had been written in UDFs, the customized UDFs are more
> important than the built-in UDFs.
> Generally, there are three kinds of UDFs in Hive: UDF, UDTF and UDAF.
> Here is the document of the Spark SQL:
> http://spark.apache.org/docs/latest/sql-programming-guide.html#compatibility-with-apache-hive
>
> Spark code:
> https://github.com/apache/spark/blob/master/sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUDFs.scala
> https://github.com/apache/spark/blob/master/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveInspectors.scala
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
