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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2014/10/01 22:00:34 UTC
[jira] [Commented] (SPARK-2693) Support for UDAF Hive Aggregates
like PERCENTILE
[ https://issues.apache.org/jira/browse/SPARK-2693?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14155388#comment-14155388 ]
Apache Spark commented on SPARK-2693:
-------------------------------------
User 'ravipesala' has created a pull request for this issue:
https://github.com/apache/spark/pull/2620
> Support for UDAF Hive Aggregates like PERCENTILE
> ------------------------------------------------
>
> Key: SPARK-2693
> URL: https://issues.apache.org/jira/browse/SPARK-2693
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Michael Armbrust
> Assignee: Ravindra Pesala
> Priority: Critical
>
> {code}
> SELECT MIN(field1), MAX(field2), AVG(field3), PERCENTILE(field4), year,month,day FROM raw_data_table GROUP BY year, month, day
> MIN, MAX and AVG functions work fine for me, but with PERCENTILE, I get an error as shown below.
> Exception in thread "main" java.lang.RuntimeException: No handler for udf class org.apache.hadoop.hive.ql.udf.UDAFPercentile
> at scala.sys.package$.error(package.scala:27)
> at org.apache.spark.sql.hive.HiveFunctionRegistry$.lookupFunction(hiveUdfs.scala:69)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$4$$anonfun$applyOrElse$3.applyOrElse(Analyzer.scala:115)
> at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$4$$anonfun$applyOrElse$3.applyOrElse(Analyzer.scala:113)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:165)
> {code}
> This aggregate extends UDAF, which we don't yet have a wrapper for.
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