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https://issues.apache.org/jira/browse/SPARK-6483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14377494#comment-14377494
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Cheng Hao commented on SPARK-6483:
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Can you re-run those 2 queries without GROUP BY?
> Spark SQL udf(ScalaUdf) is very slow
> ------------------------------------
>
> Key: SPARK-6483
> URL: https://issues.apache.org/jira/browse/SPARK-6483
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.3.0, 1.4.0
> Environment: 1. Spark version is 1.3.0
> 2. 3 node per 80G/20C
> 3. read 250G parquet files from hdfs
> Reporter: zzc
>
> Test case:
> 1.
> register "floor" func with command:
> sqlContext.udf.register("floor", (ts: Int) => ts - ts % 300),
> then run with sql "select chan, floor(ts) as tt, sum(size) from qlogbase3
> group by chan, floor(ts)",
> *it takes 17 minutes.*
> {quote}
> == Physical Plan ==
>
> Aggregate false, [chan#23015,PartialGroup#23500],
> [chan#23015,PartialGroup#23500 AS tt#23494,CombineSum(PartialSum#23499L) AS
> c2#23495L]
> Exchange (HashPartitioning [chan#23015,PartialGroup#23500], 54)
> Aggregate true, [chan#23015,scalaUDF(ts#23016)],
> [chan#23015,*scalaUDF*(ts#23016) AS PartialGroup#23500,SUM(size#23023L) AS
> PartialSum#23499L]
> PhysicalRDD [chan#23015,ts#23016,size#23023L], MapPartitionsRDD[115] at
> map at newParquet.scala:562
> {quote}
> 2.
> run with sql "select chan, (ts - ts % 300) as tt, sum(size) from qlogbase3
> group by chan, (ts - ts % 300)",
> *it takes only 5 minutes.*
> {quote}
> == Physical Plan ==
> Aggregate false, [chan#23015,PartialGroup#23349],
> [chan#23015,PartialGroup#23349 AS tt#23343,CombineSum(PartialSum#23348L) AS
> c2#23344L]
> Exchange (HashPartitioning [chan#23015,PartialGroup#23349], 54)
> Aggregate true, [chan#23015,(ts#23016 - (ts#23016 % 300))],
> [chan#23015,*(ts#23016 - (ts#23016 % 300))* AS
> PartialGroup#23349,SUM(size#23023L) AS PartialSum#23348L]
> PhysicalRDD [chan#23015,ts#23016,size#23023L], MapPartitionsRDD[83] at map
> at newParquet.scala:562
> {quote}
> 3.
> use *HiveContext* with sql "select chan, floor((ts - ts % 300)) as tt,
> sum(size) from qlogbase3 group by chan, floor((ts - ts % 300))"
> *it takes only 5 minutes too. *
> {quote}
> == Physical Plan ==
> Aggregate false, [chan#23015,PartialGroup#23108L],
> [chan#23015,PartialGroup#23108L AS tt#23102L,CombineSum(PartialSum#23107L) AS
> _c2#23103L]
> Exchange (HashPartitioning [chan#23015,PartialGroup#23108L], 54)
> Aggregate true,
> [chan#23015,HiveGenericUdf#org.apache.hadoop.hive.ql.udf.generic.GenericUDFFloor((ts#23016
> - (ts#23016 % 300)))],
> [chan#23015,*HiveGenericUdf*#org.apache.hadoop.hive.ql.udf.generic.GenericUDFFloor((ts#23016
> - (ts#23016 % 300))) AS PartialGroup#23108L,SUM(size#23023L) AS
> PartialSum#23107L]
> PhysicalRDD [chan#23015,ts#23016,size#23023L], MapPartitionsRDD[28] at map
> at newParquet.scala:562
> {quote}
> *Why? ScalaUdf is so slow?? How to improve it?*
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