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https://issues.apache.org/jira/browse/SPARK-6489?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14395643#comment-14395643
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Apache Spark commented on SPARK-6489:
-------------------------------------
User 'dreamquster' has created a pull request for this issue:
https://github.com/apache/spark/pull/5358
> Optimize lateral view with explode to not read unnecessary columns
> ------------------------------------------------------------------
>
> Key: SPARK-6489
> URL: https://issues.apache.org/jira/browse/SPARK-6489
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.3.0
> Reporter: Konstantin Shaposhnikov
> Labels: starter
>
> Currently a query with "lateral view explode(...)" results in an execution
> plan that reads all columns of the underlying RDD.
> E.g. given *ppl* table is DF created from Person case class:
> {code}
> case class Person(val name: String, val age: Int, val data: Array[Int])
> {code}
> the following SQL:
> {code}
> select name, sum(d) from ppl lateral view explode(data) d as d group by name
> {code}
> executes as follows:
> {noformat}
> == Physical Plan ==
> Aggregate false, [name#0], [name#0,SUM(PartialSum#38L) AS _c1#18L]
> Exchange (HashPartitioning [name#0], 200)
> Aggregate true, [name#0], [name#0,SUM(CAST(d#21, LongType)) AS
> PartialSum#38L]
> Project [name#0,d#21]
> Generate explode(data#2), true, false
> InMemoryColumnarTableScan [name#0,age#1,data#2], [], (InMemoryRelation
> [name#0,age#1,data#2], true, 10000, StorageLevel(true, true, false, true, 1),
> (PhysicalRDD [name#0,age#1,data#2], MapPartitionsRDD[1] at mapPartitions at
> ExistingRDD.scala:35), Some(ppl))
> {noformat}
> Note that *age* column is not needed to produce the output but it is still
> read from the underlying RDD.
> A sample program to demonstrate the issue:
> {code}
> case class Person(val name: String, val age: Int, val data: Array[Int])
> object ExplodeDemo extends App {
> val ppl = Array(
> Person("A", 20, Array(10, 12, 19)),
> Person("B", 25, Array(7, 8, 4)),
> Person("C", 19, Array(12, 4, 232)))
>
> val conf = new SparkConf().setMaster("local[2]").setAppName("sql")
> val sc = new SparkContext(conf)
> val sqlCtx = new HiveContext(sc)
> import sqlCtx.implicits._
> val df = sc.makeRDD(ppl).toDF
> df.registerTempTable("ppl")
> sqlCtx.cacheTable("ppl") // cache table otherwise ExistingRDD will be used
> that do not support column pruning
> val s = sqlCtx.sql("select name, sum(d) from ppl lateral view explode(data)
> d as d group by name")
> s.explain(true)
> }
> {code}
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