Spark Window 函数需要 HiveContext？

Question

我在这个博客 http://xinhstechblog.blogspot.in/2016/04/spark-window-functions-for-dataframes.html.

上尝试了一个 window spark 函数示例

运行 program.My 问题时出现以下错误，我们是否需要 hivecontext 来执行 spark 中的 window 函数？

Exception in thread "main" org.apache.spark.sql.AnalysisException: Could not resolve window function 'avg'. Note that, using window functions currently requires a HiveContext;
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.failAnalysis(CheckAnalysis.scala:38)
    at org.apache.spark.sql.catalyst.analysis.Analyzer.failAnalysis(Analyzer.scala:44)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$$anonfun$apply.applyOrElse(CheckAnalysis.scala:74)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$$anonfun$apply.applyOrElse(CheckAnalysis.scala:57)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp.apply(TreeNode.scala:319)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp.apply(TreeNode.scala:319)
    at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:53)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:318)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun.apply(TreeNode.scala:316)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun.apply(TreeNode.scala:316)
    at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun.apply(TreeNode.scala:265)
    at scala.collection.Iterator$$anon.next(Iterator.scala:328)
    at scala.collection.Iterator$class.foreach(Iterator.scala:727)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
    at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
    at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
    at scala.collection.AbstractIterator.to(Iterator.scala:1157)
    at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
    at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
    at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
    at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:305)
    at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:316)
    at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionUp(QueryPlan.scala:107)
    at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform(QueryPlan.scala:117)
    at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform.apply(QueryPlan.scala:121)
    at scala.collection.TraversableLike$$anonfun$map.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map.apply(TraversableLike.scala:244)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.AbstractTraversable.map(Traversable.scala:105)
    at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform(QueryPlan.scala:121)
    at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun.apply(QueryPlan.scala:125)
    at scala.collection.Iterator$$anon.next(Iterator.scala:328)
    at scala.collection.Iterator$class.foreach(Iterator.scala:727)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
    at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
    at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
    at scala.collection.AbstractIterator.to(Iterator.scala:1157)
    at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
    at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
    at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
    at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
    at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:125)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis.apply(CheckAnalysis.scala:57)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis.apply(CheckAnalysis.scala:50)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:105)
    at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:50)
    at org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:44)
    at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34)
    at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
    at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$withPlan(DataFrame.scala:2165)
    at org.apache.spark.sql.DataFrame.select(DataFrame.scala:751)
    at org.apache.spark.sql.DataFrame.withColumn(DataFrame.scala:1227)
    at WindowFunction$.main(WindowFunction.scala:23)

Answer 1

取决于版本：

Spark 1.x -> 是
Spark 2.0 -> 否

Spark Window 函数需要 HiveContext？

Spark Window Functions requires HiveContext?

window-functions

apache-spark

apache-spark-sql

spark-dataframe