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Posted to issues@spark.apache.org by "Reynold Xin (JIRA)" <ji...@apache.org> on 2016/02/23 06:17:18 UTC
[jira] [Created] (SPARK-13445) Seleting "data" with window function
does not work unless aliased (using PARTITION BY)
Reynold Xin created SPARK-13445:
-----------------------------------
Summary: Seleting "data" with window function does not work unless aliased (using PARTITION BY)
Key: SPARK-13445
URL: https://issues.apache.org/jira/browse/SPARK-13445
Project: Spark
Issue Type: Bug
Components: SQL
Reporter: Reynold Xin
The code does not throw an exception if "data" is aliased. Maybe this is a reserved word or aliases are just required when using PARTITION BY?
{code}
sql("""
SELECT
data as the_data,
row_number() over (partition BY data.type) AS foo
FROM event_record_sample
""")
{code}
However, this code throws an error:
{code}
sql("""
SELECT
data,
row_number() over (partition BY data.type) AS foo
FROM event_record_sample
""")
{code}
{code}
org.apache.spark.sql.AnalysisException: resolved attribute(s) type#15246 missing from data#15107,par_cat#15112,schemaMajorVersion#15110,source#15108,recordId#15103,features#15106,eventType#15105,ts#15104L,schemaMinorVersion#15111,issues#15109 in operator !Project [data#15107,type#15246];
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$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:183)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:50)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:105)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:104)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:104)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:104)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:104)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:104)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:104)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:104)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:104)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:104)
at org.apache.spark.sql.catalyst.analysis.CheckAnalysis$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$.apply(DataFrame.scala:52)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:816)
{code}
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