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Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2014/12/09 02:42:12 UTC
[jira] [Resolved] (SPARK-4769) CTAS does not work when reading from
temporary tables
[ https://issues.apache.org/jira/browse/SPARK-4769?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Michael Armbrust resolved SPARK-4769.
-------------------------------------
Resolution: Fixed
Fix Version/s: 1.2.0
Issue resolved by pull request 3336
[https://github.com/apache/spark/pull/3336]
> CTAS does not work when reading from temporary tables
> -----------------------------------------------------
>
> Key: SPARK-4769
> URL: https://issues.apache.org/jira/browse/SPARK-4769
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.2.0
> Reporter: Michael Armbrust
> Priority: Critical
> Fix For: 1.2.0
>
>
> {code}
> test("double nested data") {
> sparkContext.parallelize(Nested1(Nested2(Nested3(1))) ::
> Nil).registerTempTable("nested")
> checkAnswer(
> sql("SELECT f1.f2.f3 FROM nested"),
> 1)
> checkAnswer(sql("CREATE TABLE test_ctas_1234 AS SELECT * from nested"),
> Seq.empty[Row])
> checkAnswer(
> sql("SELECT * FROM test_ctas_1234"),
> sql("SELECT * FROM nested").collect().toSeq)
> }
> {code}
> {code}
> 11:57:15.974 ERROR org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:
> org.apache.hadoop.hive.ql.parse.SemanticException: Line 1:45 Table not found
> 'nested'
> at
> org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.getMetaData(SemanticAnalyzer.java:1243)
> at
> org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.getMetaData(SemanticAnalyzer.java:1192)
> at
> org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.analyzeInternal(SemanticAnalyzer.java:9209)
> at
> org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer.analyze(BaseSemanticAnalyzer.java:327)
> at
> org.apache.spark.sql.hive.execution.CreateTableAsSelect.metastoreRelation$lzycompute(CreateTableAsSelect.scala:59)
> at
> org.apache.spark.sql.hive.execution.CreateTableAsSelect.metastoreRelation(CreateTableAsSelect.scala:55)
> at
> org.apache.spark.sql.hive.execution.CreateTableAsSelect.sideEffectResult$lzycompute(CreateTableAsSelect.scala:82)
> at
> org.apache.spark.sql.hive.execution.CreateTableAsSelect.sideEffectResult(CreateTableAsSelect.scala:70)
> at
> org.apache.spark.sql.hive.execution.CreateTableAsSelect.execute(CreateTableAsSelect.scala:89)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:425)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:425)
> at org.apache.spark.sql.SchemaRDDLike$class.$init$(SchemaRDDLike.scala:58)
> at org.apache.spark.sql.SchemaRDD.<init>(SchemaRDD.scala:105)
> at org.apache.spark.sql.hive.HiveContext.sql(HiveContext.scala:103)
> {code}
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