Within a pyspark shell, both of these work for me: print hc.sql("SELECT * from raw.location_tbl LIMIT 10").collect() print sqlCtx.sql("SELECT * from raw.location_tbl LIMIT 10").collect()
But when I submit both of those in batch mode (hc and sqlCtx both exist), I get the following error. Why is this happening? I'll note that I'm running on YARN (CDH) and connecting to the Hive Metastore by setting an environment variable with export HADOOP_CONF_DIR=/etc/hive/conf/ An error occurred while calling o39.sql. : java.lang.RuntimeException: Table Not Found: raw.location_tbl at scala.sys.package$.error(package.scala:27) at org.apache.spark.sql.catalyst.analysis.SimpleCatalog$$anonfun$1.apply(Catalog.scala:111) at org.apache.spark.sql.catalyst.analysis.SimpleCatalog$$anonfun$1.apply(Catalog.scala:111) at scala.collection.MapLike$class.getOrElse(MapLike.scala:128) at scala.collection.AbstractMap.getOrElse(Map.scala:58) at org.apache.spark.sql.catalyst.analysis.SimpleCatalog.lookupRelation(Catalog.scala:111) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.getTable(Analyzer.scala:175) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:187) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:182) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:187) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:50) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:186) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at scala.collection.Iterator$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.transformChildrenDown(TreeNode.scala:236) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at scala.collection.Iterator$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$class.toArray(TraversableOnce.scala:252) at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:177) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:182) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:172) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59) at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111) at scala.collection.immutable.List.foldLeft(List.scala:84) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51) at scala.collection.immutable.List.foreach(List.scala:318) at org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51) at org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:1071) at org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:1071) at org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:1069) at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133) at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:915) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379) at py4j.Gateway.invoke(Gateway.java:259) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:207) at java.lang.Thread.run(Thread.java:745) False Traceback (most recent call last): File "/home/me/pyspark/pyspark_library_walkthrough.py", line 46, in <module> print row_objects[0].dma_code -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/sqlCtx-sql-some-hive-table-works-in-pyspark-but-not-spark-submit-tp25314.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org