Reynold Xin created SPARK-8072: ---------------------------------- Summary: Better AnalysisException for writing DataFrame with identically named columns Key: SPARK-8072 URL: https://issues.apache.org/jira/browse/SPARK-8072 Project: Spark Issue Type: Sub-task Components: SQL Reporter: Reynold Xin Priority: Blocker
We should check if there are duplicate columns, and if yes, throw an explicit error message saying there are duplicate columns. See current error message below. {code} In [3]: df.withColumn('age', df.age) Out[3]: DataFrame[age: bigint, name: string, age: bigint] In [4]: df.withColumn('age', df.age).write.parquet('test-parquet.out') --------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) <ipython-input-4-eecb85256898> in <module>() ----> 1 df.withColumn('age', df.age).write.parquet('test-parquet.out') /scratch/rxin/spark/python/pyspark/sql/readwriter.py in parquet(self, path, mode) 350 >>> df.write.parquet(os.path.join(tempfile.mkdtemp(), 'data')) 351 """ --> 352 self._jwrite.mode(mode).parquet(path) 353 354 @since(1.4) /Users/rxin/anaconda/lib/python2.7/site-packages/py4j-0.8.1-py2.7.egg/py4j/java_gateway.pyc in __call__(self, *args) 535 answer = self.gateway_client.send_command(command) 536 return_value = get_return_value(answer, self.gateway_client, --> 537 self.target_id, self.name) 538 539 for temp_arg in temp_args: /Users/rxin/anaconda/lib/python2.7/site-packages/py4j-0.8.1-py2.7.egg/py4j/protocol.pyc in get_return_value(answer, gateway_client, target_id, name) 298 raise Py4JJavaError( 299 'An error occurred while calling {0}{1}{2}.\n'. --> 300 format(target_id, '.', name), value) 301 else: 302 raise Py4JError( Py4JJavaError: An error occurred while calling o35.parquet. : org.apache.spark.sql.AnalysisException: Reference 'age' is ambiguous, could be: age#0L, age#3L.; at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolve(LogicalPlan.scala:279) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveChildren(LogicalPlan.scala:116) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$8$$anonfun$applyOrElse$4$$anonfun$16.apply(Analyzer.scala:350) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$8$$anonfun$applyOrElse$4$$anonfun$16.apply(Analyzer.scala:350) at org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:48) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$8$$anonfun$applyOrElse$4.applyOrElse(Analyzer.scala:350) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$8$$anonfun$applyOrElse$4.applyOrElse(Analyzer.scala:341) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:286) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:286) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51) at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:285) at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$transformExpressionUp$1(QueryPlan.scala:108) at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2$$anonfun$apply$2.apply(QueryPlan.scala:123) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) at scala.collection.immutable.List.foreach(List.scala:318) at scala.collection.TraversableLike$class.map(TraversableLike.scala:244) at scala.collection.AbstractTraversable.map(Traversable.scala:105) at org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$2.apply(QueryPlan.scala:122) at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) at scala.collection.Iterator$class.foreach(Iterator.scala:727) at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) at scala.collection.AbstractIterator.to(Iterator.scala:1157) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:127) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$8.applyOrElse(Analyzer.scala:341) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$8.applyOrElse(Analyzer.scala:243) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:286) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:286) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:51) at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:285) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:243) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:242) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:61) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:59) at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111) at scala.collection.immutable.List.foldLeft(List.scala:84) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:59) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:51) at scala.collection.immutable.List.foreach(List.scala:318) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:51) at org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:903) at org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:903) at org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:901) at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:131) at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) at org.apache.spark.sql.sources.InsertIntoHadoopFsRelation.run(commands.scala:98) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57) at org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:57) at org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:68) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:88) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:88) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:87) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:920) at org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:920) at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:338) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:144) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:135) at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:281) 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:744) {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org