Is it possible that Canonical_URL occurs more than once in your json ?
Can you check your json input ?
Thanks
On Sat, Sep 12, 2015 at 2:05 AM, Fengdong Yu <fengdo...@everstring.com>
wrote:
> Hi,
>
> I am using spark1.4.1 data frame, read JSON data, then save it to orc. the
> code is very simple:
>
> DataFrame json = sqlContext.read().json(input);
>
> json.write().format("orc").save(output);
>
> the job failed. what's wrong with this exception? Thanks.
>
> Exception in thread "main" org.apache.spark.sql.AnalysisException:
> Reference 'Canonical_URL' is ambiguous, could be: Canonical_URL#960,
> Canonical_URL#1010.; 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$$anonfun$execute$1.apply(RuleExecutor.scala:51)
> at scala.collection.immutable.List.foreach(List.scala:318) at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:51)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:933)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:933)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:931)
> at org.apache.spark.sql.DataFrame.(DataFrame.scala:131) at
> org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51) at
> org.apache.spark.sql.sources.InsertIntoHadoopFsRelation.run(commands.scala:132)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:57)
> at
> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:57)
> at
> org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:68)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:88)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:88)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:87) at
> org.apache.spark.sql.SQLContext$QueryExecution.toRdd$lzycompute(SQLContext.scala:950)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.toRdd(SQLContext.scala:950)
> at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:336) at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:144) at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:135) at
> com.es.infrastructure.spark.orc.transformer.JsonTransformer.run(JsonTransformer.java:22)
> at Main.main(Main.java:70) at
> sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606) at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:665)
> at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:170)
> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:193) at
> org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112) at
> org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>
>
