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Dongjoon Hyun commented on SPARK-19308: --------------------------------------- Hi, [~vapira]. Thank you for reporting. This issue seems to be fixed in SPARK-18123. {code} scala> spark.version res0: String = 2.2.0-SNAPSHOT scala> val test = sc.parallelize(Array("{\"a\":1,\"b.b\":2}")) test: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[0] at parallelize at <console>:24 scala> val j = spark.read.json(test) j: org.apache.spark.sql.DataFrame = [a: bigint, b.b: bigint] scala> j.write.mode("append").saveAsTable("test") scala> j.write.mode("append").saveAsTable("test") {code} > Unable to write to Hive table where column names contains period (.) > -------------------------------------------------------------------- > > Key: SPARK-19308 > URL: https://issues.apache.org/jira/browse/SPARK-19308 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.2, 2.1.0 > Reporter: Maria Rebelka > Labels: hive > > When saving DataFrame which contains columns with dots to Hive in append > mode, it only succeeds when the table doesn't exists yet. > {noformat} > scala> spark.sql("drop table test") > res0: org.apache.spark.sql.DataFrame = [] > scala> val test = sc.parallelize(Array("{\"a\":1,\"b.b\":2}")) > test: org.apache.spark.rdd.RDD[String] = ParallelCollectionRDD[1] at > parallelize at <console>:24 > scala> val j = spark.read.json(test) > j: org.apache.spark.sql.DataFrame = [a: bigint, b.b: bigint] > scala> j.write.mode("append").saveAsTable("test") > // succeeds > scala> j.write.mode("append").saveAsTable("test") > org.apache.spark.sql.AnalysisException: cannot resolve '`b.b`' given input > columns: [a, b.b]; line 1 pos 0; > 'Project [a#6L, 'b.b] > +- LogicalRDD [a#6L, b.b#7L] > at > org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42) > at > org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:77) > at > org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1$$anonfun$apply$2.applyOrElse(CheckAnalysis.scala:74) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:308) > at > org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:308) > at > org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69) > at > org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:307) > at > org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionUp$1(QueryPlan.scala:269) > at > org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:279) > at > org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2$1.apply(QueryPlan.scala:283) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) > at scala.collection.AbstractTraversable.map(Traversable.scala:104) > at > org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$2(QueryPlan.scala:283) > at > org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$8.apply(QueryPlan.scala:288) > at > org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:186) > at > org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsUp(QueryPlan.scala:288) > at > org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:74) > at > org.apache.spark.sql.catalyst.analysis.CheckAnalysis$$anonfun$checkAnalysis$1.apply(CheckAnalysis.scala:67) > at > org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:126) > at > org.apache.spark.sql.catalyst.analysis.CheckAnalysis$class.checkAnalysis(CheckAnalysis.scala:67) > at > org.apache.spark.sql.catalyst.analysis.Analyzer.checkAnalysis(Analyzer.scala:58) > at > org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:49) > at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64) > at > org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withPlan(Dataset.scala:2603) > at org.apache.spark.sql.Dataset.select(Dataset.scala:969) > at org.apache.spark.sql.Dataset.selectExpr(Dataset.scala:1004) > at > org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:236) > at > org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58) > at > org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56) > at > org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115) > at > org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133) > at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114) > at > org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:86) > at > org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:86) > at > org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:378) > at > org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:354) > ... 48 elided > scala> spark.sql("drop table test") > res3: org.apache.spark.sql.DataFrame = [] > scala> j.write.mode("append").saveAsTable("test") > // succeeds again > {noformat} -- 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