Support Questions
Find answers, ask questions, and share your expertise
Announcements
Alert: Welcome to the Unified Cloudera Community. Former HCC members be sure to read and learn how to activate your account here.

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed

Solved Go to solution

Exception in thread "main" java.lang.IllegalArgumentException: requirement failed

Contributor

Hi all,

Here i'm trying to add time stamp to the data frame dynamically, like this

messages.foreachRDD(rdd=>
         74 {
         75 val sqlContext = new org.apache.spark.sql.hive.HiveContext(sc)
         76 import sqlContext.implicits._
         77 val dataframe =sqlContext.read.json(rdd.map(_._2)).toDF()
         78 import org.apache.spark.sql.functions._
         79  val newDF=dataframe.withColumn("Timestamp_val",current_timestamp())
         80 newDF.show()
         81 newDF.printSchema()

But this code is giving me an headache, sometimes it is printing the schema and sometimes it is throwing this

java.lang.IllegalArgumentException: requirement failed at scala.Predef$.require(Predef.scala:221) at org.apache.spark.sql.catalyst.analysis.UnresolvedStar.expand(unresolved.scala:199) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10$$anonfun$applyOrElse$14.apply(Analyzer.scala:354) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10$$anonfun$applyOrElse$14.apply(Analyzer.scala:353) at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251) at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10.applyOrElse(Analyzer.scala:353) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$10.applyOrElse(Analyzer.scala:347) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:57) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:57) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:56) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:347) at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:328) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:83) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:80) at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111) at scala.collection.immutable.List.foldLeft(List.scala:84) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:80) at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:72) at scala.collection.immutable.List.foreach(List.scala:318) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:72) at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:36) at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:36) at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:34) at org.apache.spark.sql.DataFrame.(DataFrame.scala:133) at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$withPlan(DataFrame.scala:2126) at org.apache.spark.sql.DataFrame.select(DataFrame.scala:707) at org.apache.spark.sql.DataFrame.withColumn(DataFrame.scala:1188) at HiveGenerator$$anonfun$main$1.apply(HiveGenerator.scala:79) at HiveGenerator$$anonfun$main$1.apply(HiveGenerator.scala:73)

Where am i going wrong, please help.

1 ACCEPTED SOLUTION

Accepted Solutions

Re: Exception in thread "main" java.lang.IllegalArgumentException: requirement failed

Contributor

fixed it, like below

df.withColumn("Timestamp_val",lit(current_timestamp))

As the second argument in the .withColumn() will expect a named column and

val newDF=dataframe.withColumn("Timestamp_val",current_timestamp())

will not generate a named column.Hence the exception

1 REPLY 1

Re: Exception in thread "main" java.lang.IllegalArgumentException: requirement failed

Contributor

fixed it, like below

df.withColumn("Timestamp_val",lit(current_timestamp))

As the second argument in the .withColumn() will expect a named column and

val newDF=dataframe.withColumn("Timestamp_val",current_timestamp())

will not generate a named column.Hence the exception