Member since 
    
	
		
		
		11-22-2016
	
	
	
	
	
	
	
	
	
	
	
	
	
	
			
      
                50
            
            
                Posts
            
        
                3
            
            
                Kudos Received
            
        
                1
            
            
                Solution
            
        My Accepted Solutions
| Title | Views | Posted | 
|---|---|---|
| 3977 | 01-17-2017 02:54 PM | 
			
    
	
		
		
		10-05-2017
	
		
		07:06 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Yes, metadata does store the columns name in its database.  hive > show columns in table_name:  hive> set hive.cli.print.header=true;  To view the column names of your table. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		10-05-2017
	
		
		06:48 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 how did you run the script? it didn't return me any result. can your share your's? 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		08-21-2017
	
		
		09:53 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 But this is not a suitable solution for production environment 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		04-04-2017
	
		
		01:50 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							How did u solved it ??? Which things one has to check ?
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		04-04-2017
	
		
		01:48 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							  how did you solve it Max? 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		01-17-2017
	
		
		02:54 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 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 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		01-17-2017
	
		
		12:19 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 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. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
		
			
				
						
							Labels:
						
						
		
			
	
					
			
		
	
	
	
	
				
		
	
	
- Labels:
- 
						
							
		
			Apache Spark
			
    
	
		
		
		01-16-2017
	
		
		09:02 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Can i know which versions of hive and spark you are using? 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		01-14-2017
	
		
		09:40 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 which version spark are you using?  assuming you are using 1.4v or higher.     import org.apache.spark.sql.hive.HiveContext  import sqlContext.implicits._  val hiveObj = new HiveContext(sc)  hiveObj.refreshTable("db.table") // if you have uograded your hive do this, to refresh the tables.    val sample = sqlContext.sql("select * from table").collect()  sample.foreach(println)     This has worked for me 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		01-14-2017
	
		
		09:33 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Did this work for you?  If not, please post the code which worked for you 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		 
        













