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		03-26-2017
	
	
	
	
	
	
	
	
	
	
	
	
	
	
			
      
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        My Accepted Solutions
| Title | Views | Posted | 
|---|---|---|
| 3841 | 08-27-2018 03:19 PM | |
| 27784 | 08-27-2018 03:18 PM | |
| 11423 | 04-02-2018 01:54 PM | 
			
    
	
		
		
		11-27-2018
	
		
		08:10 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi @Felix Albani, Tanx for your response.  I reffered this site i'm thinking my issues is related to the story.  Cheers,  MJ 
						
					
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		09-17-2018
	
		
		05:57 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @Manikandan Jeyabal
  It is hard to provide the exact values based on the data size.  However you can refer to the following article to understand Executor Memory/Core/Resource Optimization.   https://community.hortonworks.com/articles/42803/spark-on-yarn-executor-resource-allocation-optimiz.html  https://dzone.com/articles/apache-spark-on-yarn-resource-planning 
						
					
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		09-17-2018
	
		
		05:53 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi @vgarg,  Since 0.11 hive has a NVL function  nvl(T value, T default_value)   which says Returns default value if value is null else returns value 
						
					
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		08-27-2018
	
		
		03:18 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi Issue got resolved,  i'm trying to perform Group by operation inside a Columns literal, group by itself will produce a new columns instead writing a query like i asked above we have to change our query accordingly as follow.  inputDf = inputDf.groupBy(col("tableName"),col("runDate"))    .agg(sum(when(col("MinBusinessDate") < col("runDate") && col("MaxBusinessDate") > col("runDate"),      when(col("business_date") > col("runDate"), col("rowCount")))).alias("NewColumnName")) 
						
					
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		08-27-2018
	
		
		03:19 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi Issue got resolved,  i'm trying to perform Group by operation inside a Columns literal, group by itself will produce a new columns instead writing a query like i asked above we have to change our query accordingly as follow.     inputDf = inputDf.groupBy(col("tableName"),col("runDate"))  .agg(sum(when(col("MinBusinessDate")< col("runDate")&& col("MaxBusinessDate")> col("runDate"),  when(col("business_date")> col("runDate"), col("rowCount")))).alias("NewColumnName"))  
						
					
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		08-25-2018
	
		
		06:40 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi @Felix Albani  yes your suggestion works fine, i think i have to extend my object as app to make it work. Tanx Bro. 
						
					
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		08-24-2018
	
		
		01:13 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi Aditya,  Tanx for your reply, is there any other posts or blog can i find how to implement the schema evolution in ORC ? 
						
					
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		07-09-2018
	
		
		08:06 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi @Sandeep Nemuri,  I think i found the answer from Stackoverflow site. Tanx for you info. 
						
					
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		07-09-2018
	
		
		08:05 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Tanx for your info @Felix Albani 
						
					
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		06-13-2018
	
		
		05:21 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 It's already installed and the issue resolved now, tanx for you response.  
						
					
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