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| Title | Views | Posted | 
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| 3970 | 10-13-2017 09:42 PM | |
| 7459 | 09-14-2017 11:15 AM | |
| 3789 | 09-13-2017 10:35 PM | |
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		02-02-2023
	
		
		03:32 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @45, as this is an older post, you would have a better chance of receiving a resolution by starting a new thread. This will also be an opportunity to provide details specific to your environment that could aid others in assisting you with a more accurate answer to your question. You can link this thread as a reference in your new post. 
						
					
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		03-17-2021
	
		
		05:21 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 This error shows up if you have selected Sentry/Ranger as dependencies but not checked true for the below config (i.e. did not enable Kerberos)   kerberos.auth.enable    
						
					
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		10-01-2020
	
		
		04:29 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hbase stores data as a sorted map by keys. HBase is considered a persistent, multidimensional, sorted map, where each cell is indexed by a row key and column key (family and qualifier). A rowkey, which is immutable and uniquely defines a row, usually spans multiple HFiles. Rowkeys are treated as byte arrays (byte[]) and are stored in a sorted order in the multi-dimensional sorted map. If you look for a row_key, Hbase is able to identify the node where this data is present. Hadoop runs its computation on the same node where the key is present and hence the performance with technologies like Spark is really good. This is called data localization. 
						
					
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		02-12-2020
	
		
		05:18 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi .     any solution you found for  same .     i having the same issue the  accessing the hive through python.        Thanks   HadoopHelp 
						
					
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		01-05-2020
	
		
		06:33 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi,     This parameter spark.executor.memory (or) spark.yarn.executor.memoryOverhead can be set in Spark submit command or you can set it Advanced configurations.     Thanks  AKR 
						
					
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		12-04-2019
	
		
		08:35 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Do you have a documentation for this 
						
					
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		07-25-2019
	
		
		10:00 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 is a bit late but i post the solution that worked for me.  the problem was the hostnames, impala with kerberos wants the hostnames in lowercase. 
						
					
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		06-14-2019
	
		
		03:39 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							The Spark 2 now is the only Spark that is supported by CDH 6.x so I am not sure you will get any reply here.  Is there any reason you are still in Spark 1.6.x?
						
					
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		06-06-2019
	
		
		11:28 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 yarn logs -applicationId  <application master ID> should help. It occurs typically due improper container memory allocation and physical memory availability on the cluster.  
						
					
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