Member since 
    
	
		
		
		05-31-2017
	
	
	
	
	
	
	
	
	
	
	
	
	
	
			
      
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        My Accepted Solutions
| Title | Views | Posted | 
|---|---|---|
| 1601 | 08-25-2023 10:48 AM | |
| 2688 | 05-24-2023 11:21 AM | |
| 5409 | 05-09-2022 02:54 PM | |
| 4179 | 04-28-2022 11:27 AM | |
| 2040 | 04-19-2022 11:03 AM | 
			
    
	
		
		
		12-12-2024
	
		
		09:32 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 Admins can enforce application lifetime SLAs at a service level by setting yarn.scheduler.capacity.<queue-path>.maximum-application-lifetime ” and “yarn.scheduler.capacity.root.<queue-path>.default-application-lifetime” in  capacity-scheduler.xml.  CM > Yarn > Configuration > Capacity Scheduler Configuration Advanced Configuration Snippet (Safety Valve)  reference link is https://blog.cloudera.com/enforcing-application-lifetime-slas-yarn/  How are you setting this parameter? Can you share the entire stacktrace of the failure?    
						
					
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		10-26-2023
	
		
		01:53 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 CDP 7.1.7 supports Spark 3.2.3 not Spark 3.3  https://docs.cloudera.com/cdp-private-cloud-base/7.1.7/cds-3/topics/spark-3-requirements.html 
						
					
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		08-25-2023
	
		
		10:48 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Spark 3.3 can be installed on CDP 7.1.8 and higher. Here is the document for pre-req and installation steps  https://docs.cloudera.com/cdp-private-cloud-base/7.1.8/cds-3/topics/spark-3-requirements.html  https://docs.cloudera.com/cdp-private-cloud-base/7.1.8/cds-3/topics/spark-install-spark-3-parcel.html 
						
					
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		05-24-2023
	
		
		11:21 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 At the moment both uber rss and apache uniffle are not supported in CDP.  Dynamic resource allocation requires an external shuffle service that runs on each worker node as an auxiliary service of NodeManager. This service is started automatically; no further steps are needed. spark.shuffle.service.enabled=true enables the external shuffle service. The external shuffle service preserves shuffle files written by executors so that the executors can be deallocated without losing work. Must be enabled if dynamic allocation is enabled. 
						
					
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		10-19-2022
	
		
		10:48 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 AFAIU It should not matter. You can choose the rolling restart option as well. So CM can decide the sequence of the broker restarts.  
						
					
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		05-09-2022
	
		
		02:54 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @bluespring One should not be deleting the offline/online partitions that may cause in data loss or under-replicated partitions. You may reassign the partitions to new hosts following the document below:  https://docs.cloudera.com/cdp-private-cloud-base/7.1.6/kafka-managing/topics/kafka-manage-cli-reassign-overview.html 
						
					
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		04-28-2022
	
		
		01:55 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @clouderaskme  The latest CDP 7.1.7 comes with the default Spark 2.4 version.   https://docs.cloudera.com/cdp-private-cloud-base/7.1.7/runtime-release-notes/topics/rt-pvc-runtime-component-versions.html  Spark 2.4 supports Python 2.7 and 3.4-3.7.  https://docs.cloudera.com/cdp-private-cloud-upgrade/latest/release-guide/topics/cdpdc-os-requirements.html    
						
					
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		04-28-2022
	
		
		11:27 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @clouderaskme Please review the documents below that provides the details on requirements for Spark3.2, 3.1 and 3.0  https://docs.cloudera.com/cdp-private-cloud-base/7.1.7/cds-3/topics/spark-3-requirements.html  https://docs.cloudera.com/cdp-private-cloud-base/7.1.6/cds-3/topics/spark-spark-3-requirements.html  https://docs.cloudera.com/cdp-private-cloud-base/7.1.4/cds-3/topics/spark-spark-3-requirements.html    Cloudera Distributed Spark 3.2 requires Python 3.6+ and requires CDP 7.1.7 and higher  Cloudera Distributed Spark 3.1 requires Python 3.6+ and requires CDP 7.1.7 and higher  Cloudera Distributed Spark 3.0 requires Python 3.4 or higher.  and requires CDP7.1.3, 7.1.4 and 7.1.5            
						
					
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		04-19-2022
	
		
		11:03 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 @Sayed016 Thank you for your question.  From the error stack of CM logs, it looks like it tries to copy the system database and information_schema.  You need to exclude the system database and information_schema  Add the following exclusion on a Hive replication: Databases: (?!information_schema|sys\b).+ Tables: [\w].+     
						
					
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		02-16-2022
	
		
		03:18 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 Please follow the steps below:   SSH to Cloudera Manager host where the Spark 3 CSDs are deployed  Find the following files and use a file manager (for example mc) or an editor to open them as zip files and edit the contents of "descriptor/service.sdl". Probably the easiest way is to open the jar files with vim:  $ vim /opt/cloudera/csd/SPARK3_ON_YARN-3.2.0.3.2.7170.0-49.jar  $ vim /opt/cloudera/csd/LIVY_FOR_SPARK3-0.6.3000.3.2.7170.0-49.jar    In the descriptor/service.sdl files, prefix the version with something that is higher than the CM version number, so instead of:   "version" : "3.0.7110.0", add "version" : "7.5.4.3.0.7110.0", 4.     Restart CM server and wait until it comes back up:   $ service cloudera-scm-server restart     Spark 3 can now be installed. Once installed, deploy client config and restart all services that have stale configs (most importantly YARN).  
						
					
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