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		01-25-2016
	
	
	
	
	
	
	
	
	
	
	
	
	
	
			
      
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| Title | Views | Posted | 
|---|---|---|
| 6085 | 10-20-2017 06:39 PM | |
| 4767 | 03-30-2017 06:03 AM | |
| 3324 | 02-16-2017 04:55 PM | |
| 17750 | 02-01-2017 04:38 PM | |
| 1448 | 01-24-2017 08:36 PM | 
			
    
	
		
		
		06-12-2025
	
		
		11:21 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 WebHCat is no longer a supported feature in Cloudera CDP.  [+] https://docs.cloudera.com/cdp-private-cloud-upgrade/latest/upgrade-cdh/topics/hive-unsupported.html  [+] https://docs.cloudera.com/cdp-private-cloud-base/7.3.1/hive-introduction/topics/hive-unsupported.html 
						
					
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		06-02-2022
	
		
		06:59 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 have u tried move out (or delete the folder for that partition ) from hdfs, then run: msck repair table <tablename> 
						
					
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		10-11-2021
	
		
		08:28 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		1 Kudo
		
	
				
		
	
		
					
							 To resolve the issue, import the Ambari certificates to the Ambari truststore. To import the Ambari certificates, do the following: 
STEP 1: 
Get certificate from ambari-server 
echo | openssl s_client -showcerts -connect <AMBARI_HOst>:<AMBARI_HTTPs_PORT> 2>&1 | sed --quiet '/-BEGIN CERTIFICATE-/,/-END CERTIFICATE-/p' > /tmp/ambari_certificate.cr 
STEP 2: 
Get path of ambari trustore and truststore password from Ambari properties 
cat /etc/ambari-server/conf/ambari.properties |grep truststore 
As per your ambari.properties below is the path and password :-
ssl.trustStore.password=refer from ambari.property file
ssl.trustStore.path=/etc/ambari-server/conf/ambari-server-truststore
STEP 3: 
keytool -importcert -file /tmp/ambari_certificate.crt -keystore <keystore-path> 
STEP 4: 
ambari-server restart
 
						
					
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		01-26-2020
	
		
		11:18 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 This worked!        I already made these changes prior to running the last command.      hdp-select status hadoop-client         Set a couple of parameters  export HADOOP_OPTS="-Dhdp.version=2.6.1.0-129”  export HADOOP_CONF_DIR=/etc/hadoop/conf     Source-in the environment  source ~/get_env.sh            Included last two lines to $SPARK_HOME/conf/spark-defaults.conf  spark.driver.extraJavaOptions   -Dhdp.version=2.6.1.0-129  spark.yarn.am.extraJavaOptions -Dhdp.version=2.6.1.0-129      Added Hadoop version under Ambari / Yarn / Advanced / Custom:   hdp.version=2.6.1.0-129         Ensure this runs okay   yarn jar hadoop-mapreduce-examples.jar pi 5 5       Run spark pi example under yarn     cd /home/spark/spark-2.4.4-bin-hadoop2.7     spark-submit   --class org.apache.spark.examples.SparkPi  --master yarn   --deploy-mode cluster   --executor-memory 2G  --num-executors 5  --executor-cores 2   --conf spark.authenticate.enableSaslEncryption=true   --conf spark.network.sasl.serverAlwaysEncrypt=true   --conf spark.authenticate=true   examples/jars/spark-examples_2.11-2.4.4.jar   100   
						
					
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		01-07-2020
	
		
		09:16 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 How did you resolve the issue ? 
						
					
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		01-02-2020
	
		
		07:08 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Hi, 
 I need to uninstall Ranger/Ranger KMS 1.2.0, how can I do it? 
 Thank, 
 Neelagandan K 
						
					
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		09-26-2019
	
		
		12:03 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 I also faced the same issue.Found the issue was with mysql-connector-java.jar. I followed the below steps   1. Check whether you are able to connect remotely to mysql database.  2.If you are able to connect , then , its mysql-connector-java.jar in ambari  3. Download the correct version of mysql jar from https://dev.mysql.com/downloads/connector/j/  4. Stop ambari server .  5.Remove the mysql connector jar from ambari  6. Set up again using  ambari-server setup --jdbc-db=mysql --jdbc-driver=/usr/share/java/ mysql-connector-java-8.0.16 
						
					
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		06-10-2018
	
		
		06:11 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							@sunile.manjee Thank you:) 
						
					
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		11-07-2017
	
		
		12:38 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Thanks. Glad to know that it helped. 
						
					
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		10-25-2017
	
		
		03:41 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							@PJ Yeah, it might be that case.Because if you are having large number of records then it will take a lot of time to convert ORC data to csv format and if you compare these two process executing query with insert overwrite directory will perform much faster with no issues and also we can keep what ever delimiter we need and we don't need to worry about size of the data.  
						
					
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