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202
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81
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Title | Views | Posted |
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4036 | 10-11-2017 09:33 PM | |
3562 | 10-11-2017 07:46 PM | |
2569 | 08-04-2017 01:37 PM | |
2207 | 08-03-2017 03:36 PM | |
2235 | 08-03-2017 12:52 PM |
08-23-2016
01:33 AM
2 Kudos
If you're looking for a sandbox/vm with HDP 2.5 then you can find it here: http://hortonworks.com/downloads/#tech-preview
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08-17-2016
07:48 PM
1 Kudo
@narender pasunooti Ubuntu 15 is not supported in HDP 2.4/2.4.2 https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.4.2/bk_HDP_RelNotes/content/upgrade_procedure.html Consider using Ubuntu 14, which is supported.
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08-16-2016
07:25 PM
You would copy the file from "/.reserved/raw/test1/file1.txt" to "/.reserved/raw/test2/file1.txt" while preserving the extended attributes (where the EZEK is saved) using the -px flag. https://hadoop.apache.org/docs/r2.7.2/hadoop-project-dist/hadoop-hdfs/TransparentEncryption.html#Running_as_the_superuser https://issues.apache.org/jira/browse/MAPREDUCE-6007
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08-16-2016
05:14 PM
*Removed my previous response and adding the link to the article below: https://community.hortonworks.com/articles/51909/how-to-copy-encrypted-data-between-two-hdp-cluster.html
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08-16-2016
02:24 PM
Thanks @Sagar Shimpi. I've seen this, but looking it the code it only seems like it's copying the master keys (EK). My understanding is that to un-encrypt a file you would need both, the master key (EK) stored in the DB as well as the file level encryption key (EDEK) which is store in the Name Node. Am I missing something or misunderstanding?
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08-16-2016
02:06 PM
When using Ranger KMS and TDE is it possible to share encryption keys across 2 clusters? The scenario is that we have a Prod and DR cluster. When doing the data replication we'd like to avoid un-encrypting it on Prod, moving it over the wire, and then re-encrypting it when we write to DR. Is this possible?
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08-15-2016
11:55 PM
2 Kudos
Because spark action in oozie is not supported in HDP 2.3.x and HDP 2.4.0, there is no workaround especially in kerberos environment. We can use either java action or shell action to launch spark job in oozie workflow. In this article, we will discuss how to use oozie shell action to run a spark job in kerberos environment. Prerequisite: 1. Spark client is installed on every host where nodemanager is running. This is because we have no control over which node the 2. Optionally, if the spark job need to interact with hbase cluster, hbase client need to be installed on every host as well. Steps: 1. Create a shell script with the spark-submit command. For example, in the script.sh: /usr/hdp/current/spark-client/bin/spark-submit --keytab keytab --principal ambari-qa-falconJ@FALCONJSECURE.COM --class org.apache.spark.examples.SparkPi --master yarn-client --driver-memory 500m --num-executors 1 --executor-memory 500m --executor-cores 1 spark-examples.jar 3 2. Prepare kerberos keytab which will be used by the spark job. For example, we use ambari smoke test user, the keytab is already generated by Ambari in/etc/security/keytabs/smokeuser.headless.keytab. 3. Create the oozie workflow with a shell action which will execute the script created above, for example, in the workflow.xml: <workflow-app name="WorkFlowForShellAction" xmlns="uri:oozie:workflow:0.4">
<start to="shellAction"/>
<action name="shellAction">
<shell xmlns="uri:oozie:shell-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<exec>script.sh</exec>
<file>/user/oozie/shell/script.sh#script.sh</file>
<file>/user/oozie/shell/smokeuser.headless.keytab#keytab</file>
<file>/user/oozie/shell/spark-examples.jar#spark-examples.jar</file>
<capture-output/>
</shell>
<ok to="end"/>
<error to="killAction"/>
</action>
<kill name="killAction">
<message>"Killed job due to error"</message>
</kill>
<end name="end"/>
</workflow-app> 4. Create the oozie job properties file. For example, in job.properties: nameNode=hdfs://falconJ1.sec.support.com:8020 jobTracker=falconJ2.sec.support.com:8050 queueName=default oozie.wf.application.path=${nameNode}/user/oozie/shell oozie.use.system.libpath=true 5. Upload the following files created above to the oozie workflow application path in HDFS (In this example: /user/oozie/shell): - workflow.xml - smokeuser.headless.keytab - script.sh - spark uber jar (In this example: /usr/hdp/current/spark-client/lib/spark-examples*.jar) - Any other configuration file mentioned in workflow (optional) 6. Execute the oozie command to run this workflow. For example: oozie job -oozie http://<oozie-server>:11000/oozie -config job.properties -run *This article was created by Hortonworks Support on 2016-04-28
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08-15-2016
10:14 PM
2 Kudos
Hi @Timothy Spann It really all depends on your particular use case and requirements. First, I'm assuming you have a custom-built application that will be querying this data store. If so, how complex do the queries need to be? Do you need Relational (SQL) or Key-Value store? Also, how much latency can you afford? I would first explore if HBase (or HBase + Phoenix) would be sufficient. This will reduce the number of moving parts you have. If you're set on in-memory data grids/stores then some options would be Redis, Hazelcast, Teracotta Big Memory and GridGain (Apache Ignite). I believe the last two have connectors to Hadoop that allow writing results of MR jobs directly to the data grid (you'll need to confirm that functionality though) Like I said before though, I recommend you exhaust the HBase option before moving out-of-stack.
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08-15-2016
09:46 PM
@SBandaru Please take a look at the link below for a discussion around installing Kylin on HDP. It refers to HDP 2.3.2 but should be applicable to 2.4 as well. https://community.hortonworks.com/questions/1293/how-to-make-kylin-work-with-hdp-23.html As for support, Hortonworks does not provide support for Kylin, but I'm sure you can get plenty of help from both, the Hortonworks and Kylin communities.
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08-15-2016
05:08 PM
@Ankit A Are you able to run the Spark job from the shell/command line? If so, then you may want to use Shell Action instead. Oozie Spark Action in HDP 2.3.4 is still in tech preview and not supported yet. The below tech note was released with the recommendation to use Shell Actions or Java Actions instead. https://community.hortonworks.com/content/kbentry/51582/how-to-use-oozie-shell-action-to-run-a-spark-job-i-1.html -------------------- Begin Tech Note -------------------- Because spark action in oozie is not supported in HDP 2.3.x and HDP 2.4.0, there is no workaround especially in kerberos environment. We can use either java action or shell action to launch spark job in oozie workflow. In this article, we will discuss how to use oozie shell action to run a spark job in kerberos environment. Prerequisite: 1. Spark client is installed on every host where nodemanager is running. This is because we have no control over which node the 2. Optionally, if the spark job need to interact with hbase cluster, hbase client need to be installed on every host as well. Steps: 1. Create a shell script with the spark-submit command. For example, in the script.sh: /usr/hdp/current/spark-client/bin/spark-submit --keytab keytab --principal ambari-qa-falconJ@FALCONJSECURE.COM --class org.apache.spark.examples.SparkPi --master yarn-client --driver-memory 500m --num-executors 1 --executor-memory 500m --executor-cores 1 spark-examples.jar 3 2. Prepare kerberos keytab which will be used by the spark job. For example, we use ambari smoke test user, the keytab is already generated by Ambari in/etc/security/keytabs/smokeuser.headless.keytab. 3. Create the oozie workflow with a shell action which will execute the script created above, for example, in the workflow.xml: <workflow-app name="WorkFlowForShellAction" xmlns="uri:oozie:workflow:0.4">
<start to="shellAction"/>
<action name="shellAction">
<shell xmlns="uri:oozie:shell-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<exec>script.sh</exec>
<file>/user/oozie/shell/script.sh#script.sh</file>
<file>/user/oozie/shell/smokeuser.headless.keytab#keytab</file>
<file>/user/oozie/shell/spark-examples.jar#spark-examples.jar</file>
<capture-output/>
</shell>
<ok to="end"/>
<error to="killAction"/>
</action>
<kill name="killAction">
<message>"Killed job due to error"</message>
</kill>
<end name="end"/>
</workflow-app> 4. Create the oozie job properties file. For example, in job.properties: nameNode=falconJ2.sec.support.com:8050 queueName=default oozie.wf.application.path=${nameNode}/user/oozie/shell oozie.use.system.libpath=true 5. Upload the following files created above to the oozie workflow application path in HDFS (In this example: /user/oozie/shell): - workflow.xml - smokeuser.headless.keytab - script.sh - spark uber jar (In this example: /usr/hdp/current/spark-client/lib/spark-examples*.jar) - Any other configuration file mentioned in workflow (optional) 6. Execute the oozie command to run this workflow. For example: oozie job -oozie http://<oozie-server>:11000/oozie -config job.properties -run -------------------- End Tech Note -------------------- See similar/related response here: https://community.hortonworks.com/questions/22772/oozie-spark-action-giving-key-not-found-spark-home.html#answer-45981
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