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1794 | 07-31-2017 03:02 PM |
07-27-2016
02:22 AM
If you don't use LDAP then linux accounts you use must be present on each node in the cluster and must have similar permissions (you can get away with this requirement if you are using Ranger and disable posix permissions using dfs.permissions.enabled = false). But without LDAP you need to have linux accounts on all machines.
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07-26-2016
09:08 PM
1 Kudo
@Vijaya Narayana Reddy Bhoomi Reddy Please see my answers inline below: Q: On which node should the distcp job be running?
My Understanding: For DR purposes, distcp job should ideally be run on one of the machines on the DR cluster as it has unused YARN capacity. The requirement for the node is to have hadoop client libraries available for it to run distcp. For example, assume the node as dr-host1@HADOOP.COM -> Running the job on destination is fine. Just remember that distcp builds a "copylist" for files to copy. For large cluster with thousands of directories and subdirectories this can be an expensive operation specially when run from remote cluster. It's totally okay. you just need to be aware of it.
Which user should the distcp job be running as? Is it someone with hdfs privileges (For example, DR-hdfs@HADOOP.COM) or any other user for example, a new user created for this purpose -replication-user (replication-user@HADOOP.COM) First, don't use hdfs. Now, the Kerberos principal you want to use must need to have read permissions on the files you will copy. If that's everything, then give appropriate permissions. If you are going to use two different principals then you need to provide the destination principal to be a proxy user aka impersonation on your source cluster. Add the following to your source cluster core-site.xml and restart source cluster. Use the new core-site.xml to connect to source cluster. property>
<name>hadoop.proxyuser.hdfsdestuser.hosts</name>
<value><destination host or wherever this user is connecting from></value>
</property>
<property>
<name>hadoop.proxyuser.hdfsdestuser.groups</name>
<value><all the groups which users belong to. this user can impersonate></value> <!--might want to start with * and then restrict>
</property>
This should enable your destination cluster to read source data. Also remember that if these users are in different kerberos realm then you need to setup cross realm trust. Check this link. If its hdfs user (DR-hdfs@HADOOP.COM), how to ensure the user is allowed access on the PRIMARY cluster? (probably through auth_to_local settings like below?) RULE: [1:$1@$0] (.*-hdfs@HADOOP.COM) s/.*/PRIMARY-hdfs/
-> Check previous answer. don't use hdfs user. auth to local may or may not be required. Depends on what access you give the destination user.
If it’s a non-standard user like replication-user, what are the considerations to be taken? Is it required / recommended to have the same user replication-user on both the clusters and have auth_to_local setting similar to above -> Check above again. If it's same user, then it will make things easy. for users that are different, changing core-site.xml to add proxy user isn't very complicated either.
As the clusters are secured by Kerberos and the principals are going to be different on the clusters, how to make this work? The replication-user's keytab file is going to be different on PRIMARY and DR cluster. What is the best approach to handle this? -> Check my answer to your question number 2.
What's the impact on the solution if the both the clusters are part of separate Kerberos realms like PRIMARY.HADOOP.COM andDR.HADOOP.COM? -> Check this link. (Already referred earlier)
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07-26-2016
03:23 PM
Which version of Hadoop are you using? there was an issue that was in fixed in version 2.6 which might be impacting you. https://issues.apache.org/jira/browse/YARN-2723 and what's the error are you getting? Can you please share that?
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07-26-2016
01:04 AM
1 Kudo
@Obaid Salikeen You can have a nifi cluster and you will not lose data. When a node goes down, NiFi cluster manager will route the data to another node. However, queued data for the failed node will still be queued for failed node. Only that data must be manually sent over to the live node in the cluster or just bring the failed node up. Any new data, will automatically be routed to other nodes in the cluster by NiFi Cluster Manager (NCM). There is no manual intervention required. Queued data is usually very small, around 1 second of data or even less. Not only can you run NiFi in a cluster to have redundancy but you can even have different NiFi clusters across different data centers, so in case of a data center failure, you are still able to ingest data. That's why the two links I shared earlier are very important as they describe the architecture you will need to implement NiFi cluster in a simple data center (one cluster scenario) as well as multiple clusters in multiple data centers.
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07-25-2016
04:41 PM
@Christopher Amatulli
Oh. That's because of how NiFi and Kafka and storm are independent of Hadoop ecosystem. They work regardless of whether data is being written to Hadoop or any other persistence layer within your organization. This enables Hortonworks to help customers who are not using Hadoop but still would like to have NiFi and Kafka to ingest/collect data and deliver to systems other than Hadoop. We have a number of customers who are using HDF and not using HDP, so keeping them separate enables us to help such customers.
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07-25-2016
03:33 PM
1 Kudo
HDF is Apache NiFi, Apache Storm and Apache Kafka where as HDP includes other Hadoop component with only overlap with Apache Storm. https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.3.2-Win/bk_HDP_Install_Win/content/iug_hdp_components.html Can you please elaborate on "options in HDP and HDF can't be same"? The reason you need different nodes is because of the requirement of the underlying differences in technologies and the use cases they serve.
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07-25-2016
03:21 PM
Can you please check your classpath? run "hadoop dfsadmin" just by itself. I think you should still run into same issue. Then you need check your classpath and compare with the nodes where this command runs successfully. Can you please try that and share with us what you see?
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07-25-2016
02:27 PM
1 Kudo
@Obaid Salikeen To answer your question number 1, the answer is you wont have data loss because for nifi you do use RAID 10 so one disk failure should not cause a data loss. To answer your question your number 2, NiFi does not replicate data like Kafka. If you lose a node, then flow can be directed to a available node however, flowfile queued for the failed node will either wait until the node comes up or the flowfile is manually is sent to another working node. Here is how to setup clustering https://nifi.apache.org/docs/nifi-docs/html/administration-guide.html#clustering Also, if you read the links I shared above, they will clear any confusion you may have.
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07-25-2016
02:15 PM
2 Kudos
@kishore sanchina What is the storage utilization on these disks? See how much is available and then check yarn.nodemanager.disk-health-checker.max-disk-utilization-per-disk-percentage to make sure the available disk space is more than this threshold.
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07-25-2016
05:49 AM
@Obaid Salikeen Check this article as well as its part 2. https://community.hortonworks.com/articles/8607/how-to-create-nifi-fault-tolerance-using-multiple.html and https://community.hortonworks.com/articles/8631/how-to-create-nifi-fault-tolerance-using-multiple-1.html
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