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Hadoop provides scalable data storage using the the Hadoop Distributed File System (HDFS) and  and fast parallel data processing on a fault-tolerant cluster of computers. Learn more about about Hadoop.

See See Hadoop and Datameer to  to learn more about Hadoop and how to use it with Datameer.

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General configuration

1. Click the Admin the Admin tab.
2. Click the the Hadoop Cluster tab  tab at the left side. The current settings are shown.
   Image RemovedImage Added 
3. Click Edit to make changes.
4. Click Click Save when  when you are finished making changes.

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1. Click the Admin tab.
2. Click the Hadoop Cluster tab at the left side. The current settings are shown.
3. Click Edit to make changes.
4. Select Hadoop Cluster for the mode.
   

5. Specify the name node and add a private folder path or use impersonation if applicable.
   Whitespaces aren't supported for use in file/folder paths. Avoid Avoid setting up Datameer storage directories (storage root path, temp paths, execution framework specific staging directories, etc.) with a whitespace in the path.

   Note

   Impersonation notes: - There is one-to-one mapping between the Datameer user and the OS user.   - The OS user who is launching the Datameer process must be a sudoer. - The temp folder for the Datameer installation local file system as well as in the Hadoop cluster (for Datameer) should have read/write access. <Datameer_Installation_Folder>/tmp (Local FileSystem) <Datameer_Private_Folder>/temp (Hadoop Cluster and MapR) Learn about Enabling Secure Impersonation with Datameer.

   

6. Specify YARN settings.
   

7. Use the properties text boxes to add Hadoop and custom properties. 
   Enter a name and value to add a property, or delete a name and value pair to delete the property.

   Note

   Within these edit fields, backslash (\) characters are interpreted by Datameer as an escape character rather than a plain text character. In order to produce the actual backslash character, you have to type two backslashes: Code Block language text example.property=example text, a backslash \\ and further text The second backslash is needed as you are effectively editing a Java properties file in these edit fields.

   
   

8. Logging options. Select the severity of messages to be logged. The logging customization field allows to record exactly what is needed.
   
9. Click Save when you are finished making changes.

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Autoconfigure grid mode 

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Warning
This feature is not supported with Cloudera Manager Safety Valve.

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1. Go to Admin tab > Hadoop Cluster.
2. Select Autoconfigure Cluster in the Mode field.
3. In the Hadoop Configuration Directory field, enter the directory where the configuration files for Hadoop are located.
4. Enter the path to the folder where Datameer puts its private information in Hadoop's file system in the Datameer Private Folder field. 
    
   
5. Enter the number of concurrent jobs.
6. Select whether to use secure impersonation. 
7. Edit the Hadoop or custom properties as necessary.
   If the yarn.timeline-service.enabled property is true in the Hadoop conf files, set yarn.timeline-service.enabled=false as a custom property. (This change is not needed as of Datameer v6.1)
    
   
8. Click Save.

To update your Datameer Autoconfig Grid Mode cluster configuration, click Edit on the Hadoop Cluster page and click Save. After saving has been completed, the updated configuration has been applied. New updates to the settings are not shown in the conductor.log but are displayed when clicking again on Edit for Autoconfigure Grid Mode under the Hadoop Properties label.

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1. Click the Admin tab at the top of the page.
2. Click the Hadoop Cluster tab at the left side. The current settings are shown.
3. Click Edit to make changes and choose MapR in the mode list.
   

4. Add the cluster name, the Datameer private folder, and check the boxes if using Simple Impersonation for Datameer to submit jobs and access the HDFS on behalf of Datameer user, and the Max Concurrent jobs. 
    
   There is one-to-one mapping between the Datameer user and the OS user.  
   The OS user who is launching the Datameer process must be a sudoer.
   The temp folder for the Datameer installation local file system as well as in the hadoop cluster (for Datameer) should have read/write access.

   • • <Datameer_Installation_Folder>/tmp (Local FileSystem)
     • <Datameer_Private_Folder>/temp (Hadoop Cluster and MapR)

   Note

   Anchor secure_mapr secure_mapr Connecting to a secure MapR cluster 1) Obtain the MapR ticket for the user who is running the Datameer application. Execute the following command on the shell: Code Block maprlogin password -user <user_who_starts_datameer> 2) Install Datameer and open <Datameer_Home>/etc/das-env.sh and add the following system property to the Java arguments: Code Block -Dmapr.secure.mode=true 3) Start and configure Datameer using MapR Grid Mode. The option to connect using Secure Impersonation is now available. 4) (Optional) If there is a failure in saving the configuration: Code Block Caused by: java.io.IOException: Can't get Master Kerberos principal for use as renewer Add the following custom Hadoop properties under the Hadoop Admin page:  Code Block yarn.resourcemanager.principal=<value> The value for this property can be found in the yarn-site.xml file in your Hadoop cluster configuration. The steps to achieve impersonation are same as for a secured Kerberos cluster.

5. If required, enter properties. Enter a name and value to add a property, or delete a name and value pair to delete that property.
   
6. Logging options. Select the severity of messages to be logged. It is also possible to write custom log settings to record exactly what is needed.
   
7. Click Save when you are finished making changes.

Anchor
HA HA

 Configuring High Availability

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1. Specify the NameService to which the Datameer instance should be working with in HDFS NameNode text box: hdfs://nameservice1

2. Specify the following Hadoop properties in Custom Property field:

   Code Block
   language bash title Custom Properties
   ### HDFS Name Node (NN) High Availability (HA) ### dfs.nameservices=nameservice1 dfs.ha.namenodes.nameservice1=nn1,nn2 dfs.namenode.rpc-address.nameservice1.nn1=<server-address>:8020 dfs.namenode.rpc-address.nameservice1.nn2=<server-address>:8020 dfs.client.failover.proxy.provider.nameservice1=org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider

   If HDFS HA is configured for automatic failover by using Quorum Journal Manager (QJM), you need to add the following additional custom properties:

   Code Block
   ### HDFS HA Autotmatic Failover # By using the Quorum Journal Manager (QJM) dfs.ha.automatic-failover.enabled=true ha.zookeeper.quorum=<zookeepperHost1>.<domain>.<tld>:2181,<zookeepperHostn>.<domain>.<tld>:2181

3. Check the current NameNode (NN) setting within the database:

   Code Block
   mysql -udap -pdap dap -Bse "SELECT uri FROM data" | cut -d"/" -f3 | sort | uniq

   The command above should have only one result, the former <host>.<domain>.<tld>:<port> value configured under Admin tab  tab > Hadoop Cluster >  > Storage Settings >  > HDFS NameNode.
   

4. Update the paths to the new location in the Datameer DB:

   Code Block
   ./bin/update_paths.sh hdfs://<old.namenode>:8020/<root-path> hdfs://nameservice1/<root-path>

5.  Check to ensure the new NameNode has been applied to the database and that the path is correct:

   Code Block
   mysql -udap -pdap dap -Bse "SELECT uri FROM data" | cut -d"/" -f3,4,5 | sort | uni

   The command above has only one result, the virtual NameNode value including the path configured under Admin tab  tab > Hadoop Cluster > Storage Settings > Datameer Private Folder.

Anchor
yarn yarn

YARN

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1. Specify the resource manager with which the Datameer instance should be working in Yarn Resource Manager Address field: yarnRM.

    

     YARN Application Classpath is a comma-separated list of CLASSPATH entries.

   
   

2. Specify the following Hadoop properties in Custom Property field:

   Code Block
   language bash title Custom Properties
   ### Resource Manager (RM) YARN High Availability (HA) ### yarn.resourcemanager.cluster-id=yarnRM yarn.resourcemanager.ha.enabled=true yarn.resourcemanager.ha.rm-ids=rm1,rm2 yarn.resourcemanager.recovery.enabled=true yarn.resourcemanager.store.class=org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore yarn.resourcemanager.zk-address=<server-adress>:2181 ## RM1 ## yarn.resourcemanager.hostname.rm1=<server> yarn.resourcemanager.address.rm1=<server-adress>:8032 yarn.resourcemanager.scheduler.address.rm1=<server-adress>:8030 yarn.resourcemanager.webapp.address.rm1=<server-adress>:8088 yarn.resourcemanager.resource-tracker.address.rm1=<server-adress>:8031 ## RM2 ## yarn.resourcemanager.hostname.rm2=<server> yarn.resourcemanager.address.rm2=<server-adress>:8032 yarn.resourcemanager.scheduler.address.rm2=<server-adress>:8030 yarn.resourcemanager.webapp.address.rm2=<server-adress>:8088 yarn.resourcemanager.resource-tracker.address.rm2=<server-adress>:8031

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Custom properties consist of a name (key) and value pair separated with a '='. These properties are used to configure Hadoop jobs.
For example you can specify the output compression codec for jobs by entering entering mapred.output.compression.codec=org.apache.hadoop.io.compress.DefaultCodec into  into the custom property field.

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There are some additional Datameer specific properties as well. These are:

Custom properties exclusive for Datameer Smart Execution 

Configuring Number of Hadoop Cluster Nodes

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1. Add all available vcores from both head and worker nodes.
2. Divide total number of vcores by the number of nodes in the cluster. This average constitutes the size of a single node. (If the node-based license allows 3 nodes, 3 times the average number of vcores can be used.)

3. Update the YARN scheduler on the Hadoop cluster to the number of specified vcores.

   Code Block
   yarn.scheduler.capacity.<queue_name>.maximum-allocation-vcores=12

4.  Add a a custom Hadoop property in Datameer to  to recognize the number of available vcores.

   For Tez:

   Code Block
   tez.queue.name=<queue_name>

   For Spark:

   Code Block
   spark.yarn.queue=<queue_name>

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Datameer's <datameer-install-path>/tmp folder  folder stores temporary files required for Datameer. 

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• tmp/tez-plugin-jars

If the /tmp folder  folder is consuming too much space and other files are present in the folder, Datameer suggests it is safe to purge files that are older than three days.

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Datameer's Distributed File System cache cache <datameer-install-path>cache/dfscache is  is used for or caching data link and import job sample records as well as log and jdbc files.

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 <cache
        name="dfsCache"
        maxEntriesLocalHeap="10000"
        timeToIdleSeconds="60"
        timeToLiveSeconds="60"
        eternal="false"
        diskPersistent="false"
        overflowToDisk="false"
    >

This This dfscache grows  grows in size as the number of sample records from import jobs and data links is increased. Follow the troubleshooting guide if the Datameer filesystem is full due to excessive reduce-part-#### files generated in in dfsCache folder folder.

The The dfscache folder  folder and its contents can be moved to a different location if needed by following the guide in our knowledge base.

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Define the time zone that should be used for displaying the date in the UI and for parsing date strings that do not specify a timezone. Use Use default as  as the value to use the local server's time zone.

In In conf/default.properties you  you can change the value designating the time zone:

If the time zone is changed on the machine where Datameer is running, Datameer must be restarted to show the new default time zone configuration.

Examples