Distribution-specific Notes

Connecting to a CDH 5.13 Quickstart VM

Start and configure the Quickstart VM

1. Download the Cloudera Quickstart VM (version 5.13) from theCloudera website．

2. Import the OVA packaged VM to your virtualization environment (Virtualbox and VMware are covered in this guide).

3. It is strongly recommended to upgrade to Java 1.8 on the single-node cluster provided by the VM. Otherwise, the execution ofSingle Process PushdownandApply Modeloperators will fail.

   You can take the following steps only if no clusters or Cloudera management services have been started yet. For the full upgrading process, readCloudera’s guide．

   Upgrading to Java 1.8:

   • Start the VM.
   • Download and unzip JDK 1.8 – preferrablyjdk1.8.0_60– to/usr/java/jdk1.8.0_60．

   • Add the following configuration line to/etc/default/cloudera-scm-server:

     export JAVA_HOME=/usr/java/jdk1.8.0_60

   • LaunchCloudera Express(or Enterprise trial version).

   • Open a web browser, and log in toCloudera Manager(quickstart.cloudera:7180) usingcloudera/clouderaas credentials. Navigate toHosts/quickstart.cloudera/Configuration．InJava Home Directoryfield, enter

     /usr/java/jdk1.8.0_60

   • On the home page ofCloudera Manager, (re)start theCloudera QuickStartcluster andCloudera Management Serviceas well.

4. If you are using Virtualbox, make sure that the VM is shut down, and set the type of the primary network adapter fromNATtoHost-only．The VM will work only with this setting in a Virtualbox environment.

5. Start the VM and wait for the boot to complete. A browser with some basic information will appear.

6. Edit yourlocalhostsfile (on your host operating system, not inside the VM) and add the following line (replacewith the IP address of the VM):

   quickstart.cloudera

Setup the connection in RapidMiner Studio

1. Click onNew Connectionbutton and chooseAdd Connection Manually

2. SetHadoop usernametohive．(As an alternative, you can setbothHadoop usernameandUsernameonHivetab to your own user.)

3. Addquickstart.clouderaasNameNode Address

4. Addquickstart.clouderaasResource Manager Address

5. Addquickstart.clouderaasHive Server Address

6. Select Cloudera Hadoop (CDH5) asHadoop version

7. Add the following entries to theAdvanced Hadoop Parameters:

   Key	Value
   dfs.client.use.datanode.hostname	true

   (This parameter is not required when using theImport Hadoop Configuration Filesoption):

   Key	Value
   mapreduce.map.java.opts	-Xmx256m

8. Select the appropriateSpark Version(this should beSpark 1.6if you want use the VM’s built-in Spark assembly jar) and set theAssembly Jar Locationto the following value:

   local:///usr/lib/spark/lib/spark-assembly.jar

Connecting to a 3.0.1+ Sandbox VM

Start and configure the Sandbox VM

1. Download the Hortonworks Sandbox VM for VirtualBox (version 3.0.1+) from theHortonworks website．

2. Import the OVA packaged VM to your virtualization environment (Virtualbox is covered in this guide).

3. Start the VM. After powering it on, you have to select the first option from the boot menu, then wait for the boot to complete.

4. Log in to the VM. You can do this by switching to the login console (Alt+F5), or even better via SSH on localhost port2122．It is important to note that there are 2 exposed SSH ports on the VM, one belongs to the VM itself (2122), while the other (2222) belongs to a Docker container running inside the VM. The username isroot, the password ishadoopfor both.

5. Edit the/sandbox/proxy/generate-proxy-deploy-script.shby include the following ports in thetcpPortsHDParray 8025, 8030, 8050, 10020, 50010.
   1. vi /sandbox/proxy/generate-proxy-deploy-script.sh

   2. FindtcpPortsHDPvariable, leaving the other values in place, add to the hashtable assignment:

      [8025]=8025 [8030]=8030 [8050]=8050 [10020]=10020 [50010]=50010

6. Run the editedgenerate-proxy-deploy-script.shvia/sandbox/proxy/generate-proxy-deploy-script.sh
   • This will re-create the/sandbox/proxy/proxy-deploy.shscript along with config files in/sandbox/proxy/conf.dand/sandbox/proxy/conf.stream.d, thus exposing the additional ports added to thetcpPortsHDPhashtable in previous step.
7. Run the/sandbox/proxy/proxy-deploy.shscript via/sandbox/proxy/proxy-deploy.sh
   • Running thedocker pscommand, will show an instance namedsandbox-proxyand the ports it has exposed. The inserted values to thetcpPortsHDPhashtable should be shown in the output, looking like0.0.0.0:10020->10020/tcp．

8. These changes only made sure that the referenced ports of the Docker container are accessible on the respective ports of the VM. Since the network adapter of the VM is attached to NAT, these ports are not accessible from your local machine. To make them available you have to add the port forwarding rules listed below to the VM. In VirtualBox you can find these settings underMachine/Settings/Network/Adapter 1/Advanced/Port Forwarding．

   Name	Protocol	Host Ip	Host Port	Guest Ip	Guest Port
   resourcetracker	TCP	127.0.0.1	8025		8025
   resourcescheduler	TCP	127.0.0.1	8030		8030
   resoucemanager	TCP	127.0.0.1	8050		8050
   jobhistory	TCP	127.0.0.1	10020		10020
   datanode	TCP	127.0.0.1	50010		50010

9. Edit yourlocalhostsfile (on your host operating system, not inside the VM), addsandbox.hortonworks.comandsandbox-hdp.hortonworks.comto your localhost entry. At the end it should look something like this:

   127.0.0.1 localhost sandbox.hortonworks.com sandbox-hdp.hortonworks.com

10. Reset Ambari access. Use an SSH client to login tolocalhost as root, this time using port2222!(For example, on OS X or Linux, use the commandssh root@localhost -p 2222, password:hadoop)

    • (At first login you have to set a new root password, do it and remember it.)
    • Runambari-admin-password-resetas root user.
    • Provide a new admin password for Ambari.
    • Runambari-agent restart．

11. Open the Ambari website:http://sandbox.hortonworks.com:8080

    • Login withadminand the password you chose in the previous step.
    • Navigate to theYARN/Configs/Memoryconfiguration page.
    • Edit theMemory NodeSetting to at least 7 GB and click Override.
      • User will be prompted to create a new “YARN Configuration Group”, enter a new name.
      • On the “Save Configuration Group” dialog, click theManage Hostsbutton.
      • On the “Manage YARN Configuration Groups page” take the node in the “Default” group and add the node into the group created in the “YARN Configuration Group” name step.
      • “Warning” Dialog will open requesting adding notes click theSavebutton.
      • “Dependent Configurations” dialog will open with Ambari providing recommendations to modify some related properties automatically. If so, unticktez.runtime.io.sort.mbto keep its original value. Click theOkbutton.
        • Ambari may open a “Configurations” page suggesting stuff. Review accordingly, but this is out of the scope of this document, so just clickProceed Anyway．
    • Navigate to theHive/Configs/Advancedconfiguration page.

    • In theCustom hiveserver2-sitesection. Thehive.security.authorization.sqlstd.confwhitelist.appendneeds to be added via theAdd Property…and be set to the following (it must not contain whitespaces):

      radoop\.operation\.id|mapred\.job\.name|hive\.warehouse\.subdir\.inherit\.perms|hive\.exec\.max\.dynamic\.partitions|hive\.exec\.max\.dynamic\.partitions\.pernode|spark\.app\.name|hive\.remove\.orderby\.in\.subquery

    • Save the configuration and restart all affected services. More details onhive.security.authorization.sqlstd.confwhitelist.appendcan be found inHadoop Security/Configuring Apache Hive SQL Standard-based authorizationsection.

Setup the connection in RapidMiner Studio

1. Click onNew Connectionbutton and chooseImport from Cluster Manageroption to create the connection directly from the conifguration retrieved from Ambari.

2. On theImport Connection from Cluster Managerdialog enter
   • Cluster Manager URL:http://sandbox-hdp.hortonworks.com:8080
   • Username:admin
   • Password: password used in Reset Amabari step.

3. ClickImport Configuration

4. Hadoop Configuration Importdialog will open up
   • If successful clickNextbutton andConnection Settingsdialog will open.
   • If failed clickBackbutton and review above steps and logs to solve issue(s).

5. On theConnection SettingsDialog, which opens whenNextbutton is clicked from step above.

6. Connection Namecan stay defaulted or be changed by user.

7. Globaltab
   • Hadoop Versionshould beHortonworks HDP 3.x
   • SetHadoop usernametohadoop．
8. Hadooptab
   • NameNode Addressshould besandbox-hdp.hortonworks.com
   • NameNode Portshould be8020
   • Resource Manager Addressshould besandbox-hdp.hortonworks.com
   • Resource Manager Portshould be8050
   • JobHistory Server Addressshould besandbox-hdp.hortonworks.com
   • JobHistory Server Portshould be10020

   • Advanced Hadoop Parametersadd the following parameters:

     Key	Value
     dfs.client.use.datanode.hostname	true

     (This parameter is not required when using theImport Hadoop Configuration Filesoption):

     Key	Value
     mapreduce.map.java.opts	-Xmx256m

9. Sparktab
   • Spark VersionselectSpark 2.3 (HDP)
   • CheckUse default Spark path
10. Hivetab
    • Hive Versionshould beHiveServer3 (Hive 3 or newer)
    • Hive High Availabilityshould be checked
    • ZooKeeper Quorumshould besandbox-hdp.hortonworks.com:2181
    • ZooKeeper Namespaceshould behiverserver2
    • Database Nameshould bedefault
    • JDBC URL Postfixshould be empty
    • Usernameshould behive
    • Passwordshould be empty
    • UDFs are installed manuallyandUse custom database for UDFsare both unchecked
    • Hive on Spark/Tez container reuseshould be checked

11. ClickOKbutton, theConnection Settingsdialog will close

12. User can test the connection created above onnManage Radoop Connectionspage select the connection created and clicking theQuick TestandFull Test…buttons.

It is highly recommended to useNew Connection/Import from Cluster Manageroption to create the connection directly from the configuration retrieved from Cloudera Manager. If you do not have a Cloudera Manager account that has access to the configuration, an administrator should be able toDownload Client Configuration．Using the client configuration files, chooseNew Connection/Import Hadoop Configuration Filesto create the connection from those files.

If security is enabled on the cluster, make sure you checkConfiguring Apache Sentry authorizationsection of theHadoop Security一章。

Configuring Spark

If you are using Spark 1.6 version you may need to selectSpark 1.6 (CDH)for more recent CDH 5.x Cloudera Hadoop releases andSpark 1.6for older CDH 5.x releases. Select any of them and then run theSpark job test(enable only this test inFull Test…/Customize…) that automatically detects the proper version for you. Please choose the setting that this test recommends.

Using any other Spark version should be straightforward.

The following describes setup for HDP 2.2.6, 2.3.0, 2.3.2, 2.3.4, 2.4.0, 2.5.0, 2.6.0, 3.0 and 3.1. Setup for other HDP versions should be similar.

Configuring the cluster

If there are restrictions on Hive commands on your cluster (for example,SQL Standard Based Hive Authorizationis enabled on it), then the change of certain properties through HiveServer2 must be explicitly enabled. This is required if you get the following error message when running a Full Test in RapidMiner Radoop:Cannot modify radoop.operation.id at runtime．In this case a property must be added on the Ambari interface to resolve this issue.

• Login to the Ambari interface.
• Navigate to theHive/Configs/Advancedconfiguration page
• Add thehive.security.authorization.sqlstd.confwhitelist.appendsetting as a new property to bothCustom hive-siteandCustom hiveserver2-site．The value should the following (it must contain no whitespaces):radoop\.operation\.id|mapred\.job\.name|hive\.warehouse\.subdir\.inherit\.perms|hive\.exec\.max\.dynamic\.partitions|hive\.exec\.max\.dynamic\.partitions\.pernode|spark\.app\.name

• Save the configuration and restart the proposed services.

For a more detailed explanation, see theHadoop securitysection.

To enable Spark operators in RapidMiner Radoop, make the following changes in theConnection Settingsdialog:

1. Select the appropriateSpark Versionoption in theSpark Settings．If Spark is installed with Ambari, theSpark Versiondepends on the cluster’s HDP version.

   HDP version	Spark assembly JAR location
   3.1.x	Spark 2.3 (HDP)
   3.0.x	Spark 2.3 (HDP)
   2.6.x	Spark 1.6 or Spark 2.1 / Spark 2.2
   2.5.x	Spark 1.6 or Spark 2.0
   2.4.x	Spark 1.6
   2.3.4	Spark 1.5
   2.3.2	Spark 1.4 or below
   2.3.0	Spark 1.4 or below
   2.2.6	Spark 1.4 or below

2. Set theAssembly Jar Location/Spark Archive pathto point to the Spark location on your cluster. The following table contains the default local locations depending on your HDP version. Refer to your Hadoop administrator if the specified path does not seem to work.

   HDP version	Spark 1.x assembly JAR location	Spark 2.x archive path
   3.1.x		local:///usr/hdp/current/spark2-client/jars/
   3.0.x		local:///usr/hdp/current/spark2-client/jars/
   2.6.x	local:///usr/hdp/current/spark-client/lib/spark-hdp-assembly.jar	local:///usr/hdp/current/spark2-client/jars/
   2.5.0	local:///usr/hdp/current/spark-client/lib/spark-hdp-assembly.jar
   2.4.2	local:///usr/hdp/current/spark-client/lib/spark-assembly.jar
   2.4.0	local:///usr/hdp/current/spark-client/lib/spark-assembly-1.6.0.2.4.0.0-169-hadoop2.7.1.2.4.0.0-169.jar
   2.3.4	local:///usr/hdp/current/spark-client/lib/spark-assembly-1.5.2.2.3.4.0-3485-hadoop2.7.1.2.3.4.0-3485.jar
   2.3.2	local:///usr/hdp/current/spark-client/lib/spark-assembly-1.4.1.2.3.2.0-2950-hadoop2.7.1.2.3.2.0-2950.jar
   2.3.0	local:///usr/hdp/current/spark-client/lib/spark-assembly-1.3.1.2.3.0.0-2557-hadoop2.7.1.2.3.0.0-2557.jar
   2.2.6	local:///usr/hdp/current/spark-client/lib/spark-assembly-1.2.1.2.2.6.0-2800-hadoop2.6.0.2.2.6.0-2800.jar

Notes on security

If you receive a permission error during connection Full Test, verify that:

• The/user/directory exists on the HDFS and is owned by . (If the Hadoop username setting is empty, the client OS username is used.)
• The has write privileges on/user/historydirectory on the HDFS.

SQL Standard Based Hive Authorization may require that the user running HiveServer2 owns the files and directories loaded into Hive. This can disrupt the normal operation of RapidMiner Radoop. In case of a permission error, consult your Hadoop administrator.

Connecting to an Azure HDInsight 3.6 cluster using Radoop Proxy

As of this writing RapidMiner Radoop supports 3.5 and 3.6 versions of Azure HDInsight, a cloud-based Hadoop service that is built upon Hortonworks Data Platform (HDP) distribution. If RapidMiner Radoop does not run inside the Azure network, there are a couple of options for the networking setup. A solution likeAzure ExpressRouteor a VPN can simplify the setup. However, if those options are not available, the HDInsight clusters can be accessed using Radoop Proxy, which coordinates all the communication between RapidMiner Studio and the cluster resources. Since this setup is the most complex, this guides assumes this scenario, feel free to skip steps that are not required because of an easier networking setup.

For a proper networking setup, a RapidMiner Server instance (withRadoop Proxyenabled) should be installed on an additional machine that is located in the same virtual network as the cluster nodes. The following guide provides the necessary steps for establishing a proxied connection to an HDInsight cluster.

Starting an HDInsight cluster

If you already have an HDInsight cluster running in the Azure network, skip these steps entirely.

1. Create a newVirtual networkfor all the network resources that will be created during cluster setup. The defaultAddress spaceandSubnet address rangemay be suitable for this purpose. Use the sameResource groupfor all resources that are created during the whole cluster setup procedure.

2. Use theCustom (size, settings, apps)option instead ofQuick createfor creating the cluster. ChooseSparkcluster type withLinuxoperating system, and the latest Spark version supported by Radoop, which isSpark 2.2.0 (HDI 3.6)as of this writing. Fill all the required login credential fields. Select the previously definedResource group．

   

3. Choose thePrimary storage typeof the cluster. You may specify additional storage accounts as well.

   • Azure Storage: Provide a new or already existingStorage accountand aDefault containername. You may connect to as many Azure Storage accounts as needed.
   • Data Lake Store: Provide aData Lake Store account．Make sure that the root path exists and the associated Service principal has adequate privileges for accessing the chosen Data Lake Store and path. Please note that a Service principal can be re-used for other cluster setups as well. For this purpose, it is recommended to save theCertificatefile and theCertificate passwordfor future reference. Once a Service principal is chosen, the access rights for any Data Lake Stores can be configured via this single Service principal object.

4. Configure theCluster sizeof your choice.

5. OnAdvanced settingstab, choose the previously createdVirtual networkandSubnet．

6. 通过向导的所有步骤后,create the cluster. After it has started, please find the private IPs and private domain names of the master nodes. You will need to copy these to your local machine. This step is required because some domain name resolutions need to take place on the client (RapidMiner Studio) side. The easiest way to do this is by copying it from one of the cluster nodes. Navigate to the dashboard of your HDInsight cluster, and select theSSH + Cluster loginoption. Choose any item from theHostnameselector. On Linux and Mac systems you can use the ssh command appearing below the selector. On Windows systems you will have to extract the hostname and the username from the command, and usePuTTY连接到主机。是你的密码u provided in step 2. Once you are connected, view the contents of the /etc/hosts file of the remote host, for example by issuing the following command:cat /etc/hosts．Copy all the entries with long, generated hostnames. Paste them into thehostsfile of yourlocal machine, which is available at the following location:

   • For Windows systems: Windows\system32\drivers\etc\hosts
   • For Linux and Mac systems: /etc/hosts

Starting RapidMiner Server and Radoop Proxy

1. Create a new RapidMiner Server virtual machine in Azure. For this you will need to select the“Create a resource”option and search the Marketplace for RapidMiner Server. Select theBYOLversion which best matches your Studio version. PressCreateand start configuring the virtual machine. Provide the Basic settings according to your taste, but make sure that you use the previously configuredResource groupand the sameLocationas for your cluster. ClickOk,然后选择至少一个虚拟机大小10GB of RAM. Configure optional features. It is essential that the sameVirtual networkandSubnetare selected in theNetworksettings as the ones used for the cluster. All other settings may remain unchanged. Check the summary, then clickCreate．

2. Once the VM is started, you still need to wait a few minutes for RapidMiner Server to start. The easiest way to validate this is to open (Public IP address of the VM):8080 in your browser. Once that page loads, you can log in withadminusername and the name of your VM in Azure as password. You will immediately be asked for a valid license key. A free license is perfectly fine for this purpose. If your license is accepted you can close this window, you will not need it anymore.

Setting up the connection in RapidMiner Studio

First, create a Radoop Proxy Connection for the newly installed Radoop Proxy (describedherein Step 1). The needed properties are:

Field	Value
Radoop Proxy server host	Provide the IP address of the MySQL server instance.
Radoop Proxy server port	The value ofradoop_proxy_portin the used RapidMiner Server install configuration XML (1081by default).
RapidMiner Server username	admin(by default)
RapidMiner Server password	name of Azure proxy VM(by default)
Use SSL	false(by default)

Forsetting up a new Radoop connectionto an Azure HDInsight 3.6 cluster, we strongly recommend to chooseImport from Cluster Manageroption, as it offers by far the easiest way to make the connection work correctly.Thissection describes the Cluster Manager import process. TheCluster Manager URLshould be the base URL of the Ambari interface web page (e.g.https://radoopcluster.azurehdinsight.net). You can easily access it by clickingAmbari Viewson the cluster dashboard.

进口连接后,大部分required settings are filled automatically. In most cases, only the following properties have to be provided manually:

Field	Value
Advanced Hadoop Parameters	Disable the following properties:io.compression.codec.lzo.classandio.compression.codecs
Hive Server Address	This is only needed, if you do not use the ZooKeeper service discovery(Hive High Availabilityis unchecked). Can be found on Ambari interface (Hive / HiveServer2). In most cases, it is the same as theNameNode address．
Radoop Proxy Connection	The previously created Radoop Proxy Connection should be chosen.
Spark Version	Select the version matching the Spark installation on the cluster, which isSpark 2.2if you followed above steps for HDInsight install.
Spark Archive (or libs) path	ForSpark 2.2(with HDInsight 3.6), the default value is (local:///usr/hdp/current/spark2-client/jars). Unless using a different Spark version you are fine with leavingUse default Spark pathcheckbox selected.
Advanced Spark Parameter	Createspark.yarn.appMasterEnv.PYSPARK_PYTHONproperty with a value of/usr/bin/anaconda/bin/python．

You will also need to configure your storage credentials, which is described by theStorage credentials setupsection. If you want to connect to a premium cluster you will need to follow the steps in theConnecting to a Premium clustersection. Once you completed these steps, you can clickOKon theConnection Settingsdialog, and save your connection.

Storage credentials setup

An HDInsight cluster can have more storage instances attached, which may even have different storage types (Azure StorageandData Lake Store). For accessing them, the related credentials must be provided inAdvanced Hadoop Parameterstable. The following sections clarify the type of credentials needed, and how they can be acquired.

Connecting to a Premium cluster (having Kerberos enabled)

If you have set up or have a Premium HDInsight cluster (subscription required), some additional connection settings are required for Kerberos-based authentication.

• Configuring Kerberos authenticationsection describes general Kerberos-related settings.
• As for all Hortonworks distribution based clusters, you also have to apply a Hive setting (hive.security.authorization.sqlstd.confwhitelist.append) described inthis section．Please note that a Hive service restart will be needed.
• Westronglyadvise to useImport from Cluster Manageroption for creating a Radoop connection to the Kerberized cluster. The import process covers some necessary changes inAdvanced Hadoop Parametersthat are required for the connection to work as expected.

从另一个网络连接到EMR

RapidMiner Radoop supports connecting to an EMR cluster using SOCKS proxy, VPN orRadoop Proxy．The following steps will guide you, how to start and configure an EMR cluster to use with RapidMiner Radoop and how to setup the networking and the Radoop connection to connect to the cluster. The steps required for a VPN setup can be found in a separated collapse boxbelow．

Starting an EMR cluster

Skip these steps if you already have an EMR cluster running that has Java 8.

1. Use the advanced options for creating the cluster. Select EMR release4.4 or newer．Make sure thatHadoop,HiveandSparkare selected for installation.

2. Add the following configuration in order to configure Java 8:

   [ { "Classification": "hadoop-env", "Configurations": [ { "Classification": "export", "Configurations": [], "Properties": { "JAVA_HOME": "/usr/lib/jvm/java-1.8.0" } } ], "Properties": {} }, { "Classification": "spark-env", "Configurations": [ { "Classification": "export", "Configurations": [], "Properties": { "JAVA_HOME": "/usr/lib/jvm/java-1.8.0" } } ], "Properties": {} } ]

3. 通过向导的所有步骤后,create the cluster. If it has been started, the private IPs and private domain names of the EC2 instances should be available.

Configure the cluster

Using an SSH access, configure the cluster as follows. Log into the master node using thehadoopusername and private key set during the launch. Execute the following commands to create the necessary staging directories:

hadoop fs -mkdir -p /tmp/hadoop-yarn/staging/history hadoop fs -chmod -R 777 /tmp/hadoop-yarn hadoop fs -mkdir /user hadoop fs -chmod 777 /user

Setup networking

If you can install RapidMiner Server into an edge node on the EMR cluster, we strongly recommend to useRadoop Proxy．As a second option, you can use SOCKS proxy to connect to your EMR cluster. See theNetworking Setupsection for information on starting a SOCKS proxy and an SSH tunnel. Please open the SSH tunnel and the SOCKS proxy. The third option is to use aVPN connection．Please initiate the VPN connection to the cluster.

Setup the connection in RapidMiner Studio

When using the SOCKS proxy, the standard SOCKS proxy connection (described inNetworking Setup) should be used with the following settings:

Property	Value
Hadoop version	Amazon Elastic MapReduce (EMR) 4.4+
NameNode Address	(e.g.10.1.2.3.)
Resource Manager Address
Hive Server Address	localhost
Hive port	1235
Advanced Hadoop parameters	Key:hadoop.rpc.socket.factory.class.default Value:org.apache.hadoop.net.SocksSocketFactory Enabled: yes
Advanced Hadoop parameters	Key:hadoop.socks.server Value:localhost:1234 Enabled: yes
Advanced Hadoop parameters (to avoid bugHDFS-3068when using a proxy)	Key:dfs.client.use.legacy.blockreader Value:true Enabled: yes

To use Spark operators in RapidMiner Radoop, enable them by selecting the appropriateSpark Versionoption in theSpark Settings．Then provide the path to the Spark libraries:

• If you have added Spark 1.x on the cluster creation page, upload the Spark assembly jar to HDFS:

  hadoop fs -mkdir -p /user/spark hadoop fs -put /usr/lib/spark/lib/spark-assembly.jar /user/spark

  Sethdfs:///user/spark/spark-assembly.jarasAssembly Jar Location．

• For Spark 2.x versions, the best practice is to upload the compressed Spark jar files to HDFS. This can easily be done by issuing the following commands:

  cd /usr/lib/spark/jars zip -r /tmp/spark.zip . hadoop fs -mkdir -p /user/spark hadoop fs -put /tmp/spark.zip /user/spark

  Sethdfs:///user/spark/spark.zipasSpark Archive path．

Radoop supports MapR 5.x/6.x for both RapidMiner Studio and RapidMiner Server. Note that MapR support on Serverrequires RapidMiner Server version 8.1 or later．

Setting up cluster machines

1. 确保DNS和梦rse DNS resolution works on all of the cluster machines even if it is a single node cluster. To achieve such you might as well setup a DNS service or manually edit the/etc/hostsfile on each node.

Setting up client machine

1. Studio and Server Job Agents must be running on host machines with MapR 5.x or 6.x client installed and connected.

   1. Depending on the MapR cluster version user will need to follow instructions for installing eitherMapR 5.x Clientor theMapR 6.x Client．Make sure to pick the version corresponding to the cluster.
   2. Set the following system environment variables properly:
      • MAPR_HOME- this is the path to MapR client, on a default installation it would be either/opt/maprorC:\opt\mapr
      • HADOOP_HOME- this is the path to MapR Hadoop files on the client, typically will be${MAPR_HOME}/hadoop/hadoop-x.y.z(withx.y.zbeing the version number of hadoop), this is required on Windows for running Radoop, if not set properly user could see error messages ofERROR util.Shell: Failed to locate winutils binary in the hadoop binary pathwhen establishing connections to the MapR cluster
      • MAPR_SUBNETS- system environment variable contains the internal subnet of the MapR cluster. More info onMAPR_SUBNETSfoundhere
      • Add${HADOOP_HOME}\binto the system-wide environment variablePATH, if not set properly user could see error messages ofjava.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Zwhen establishing connections to the MapR cluster.
   3. Double check the content of your${MAPR_HOME}/conf/mapr-cluster.conffile. Check that all addresses listed are reachable from the client machine.
   4. User setup for insecure clusters
      • On OS X or Linux in secure configurations make sure that the user is available on all of the cluster nodes. It can be done on cluster side by creating a new user with an UID which matches the client side. This can be achieved by using theadduserunix command.
      • On Windows, edit${MAPR_HOME}/hadoop/hadoop-x.y.z/etc/hadoop/core-site.xmlto configure the UID, GID and user name of the cluster user that will be used to access the cluster, seeConfiguring MapR Client User on Windows．This is required for both the MapR 5.x and MapR 6.x client.
   5. 确认客户端机器连接,用户hould be able to perform the following commands from the command line and get back a valid result. Both theyarnandhadoopcommands should be accesible, because of the adding of$HADOOP_HOME/binto the system-wide environmentPATH．SeeMapR Your First Hadoop Jobfor details. (If the cluster is secure acquiring a MapR ticket viamaprloginmay be required before running the commands.)
      • hadoop fs -ls /should return a file list
      • yarn jar ${HADOOP_HOME}/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.0-mapr-1803.jar pi 10 1000将运行hadoop mapreduce的提供的例子吗job on the cluster calculating Pi. For the result please check application logs in the Job History Server.

2. If your HiveServer2 instance is secured by MapR Security, you need to do additional setup for Hive access. If it is not, this step can be skipped. Copy the jars according to theMapR JDBC Connections docsto a common directory on the host machine. These jars should be available to be copied by from the MapR 5.x/6.x cluster machine with Hive installed typically in the${MAPR_HOME}/hive/hive-/libdirectory. See an example list below. Note that the files may differ on your environment.

Radoop Connection Setup

Click onNew Connectionbutton and chooseAdd Connection Manually

Global tab

1. Choose eitherMapR 5.xorMapR 6.xfor theHadoop version．

   • Please verify theMapR Client HomeandMapR Subnetsas they are displayed on the dialog as taken from the System environment.

2. Select or Enter the MapR Cluster name in theMapR cluster．This pull down is developed from the${MAPR_HOME}/conf/mapr-clusters.conffile. If cluster name is not listed here chances are that MapR client wasn’t properly setup in the Setting up client machine section.

3. If the Hadoop instance is secured by MapR Security selectEnable MapR Security．

Hadoop tab

1. EnterResource Manager AddressandJobHistory Server Addressfields.

2. Review default port settings inJobHistory Server Portfield.

Spark tab

1. Select theSpark Versionaccording to the installed Spark version on the cluster. If none is installed selectNone．For more information seeInstall Spark on Yarn in MapR documentationfor cluster installation instructions.

2. You may eitherUse default Spark pathor by unchecking it provide the actual path by editing theSpark Archive (or libs) pathtextfield.

   • Based on the selectedHadoop version,Spark Archive (or libs) pathfield is defaulted to:
     • MapR 5.x –local:///opt/mapr/spark/spark-2.1.0/jars
     • MapR 6.x –local:///opt/mapr/spark/spark-2.2.0/jars
   • The path must be accessible on the cluster and contain the spark artifacts.

3. ProvideSpark Resource Allocation Policyaccording to your Spark setup on the cluster.

   • Spark Resource Allocation Policyis defaulted toDynamic Resource Allocation．If the cluster is not configured for this, Spark test will time out and log entries ofInvalidAuxServiceException: The auxService:spark_shuffle does not existwill appear in the logs for the corresponding Spark job. In this case, either change cluster to enableDynamic Resource AllocationseeMapR - Enabling Dynamic Allocation in Apache Sparkor change to differentResource Allocation Policyon the Radoop connection (e.g. toStatic, Default Configuration).

4. On Windows, add the followingAdvanced Spark Parametersentry. Here we assume that the$MAPR_HOMEon the cluster is/opt/mapr, please change the value if this is not the case.

   Key	Value
   spark.driver.extraClassPath	/opt/mapr/hadoop/hadoop-2.7.0/share/hadoop/mapreduce/*

5. If the MapR Cluster being connected to has High-Availability enabled. You will also have to transpose the contents of the${HADOOP_HOME}/etc/hadoop/yarn-site.xmlto theAdvanced Spark Parameters．
   For everypropertyelement present in the${HADOOP_HOME}/etc/hadoop/yarn-site.xmldo the following:
   1. Create a newAdvanced Spark Parameterrow
   2. Copy thenameelement value to theKeyfield appendspark.hadoop.to the value
   3. Copy thevalueelement to theValuefield
   4. Ensure the new row is marked enabled

   

6. At this point Spark settings may look like this.

   

Hive tab

1. Depending on security setup of Hive
   • IfMapR securityis not enabled
     1. ForHive VersionselectHiveServer2 (Hive 0.13 or newer)
   • If your HiveServer2 instance is secured byMapR Security
     1. ForHive VersionselectCustom HiveServer2
     2. InCustom Hive Lib Directoryselect the directory where jars were copied to in step 2 ofSetting up client machinesection.
     3. ForJDBC URL Postfixappendauth=maprsasl;saslQop=auth-confto the textfield. If Hive server was setup with SSL then seeHive SSL Setup in Notes
   • Additionally if your HiveServer2 instance is secured with SSL it will require a truststore and an optional truststore password. For this user need to adjust theJDBC URL Postfixconnection field.
     • If truststore is not passed into the running JVM, user will need to appendssl=true;sslTrustStore=;sslTrustStorePassword=
     • If the truststore is known by the JVM, user will only need to appendssl=true．Truststores can be installed to the the JVM either by
       • Installing trusted MapR certificates into the default Java Keystore.
       • Including-Djavax.net.ssl.trustStore= -Djavax.net.ssl.trustStorePassword=to the Rapidminer Studio/Server JVM startup command.

2. Enter and verifyHive AddressandHive Portfields.

3. Enter your login credentials in theHive UsernameandHive Passwordfields. ProvidedHive Usernamemust be an existing identity on the cluster. Please note depending on cluster setup these fields can be blank.

4. At this point Hive settings may look like this.

   

Notes on configuring user impersonation on Server

For RapidMiner Server, user impersonation makes it possible to act as different users on cluster. The user will always be the actual RapidMiner Server user authenticated by Server. The Server users allowed to access the MapR cluster must therefore exist on the cluster as well.

1. Follow theinstructions of the Radoop on Server guideto setup the Radoop connections.

2. Acquire a long-lived MapR ticket that can impersonate other users on all Job Agent hosts. The following commands are just examples, please refer to MapR documentation for more info. Note that you have to make sure that the Job Agents see theMAPR_TICKETFILE_LOCATIONenvironment variable (you may need to modify their startup script for that). Set the file permissions for the generated ticket properly, so that it cannot be accessed by unauthorized users. You may also want to adjust related settings, seesettings related to resolving usernames．

   maprlogin password maprlogin generateticket -type servicewithimpersonation -out /var/tmp/impersonation_ticket -duration 30:0:0 -renewal 90:0:0 export MAPR_TICKETFILE_LOCATION=/var/tmp/impersonation_ticket

Connecting to an IBM Open Platform (IOP) cluster with default settings usually works without any special setting on theConnection Settingsdialog. SelectIBM开放平台4.1 +asHadoop version, and provide the appropriate address fields. If the SQL Standard Based Hive Authorization is enabled for your cluster or any unexpected error occurs, please refer to theHortonworks Data Platformdescription.