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Set Up Pentaho to Connect to a MapR Cluster

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Before You Begin

Before you begin, you'll need to do a few things.

  1. Verify Support
    Check the Component Reference to verify that your Pentaho version supports your version of the MapR cluster.
     
  2. Set Up a MapR cluster
    Pentaho can connect to secured and unsecured MapR Clusters.
    1. Configure a MapR cluster.  See MapR's documentation if you need help.
    2. Install any required services and and service client tools.
    3. Test the cluster.
       
  3. Set up MapR Client

    1. Install the MapR client, then test to make sure it is properly installed on your computer and is able to connect to and browse your MapR cluster. For more information on how to do this, visit the MapR site.

    2. Set the MAPR_HOME environment variable to the installation location of the MapR client.
       

      If you are installing MapR 4.0.1 on Windows, use version 4.0.1.31009GA or later as your MapR client.  If you are using MapR 4.1.0, use version 4.1.0.31175GA  of the MapR client.  The software can be obtained from MapR.
       

  4. Review the Version-Specific Notes Section
    Read the Version-Specific Notes section to review special configuration instructions for your version of MapR.

If you are connecting to a secured MapR cluster there are a few additional things you need to do.

  1. Secure the MapR Cluster with Kerberos
    Pentaho supports Kerberos authentication.  You will need to:
    1. Configure Kerberos security on the cluster, including the Kerberos Realm, Kerberos KDC, and Kerberos Administrative Server.
    2. Configure the name, data, secondary name, job tracker, and task tracker nodes to accept remote connection requests.
    3. Set up Kerberos for name, data, secondary name, job tracker, and task tracker nodes if you are have deployed Hadoop using an enterprise-level program.
    4. Add the user account credential for each Pentaho user that should have access to the Hadoop cluster to the Kerberos database.  Make sure there is an operating system user account on each node in the Hadoop cluster for each user that you want to add to the Kerberos database. Add operating system user accounts if necessary. Note that the user account UIDs must be greater than the minimum user ID value (min.user.id). Usually, the minimum user ID value is set to 1000.
       
  2. Set up Kerberos on your Pentaho computers
    Instructions for how to do this appear in Set up Kerberos on Your Pentaho Computer.
     
  3. Set up Impersonation

    1. If you will be using impersonation, you will also need to complete the steps in MapR Impersonation article.

    2. If you plan to use spoofing or impersonation to connect to the MapR client, specify the appropriate User ID (UID), Group ID (GID), and name as indicated in the MapR documentation.  (NOTE: Make sure that the account that you use for spoofing is created the client and on each node.  Each "spoofing" account should have the same UID and GID as the one on the client.)

There are no edits that need to be made to the *-site.xml configuration files on the cluster.

Configure Pentaho Component Shims

You must configure the shim for each of the following that you want to connect to the MapR Cluster:

  • Spoon (PDI Client)
  • Pentaho Server 
  • Pentaho Report Designer (PRD)
  • Pentaho Metadata Editor (PME)

As a best practice, configure the shim in Spoon first.  Spoon has features that will help you test your configuration.  Then copy the tested Spoon configuration files to other components, making changes if necessary. 

You can also opt to go through these instructions for each Pentaho component, and not copy the shim files from Spoon.  If you do not plan to connect to the cluster from Spoon, you can configure the shim in another component first instead.

If you do not not plan to connect to the cluster from Spoon, you can configure the connection to another component first instead.

Step 1: Locate the Pentaho Big Data Plugin and Shim Directories

Shims and other parts of the Pentaho Adaptive Big Data Layer are in the Pentaho Big Data Plugin directory.  The path to this directory differs by component. You need to know the locations of this directory, in each component, to complete shim configuration and testing tasks.

<pentaho home> is the directory where Pentaho is installed.

Components Location of Pentaho Big Data Plugin Directory
Spoon <pentaho home>/design-tools/data-integration/plugins/pentaho-big-data-plugin
Pentaho Server <pentaho home>/server/pentaho-server/pentaho-solutions/system/kettle/plugins/pentaho-big-data-plugin
Pentaho Report Designer <pentaho home>/design-tools/report-designer/plugins/pentaho-big-data-plugin
Pentaho Metadata Editor <pentaho home>/design-tools/metadata-editor/plugins/pentaho-big-data-plugin

Shims are located in the pentaho-big-data-plugin/hadoop-configurations directory.  Shim directory names consist of a three or four letter Hadoop Distribution abbreviation followed by the Hadoop Distribution's version number.  The version number does not contain a decimal point.  For example, the shim directory named cdh54 is the shim for the CDH (Cloudera Distribution for Hadoop), version 5.4.  Here is a list of the shim directory abbreviations.

Abbreviation Shim
cdh Cloudera's Distribution of Apache Hadoop
emr Amazon Elastic Map Reduce
hdp Hortonworks Data Platform
mapr MapR

Step 2: Select the Correct Shim

Although Pentaho often supports one or more versions of a Hadoop distribution, the download of the Pentaho suite only contains the latest, supported, Pentaho-certified version of the shim.  The other supported versions of shims can be downloaded from the Pentaho Customer Support Portal. 

Before you begin, verify that the shim you want is supported by your version of Pentaho shown in the Components Reference.

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations directory to view the shim directories. If the shim you want to use is already there, you can go to Step 3: Copy the Configuration Files from Cluster to Shim. 
  2. On the Customer Portal home page, sign in using the Pentaho support user name and password provided to you in your Pentaho Welcome Packet. 
  3. In the search box, enter the name of the shim you want. Select the shim from the search results. Optionally, you can browse the shims by version on the Downloads page. 
  4. Read all prerequisites, warnings, and instructions. On the bottom of the page in the Box widget, click the shim zip file to download it. 
  5. Unzip the downloaded shim package to the pentaho-big-data-plugin/hadoop-configurations directory.

Step 3: Copy the Configuration Files from Cluster to Shim

If you are using a cluster, copying configuration files from the cluster to the shim keeps the configuration files in sync and reduces troubleshooting errors.

  1. Back up the existing MapR shim files in the pentaho-big-data-plugin/hadoop-configurations/maprxx directory. 
  2. Copy the following configuration files from the MapR cluster to pentaho-big-data-plugin/hadoop-configurations/maprxx. You should overwrite the existing files.
  • hbase-site.xml
  • hdfs-site.xml
  • hive-site.xml
  1. Copy the following configuration files from the MapR cluster to the Hadoop directory under the MapR Client installed on your computer.  

The Winows path to the MapR client is usually C:\opt\mapr\hadoop\hadoop-2.x.x\etc\hadoop.  In Linux the path is usually /opt/mapr/hadoop/hadoop-2.x.x/etc/hadoop. 

  • core-site.xml
  • mapred-site.xml
  • yarn-site.xml
  1. Edit the shim configuration files.

Step 4: Edit the Shim Configuration Files

You need to verify or change settings in authentication, Oozie, Hive, MapReduce, and YARN in these shim configuration files:

  • config.properties
  • mapred-site.xml
  • yarn-site.xml

Edit config.properties (Windows)

If you are connecting to an unsecured cluster (default), verify that these values are properly set.

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/maprxx directory and open the config.properties file.
  2. Add the following values:
Parameter Values
windows.classpath ​This value should match your local MapR client tools installation directory.  Set the windows.classpath parameter equal to these:
  • Hadoop classpath
  • Pentaho installation directory path
  • MapR shim directory path

The MapR shim might fail to load correctly if the drive letter in the Windows classpath or library path has a capital letter. This is a known issue with MapR software.  If this happens, use the lower case instead, like this: file:///c:/opt/mapr.

The value of windows.classpath parameter should include lib/hadoop2-windows-patch-08072014.jar as a first entry in the string, the Hadoop classpath of MapR client on the current machine, a full directory path where MapR shim is located under each Pentaho component, and this entry: file:///c:/opt/mapr/lib. To determine your hadoop classpath, execute the hadoop classpath command and use those values instead. Convert any directory paths to Windows URL format.  The following is an example. 

EXAMPLE:

windows.classpath=lib/hadoop2-windows-patch-08072014.jar,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/etc/hadoop,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/etc/hadoop,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/common/lib,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/common,file:///C://opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/hdfs,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/yarn,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib,file:///C:/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/mapreduce,file:///C:/opt/mapr/sqoop/sqoop-1.4.5,file:///C:/opt/mapr/sqoop/sqoop-1.4.5/lib,file:///C:/contrib/capacity-scheduler,file:///C:/opt/Pentaho/design-tools/data-integration/plugins/pentaho-big-data-plugin/hadoop-configurations/mapr401,file:///C:/opt/Pentaho/design-tools/data-integration/plugins/pentaho-big-data-plugin/hadoop-configurations/mapr401/lib,file:///C:​/opt/mapr/lib​
windows.library.path 
windows.library.path=C:\\opt\\mapr\\lib
pentaho.oozie.proxy.user You do not need to verify this unless you plan to access the oozie service through a proxy.  If so, add the proxy user's name here.
  1. Save and close the file.

Edit config.properties (Linux)

To configure the config.properties file, do these things.

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/maprxx directory and open the config.properties file.
  2. Add the following values:
Parameter Values
linux.classpath Edit this value to match your local MapR client tools installation directory. Set the linux.classpath parameter equal to these:
  • Hadoop classpath
  • Pentaho installation directory path
  • MapR shim directory path

The linux.classpath should contain the Hadoop classpath of MapR client on the current machine, a full directory path where MapR shim is located under each Pentaho component, and this entry: /opt/mapr/lib. To determine your hadoop classpath, execute the hadoop classpath command and use those values instead. the following is an example.

EXAMPLE:

linux.classpath=/opt/mapr/hadoop/hadoop-2.4.1/etc/hadoop,/opt/mapr/hadoop/hadoop-2.4.1/etc/hadoop,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/common/lib,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/common,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/hdfs,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/yarn,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib,/opt/mapr/hadoop/hadoop-2.4.1/share/hadoop/mapreduce,/opt/mapr/sqoop/sqoop-1.4.5,/opt/mapr/sqoop/sqoop-1.4.5/lib,/contrib/capacity-scheduler,/opt/Pentaho/design-tools/data-integration/plugins/pentaho-big-data-plugin/hadoop-configurations/mapr401,/opt/Pentaho/design-tools/data-integration/plugins/pentaho-big-data-plugin/hadoop-configurations/mapr401/lib,/opt/mapr/lib​
linux.library.path 
linux.library.path=/opt/mapr/lib
pentaho.oozie.proxy.user You do not need to verify this unless you plan to access the Oozie service through a proxy.  If so, add the proxy user's name here.
  1. Save and close the file.

Edit mapred-site.xml

Edit the mapred-site.xml file to indicate where the job history logs are stored and to allow MapReduce jobs to run across platforms.

  1. Navigate to the Hadoop directory in your MapR Client and open the mapred-site.xml file.
  2. Add the following values:
Parameter Value
mapreduce.jobhistory.address Set this to the place where job history logs are stored.
mapreduce.app-submission.cross-platform

Add this property to allow MapReduce jobs to run on either Windows client or Linux server platforms .

<property>
  <name>mapreduce.app-submission.cross-platform</name>
  <value>true</value>
</property>

 
  1. Save and close the file.

Edit yarn-site.xml

Make changes to these yarn parameters, if necessary.

  1. Navigate to the Hadoop directory in your MapR Client and open the yarn-site.xml file.
  2. Add the following values:  
Parameter Values
yarn.application.classpath ​ 
<property>
<name>yarn.application.classpath</name>
<value>$HADOOP_CONF_DIR:$HADOOP_COMMON_HOME/share/hadoop/common/*
:$HADOOP_COMMON_HOME/share/hadoop/common/lib/*:$HADOOP_HDFS_HOME/share/hadoop/hdfs/*
:$HADOOP_HDFS_HOME/share/hadoop/hdfs/lib/*:$HADOOP_YARN_HOME/share/hadoop/yarn/*
:$HADOOP_YARN_HOME/share/hadoop/yarn/lib/*:/usr/share/aws/emr/emrfs/lib/*
:/usr/share/aws/emr/lib/*:/usr/share/aws/emr/auxlib/*:$PWD/*:%PWD%/*
</value>
</property>
yarn.resourcemanager.hostname Change to the hostname of the resource manager in your environment.
yarn.resourcemanager.address Change to the hostname and port for your environment.
yarn.resourcemanager.admin.address Change to the hostname and port for your environment.
  1. Save and close the file.

Set MAPR_HOME

Set the MAPR_HOME environment variable to the installation location of the MapR client, then restart your computer.

Create a Connection to the MapR Cluster

Creating a connection to the cluster involves setting an active shim, then configuring and testing the connection to the cluster.  Making a shim active means it is used by default when you access a cluster.  When you initially install Pentaho, no shim is active by default.  You must choose a shim to make active before you can connect to a cluster.   Only one shim can be active at a time.  The way you make a shim active, as well as the way you configure and test the cluster connection differs by Pentaho component.

Create and Test a Connection to the Cluster in Spoon

Creating and testing a connection to the MapR cluster from Spoon involves two tasks:

  • Set the active shim in Spoon
  • Configure and test the cluster connection

Set the Active Shim in Spoon

Set the active shim when you want to connect to a Hadoop cluster the first time, or when you want to switch clusters. To set a shim as active, complete the following steps:

  1. Start Spoon.
  2. Select Hadoop Distribution... from the Tools menu.

HadoopDistribution.png

  1. In the Hadoop Distribution window, select the Hadoop distribution you want.
  2. Click OK.
  3. Stop, then restart Spoon.

Configure and Test the Cluster Connection

You must provide connection details for the cluster and services you will use, such as the hostname for HDFS or the URL for Oozie.  Then, you can use a built-in tool to test your configuration to find and troubleshoot common configuration issues, such as wrong hostnames and user permission errors.

Connection settings are set in the Hadoop cluster window.  You can get to the settings from several places, but in these instructions, you will get the Hadoop cluster window from the View tab in a transformation or job. Complete the following steps to configure and test a connection:

  1. In Spoon, create a new job or transformation or open an existing one.
  2. Click the View tab.

clusterss.png

  1. Right-click the Hadoop cluster folder, then click New.  The Hadoop cluster window appears.  
  2. Enter information in the Hadoop cluster window.  You can get this information from your Hadoop Administrator.

As a best practice, use Kettle variables for each connection parameter value to mitigate risks associated with running jobs and transformations in environments that are disconnected from the repository. 

HadoopClusterWindow.png

Option Definition
Cluster Name Name that you assign the cluster connection.
Use MapR Client Indicates that this connection is for a MapR cluster.  If this box is checked, the fields in the HDFS and JobTracker sections are disabled because those parameters are not needed to configure MapR.
Hostname (in HDFS section) Hostname for the HDFS node in your Hadoop cluster.
Port (in HDFS section) Port for the HDFS node in your Hadoop cluster.  
Username (in HDFS section) Username for the HDFS node.
Password (in HDFS section) Password for the HDFS node.
Hostname (in JobTracker section) Hostname for the JobTracker node in your Hadoop cluster.  If you have a separate job tracker node, type in the hostname here. Otherwise use the HDFS hostname.
Port (in JobTracker section) Port for the JobTracker in your Hadoop cluster.  Job tracker port number; this cannot be the same as the HDFS port number.
Hostname (in ZooKeeper section) Hostname for the ZooKeeper node in your Hadoop cluster.  Supply this only if you want to connect to a ZooKeeper service.
Port (in Zookeeper section) Port for the ZooKeeper node in your Hadoop cluster.  Supply this only if you want to connect to a ZooKeeper service.
URL (in Oozie section) Oozie client address.  Supply this only if you want to connect to the Oozie service.
  1. Click the Test button.  Test results appear in the Hadoop Cluster Test window.  If you have errors, see the Troubleshoot Cluster and Service Configuration Issues section below to resolve the issues, then test again.

HadoopClusterTest.png

  1. Click Close on the Hadoop Cluster Test window, then click OK to close the Hadoop cluster window.

Copy Spoon Shim Files to Other Pentaho Components

Once your connection has been properly configured on Spoon, copy configuration files to the shim directories in other Pentaho components.

  1. Copy following configuration files from the pentaho-big-data-plugin/hadoop-configurations/maprxx directory in Spoon to pentaho-big-data-shim/maprxx on the Pentaho Server, PRD, or PME.
  • hbase-site.xml
  • hdfs-site.xml
  • hive-site.xml
  1. Copy the core-site.xml, mapred-site.xml, and yarn-site.xml files from the Hadoop directory under the MapR Client on your computer to same place in the MapR Client directory structure on the Pentaho Server, PRD, or PME.

Connect Other Pentaho Components to the MapR Cluster

These instructions explain how to create and test a connection to the cluster in the Pentaho Server, PRD, and PME. Creating and testing a connection to the cluster in Spoon involves two tasks:

  • Set the active shim on PRD, PME, and the Pentaho Server
  • Configure and test the cluster connections.

Set the Active Shim on PRD, PME, and the Pentaho Server

Modify the plugin.properties file to set the active shim for the Pentaho Server, PRD, and PME.

  1. Stop the component.
  2. Locate the pentaho-big-data-plugin directory for your component. 
  3. Navigate to the hadoop-configurations directory.
  4. Navigate to the pentaho-big-data-plugin directory and open the plugin.properties file.
  5. Set the active.hadoop.configuration property to the directory name of the shim you want to make active.  Here is an example:
active.hadoop.configuation=mpr410
  1. Save and close the plugin.properties file.
  2. Restart the component.

Create and Test Connections

Connection tests appear in the following table.

Component Test
Pentaho Server for DI Create a transformation in Spoon and run it remotely.
Pentaho Server for BA Create a connection to the cluster in the Data Source Wizard.
PME Create a connection to the cluster in PME.
PRD Create a connection to the cluster in PRD.

Once you've connected to the cluster and its services properly, provide connection information to users who need access to the cluster and its services.  Those users can only obtain access from computers that have been properly configured to connect to the cluster.

Here is what they need to connect:

  • Hadoop Distribution and Version of the Cluster
  • HDFS, JobTracker, ZooKeeper, and Hive2/Impala Hostnames, IP addresses and port numbers
  • Oozie URL (if used)
  • Users also require the appropriate permissions to access the directories they need on HDFS.  This typically includes their home directory and any other required directories.

They might also need more information depending on the job entries, transformation steps, and services they use.  Here's a more detailed list of information that your users might need from you.

General Notes

Set Hive Database Connection Parameters (Secured Clusters Only)

To access Hive, you need to set several database connection parameters from within Spoon.

  1. Open the hive-site.xml file that is on the hive server host.  Note the values for the kerberos.principal and the sasl.qop.

  2. Close the hive-site.xml file.

  3. Start Spoon.

  4. In Spoon, open the Database Connection window.

  5. Click Options.
  6. Add the following parameters and set them to the values that you noted in the hive-site.xml file:
  • sasl.qop
  • principal

The principal typically has a mapr prefix before the name, like this:  mapr/mapr31.pentaho@mydomain.

  1. Click OK to close the window.

Sqoop "Unsupported major.minor version" Error

If you are using Pentaho 6.0 and the Java version on your cluster is older than the Java version that Pentaho uses, you must change Pentaho's JDK so it is the same major version as the JDK on the cluster. The JDK that you install for Pentaho must meet the requirements in the Supported Components matrix. To learn how to download and install the JDK read this article. 

Version-Specific Notes

The following are special topics for MapR.

Drive Letter Casing Issue (Windows)

The MapR shim might fail to load correctly if the drive letter in the Windows classpath or library path has a capital letter. This is a known issue with MapR software.  If this happens, use the lower case instead, like this: file:///c:/opt/mapr.

MapR 4.1 Notes

The following notes address issues with MapR 4.1.

Impala Support Note

Pentaho does not support connections to Impala on a secured MapR 4.1 cluster.  For more information, please see these references:

Troubleshoot Cluster and Service Configuration Issues

General Configuration Problems

The issues in this section explain how to resolve common configuration problems. 

Shim and Configuration Issues

Symptoms Common Causes Common Resolutions

No shim
  • Active shim was not selected.
  • Shim was installed in the  wrong place.
  • Shim name was not entered correctly in the plugin.properties file.
  • Verify that the plugin name that is in the plugin.properties file matches the directory name in the pentaho-big-data-plugin/hadoop-configurations directory. 
  • Make sure the shim is installed in the correct place.
  • Check the instructions for your Hadoop distribution in the Set Up Pentaho to Connect to an Apache Hadoop Cluster article for more details on how to verify the plugin name and shim installation directory.
Shim doesn't load
  • Required licenses are not installed.
  • You tried to load a shim that is not supported by your version of Pentaho.
  • If you are using MapR, the client might not have been installed correctly. 
  • Configuration file changes were made incorrectly.
The file system's URL does not match the URL in the configuration file. Configuration files (*-site.xml files) were not configured properly.  Verify that the configuration files were configured correctly.  Verify that the core-site.xml file is configured correctly.  See the instructions for your Hadoop distribution in the Set Up Pentaho to Connect to an Apache Hadoop Cluster article for details.

 

Connection Problems

Symptoms Common Causes Common Resolutions
Hostname incorrect or not resolving properly.
  • No hostname has been specified.
  • Hostname/IP Address is incorrect.
  • Hostname is not resolving properly in the DNS.
  • Verify that the Hostname/IP address is correct.
  • Check the DNS to make sure the Hostname is resolving properly. 
Port name is incorrect.
  • No port number has been specified.
  • Port  number is incorrect.
  • Port number is not numeric.
  • Verify that the port number is correct.
  • If you don't have a port number, determine whether your cluster has been enabled for high availability. If it has, then you do not need a port number.
Can't connect.
  • Firewall is a barrier to connecting.
  • Other networking issues are occurring.
  • Verify that a firewall is not impeding the connection and that there aren't other network issues. 

Directory Access or Permissions Issues

Symptoms Common Causes Common Resolutions

Can't access directory.
  • Authorization and/or authentication issues.
  • Directory is not on the cluster.
  • Make sure the user has been granted read, write, and execute access to the directory. 
  • Ensure security settings for the cluster and shim allow access.
  • Verify the hostname and port number are correct for the Hadoop File System's namenode. 

Can't create, read, update, or delete files or directories

Authorization and/or authentication issues.
  • Make sure the user has been authorized execute access to the directory. 
  • Ensure security settings for the cluster and shim allow access.
  • Verify that the hostname and port number are correct for the Hadoop File System's namenode. 
Test file cannot be overwritten.  Pentaho test file is already in the directory.
  • A file with the same name as the Pentaho test file is already in the directory.  The test file is used to make sure that the user can create, write, and delete in the user's home directory.
  • The test was run, but the file was not deleted.  You will need to manually delete the test file.  Check the log fo the test file name.

Oozie Issues

Symptoms Common Causes Common Resolutions

Can't connect to Oozie.
  • Firewall issue.
  • Other networking issues.
  • Oozie URL is incorrect.
  • Verify that the Oozie URL was correctly entered.
  • Verify that a firewall is not impeding the connection. 

Zookeeper Problems

Symptoms Common Causes Common Resolutions

Can't connect to ZooKeeper .
  • Firewall is hindering connection with the ZooKeeper service.
  • Other networking issues.
  • Verify that a firewall is not impeding the connection. 

ZooKeeper hostname or port not found or doesn't resolve properly.  
  • Hostname/IP Address and Port name is missing or is incorrect.
  • Try to connect to the ZooKeeper nodes using ping or another method.
  • Verify that the Hostname/IP address and port numbers are correct.