1. Documentation
2. 2024.1 (Latest) 2024.0 10.3 10.2 10.1 10.0 9.10 9.9 9.8 9.7 9.6 9.5 9.4 9.3 9.2 9.1 9.0 8.2 8.1 8.0 7.6
3. Radoop
4. Installation
5. Configuring Radoop Connections

Configuring RapidMiner Radoop Connections on RapidMiner Studio

You configure connections between RapidMiner Radoop on RapidMiner Studio and one or more Hadoop clusters from the basic and advanced Connection Setup windows. You can access these windows from the Connections menu, the Hadoop Data view, or the Design view. After configuring and saving the connection entries, you can test them before deployment. The test validates the connection to the cluster and verifies that the connection settings comply with the RapidMiner Radoop requirements described in the section on prerequisites.

There are three methods to create a Radoop connection. If you have access to the cluster manager software (Apache Ambari or Cloudera Manager), we strongly recommend to use the Import from Cluster Manager option. This method is the simplest one. If you do not use or do not have access to a cluster manager, but can ask for the client configuration files, then use the Import Hadoop Configuration Files option. Otherwise, you always have the option to Add Connection Manually. This last option also allows you to import a Radoop connection that someone shared with you by clicking on the Edit XML... button, once the Advanced Connection Properties dialog appears.

Note: When configuring RapidMiner Radoop, you must provide the internal domain name or IP address of the master node (that is, the domain name or IP address that the master node knows about itself). See the networking setup overview for details on how to ensure that your data is safe from unauthorized access.

Basic RapidMiner Radoop connection configuration

Once RapidMiner Radoop is installed, you can create a connection.

1. Restart RapidMiner Studio so that it recognizes the RapidMiner Radoop extension. Once it restarts, you will see a new Manage Radoop Connections option in the Connections menu:

   

2. Select the Manage Radoop Connections menu item and the Manage Radoop Connections window opens:

   

   For more details on this dialog, see Manage Radoop Connections section below.

3. Click on New Connection button and choose Add Connection Manually:

   

   If you wish to create the connection by importing client configuration files or by using a cluster management service, read the Importing Hadoop configuration section.

4. You can edit the connection properties on the Advanced Connection Properties window.

   

   Complete the required connection fields:

   Field	Description
   Name	A name for the connection.
   Hadoop Version	The distribution that defines the Hadoop version type for this connection.
   Master Address	The master address of the cluster. This is the hostname of the machine in the cluster that runs NameNode and all other master services. If master services are running on different nodes, you can specify them by checking Multiple Masters. Note that DNS and reverse DNS should work for all specified addresses, so the client machine must have access to the network name resolution system of the cluster or be able to resolve the addresses locally.

   For further details, see Advanced Connection Properties section below.

   Click OK to create the connection entry.

5. Click Save to add the entry to the available connections.

6. Test the connection between RapidMiner Radoop and the Hadoop cluster. If necessary, and with the assistance of your Hadoop administrator, set the advanced settings based on the distribution specific notes.

Your connection settings are saved in a file called radoop_connections.xml in your .RapidMiner directory.

Importing a connection

Configuring a connection manually can be cumbersome for a more complicated cluster. In this case using one of the connection import features is recommended. There are two options: you can create a connection using the cluster's client configuration files, or by providing the URL and credentials for the cluster's management service (Cloudera Manager or Ambari).

Manage Radoop Connections window

The Manage Radoop Connections window was completely redesigned in RapidMiner Radoop 7.1:

This window consists of 3 panels. The upper left panel lists all known connection entries. For each entry, one or more icons may be present showing some additional information, namely:

• Spark is configured for this connection
• The connection uses Impala as query engine
• Connection to a secure cluster

The basic properties of the currently selected connection are gathered on the right-hand side panel. There are also buttons executing several actions available on the selected connection:

• Configure...: Opens the Advanced Connection Properties window where you can configure the connection properties. Check the Advanced connection settings section for more details.
• Save: Saves the currently displayed connection.
• Save As...: Saves a copy of the currently displayed connection. Useful for saving a slightly modified connection while keeping the original entry.
• Quick Test: Runs a Quick Test on the currently displayed connection.
• Full Test...: Runs a Full Integration Test on this connection. More information on the connection tests can be found in the Testing RapidMiner Radoop connections section.
• Rename Action: Renames the current connection. Please note that all connection names should be unique.

The lower panel shows logs of the running tests. Several actions can be performed on this panel too:

• Extract logs...: This action creates a bundled zip file containing all relevant logs of your recent Radoop-related activities. See related section for more details.
• Clear logs: Clears the connection log field.
• Stop Test: The Stop Test action will halt the currently running test execution (see the Testing RapidMiner Radoop connections section).

Testing RapidMiner Radoop cluster connections

RapidMiner Radoop's built-in test functions help with troubleshooting before trouble begins.

Basic connection test

Click the Quick Test button in the Manage Radoop Connections window to test the connection to the cluster. Through a series of simple tests to different components (APIs) on the cluster, the test verifies that the cluster is running and that the RapidMiner Radoop client can access it. You can stop the test anytime by clicking the Stop Test button.

Full connection tests

Once your test succeeds, run a complete test (which may take several minutes) by clicking the Full Test... button. It's possible to customize a full connection test by clicking the Customize... button. In this panel you can enable or disable tests, change the timeout and enable or disable the cleaning after the tests. These values are reset to the defaults after closing the Manage Radoop Connections window. Click Run to start the test.

The full test initiates several jobs and applications on the cluster and then checks the results. By successfully and extensively exercising RapidMiner Radoop interactions with your cluster, you can feel confident in your RapidMiner Radoop process design and execution.

In addition to testing connections when you first create a RapidMiner Radoop configuration, you can use the Full Test if you have an error in process execution or a change in the cluster. The output of the full test results can help identify the root cause of the problem for easier troubleshooting. You can stop the Full Test anytime by clicking the Stop Test button. Stopping the current test process may take some time.

Note: The cluster connection initial test also starts automatically in the background when you open a process containing a RapidMiner Radoop Nest operator (indicated by the status bar in the bottom right corner of the RapidMiner Studio screen).

Advanced connection settings

You can use the Advanced Connection Properties window to edit the connection parameters. For example, you can change port numbers or define arbitrary parameters for Hadoop and Hive using key-value pairs. Do not modify the connection settings without first consulting with your organization's IT administrator. To open the Advanced Connection Properties window, click the Configure... button from the Manage Radoop Connections window.

Note: The fields displayed depend on the selections (for example, the selected Hadoop version). Also, some fields prepopulate based on the Hadoop version selection from the basic settings. If a field is bold in the window, it is required.

The following table briefly describes the fields of the Advanced Connection Properties window. For advanced configuration details related to your environment, see the distribution specific notes.

Field	Description
Name	A name for the connection.
Hadoop Version	The distribution that defines the Hadoop version type for this connection.
Additional Libraries Directory	Any additional libraries (JAR files) on the client needed to connect to the cluster (optional, for expert users only).
Hadoop Username	The name of the Hadoop user. In most cases, the user must have appropriate permissions on the cluster. For a new connection, the default is the OS user.
Master Address	The master address of the cluster. This is the address (usually hostname) of the machine in the cluster that runs the NameNode and all other master services. If master services are running on different nodes, check the Multiple Masters box. Note that DNS and reverse DNS should work for all specified addresses, so the client machine must have access to the network name resolution system of the cluster or be able to resolve the addresses locally.
Multiple Masters	Check this box if master services are running on different nodes. If checked, the following three fields become available.
NameNode Address	Only with Multiple Masters checked. Address (usually hostname) of the node running the NameNode service. (Requires a working network name resolution system.)
Resource Manager Address	Only with Multiple Masters checked. Address (usually hostname) of the node running Resource Manager service.
JobHistory Server Address	Address (usually hostname) of the node running the Job History Server service.
Hive Server Address/Impala Server Address	Only with Multiple Masters checked. Address (usually hostname) of the node running the Hive Server or the Impala Server.
Change Default Ports	Check this box if any of the services can be accessed on a non-default port.
Namenode Port	Only with Change Default Ports checked. Port of the NameNode service.
Resource Manager Port	Only with Change Default Ports checked. Port of the Resource Manager service.
JobHistory Server Port	Port of the Job History Server service.
Hive Port/Impala Port	Only with Change Default Ports checked. Port of the Hive Server or Impala Server.
Use Radoop Proxy	Check this box if you want to access the Hadoop Cluster through a Radoop Proxy.
SQL Settings	Select the appropriate Data Warehouse System — HiveServer2 (Hive 0.13 or newer) or Impala. Alternatively, you can select Custom HiveServer2 and provide your own Hive jars.
Custom Hive Lib Directory	Only with Custom Hiveserver2 selected. Select a directory that contains the libraries (JAR files) needed to connect to the cluster.
Database name	Name of the database to connect to.
JDBC URL Postfix	Optional postfix for the JDBC URL. The default is "auth=noSasl" for Impala connections.
Username	Username for connecting to the specified database. The default is "hive" for all HiveServer2 version connections. This user should have access to the HDFS directory that Radoop uses for storing files temporarily. If this directory is located in an encryption zone, the user should also have permissions to access the encryption zone key.
Password	Password for connecting to the specified database. RapidMiner Radoop uses the cipher.key file to encrypt the password in radoop_connections.xml.
UDFs are installed manually	Check this box if the Radoop UDFs are installed on the cluster manually. More information on the manual UDF installation can be found on the Operation and Maintenance page.
Use custom database for UDFs	Check this box if a custom database should be used for storing and accessing Radoop UDFs. This is useful when more users (having different project databases and granted privileges) wish to use Radoop. This common database should be accessible by all of them. The UDFs can still be automatically or manually created.
Custom database for UDFs	Define the database dedicated for storing Radoop UDFs (see above). The database must exist.
Enable Hive on Spark / Tez container reuse	Check this box if you would like to benefit from Hive on Spark / Hive on Tez container reuse.
Enable Security	Check this box to connect to a secure Hadoop cluster.
Additional security settings	For more information on these settings and connecting to a secured cluster, see the Hadoop Security section.
RapidMiner Server Settings	Within this group, some multi-user configuration properties are listed that affect the execution on RapidMiner Server. For more information and best practice solutions, see the relevant sections of Installing Radoop on Server page.
Spark Version	Selecting the appropriate Spark Version enables the Spark operators in Radoop. For more information on using Spark operators, see the Configuring Spark section.
Assembly JAR Location / Spark Archive (or libs) path	The HDFS location or local path (on all cluster nodes) of the Spark Assembly JAR file / Spark JAR files.
Spark Resource Allocation Policy	The resource allocation policy for Spark jobs. The default, Static, Heuristic Configuration, is typically applicable. See more Spark policy information.
Resource Allocation %	Percentage of cluster resources allocated for a Spark job. This field is only enabled when Static, Heuristic Configuration is the Spark resource allocation policy.
Advanced Spark Parameters	Key-value properties that customize RapidMiner Radoop's Spark jobs. See the instructions for configuring Spark.
Advanced Hadoop Parameters	Key-value properties to customize the Hadoop connection and Radoop's Yarn/MapReduce jobs. Some connections require certain advanced parameters. For detailed information, see the distribution specific notes.
Advanced Hive Parameters	Key-value properties to customize the behavior of Hive. This field is hidden when using Impala.

XML connection editor

Starting from RapidMiner Radoop 7.0 the connection XML can be edited manually by clicking the Edit XML... button on the Advanced Connection Properties window. Please note that this feature should be used carefully as it's easy to make mistakes in a connection entry through the XML editor. The main purpose of the editor is to make connection sharing and copy-pasting some parts of it (e.g. Advanced Hadoop Parameters) much easier. When you close the window with the OK button, your changes appear in the fields of the Advanced Connection Properties window.

Note: Adding a separate key attribute to <radoop-connection-entry> tag in the XML editor will have no effect. It can only be added in radoop_connections.xml, manually.

Configuring non-default properties

If your Hadoop cluster uses non-default properties, additional key-value pairs may be required. Cluster management tools like Cloudera Manager and Ambari allow you to download the client configuration files. You may have to add cluster connection-related properties from these files to the Advanced Hadoop Parameters list. See below for single properties that occur to be (re)set frequently, and more complex examples describing the properties required to connect to a cluster with High Availability (HA) enabled. The following tables list the keys of the potentially required client-side settings. The values should be set to the appropriate property values from the client configuration files. Note that not all keys related to these features may be required, the required set of key-value pairs depend on your cluster settings.

Configuring Spark for a RapidMiner Radoop connection

By configuring Spark for a RapidMiner Radoop connection, you enable the Logistic Regression, Linear Regression, Decision Tree (MLlib binominal), Support Vector Machine and - if using Spark 1.5 or later - the Spark Script, Decision Tree, Random Forest and the Single Process Pushdown operators. The machine learning operators use the corresponding functions in Spark MLlib or Spark ML.

To enable Spark, select Spark 1.4 or below, Spark 1.5, Spark 1.6, Spark 2.0 or Spark 2.1 in the Spark version dropdown list in the Advanced Connection Properties window.

You must provide the following mandatory inputs on the Advanced Connection Properties window:

Field	Description
Spark Version	The version of the Spark assembly JAR on your cluster. For Spark versions 1.2.x, 1.3.x and 1.4.x please select Spark 1.4 or below. If you have Spark 1.5.x, Spark 1.6.x, Spark 2.0.x or Spark 2.1.x on your cluster, select Spark 1.5, Spark 1.6, Spark 2.0, or Spark 2.1, respectively. If no Spark is needed then select None option.
Assembly JAR location / Spark Archive (or libs) path	The HDFS or local path of the distribution-specific Spark assembly JAR file / Spark JAR files. If you provide a local path then it must be the same on every node in your cluster. Specifying the local path is recommended if Spark is automatically installed (e.g. with Cloudera Manager or Ambari) on the cluster. For some Hadoop versions, the pre-built Spark assembly JAR can be downloaded from the Apache Spark download page. Some vendors (like Cloudera) provide a distribution-specific Spark assembly JAR. For the HDFS path of the JAR, contact your Hadoop administrator. For example, to install Spark 1.5 manually, refer to the Spark requirements section. If you followed the instructions there, your assembly jar is at the following location on the HDFS: hdfs:///tmp/spark/spark-assembly-1.5.2-hadoop2.6.0.jar
Spark resource allocation policy	Spark needs explicit specification of the cluster resources it is allowed use. See the Spark resource allocation policy descriptions
Advanced Spark Parameters	Key-value pairs that can be applied to a Spark-on-YARN job. If the change has no effect on your Spark job, most likely it is ignored by YARN itself. To check the properties in the application log, set spark.logConf to true.

Spark resource allocation policies

RapidMiner Radoop supports the following resource allocation policies:

Static, Heuristic Configuration

• This is the default policy. If you use this option, you do not need to set any advanced resource allocation settings. The Resource Allocation % field sets the percentage of cluster resources (cluster memory, number of cores) to be used for a Spark job. Note that if you set this value too high, other jobs on the cluster might suffer. The default value is 70%.

Static, Default Configuration

• A policy that uses Spark's default settings for resource allocation. This value is very low and may not support a real cluster, but it may be a viable option for VMs/sandboxes.

Static, Manual Configuration

• This policy requires that you set the following properties under Advanced Spark Parameters of the Advanced Connection Properties window. The Spark documentation describes each property. (The corresponding Spark on YARN command line arguments are shown in parentheses.)
  • spark.executor.cores (--executor-cores)
  • spark.executor.instances (--num-executors)
  • spark.executor.memory (--executor-memory)
  • (optional) spark.driver.memory (--driver-memory)
    

Dynamic Resource Allocation

• This policy provides convenient elastic resource management but requires advanced configuration steps on the cluster. The following properties must be defined under Advanced Spark Parameters of the Advanced Connection Properties window:
  • spark.dynamicAllocation.minExecutors
  • spark.dynamicAllocation.maxExecutors

  With this policy you must configure an external shuffle service on the cluster. For more information about the required cluster configuration steps see the Spark Dynamic Allocation documentation.

Note: Because of SPARK-6962, RapidMiner Radoop changes the default value of spark.shuffle.blockTransferService to nio instead of netty. To override this setting, in the Advanced Spark Parameters field configure the key spark.shuffle.blockTransferService to the value netty. Starting from 1.6.0, this setting is ignored by Spark, the BlockTransferService is always netty.

Hive on Spark & Hive on Tez container reuse

Reusing the containers of the Hive execution engine can dramatically speed up Radoop processes, especially if there are lots of Hive-only tasks. It is achieved by keeping a number of Spark / Tez containers (applications) in running state for executing Hive queries. Keep in mind that these containers will use cluster resources even if there are no running processes. Radoop tries to estimate the optimal number of containers by default, but it also can be changed to a fix number in the settings (see below). Idle containers are automatically closed after a timeout.

To use this feature, your cluster must support Hive on Spark or Hive on Tez, and in your connection have to set hive.execution.engine to spark or tez in Advanced Hive Parameters and check Hive on Spark / Tez container reuse checkbox (this is the default value):

A number of global Radoop settings can be used to control the container reuse behaviour. You may want to test different settings to use your cluster optimally, see Radoop Settings for details.

Impala connections

If your are configuring an Impala connection some Advanced Hadoop Parameters need to be added manually. If you forget to add any of those, a warning message will warn you about the missing ones. The Add Required Entries button adds the keys of these properties to the list, but their values must be set manually according to the cluster configuration.