Install On-Premises

To install  Designer Cloud Enterprise Edition inside your enterprise infrastructure, please review and complete the following sections in the order listed below.

Scenario Description

• Installation of  Designer Cloud Enterprise Edition on a server on-premises
• Installation of Alteryx databases on a server on-premises
• Integration with a supported Hadoop cluster on premises.
• Base storage layer of HDFS

Preparation

1. Review Planning Guide: Please review and verify Install Preparation and sub-topics.
2. Acquire Assets: Acquire the installation package for your operating system and your license key. For more information, contact Alteryx Support.
   
   1. If you are completing the installation without Internet access, you must also acquire the offline versions of the system dependencies. See Install Dependencies without Internet Access.

3. Deploy Hadoop cluster: In this scenario, the Designer Cloud Powered by Trifacta platform does not create a Hadoop cluster. See below.

   NOTE: Installation and maintenance of a working Hadoop cluster is the responsibility of the Designer Cloud Enterprise Edition customer. Guidance is provided below on the requirements for integrating the platform with the cluster.

4. Deploy Alteryx node: Designer Cloud Enterprise Edition must be installed on an edge node of the cluster. Details are below.

Limitations: For more information on limitations of this scenario, see Product Limitations in the Install Preparation area.

Deploy the Cluster

In your enterprise infrastructure, you must deploy a cluster using a supported version of Hadoop to manage the expected data volumes of your Alteryx jobs. For more information on suggested sizing, see Sizing Guidelines in the Install Preparation area.

When you configure the platform to integrate with the cluster, you must acquire information about the cluster configuration. For more information on the set of information to collect, see Pre-Install Checklist in the Install Preparation area.

The Designer Cloud Powered by Trifacta platform supports integration with the following cluster types. For more information on the supported versions, please see the listed sections below.

• See Supported Deployment Scenarios for Cloudera.
• See Supported Deployment Scenarios for Hortonworks.

Prepare the cluster

Before installing software, please complete the following steps if you are integrating with a Hadoop cluster.

Before you begin, please verify or complete the following:

1. On the Hadoop cluster: 
   
   1. Create a user [hadoop.user (default=trifacta)] and a group for it [hadoop.group (default=trifactausers)].
   2. Create the following directories: 
      1. /trifacta
      2. /user/trifacta

   3. Change the ownership of /trifacta and /user/trifacta to trifacta:trifacta or the corresponding values for the Hadoop user in your environment.

      NOTE:  You must verify that the [hadoop.user] user has complete ownership and full access to Read, Write and Execute on these directories recursively.

2. Verify that WebHDFS is configured and running on the cluster.

    

3. Software installation is completed on a dedicated node in the cluster. The user installing the Alteryx software must have sudo access.
   
   
   
4. If you are installing on a server with an older instance of Postgres, you should remove the older version or change the default ports. 

For more information, see Prepare Hadoop for Integration with the Platform. 

Additional users may be required. For more information, see Required Users and Groups in the Install Preparation area.

Deploy the Alteryx node

An edge node of the cluster is required to host the Designer Cloud Powered by Trifacta platform software. For more information on the requirements of this node, see System Requirements. 

Install Workflow

Configure for Hadoop

After you have performed the base installation of the Designer Cloud Powered by Trifacta® platform, please complete the following steps if you are integrating with a Hadoop cluster.

Apply cluster configuration files - non-edge node

If the Designer Cloud Powered by Trifacta platform is being installed on a non-edge node, you must copy over the Hadoop Client Configuration files from the cluster. 

1. Download the Hadoop Client Configuration files from the Hadoop cluster. The required files are the following:
   1. core-site.xml
   2. hdfs-site.xml
   3. mapred-site.xml
   4. yarn-site.xml
   5. hive-site.xml (if you are using Hive)

2. These configuration files must be moved to the Alteryx deployment. By default, these files are in /etc/hadoop/conf:

   sudo cp <location>/*.xml /opt/trifacta/conf/hadoop-site/
   sudo chown trifacta:trifacta /opt/trifacta/conf/hadoop-site/*.xml 
   

For more information, see Configure for Hadoop.

Apply cluster configuration files - edge node

If the Designer Cloud Powered by Trifacta platform is being installed on an edge node of the cluster, you can create a symlink from a local directory to the source cluster files so that they are automatically updated as needed.

1. Navigate to the following directory on the Alteryx node:

   cd /opt/trifacta/conf/hadoop-site

2. Create a symlink for each of the Hadoop Client Configuration files referenced in the previous steps. Example:

   ln -s /etc/hadoop/conf/core-site.xml core-site.xml

3. Repeat the above steps for each of the Hadoop Client Configuration files.

For more information, see Configure for Hadoop.

Modify Alteryx configuration changes

1. To apply this configuration change, login as an administrator to the Alteryx node. Then, edit trifacta-conf.json. For more information, see Platform Configuration Methods.

2. HDFS: Change the host and port information for HDFS as needed. Please apply the port numbers for your distribution:

   "hdfs.namenode.host": "<namenode>",
   "hdfs.namenode.port": <hdfs_port_num>
   "hdfs.yarn.resourcemanager": {
   "hdfs.yarn.webappPort": 8088,
   "hdfs.yarn.adminPort": 8033,
   "hdfs.yarn.host": "<resourcemanager_host>",
   "hdfs.yarn.port": <resourcemanager_port>,
   "hdfs.yarn.schedulerPort": 8030

   For more information, see Configure for Hadoop.
    

3. Save your changes and restart the platform.

Configure Spark Job Service

The Spark Job Service must be enabled for both execution and profiling jobs to work in Spark.

Below is a sample configuration and description of each property. You can apply this change through the Admin Settings Page (recommended) or trifacta-conf.json. For more information, see Platform Configuration Methods..

"spark-job-service" : {
  "systemProperties" : {
    "java.net.preferIPv4Stack": "true",
    "SPARK_YARN_MODE": "true"
  },
  "sparkImpersonationOn": false,
  "optimizeLocalization": true,
  "mainClass": "com.trifacta.jobserver.SparkJobServer",
  "jvmOptions": [
"-Xmx128m"
],
  "hiveDependenciesLocation": "%(topOfTree)s/hadoop-deps/cdh-5.4/build/libs",
  "env": {
    "SPARK_JOB_SERVICE_PORT": "4007",
    "SPARK_DIST_CLASSPATH": "",
    "MAPR_TICKETFILE_LOCATION": "<MAPR_TICKETFILE_LOCATION>",
    "MAPR_IMPERSONATION_ENABLED": "0",
    "HADOOP_USER_NAME": "trifacta",
    "HADOOP_CONF_DIR": "%(topOfTree)s/conf/hadoop-site/"
  },
  "enabled": true,
  "enableHiveSupport": true,
  "enableHistoryServer": false,
  "classpath": "%(topOfTree)s/services/spark-job-server/server/build/libs/spark-job-server-bundle.jar:%(topOfTree)s/conf/hadoop-site/:%(topOfTree)s/services/spark-job-server/build/bundle/*:%(topOfTree)s/%(hadoopBundleJar)s",
  "autoRestart": false,
},

The following properties can be modified based on your needs:

hiveDependenciesLocation

enableHiveSupport

After making any changes, save the file and restart the platform. See Start and Stop the Platform.

Configure service for Hive

Depending on the environment, please apply the following configuration changes to manage Spark interactions with Hive:

If Hive is present on the cluster and either enabled or disabled: the hive-site.xml file must be copied to the correct directory:

cp /etc/hive/conf/hive-site.xml /opt/trifacta/conf/hadoop-site/hive-site.xml

At this point, the platform only expects that a hive-site.xml file has been installed on the Alteryx node . A valid connection is not required. For more information, see Configure for Hive .

Configure Spark

After the Spark Job Service has been enabled, please complete the following sections to configure it for the Designer Cloud Powered by Trifacta platform.

Yarn cluster mode

All jobs submitted to the Spark Job Service are executed in YARN cluster mode. No other cluster mode is supported for the Spark Job Service.

Configure access for secure impersonation

The Spark Job Service can run under secure impersonation. For more information, see Configure for Secure Impersonation.

When running under secure impersonation, the Spark Job Service requires access to the following folders. Read, write, and execute access must be provided to the Alteryx user and the impersonated user.

Identify Hadoop libraries on the cluster

The Spark Job Service does not require additional installation on the Alteryx node or on the Hadoop cluster. Instead, it references the spark-assembly JAR that is provided with the Alteryx distribution.

This JAR file does not include the Hadoop client libraries. You must point the Designer Cloud Powered by Trifacta platform to the appropriate libraries.

Steps:

1. In platform configuration, locate the spark-job-service configuration block.

2. Set the following property:

   "spark-job-service.env.HADOOP_CONF_DIR": "<path_to_Hadoop_conf_dir_on_Hadoop_cluster>",

   Property	Description
   spark-job-service.env.HADOOP_CONF_DIR	Path to the Hadoop configuration directory on the Hadoop cluster.

3. In the same block, the SPARK_DIST_CLASSPATH property must be set depending on your Hadoop distribution.
   
   1. For Cloudera 5.x: This property can be left blank.

   2. For Hortonworks 2.x: This property configuration is covered later in this section.

4. Save your changes.

Locate Hive dependencies location

If the Designer Cloud Powered by Trifacta platform is also connected to a Hive instance, please verify the location of the Hive dependencies on the Alteryx node. The following example is from Cloudera 5.10:

"spark-job-service.hiveDependenciesLocation":"%(topOfTree)s/hadoop-deps/cdh-5.10/build/libs",

For more information, see Configure for Spark.

Enable High Availability

Configure for Designer Cloud Powered by Trifacta platform

Set base storage layer

The platform requires that one backend datastore be configured as the base storage layer. This base storage layer is used for storing uploaded data and writing results and profiles. 

See Set Base Storage Layer.
 

Verify Operations

Prepare Your Sample Dataset

To complete this test, you should locate or create a simple dataset. Your dataset should be created in the format that you wish to test.

Characteristics:

• Two or more columns. 
• If there are specific data types that you would like to test, please be sure to include them in the dataset.
• A minimum of 25 rows is required for best results of type inference.
• Ideally, your dataset is a single file or sheet. 

Store Your Dataset

If you are testing an integration, you should store your dataset in the datastore with which the product is integrated.

• You may need to create a connection between the platform and the datastore.
• Read and write permissions must be enabled for the connecting user to the datastore.
• For more information, see Connections Page.

Verification Steps

Steps:

1. Login to the application. See Login.
2. In the application menu bar, click Library.
3. Click Import Data. See Import Data Page.
   1. Select the connection where the dataset is stored. For datasets stored on your local desktop, click Upload.
   2. Select the dataset.
   3. In the right panel, click the Add Dataset to a Flow checkbox. Enter a name for the new flow.
   4. Click Import and Add to Flow.

   5. Troubleshooting:   At this point, you have read access to your datastore from the platform. If not, please check the logs, permissions, and your Alteryx® configuration.

4. In the left menu bar, click the Flows icon. Flows page, open the flow you just created. See Flows Page.
5. In the Flows page, click the dataset you just imported. Click Add new Recipe.
6. Select the recipe. Click Edit Recipe.
7. The initial sample of the dataset is opened in the Transformer page, where you can edit your recipe to transform the dataset.
   
   1. In the Transformer page, some steps are automatically added to the recipe for you. So, you can run the job immediately.
   2. You can add additional steps if desired. See Transformer Page.
8. Click Run Job. 

   1. If options are presented, select the defaults.

   2. To generate results in other formats or output locations, click Add Publishing Destination. Configure the output formats and locations. 
   3. To test dataset profiling, click the Profile Results checkbox. Note that profiling runs as a separate job and may take considerably longer. 
   4. See Run Job Page.

   5. Troubleshooting: Later, you can re-run this job on a different running environment. Some formats are not available across all running environments.

9. When the job completes, you should see a success message under the Jobs tab in the Flow View page. 
   
   1. Troubleshooting: Either the Transform job or the Profiling job may break. To localize the problem, try re-running a job by deselecting the broken job type or running the job on a different running environment (if available). You can also download the log files to try to identify the problem. See Job Details Page.
10. Click View Results from the context menu for the job listing. In the Job Details page, you can see a visual profile of the generated results. See Job Details Page.
11. In the Output Destinations tab, click a link to download the results to your local desktop. 
12. Load these results into a local application to verify that the content looks ok.

Documentation

You can access complete product documentation online and in PDF format. From within the Designer Cloud application, select Help menu > Product Docs.

Next Steps

After you have accessed the documentation, the following topics are relevant to on-premises deployments. Please review them in order.