VMware vSphere Big Data Extensions 2.3 Release Notes

vSphere Big Data Extensions 2.3.1 | 30 March 2016 | Build 3694787

Last Updated on 30 March 2016

Check for additions and updates to these release notes.

What's in the Release Notes

These release notes apply to vSphere Big Data Extensions 2.3 and cover the following topics:

What's New in vSphere Big Data Extensions 2.3.1

Big Data Extensions 2.3.1 is a security update that addresses the Common Vulnerability and Exposure (CVE) item security issue CVE-2015-7547, a security vulnerability exploiting the stack buffer overflow in the glibc library.

If you currently use Big Data Extensions 2.3 or earlier releases, update your environment to Big Data Extensions 2.3.1. To perform the update, follow the upgrade instructions in the VMware vSphere Big Data Extensions Administrator's and User's Guide.

To correct this security issue for existing cluster nodes you may hve created with an earlier version of Big Data Extensions, install and apply the VMware provided security patch. For information on the patch, and instructions on how to download and install it, see KB #2144424

What's New in vSphere Big Data Extensions 2.3

Big Data Extensions enables the rapid deployment of Hadoop clusters on a VMware vSphere virtual platform. This release provides the following new features and enhancements.

Enhancements for Large Scale Production Environments

  • Optimized for Large Scale Deployment. Big Data Extensions provides improved performance, robustness, and fault tolerance in large scale deployments.

  • Multi-Template Virtual Machines.You can configure multiple virtual machine templates and choose which one to use when you create a Big Data cluster. This lets you satisfy customization requirements for different use cases.

  • Add New vSphere Resources. You can add additional resource pools and datastores to a running Big Data cluster, letting you easily expand your environment when a Big Data cluster grows beyond multiple vSphere clusters.

  • Add New Node Groups. You can expand a running Big Data cluster with new node groups. The node groups can use different virtual machine specifications or roles to satisfy new business requirements.
  • Customize Virtual Disks and Controllers. You can control the number of virtual disks per virtual machine in a node group, and specify different virtual disk controller types.

  • Recover from Hardware Failures. If you experience disk or server failures you can recover a cluster using the cluster recover command. Big Data Extensions creates new VMDKs or virtual machines from the available resources, and adds them to the cluster.

Big Data Ecosystem Integration

  • Support for Spark Clusters. You can easily create a Spark cluster using either the Big Data Extensions GUI or Serengeti Command-line interface.

  • Improved HBase Performance. Using new configuration parameters you can create HBase clusters with improved performance.

  • Support for the Latest Hadoop Distributions. Big Data Extensions supports Cloudera CDH 5.4 with Cloudera Manager 5.4, Hortonworks HDP 2.3 with Ambari 2.1, Pivotal PHD 3.0 with Ambari 1.7, MapR 5.0, Apache Bigtop 1.0, and Isilon OneFS 7.2.

Big Data Extensions Operations Management

  • Improved Upgrade and Restoration. You can export configuration information and data from one Big Data Extensions deployment and import it to another Big Data Extensions deployment. This lets you backup and restore a Hadoop or Hbase instance, or upgrade a new Big Data Extensions instance while retaining all data from the previous version.

  • New Linux OS. The Serengeti Management Server and default Hadoop Template virtual machine now use CentOS 6.7.

  • Custom sudo Command. You can specify an alternative sudo command when performing OS level configuration with Big Data Extensions. This lets you use root user management tools such as PowerBroker, a centralized application for the authorization and auditing of commands run as the root user. PowerBroker let's you assign root user privileges to specific users, and authorize and audit their use of the environment.

Before You Begin

Read the vSphere Big Data Extensions documentation for step-by-step instructions on installing and configuring Big Data Extensions.

  • If you currently have Big Data Extensions 1.x, 2.0, or 2.1 and want to upgrade to version 2.3, you must first upgrade to version 2.2 and then upgrade to version 2.3. You cannot upgrade directly from Big Data Extensions 1.x, 2.0, or 2.1 to version 2.3.

  • Use the new upgrade and restoration procedure to upgrade from Big Data Extensions 2.2 to 2.3. This new procedure replaces Virtual Update Manager (VUM), which is not supported in Big Data Extensions 2.3. See Chapter 3, "Upgrading Big Data Extensions" in the VMware vSphere Big Data Extensions Administrator's and User's Guide.

Resolved Issues

The following issues have been resolved for Big Data Extensions 2.3.

  • Updated A critical security vulnerability exploiting the stack buffer overflow in the glibc library was disclosed.

    If you are running Big Data Extensions 2.3, your environment is vulnerable to Common Vulnerability and Exposure (CVE) security issue CVE-2015-7547. You should install and apply the patch to address this issue.

    For information on the patch, and instructions on how to download and install it, see KB #2144424.

  • Specify which network port group to use when creating a network resource with the Big Data Extensions plug-in interface in the vSphere Web Client.
  • In the previous release, when creating a Network Resource using the Big Data Extensions Plug-in, you cloud not select network port groups even though your vCenter Server environment may have been configured with multiple port groups. The Big Data Extensions graphical user interface now lets you select individual port groups.

Known Issues

Big Data Extensions 2.3 has the following known issues. If you encounter an issue that is not in this known issues list, search the VMware Knowledge Base, or let us know by contacting VMware Technical Support.

  • Installation of Big Data Extensions fails if the user name of the logged-in user contains non-ASCII characters
    If the user name of the user who is currently logged in to Big Data Extensions contains non-ASCII characters, the installation of Big Data Extensions fails with the error message: An internal error has occurred - Error #1009.

    Workaround: Log in with a user name that does not contain non-ASCII characters and retry the installation.

  • The German and French versions of the Serengeti Command-Line Client display non-ASCII characters as questions marks.

    When running the German and French versions of the Serengeti CLI from a Windows command console, non-ASCII characters display as questions marks.

    Workaround: Use only ASCII characters for user names, object labels, and configuration values within your Big Data Extensions Environment when using the German and French versions of the Serengeti CLI.