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VMware vSphere Big Data Extensions Release Notes

VMware vSphere Big Data Extensions 1.0 Beta Release Notes

All information about this release is highly confidential and subject to the non-disclosure terms and conditions in the Master Software Beta Test Agreement that your company has already agreed to.

VMware vSphere Big Data Extensions 1.0 Beta Release Notes | 25 June 2013 | Build 1190989

What's in the Release Notes

These release notes discuss the following topics:

What's New in vSphere Big Data Extensions

vSphere Big Data Extensions is a virtualization platform that enables provisioning and lifecycle management of Hadoop on VMware vSphere. This release provides the following features and enhancements.

  • Big Data Extensions Graphical User Interface. Installed as a plug-in within vSphere Web Client, Big Data Extensions graphical user interface is designed to make administration of Hadoop clusters running within vSphere simple and straightforward. With Big Data Extensions you can easily deploy and operate Hadoop and HBase clusters. The application automates the provisioning process, reducing deployment time from weeks to minutes, gives you a real-time view of running nodes and services, provides a single management console from which to scale the size of your Hadoop clusters, and incorporates reporting and diagnostic tools to help you optimize performance and utilization.
  • You can perform the following tasks with the Big Data Extensions graphical user interface.

    • Create, scale-out, and delete clusters.
    • Manage vSphere resources for use by Hadoop clusters.
    • Manage and monitor Hadoop clusters.
    • Control Hadoop resource usage.

  • Support for all Major Hadoop Distributions. Big Data Extensions supports the following Hadoop distributions.
  • Apache Hadoop 1.2. Contains VMware’s Hadoop Virtualization Extensions(HVE), which improves Apache Hadoop performance in virtual environments by enhancing Hadoop’s topology awareness mechanism to account for the virtualization layer.

    Cloudera Distribution for Apache Hadoop 4.2 (CDH4). CDH4 provides support for both MapReduce v1 and MapReduce v2.

    Cloudera Distribution for Apache Hadoop 3 (CDH3) Update 6.

    Hortonworks Data Platform (HDP) 1.3.

    MapR 2.1.3. Enables separation of data and compute in MapR clusters.

    Pivotal HD 1.0 (with MapReduce v2). Pivotal HD 1.0 uses VMware’s Hadoop Virtualization Extensions (HVE), which improves Apache Hadoop performance in virtual environments by enhancing Hadoop’s topology awareness mechanism to account for the virtualization layer


  • Automatic Elasticity. Big Data Extensions can automatically scale the number of compute virtual machines in a Hadoop cluster based on contention from other workloads running on the same shared physical infrastructure. Compute virtual machines are added or removed from the Hadoop cluster as needed to best meet performance requirements for all workloads running on your vSphere ESXi deployment. This allows you to efficiently share resources across multiple Hadoop clusters.
  • Additionally, Big Data Extensions effectively isolates each Hadoop cluster in its own dedicated resource pool, providing control of cluster resource usage using shares, limits, and reservations.

  • Adjust the Compute and Memory Resources of Running Hadoop Clusters. You can increase or decrease the virtual CPU (vCPU) and memory resources of Hadoop node virtual machines in a running Hadoop cluster to best suit your workloads.

  • Disk Failure Recovery. Using the cluster fix utility, you can easily recover from disk failures of slave nodes in a running Hadoop cluster. The new disk matches the previous disk�s storage type and placement policies.

  • Create a Hadoop Virtual Machine with a Custom Linux CentOS Operating System Configuration. You can create a virtual machine to run your Hadoop cluster using Linux CentOS 6.x with customizations specific to your IT environment. For example, if you want to run Hadoop on Linux CentOS with patches and security settings in support of your organization's IT security policies, you can create a virtual machine using this operating system, and then install Hadoop within this to create a deployment using your preferred operating system configuration.

  • Support for vSphere Standard Edition When Using the Technology Preview. You can use Big Data Extensions with vSphere Standard Edition when using the Technology Preview version of Big Data Extensions.

Installing vSphere Big Data Extensions

Read the vSphere Big Data Extensions Administrator's and User's Guide documentation for step-by-step instructions on installing and configuring Big Data Extensions.

How to Provide Feedback

Your feedback is appreciated. To provide feedback:

Open Source Components for vSphere Big Data Extensions 1.0 Beta

The copyright statements and licenses applicable to the various open source software components distributed in the vSphere Big data Extensions 1.0 Beta are available from the VMware vSphere Big Data Extensions Beta Program page. Click Download Beta and look for Open Source License information within the download page for each of the products included in the Beta program. Because vSphere Big Data Extensions is in Beta phase, these files detail the known open source software components distributed in conjunction with the VMware product as of the publication date of each file and are subject to change.

Notes for the Product Guides

The following information is not currently addressed by the Big Data Extensions product guides.

vCenter Single Sign-On Must Be Enabled When Deploying on vSphere 5.1 or Later When installing Big Data Extensions on vSphere 5.1 or later, you must use vCenter Single Sign-On (SSO) to provide user authentication. When logging in to vSphere 5.1 you pass authentication to the vCenter Single Sign-On server, which you can configure with multiple identity sources such as Active Directory and OpenLDAP. On successful authentication, your username and password is exchanged for a security token which is used to access vSphere components such as Big Data Extensions.

The documentation provided with this Beta release incorrectly states that if you do not enable vCenter SSO, a default administrator credential is used, which you can change at a later time. In fact both the Big Data Extensions plug-in installed within the vSphere Web Client, and the Serengeti Command-Line Interface console fail to authenticate if SSO is not enabled.

Workaround:

  1. When deploying Big Data Extensions on vSphere 5.1 or later, ensure that your environment includes vCenter Single Sign-On.
  2. Provide a vCenter Single Sign-On look-up URL when prompted to do so during the Big Data Extensions installation procedure.

Known Issues

vSphere Big Data Extensions has the following known issues. If you encounter an issue that is not documented in these release notes, search the VMware Knowledge Base, or let us know by contacting VMware Technical Support.


Password Field of the CLI Console Fails to Display When Using Linux CentOS 6.x When using Big Data Extensions with Linux CentOS 6.x, the password field of the deployed Hadoop node console fails to display, preventing you from entering a password and connecting to the nodes in your Hadoop cluster.

Workaround:

  1. Use PuTTY or another Secure Shell (SSH) client to log into the Serengeti Management Server as the user serengeti.
  2. From the same SSH session, connect to a client node as the serengeti user from the Serengeti Management Server.
  3. Change the serengeti user's password on the client node by running the command: sudo passwd serengeti
  4. You are prompted to type a new password for the serengeti user on the client node.
  5. Verify that you can establish an SSH session to the client node using the new password.