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vSphere Big Data Extensions - 2.1
User’s Manual
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VMware vSphere Big Data Extensions - 2.1 Administrator’s Guide

VMware vSphere Big Data Extensions
Administrator's and User's Guide
vSphere Big Data Extensions 2.1
This document supports the version of each product listed and supports all subsequent versions until the document is replaced by a new edition. To check for more recent editions of this document, see http://www.vmware.com/support/pubs.
EN-001535-00
You can find the most up-to-date technical documentation on the VMware Web site at:
http://www.vmware.com/support/
The VMware Web site also provides the latest product updates.
If you have comments about this documentation, submit your feedback to:
docfeedback@vmware.com
Copyright © 2013, 2014 VMware, Inc. All rights reserved. Copyright and trademark information. This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 United States License
(http://creativecommons.org/licenses/by-nd/3.0/us/legalcode).
VMware, Inc.
3401 Hillview Ave. Palo Alto, CA 94304 www.vmware.com
2 VMware, Inc.

Contents

About This Book 7
About VMware vSphere Big Data Extensions 9
1
Getting Started with Big Data Extensions 9
Big Data Extensions and Project Serengeti 10
About Big Data Extensions Architecture 12
About Application Managers 12
Big Data Extensions Support for Hadoop Features By Distribution 15
Hadoop Feature Support By Distribution 17
Installing Big Data Extensions 19
2
System Requirements for Big Data Extensions 19
Internationalization and Localization 22
Deploy the Big Data Extensions vApp in the vSphere Web Client 23
Install RPMs in the Serengeti Management Server Yum Repository 25
Install the Big Data Extensions Plug-In 26
Connect to a Serengeti Management Server 28
Install the Serengeti Remote Command-Line Interface Client 29
Access the Serengeti CLI By Using the Remote CLI Client 30
Upgrading Big Data Extensions 33
3
Prepare to Upgrade Big Data Extensions 33
Upgrade Big Data Extensions Virtual Appliance 34
Upgrade the Big Data Extensions Plug-in 38
Upgrade the Serengeti CLI 38
Upgrade Big Data Extensions Virtual Machine Components by Using the Serengeti Command-Line
Interface 39
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Managing Hadoop Distributions 41
4
Managing Application Managers 41
Hadoop Distribution Deployment Types 43
Configure a Tarball-Deployed Hadoop Distribution by Using the Serengeti Command-Line
Interface 44
Configuring Yum and Yum Repositories 46
Create a Hadoop Template Virtual Machine using RHEL Server 6.x and VMware Tools 54
Maintain a Customized Hadoop Template Virtual Machine 57
Managing the Big Data Extensions Environment 59
5
Add Specific User Names to Connect to the Serengeti Management Server 59
Change the Password for the Serengeti Management Server 60
Configure vCenter Single Sign-On Settings for the Serengeti Management Server 61
3
Create a User Name and Password for the Serengeti Command-Line Interface 61
Stop and Start Serengeti Services 62
Managing vSphere Resources for Clusters 63
6
Add a Resource Pool with the Serengeti Command-Line Interface 63
Remove a Resource Pool with the Serengeti Command-Line Interface 64
Add a Datastore in the vSphere Web Client 64
Remove a Datastore in the vSphere Web Client 65
Add a Network in the vSphere Web Client 65
Reconfigure a Static IP Network in the vSphere Web Client 66
Remove a Network in the vSphere Web Client 66
Creating Hadoop and HBase Clusters 67
7
About Hadoop and HBase Cluster Deployment Types 68
Hadoop Distributions Supporting MapReduce v1 and MapReduce v2 (YARN) 68
About Cluster Topology 69
About HBase Database Access 69
Create a Big Data Cluster in the vSphere Web Client 70
Create an HBase Only Cluster in Big Data Extensions 73
Create a Cluster with an Application Manager by Using the vSphere Web Client 75
Create a Compute Workers Only Cluster by Using the Web Client 75
Managing Hadoop and HBase Clusters 77
8
Set Up a Local Yum Repository for Cloudera Manager Application Manager 78
Set Up a Local Yum Repository for Ambari Application Manager 81
Stop and Start a Hadoop Cluster in the vSphere Web Client 86
Scale Out a Hadoop Cluster in the vSphere Web Client 87
Scale CPU and RAM in the vSphere Web Client 87
Reconfigure a Big Data Cluster with the Serengeti Command-Line Interface 88
Delete a Cluster in the vSphere Web Client 90
About Resource Usage and Elastic Scaling 90
Use Disk I/O Shares to Prioritize Cluster Virtual Machines in the vSphere Web Client 95
About vSphere High Availability and vSphere Fault Tolerance 95
Recover from Disk Failure with the Serengeti Command-Line Interface Client 95
Log in to Hadoop Nodes with the Serengeti Command-Line Interface Client 96
Change the User Password on All of the Nodes of a Cluster 97
Monitoring the Big Data Extensions Environment 99
9
View Serengeti Management Server Initialization Status 99
View Clusters in the vSphere Web Client 100
View Provisioned Clusters in the vSphere Web Client 100
View Cluster Information in the vSphere Web Client 101
Monitor the Hadoop Distributed File System Status in the vSphere Web Client 102
Monitor MapReduce Status in the vSphere Web Client 103
Monitor HBase Status in the vSphere Web Client 103
Accessing Hive Data with JDBC or ODBC 105
10
Configure Hive to Work with JDBC 105
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Configure Hive to Work with ODBC 107
Contents
Troubleshooting 109
11
Log Files for Troubleshooting 110
Configure Serengeti Logging Levels 110
Collect Log Files for Troubleshooting 111
Big Data Extensions Virtual Appliance Upgrade Fails 111
Troubleshooting Cluster Creation Failures 112
Cannot Restart or Reconfigure a Cluster For Which the Time Is Not Synchronized 118
Cannot Restart or Reconfigure a Cluster After Changing Its Distribution 119
Virtual Machine Cannot Get IP Address and Command Fails 119
vCenter Server Connections Fail to Log In 119
SSL Certificate Error When Connecting to Non-Serengeti Server with the vSphere Console 120
Serengeti Operations Fail After You Rename a Resource in vSphere 120
A New Plug-In Instance with the Same or Earlier Version Number as a Previous Plug-In Instance
Does Not Load 121
MapReduce Job Fails to Run and Does Not Appear In the Job History 121
Cannot Submit MapReduce Jobs for Compute-Only Clusters with External Isilon HDFS 122
MapReduce Job Stops Responding on a PHD or CDH4 YARN Cluster 122
Unable to Connect the Big Data Extensions Plug-In to the Serengeti Server 123
Cannot Perform Serengeti Operations after Deploying Big Data Extensions 123
Host Name and FQDN Do Not Match for Serengeti Management Server 124
Upgrade Cluster Error When Using Cluster Created in Earlier Version of Big Data Extensions 125
Non-ASCII characters are not displayed correctly 126
Cannot Change the Serengeti Server IP Address From the vSphere Web Client 126
Big Data Extensions Server Does Not Accept Resource Names With Two or More Contiguous
White Spaces 127
Remove the HBase Rootdir in HDFS Before You Delete the HBase Only Cluster 127
Management Server Cannot Connect to vCenter Server 127
Virtual Update Manager Does Not Upgrade the Hadoop Template Virtual Machine Under Big
Data Extensions vApp 128
Cannot Download the Package When Using Downloadonly Plugin 128
Cannot Find Packages When You Use Yum Search 129
Index 131
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6 VMware, Inc.

About This Book

VMware vSphere Big Data Extensions Administrator's and User's Guide describes how to install VMware vSphere Big Data Extensions™ within your vSphere environment, and how to manage and monitor Hadoop and HBase clusters using the Big Data Extensions plug-in for vSphere Web Client.
VMware vSphere Big Data Extensions Administrator's and User's Guide also describes how to perform Hadoop and HBase operations using the VMware Serengeti™ Command-Line Interface Client, which provides a greater degree of control for certain system management and big data cluster creation tasks.
Intended Audience
This guide is for system administrators and developers who want to use Big Data Extensions to deploy and manage Hadoop clusters. To successfully work with Big Data Extensions, you should be familiar with VMware® vSphere® and Hadoop and HBase deployment and operation.
VMware Technical Publications Glossary
VMware Technical Publications provides a glossary of terms that might be unfamiliar to you. For definitions of terms as they are used in VMware technical documentation, go to
http://www.vmware.com/support/pubs.
VMware, Inc.
7
8 VMware, Inc.
About VMware vSphere Big Data
Extensions 1
VMware vSphere Big Data Extensions lets you deploy and centrally operate big data clusters running on VMware vSphere. Big Data Extensions simplifies the Hadoop and HBase deployment and provisioning process, and gives you a real time view of the running services and the status of their virtual hosts. It provides a central place from which to manage and monitor your big data cluster, and incorporates a full range of tools to help you optimize cluster performance and utilization.
This chapter includes the following topics:
“Getting Started with Big Data Extensions,” on page 9
n
“Big Data Extensions and Project Serengeti,” on page 10
n
“About Big Data Extensions Architecture,” on page 12
n
“About Application Managers,” on page 12
n
“Big Data Extensions Support for Hadoop Features By Distribution,” on page 15
n
“Hadoop Feature Support By Distribution,” on page 17
n

Getting Started with Big Data Extensions

Big Data Extensions lets you deploy big data clusters. The tasks in this section describe how to set up VMware vSphere® for use with Big Data Extensions, deploy the Big Data Extensions vApp, access the VMware vCenter Server® and command-line interface (CLI) administrative consoles, and configure a Hadoop distribution for use with Big Data Extensions.
Prerequisites
Understand what Project Serengeti® and Big Data Extensions is so that you know how they fit into your
n
big data workflow and vSphere environment.
Verify that the Big Data Extensions features that you want to use, such as data-compute separated
n
clusters and elastic scaling, are supported by Big Data Extensions for the Hadoop distribution that you want to use.
Understand which features are supported by your Hadoop distribution.
n
Procedure
1 Do one of the following.
Install Big Data Extensions for the first time. Review the system requirements, install vSphere, and
n
install the Big Data Extensions components: Big Data Extensions vApp, Big Data Extensions plug­in for vCenter Server, and Serengeti CLI Client.
Upgrade Big Data Extensions from a previous version. Perform the upgrade steps.
n
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9
2 (Optional) Install and configure a distribution other than Apache Hadoop for use with
Big Data Extensions.
Apache Hadoop is included in the Serengeti Management Server, but you can use any Hadoop distribution that Big Data Extensions supports.
What to do next
After you have successfully installed and configured your Big Data Extensions environment, you can perform the following additional tasks, in any order.
Stop and start the Serengeti services, create user accounts, manage passwords, and log in to cluster
n
nodes to perform troubleshooting.
Manage the vSphere resource pools, datastores, and networks that you use to create Hadoop and HBase
n
clusters.
Create, provision, and manage big data clusters.
n
Monitor the status of the clusters that you create, including their datastores, networks, and resource
n
pools, through the vSphere Web Client and the Serengeti Command-Line Interface.
On your Big Data clusters, run HDFS commands, Hive and Pig scripts, and MapReduce jobs, and access
n
Hive data.
If you encounter any problems when using Big Data Extensions, see Chapter 11, “Troubleshooting,” on
n
page 109.

Big Data Extensions and Project Serengeti

Big Data Extensions runs on top of Project Serengeti, the open source project initiated by VMware to automate the deployment and management of Hadoop and HBase clusters on virtual environments such as vSphere.
Big Data Extensions and Project Serengeti provide the following components.
Project Serengeti
Serengeti Management Server
An open source project initiated by VMware, Project Serengeti lets users deploy and manage big data clusters in a vCenter Server managed environment. The major components are the Serengeti Management Server, which provides cluster provisioning, software configuration, and management services; an elastic scaling framework; and command-line interface. Project Serengeti is made available under the Apache 2.0 license, under which anyone can modify and redistribute Project Serengeti according to the terms of the license.
Provides the framework and services to run Big Data clusters on vSphere. The Serengeti Management Server performs resource management, policy­based virtual machine placement, cluster provisioning, software configuration management, and environment monitoring.
10 VMware, Inc.
Chapter 1 About VMware vSphere Big Data Extensions
Serengeti Command­Line Interface Client
Big Data Extensions
The command-line interface (CLI) client provides a comprehensive set of tools and utilities with which to monitor and manage your Big Data deployment. If you are using the open source version of Serengeti without Big Data Extensions, the CLI is the only interface through which you can perform administrative tasks. For more information about the CLI, see the VMware vSphere Big Data Extensions Command-Line Interface Guide.
The commercial version of the open source Project Serengeti from VMware, Big Data Extensions, is delivered as a vCenter Server Appliance. Big Data Extensions includes all the Project Serengeti functions and the following additional features and components.
Enterprise level support from VMware.
n
Hadoop distribution from the Apache community.
n
NOTE VMware provides the Hadoop distribution as a convenience but does not provide enterprise-level support. The Apache Hadoop distribution is supported by the open source community.
The Big Data Extensions plug-in, a graphical user interface integrated
n
with vSphere Web Client. This plug-in lets you perform common Hadoop infrastructure and cluster management administrative tasks.
Elastic scaling lets you optimize cluster performance and utilization of
n
physical compute resources in a vSphere environment. Elasticity­enabled clusters start and stop virtual machines, adjusting the number of active compute nodes based on configuration settings that you specify, to optimize resource consumption. Elasticity is ideal in a mixed workload environment to ensure that workloads can efficiently share the underlying physical resources while high-priority jobs are assigned sufficient resources.
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CLI GUI
Rest API
VM and Application
Provisioning Framework
Software Management SPI
Default
adapter
Cloudera
adapter
Ambari
adapter
Software
Management
Thrift Service
Cloudera
Manager
Server
Ambari
Server

About Big Data Extensions Architecture

The Serengeti Management Server and Hadoop Template virtual machine work together to configure and provision big data clusters.
Figure 1‑1. Big Data Extensions Architecture
Big Data Extensions performs the following steps to deploy a big data cluster.
1 The Serengeti Management Server searches for ESXi hosts with sufficient resources to operate the
cluster based on the configuration settings that you specify, and then selects the ESXi hosts on which to place Hadoop virtual machines.
2 The Serengeti Management Server sends a request to the vCenter Server to clone and configure virtual
machines to use with the big data cluster.
3 The Serengeti Management Server configures the operating system and network parameters for the
new virtual machines.
4 Each virtual machine downloads the Hadoop software packages and installs them by applying the
distribution and installation information from the Serengeti Management Server.
5 The Serengeti Management Server configures the Hadoop parameters for the new virtual machines
based on the cluster configuration settings that you specify.
6 The Hadoop services are started on the new virtual machines, at which point you have a running
cluster based on your configuration settings.

About Application Managers

You can use Cloudera Manager, Ambari, and the default application manager to provision and manage clusters with VMware vSphere Big Data Extensions.
After you add a new Cloudera Manager or Ambari application manager to Big Data Extensions, you can redirect your software management tasks, including monitoring and managing clusters, to that application manager.
12 VMware, Inc.
Chapter 1 About VMware vSphere Big Data Extensions
You can use an application manager to perform the following tasks:
List all available vendor instances, supported distributions, and configurations or roles for a specific
n
application manager and distribution.
Create clusters.
n
Monitor and manage services from the application manager console.
n
Check the documentation for your application manager for tool-specific requirements.
Restrictions
The following restrictions apply to Cloudera Manager and Ambari application managers:
To add a application manager with HTTPS, use the FQDN instead of the URL.
n
You cannot rename a cluster that was created with a Cloudera Manager or Ambari application
n
manager.
You cannot change services for a big data cluster from Big Data Extensions if the cluster was created
n
with Ambari or Cloudera application manager.
To change services, configurations, or both, you must make the changes manually from the application
n
manager on the nodes.
If you install new services, Big Data Extensions starts and stops the new services together with old services.
If you use an application manager to change services and big data cluster configurations, those changes
n
cannot be synced from Big Data Extensions. The nodes that you created with Big Data Extensions do not contain the new services or configurations.

Services and Operations Supported by the Application Managers

If you use Cloudera Manager or Ambari with Big Data Extensions, there are several additional services that are available for your use.
Supported Application Managers and Distributions
Big Data Extensions supports certain application managers and Hadoop distributions.
Table 1‑1. Supported application managers and Hadoop distributions
Application Managers Supported Version Supported Distributions
Cloudera Manager 5 CDH 4.7, 5.0, 5.1
Ambari 1.6 HDP 1.3.2, 2.0, 2.1
Default .8 CDH 4.7, 5.0, 5.1, HDP 1.3, 2.0, 2.1
Supported Features and Operations
The following features and operations are available when you use the Ambari application manager 1.6.0,
1.6.1 (with versions HDP 1.3, 1.3.2, 2.0, 2.1) and the Cloudera Manager application manager 5.0.x, 5.1.x (with versions CDH 4.x, 5.x) on Big Data Extensions.
Cluster Delete
n
Cluster Export (can only be performed with the Serengeti CLI)
n
Cluster List
n
Cluster Resume
n
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Cluster Start/Stop
n
Hadoop Cluster
n
HBase Cluster
n
HDFS High Availability (available only with Cloudera Manager)
n
Scale Out
n
Topology Awareness (RACK_AS_RACK or HOST_AS_RACK)
n
vSphere Fault Tolerance
n
vSphere High Availability
n
Services supported on Cloudera Manager and Ambari
Table 1‑2. Services supported on Cloudera Manager and Ambari
Service Name Cloudera Manager 5.1 Cloudera Manager 5.0 Ambari 1.6
Falcon X
Flume X
Ganglia X
HBase X X X
HCatalog X
HDFS X X X
Hive X X X
Hue X X X
Impala X X
MapReduce X X X
Nagios X
Oozie X X X
Pig X
Sentry X
Solr X X
Spark X
Sqoop X
Storm X
TEZ X
WebHCAT X
YARN X X X
Zookeeper X X X
For information about how to use an application manager with the CLI, see the VMware vSphere Big Data Extensions Command-Line Interface Guide.
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Chapter 1 About VMware vSphere Big Data Extensions

Big Data Extensions Support for Hadoop Features By Distribution

Big Data Extensions provides different levels of feature support depending on the distribution and version that you configure for use with the default application manager.
Support for Hadoop MapReduce v1 Distribution Features
Table 1-3 lists the supported Hadoop MapReduce v1 distributions and indicates which features are
supported when you use the distribution with the default application manager on Big Data Extensions.
Table 1‑3. Big Data Extensions Feature Support for Hadoop MapReduce v1 Distributions
Apache Hadoop Cloudera Hortonworks MapR
Version 1.2.1 4.7 - 5.1 1.3 - 2.1 3.0.2-3.1.0
Automatic Deployment
Scale Out Yes Yes Yes Yes
Create Cluster with Multiple Networks
Data-Compute Separation
Compute-only Yes Yes Yes No
Elastic Scaling of Compute Nodes
Hadoop Configuration
Hadoop Topology Configuration
Run Hadoop Commands from the CLI
Hadoop Virtualization Extensions (HVE)
vSphere HA Yes Yes Yes Yes
Service Level vSphere HA
vSphere FT Yes Yes Yes Yes
Yes Yes Yes Yes
Yes Yes Yes No
Yes Yes Yes Yes
Yes Yes when using
MapReduce v1
Yes Yes Yes No
Yes Yes Yes No
Yes No No No
Yes No Yes No
Yes See “About Service
Level vSphere HA for Cloudera,” on
page 16
Yes No
Yes No
Support for Hadoop MapReduce v2 (YARN) Distribution Features
Table 1-4 lists the supported Hadoop MapReduce v2 distributions and indicates which features are
supported when you use the distribution with the default application manager on Big Data Extensions.
VMware, Inc. 15
Table 1‑4. Big Data Extensions Feature Support for Hadoop MapReduce v2 (YARN) Distributions
Apache Bigtop
Apache Hadoop Cloudera Cloudera
Version 0.8 2.0 4.7 5.0, 5.1 1.3 - 2.1 2.0, 2.1
Automatic
Yes Yes Yes Yes Yes Yes Deploymen t
Scale Out Yes Yes Yes Yes Yes Yes
Create
Yes Yes Yes Yes Yes Yes Cluster with Multiple Networks
Data-
Yes Yes Yes Yes Yes Yes Compute Separation
Compute-
Yes Yes Yes Yes Yes Yes only
Elastic
Yes Yes No when Scaling of Compute Nodes
Hadoop
Yes Yes Yes Yes Yes Yes Configurati on
Hadoop
Yes Yes Yes Yes Yes Yes Topology Configurati on
Run
No No No No No No Hadoop Commands from the CLI
Hadoop Virtualizati
Support only
for HDFS
Support only
for HDFS on Extensions (HVE)
vSphere
No No No No No No
HA
Service
No No See “About Level vSphere HA
vSphere FT No No No No No No
No when using MapReduce 2
using
MapReduce
2
No Support only
for HDFS
See “About
Service Level vSphere HA for Cloudera,”
on page 16
Service Level
vSphere HA
for
Cloudera,”
on page 16
Hortonwork s Pivotal
Yes No
Support only
Yes for HDFS. HDP 1.3 provides full support.
No No
About Service Level vSphere HA for Cloudera
The Cloudera distributions offer the following support for Service Level vSphere HA.
Cloudera using MapReduce v1 provides service level vSphere HA support for JobTracker.
n
Cloudera provides its own service level HA support for NameNode through HDFS2.
n
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Chapter 1 About VMware vSphere Big Data Extensions

Hadoop Feature Support By Distribution

Each Hadoop distribution and version provides differing feature support. Learn which Hadoop distributions support which features.
Hadoop Features
The table illustrates which Hadoop distributions support which features when you use the distributions with the default application manager on Big Data Extensions.
Table 1‑5. Hadoop Feature Support
Apache Hadoop
Version 1.2.1 0.8 4.7 -5.1 1.3 2.0, 2.1 3.0.2-3.1.0 2.0 , 2.1
HDFS1 Yes Yes No Yes Yes No No
HDFS2 No Yes Yes No No No Yes
MapReduce v1 Yes Yes Yes Yes Yes Yes No
MapReduce v2 (YARN)
Pig Yes Yes Yes Yes Yes Yes Yes
Hive Yes Yes Yes Yes Yes Yes Yes
Hive Server Yes Yes Yes Yes Yes Yes Yes
HBase Yes Yes Yes Yes Yes Yes Yes
ZooKeeper Yes Yes Yes Yes Yes Yes Yes
No Yes Yes No Yes No Yes
Apache Bigtop Cloudera Hortonworks Hortonworks MapR Pivotal
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Installing Big Data Extensions 2

To install Big Data Extensions so that you can create and provision big data clusters, you must install the Big Data Extensions components in the order described.
What to do next
If you want to create clusters on any Hadoop distribution other than Apache Hadoop, which is included in theSerengeti Management Server, install and configure the distribution for use with Big Data Extensions.
This chapter includes the following topics:
“System Requirements for Big Data Extensions,” on page 19
n
“Internationalization and Localization,” on page 22
n
“Deploy the Big Data Extensions vApp in the vSphere Web Client,” on page 23
n
“Install RPMs in the Serengeti Management Server Yum Repository,” on page 25
n
“Install the Big Data Extensions Plug-In,” on page 26
n
“Connect to a Serengeti Management Server,” on page 28
n
“Install the Serengeti Remote Command-Line Interface Client,” on page 29
n
“Access the Serengeti CLI By Using the Remote CLI Client,” on page 30
n

System Requirements for Big Data Extensions

Before you begin the Big Data Extensions deployment tasks, your system must meet all of the prerequisites for vSphere, clusters, networks, storage, hardware, and licensing.
Big Data Extensions requires that you install and configure vSphere and that your environment meets minimum resource requirements. Make sure that you have licenses for the VMware components of your deployment.
vSphere Requirements
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Before you install Big Data Extensions, set up the following VMware products.
Install vSphere 5.0 (or later) Enterprise or Enterprise Plus.
n
NOTE The Big Data Extensions graphical user interface is supported only when using vSphere Web Client 5.1 and later. If you install Big Data Extensions on vSphere 5.0, perform all administrative tasks using the Serengeti CLI.
When you install Big Data Extensions on vSphere 5.1 or later, use
n
VMware® vCenter™ Single Sign-On to provide user authentication. When logging in to vSphere 5.1 or later 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 user name and password is exchanged for a security token that is used to access vSphere components such as Big Data Extensions.
Configure all ESXi hosts to use the same Network Time Protocol (NTP)
n
server.
On each ESXi host, add the NTP server to the host configuration, and
n
from the host configuration's Startup Policy list, select Start and stop with host. The NTP daemon ensures that time-dependent processes
occur in sync across hosts.
Cluster Settings
Network Settings
Configure your cluster with the following settings.
Enable vSphere HA and VMware vSphere® Distributed Resource
n
Scheduler™.
Enable Host Monitoring.
n
Enable admission control and set the policy you want. The default
n
policy is to tolerate one host failure.
Set the virtual machine restart priority to high.
n
Set the virtual machine monitoring to virtual machine and application
n
monitoring.
Set the monitoring sensitivity to high.
n
Enable vMotion and Fault Tolerance logging.
n
All hosts in the cluster have Hardware VT enabled in the BIOS.
n
The Management Network VMkernel Port has vMotion and Fault
n
Tolerance logging enabled.
Big Data Extensions can deploy clusters on a single network or use multiple networks. The environment determines how port groups that are attached to NICs are configured and which network backs each port group.
You can use either a vSwitch or vSphere Distributed Switch (vDS) to provide the port group backing a Serengeti cluster. vDS acts as a single virtual switch across all attached hosts while a vSwitch is per-host and requires the port group to be configured manually.
When you configure your networks to use with Big Data Extensions, verify that the following ports are open as listening ports.
Ports 8080 and 8443 are used by the Big Data Extensions plug-in user
n
interface and the Serengeti Command-Line Interface Client.
Port 5480 is used by vCenter Single Sign-On for monitoring and
n
management.
Port 22 is used by SSH clients.
n
To prevent having to open a network firewall port to access Hadoop
n
services, log into the Hadoop client node, and from that node you can access your cluster.
20 VMware, Inc.
Chapter 2 Installing Big Data Extensions
To connect to the internet (for example, to create an internal yum
n
repository from which to install Hadoop distributions), you may use a proxy.
To enable communications, be sure that firewalls and web filters do not
n
block the Serengeti Management Server or other Serengeti nodes.
Direct Attached Storage
Resource Requirements for the vSphere Management Server and Templates
Resource Requirements for the Hadoop Cluster
Attach and configure direct attached storage on the physical controller to present each disk separately to the operating system. This configuration is commonly described as Just A Bunch Of Disks (JBOD). Create VMFS datastores on direct attached storage using the following disk drive recommendations.
8-12 disk drives per host. The more disk drives per host, the better the
n
performance.
1-1.5 disk drives per processor core.
n
7,200 RPM disk Serial ATA disk drives.
n
Resource pool with at least 27.5GB RAM.
n
40GB or more (recommended) disk space for the management server
n
and Hadoop template virtual disks.
Datastore free space is not less than the total size needed by the Hadoop
n
cluster, plus swap disks for each Hadoop node that is equal to the memory size requested.
Network configured across all relevant ESXi hosts, and has connectivity
n
with the network in use by the management server.
vSphere HA is enabled for the master node if vSphere HA protection is
n
needed. To use vSphere HA or vSphere FT to protect the Hadoop master node, you must use shared storage.
Hardware Requirements for the vSphere and Big Data Extensions Environment
Tested Host and Virtual Machine Support
vSphere Licensing
Host hardware is listed in the VMware Compatibility Guide. To run at optimal performance, install your vSphere and Big Data Extensions environment on the following hardware.
Dual Quad-core CPUs or greater that have Hyper-Threading enabled. If
n
you can estimate your computing workload, consider using a more powerful CPU.
Use High Availability (HA) and dual power supplies for the master
n
node's host machine.
4-8 GBs of memory for each processor core, with 6% overhead for
n
virtualization.
Use a 1GB Ethernet interface or greater to provide adequate network
n
bandwidth.
The maximum host and virtual machine support that has been confirmed to successfully run with Big Data Extensions is 128 physical hosts running a total of 512 virtual machines.
You must use a vSphere Enterprise license or above to use VMware vSphere HA and vSphere DRS.
VMware, Inc. 21

Internationalization and Localization

Big Data Extensions supports internationalization (I18N) level 1. However, there are resources you specify that do not provide UTF-8 support. You can use only ASCII attribute names consisting of alphanumeric characters and underscores (_) for these resources.
Big Data Extensions Supports Unicode UTF-8
vCenter Server resources you specify using both the CLI and vSphere Web Client can be expressed with underscore (_), hyphen (-), blank spaces, and all letters and numbers from any language. For example, you can specify resources such as datastores labeled using non-English characters.
When using a Linux operating system, you should configure the system for use with UTF-8 encoding specific to your locale. For example, to use U.S. English, specify the following locale encoding: en_US.UTF-8. See your vendor's documentation for information on configuring UTF-8 encoding for your Linux environment.
Special Character Support
The following vCenter Server resources can have a period (.) in their name, letting you select them using both the CLI and vSphere Web Client.
portgroup name
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cluster name
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resource pool name
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datastore name
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The use of a period is not allowed in the Serengeti resource name.
Resources Excluded From Unicode UTF-8 Support
The Serengeti cluster specification file, manifest file, and topology racks-hosts mapping file do not provide UTF-8 support. When you create these files to define the nodes and resources for use by the cluster, use only ASCII attribute names consisting of alphanumeric characters and underscores (_).
The following resource names are excluded from UTF-8 support:
cluster name
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nodeGroup name
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node name
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virtual machine name
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The following attributes in the Serengeti cluster specification file are excluded from UTF-8 support:
distro name
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role
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cluster configuration
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storage type
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haFlag
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instanceType
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Chapter 2 Installing Big Data Extensions
groupAssociationsType
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The rack name in the topology racks-hosts mapping file, and the placementPolicies field of the Serengeti cluster specification file is also excluded from UTF-8 support.

Deploy the Big Data Extensions vApp in the vSphere Web Client

Deploying the Big Data Extensions vApp is the first step in getting your Hadoop cluster up and running with Big Data Extensions.
Prerequisites
Install and configure vSphere.
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Configure all ESXi hosts to use the same NTP server.
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On each ESXi host, add the NTP server to the host configuration, and from the host configuration's
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Startup Policy list, select Start and stop with host. The NTP daemon ensures that time-dependent processes occur in sync across hosts.
When installing Big Data Extensions on vSphere 5.1 or later, use vCenter Single Sign-On to provide
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user authentication.
Verify that you have one vSphere Enterprise license for each host on which you deploy virtual Hadoop
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nodes. You manage your vSphere licenses in the vSphere Web Client or in vCenter Server.
Install the Client Integration plug-in for the vSphere Web Client. This plug-in enables OVF deployment
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on your local file system.
NOTE Depending on the security settings of your browser, you might have to approve the plug-in when you use it the first time.
Download theBig Data ExtensionsOVA from the VMware download site.
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Verify that you have at least 40GB disk space available for the OVA. You need additional resources for
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the Hadoop cluster.
Ensure that you know the vCenter Single Sign-On Look-up Service URL for your vCenter Single Sign-
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On service.
If you are installing Big Data Extensions on vSphere 5.1 or later, ensure that your environment includes vCenter Single Sign-On. Use vCenter Single Sign-On to provide user authentication on vSphere 5.1 or later.
Procedure
1 In the vSphere Web Client vCenter Hosts and Clusters view, select Actions > All vCenter Actions >
Deploy OVF Template.
2 Choose the location where the Big Data Extensions OVA resides and click Next.
Option Description
Deploy from File
Deploy from URL
Browse your file system for an OVF or OVA template.
Type a URL to an OVF or OVA template located on the internet. For example: http://vmware.com/VMTN/appliance.ovf.
3 View the OVF Template Details page and click Next.
4 Accept the license agreement and click Next.
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5 Specify a name for the vApp, select a target datacenter for the OVA, and click Next.
The only valid characters for Big Data Extensions vApp names are alphanumeric and underscores. The vApp name must be < 60 characters. When you choose the vApp name, also consider how you will name your clusters. Together the vApp and cluster names must be < 80 characters.
6 Select a vSphere resource pool for the OVA and click Next.
Select a top-level resource pool. Child resource pools are not supported by Big Data Extensions even though you can select a child resource pool. If you select a child resource pool, you will not be able to create clusters from Big Data Extensions.
7 Select shared storage for the OVA and click Next.
If shared storage is not available, local storage is acceptable.
8 For each network specified in the OVF template, select a network in the Destination Networks column
in your infrastructure to set up the network mapping.
The first network lets the Management Server communicate with your Hadoop cluster. The second network lets the Management Server communicate with vCenter Server. If your vCenter Server deployment does not use IPv6, you can specify the same IPv4 destination network for use by both source networks.
9 Configure the network settings for your environment, and click Next.
a Enter the network settings that let the Management Server communicate with your Hadoop
cluster.
Use a static IPv4 (IP) network. An IPv4 address is four numbers separated by dots as in aaa.bbb.ccc.ddd, where each number ranges from 0 to 255. You must enter a netmask, such as
255.255.255.0, and a gateway address, such as 192.168.1.253.
If the vCenter Server or any ESXi host or Hadoop distribution repository is resolved using a fully qualified domain name (FQDN), you must enter a DNS address. Enter the DNS server IP address as DNS Server 1. If there is a secondary DNS server, enter its IP address as DNS Server 2.
NOTE You cannot use a shared IP pool with Big Data Extensions.
b (Optional) If you are using IPv6 between the Management Server and vCenter Server, select the
Enable Ipv6 Connection checkbox.
Enter the IPv6 address, or FQDN, of the vCenter Server. The IPv6 address size is 128 bits. The preferred IPv6 address representation is: xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx where each x is a hexadecimal digit representing 4 bits. IPv6 addresses range from 0000:0000:0000:0000:0000:0000:0000:0000 to ffff:ffff:ffff:ffff:ffff:ffff:ffff:ffff. For convenience, an IPv6 address may be abbreviated to shorter notations by application of the following rules.
Remove one or more leading zeroes from any groups of hexadecimal digits. This is usually
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done to either all or none of the leading zeroes. For example, the group 0042 is converted to 42.
Replace consecutive sections of zeroes with a double colon (::). You may only use the double
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colon once in an address, as multiple uses would render the address indeterminate. RFC 5952 recommends that a double colon not be used to denote an omitted single section of zeroes.
The following example demonstrates applying these rules to the address
2001:0db8:0000:0000:0000:ff00:0042:8329.
Removing all leading zeroes results in the address 2001:db8:0:0:0:ff00:42:8329.
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Omitting consecutive sections of zeroes results in the address 2001:db8::ff00:42:8329.
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See RFC 4291 for more information on IPv6 address notation.
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Chapter 2 Installing Big Data Extensions
10 Verify that the Initialize Resources check box is selected and click Next.
If the check box is unselected, the resource pool, data store, and network connection assigned to the vApp will not be added to Big Data Extensions.
If you do not add the resource pool, datastore, and network when you deploy the vApp, use the vSphere Web Client or the Serengeti CLI Client to specify the resource pool, datastore, and network information before you create a Hadoop cluster.
11 Run the vCenter SSO Lookup Service URL to enable vCenter SSO.
If you use vCenter 5.x, use the following URL: https://FQDN_or_IP_of_SSO_SERVER:
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7444/lookupservice/sdk
If you use vCenter 6.0, use the following URL: https://FQDN_of_SSO_SERVER:
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443/lookupservice/sdk
If you don't input the URL, vCenter SSO is disabled.
12 Verify the vService bindings and click Next.
13 Verify the installation information and click Finish.
vCenter Server deploys the Big Data Extensions vApp. When deployment finishes, two virtual machines are available in the vApp.
The Management Server virtual machine, management-server (also called the Serengeti
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Management Server), which is started as part of the OVA deployment.
The Hadoop Template virtual machine, hadoop-template, which is not started. Big Data Extensions
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clones Hadoop nodes from this template when provisioning a cluster. Do not start or stop this virtual machine without good reason. The template does not include a Hadoop distribution.
IMPORTANT Do not delete any files under the /opt/serengeti/.chef directory. If you delete any of these files, such as the sernegeti.pem file, subsequent upgrades to Big Data Extensions might fail without displaying error notifications.
What to do next
Install the Big Data Extensions plug-in within the vSphere Web Client. See “Install the Big Data Extensions
Plug-In,” on page 26.
If the Initialize Resources check box is not selected, add resources to the Big Data Extensions server before you create a Hadoop cluster.

Install RPMs in the Serengeti Management Server Yum Repository

Install the wsdl4j and mailx RPM packages within the internal Yum repository of the Serengeti Management Server.
Prerequisites
Deploy the Big Data Extensions vApp.
Procedure
1 Open a command shell, such as Bash or PuTTY, and log in to the Serengeti Management Server as the
user serengeti.
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2 Download and install the wsdl4j and mailx RPM packages.
If the Serengeti Management Server can connect to the Internet, run the commands as shown in the
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example below to download the RPMs, copy the files to the required directory, and create a repository.
cd /opt/serengeti/www/yum/repos/centos/6/base/RPMS/ wget http://mirror.centos.org/centos/6/os/x86_64/Packages/mailx-12.4-7.el6.x86_64.rpm wget http://mirror.centos.org/centos/6/os/x86_64/Packages/wsdl4j-1.5.2-7.8.el6.noarch.rpm createrepo ..
If the Serengeti Management Server can not connect to the Internet, you must manually download
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the RPMs, copy the files to the required directory, and create a repository.
a Download the RPM files as shown in the example below.
http://mirror.centos.org/centos/6/os/x86_64/Packages/mailx-12.4-7.el6.x86_64.rpm http://mirror.centos.org/centos/6/os/x86_64/Packages/wsdl4j-1.5.2-7.8.el6.noarch.rpm
b Copy the RPM files to /opt/serengeti/www/yum/repos/centos/6/base/RPMS/.
c Run the createrepo command to create a repository from the RPMs you downloaded.
createrepo /opt/serengeti/www/yum/repos/centos/6/base/
What to do next
Install the Serengeti Remote Command-Line Interface client.

Install the Big Data Extensions Plug-In

To enable the Big Data Extensions user interface for use with a vCenter Server Web Client, register the plug­in with the vSphere Web Client. The Big Data Extensions graphical user interface is supported only when you use vSphere Web Client 5.1 and later.
If you install Big Data Extensions on vSphere 5.0, perform all administrative tasks by using the Serengeti Serengeti CLI Client.
The Big Data Extensions plug-in provides a GUI that integrates with the vSphere Web Client. Using the Big Data Extensions plug-in interface you can perform common Hadoop infrastructure and cluster management tasks.
NOTE Use only the Big Data Extensions plug-in interface in the vSphere Web Client or the Serengeti CLI Client to monitor and manage your Big Data Extensions environment. Performing management operations in vCenter Server might cause the Big Data Extensions management tools to become unsynchronized and unable to accurately report the operational status of your Big Data Extensions environment.
Prerequisites
Deploy the Big Data Extensions vApp.
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Ensure that you have login credentials with administrator privileges for the vCenter Server system with
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which you are registering Big Data Extensions.
NOTE The user name and password you use to login cannot contain characters whose UTF-8 encoding is greater than 0x8000.
If you want to use the vCenter Server IP address to access the vSphere Web Client, and your browser
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uses a proxy, add the vCenter Server IP address to the list of proxy exceptions.
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Chapter 2 Installing Big Data Extensions
Procedure
1 Open a Web browser and go to the URL of vSphere Web Client 5.1 or later.
https://hostname-or-ip-address:port/vsphere-client
The hostname-or-ip-address can be either the DNS hostname or IP address of vCenter Server. By default the port is 9443, but this might have changed during installation of the vSphere Web Client.
2 Enter the user name and password with administrative privileges that has permissions on
vCenter Server, and click Login.
3 Using the vSphere Web Client Navigator pane, locate the ZIP file on the Serengeti Management Server
that contains the Big Data Extensions plug-in to register to the vCenter Server.
You can find the Serengeti Management Server under the datacenter and resource pool to which you deployed it.
4 From the inventory tree, select management-server to display information about the
Serengeti Management Server in the center pane.
Click the Summary tab in the center pane to access additional information.
5 Note the IP address of the Serengeti Management Server virtual machine.
6 Open a Web browser and go to the URL of the management-server virtual machine.
https://management-server-ip-address:8443/register-plugin
The management-server-ip-address is the IP address you noted in Step 5.
7 Enter the information to register the plug-in.
Option Action
Register or Unregister
vCenter Server host name or IP address
User Name and Password
Big Data Extensions Package URL
Click Install to install the plug-in. Select Uninstall to uninstall the plug-in.
Enter the server host name or IP address of vCenter Server. Do not include http:// or https:// when you enter the host name or IP
address.
Enter the user name and password with administrative privileges that you use to connect to vCenter Server. The user name and password cannot contain characters whose UTF-8 encoding is greater than 0x8000.
Enter the URL with the IP address of the management-server virtual machine where the Big Data Extensions plug-in package is located:
https://management-server-ip-address/vcplugin/serengeti­plugin.zip
8 Click Submit.
The Big Data Extensions plug-in registers with vCenter Server and with the vSphere Web Client.
9 Log out of the vSphere Web Client, and log back in using your vCenter Server user name and
password.
The Big Data Extensions icon appears in the list of objects in the inventory.
10 Click Big Data Extensions in the Inventory pane.
What to do next
Connect the Big Data Extensions plug-in to the Big Data Extensions instance that you want to manage by connecting to the corresponding Serengeti Management Server. See “Connect to a Serengeti Management
Server,” on page 28.
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Connect to a Serengeti Management Server

To use the Big Data Extensions plug-in to manage and monitor big data clusters and Hadoop distributions, you must connect the Big Data Extensions plug-in to the Serengeti Management Server in your Big Data Extensions deployment.
You can deploy multiple instances of the Serengeti Management Server in your environment. However, you can connect the Big Data Extensions plug-in with only one Serengeti Management Server instance at a time. You can change which Serengeti Management Server instance the plug-in connects to, and use the Big Data Extensions plug-in interface to manage and monitor multiple Hadoop and HBase distributions deployed in your environment.
IMPORTANT The Serengeti Management Server that you connect to is shared by all users of the Big Data Extensions plug-in interface in the vSphere Web Client. If a user connects to a different Serengeti Management Server, all other users are affected by this change.
Prerequisites
Verify that the Big Data Extensions vApp deployment was successful and that the
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Serengeti Management Server virtual machine is running.
Verify that the version of the Serengeti Management Server and the Big Data Extensions plug-in is the
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same.
Ensure that vCenter Single Sign-On is enabled and configured for use by Big Data Extensions for
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vSphere 5.1 and later.
Install theBig Data Extensions plug-in.
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Procedure
1 Use the vSphere Web Client to log in to vCenter Server.
2 Select Big Data Extensions.
3 Click the Summary tab.
4 In the Connected Server pane, click the Connect Server link.
5 Navigate to the Serengeti Management Server virtual machine in the Big Data Extensions vApp to
which to connect, select it, and click OK.
The Big Data Extensions plug-in communicates using SSL with the Serengeti Management Server. When you connect to a Serengeti server instance, the plug-in verifies that the SSL certificate in use by the server is installed, valid, and trusted.
The Serengeti server instance appears as the connected server on the Summary tab of the Big Data Extensions Home page.
What to do next
You can add resource pool, datastore, and network resources to your Big Data Extensions deployment, and create big data clusters that you can provision for use.
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Chapter 2 Installing Big Data Extensions

Install the Serengeti Remote Command-Line Interface Client

Although theBig Data Extensions Plug-in for vSphere Web Client supports basic resource and cluster management tasks, you can perform a greater number of the management tasks using the Serengeti CLI Client.
IMPORTANT You can only run Hadoop commands from the Serengeti CLI on a cluster running the Apache Hadoop 1.2.1 distribution. To use the command-line to run Hadoop administrative commands for clusters running other Hadoop distributions, such as cfg, fs, mr, pig, and hive, use a Hadoop client node to run these commands.
Prerequisites
Verify that the Big Data Extensions vApp deployment was successful and that the Management Server
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is running.
Verify that you have the correct user name and password to log into the Serengeti CLI Client.
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If you are deploying on vSphere 5.1 or later, the Serengeti CLI Client uses your vCenter Single
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Sign-On credentials.
If you are deploying on vSphere 5.0, the Serengeti CLI Client uses the default vCenter Server
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administrator credentials.
Verify that the Java Runtime Environment (JRE) is installed in your environment, and that its location is
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in your PATH environment variable.
Procedure
1 Use the vSphere Web Client to log in to vCenter Server.
2 Select Big Data Extensions.
3 Click the Getting Started tab, and click the Download Serengeti CLI Console link.
A ZIP file containing the Serengeti CLI Client downloads to your computer.
4 Unzip and examine the download, which includes the following components in the cli directory.
The serengeti-cli-version JAR file, which includes the Serengeti CLI Client.
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The samples directory, which includes sample cluster configurations.
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Libraries in the lib directory.
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5 Open a command shell, and navigate to the directory where you unzipped the Serengeti CLI Client
download package.
6 Change to the cli directory, and run the following command to open the Serengeti CLI Client:
java -jar serengeti-cli-version.jar
What to do next
To learn more about using the Serengeti CLI Client, see the VMware vSphere Big Data Extensions Command­line Interface Guide.
VMware, Inc. 29

Access the Serengeti CLI By Using the Remote CLI Client

You can access the Serengeti Command-Line Interface (CLI) to perform Serengeti administrative tasks with the Serengeti Remote CLI Client.
IMPORTANT You can only run Hadoop commands from the Serengeti CLI on a cluster running the Apache Hadoop 1.2.1 distribution. To use the command-line to run Hadoop administrative commands for clusters running other Hadoop distributions, such as cfg, fs, mr, pig, and hive, use a Hadoop client node to run these commands.
Prerequisites
Use the VMware vSphere Web Client to log in to the VMware vCenter Server® on which you deployed
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the Serengeti vApp.
Verify that the Serengeti vApp deployment was successful and that the Management Server is running.
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Verify that you have the correct password to log in to Serengeti CLI. See the VMware vSphere Big Data
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Extensions Administrator's and User's Guide.
The Serengeti CLI uses its vCenter Server credentials.
Verify that the Java Runtime Environment (JRE) is installed in your environment and that its location is
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in your path environment variable.
Procedure
1 Open a Web browser to connect to the Serengeti Management Server cli directory.
http://ip_address/cli
2 Download the ZIP file for your version and build.
The filename is in the format VMware-Serengeti-cli-version_number-build_number.ZIP.
3 Unzip the download.
The download includes the following components.
The serengeti-cli-version_number JAR file, which includes the Serengeti Remote CLI Client.
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The samples directory, which includes sample cluster configurations.
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Libraries in the lib directory.
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4 Open a command shell, and change to the directory where you unzipped the package.
5 Change to the cli directory, and run the following command to enter the Serengeti CLI.
For any language other than French or German, run the following command.
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java -jar serengeti-cli-version_number.jar
For French or German languages, which use code page 850 (CP 850) language encoding when
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running the Serengeti CLI from a Windows command console, run the following command.
java -Dfile.encoding=cp850 -jar serengeti-cli-version_number.jar
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