As an open source, distributed, big data store, HBase scales to billions of rows, with millions of columns and sits on top of the clusters of commodity machines. If you are looking for a way to store and access a huge amount of data in real time, then look no further than HBase.
HBase Administration Cookbook provides practical examples and simple step-by-step instructions for you to administrate HBase with ease. The recipes cover a wide range of processes for managing a fully distributed, highly available HBase cluster on the cloud. Working with such a huge amount of data means that an organized and manageable process is key, and this book will help you to achieve that.
The recipes in this practical cookbook start with setting up a fully distributed HBase cluster and moving data into it. You will learn how to use all the tools for day-to-day administration tasks, as well as for efficiently managing and monitoring the cluster to achieve the best performance possible. Understanding the relationship between Hadoop and HBase will allow you to get the best out of HBase; so this book will show you how to set up Hadoop clusters, configure Hadoop to cooperate with HBase, and tune its performance.
Chapter 1, Setting Up HBase Cluster: This chapter explains how to set up an HBase cluster, from a basic standalone HBase instance to a fully distributed, highly available HBase cluster on Amazon EC2.
Chapter 2, Data Migration: In this chapter, we will start with the simple task of importing data from MySQL to HBase, using its Put API. We will then describe how to use the importtsv and bulk load tools to load TSV data files into HBase. We will also use a MapReduce sample to import data from other file formats. This includes putting data directly into an HBase table and writing to HFile format files on Hadoop Distributed File System (HDFS). The last recipe in this chapter explains how to precreate regions before loading data into HBase.
This chapter ships with several sample sources written in Java. It assumes that you have basic Java knowledge, so it does not explain how to compile and package the sample Java source in the recipes.
Chapter 3, Using Administration Tools: In this chapter, we describe the usage of various administration tools such as HBase web UI, HBase Shell, HBase hbck, and others. We explain what the tools are for, and how to use them to resolve a particular task.
Chapter 4, Backing Up and Restoring HBase Data: In this chapter, we will describe how to back up HBase data using various approaches, their pros and cons, and which approach to choose depending on your dataset size, resources, and requirements.
Chapter 5, Monitoring and Diagnosis: In this chapter, we will describe how to monitor and diagnose HBase cluster with Ganglia, OpenTSDB, Nagios, and other tools. We will start with a simple task to show the disk utilization of HBase tables. We will install and configure Ganglia to monitor an HBase metrics and show an example usage of Ganglia graphs. We will also set up OpenTSDB, which is similar to Ganglia, but more scalable as it is built on the top of HBase.
We will set up Nagios to check everything we want to check, including HBase-related daemon health, Hadoop/HBase logs, HBase inconsistencies, HDFS health, and space utilization.
In the last recipe, we will describe an approach to diagnose and fix the frequently asked hot spot region issue.
Chapter 6, Maintenance and Security: In the first six recipes of this chapter we will learn about the various HBase maintenance tasks, such as finding and correcting faults, changing cluster size, making configuration changes, and so on.
We will also look at security in this chapter. In the last three recipes, we will install Kerberos and then set up HDFS security with Kerberos, and finally set up secure HBase client access.
Chapter 7, Troubleshooting: In this chapter, we will look through several of the most confronted issues. We will describe the error messages of these issues, why they happen, and how to fix them with the troubleshooting tools.
Chapter 8, Basic Performance Tuning: In this chapter, we will describe how to tune HBase to gain better performance. We will also include recipes to tune other tuning points such as Hadoop configurations, the JVM garbage collection settings, and the OS kernel parameters.
Chapter 9, Advanced Configurations and Tuning: This is another chapter about performance tuning in the book. The previous chapter describes some recipes to tune Hadoop, OS setting, Java, and HBase itself, to improve the overall performance of the HBase cluster. These are general improvements for many use cases. In this chapter, we will describe more specific recipes, some of which are for write-heavy clusters, while some are aimed at improving the read performance of the cluster.
Everything you need is listed in each recipe.
The basic list of software required for this book are as follows:
Debian 6.0.1 (squeeze)
Oracle JDK (Java Development Kit) SE 6
HBase 0.92.1
Hadoop 1.0.2
ZooKeeper 3.4.3
This book is for HBase administrators, developers, and will even help Hadoop administrators. You are not required to have HBase experience, but are expected to have a basic understanding of Hadoop and MapReduce.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text are shown as follows: "HBase can be stopped using its stop-hbase.sh script."
A block of code is set as follows:
nameserver 10.160.49.250 #private IP of ns search hbase-admin-cookbook.com #domain name
When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
MAJOR_COMPACTION_KEY = \x00
MAX_SEQ_ID_KEY = 96573
TIMERANGE = 1323026325955....1323026325955
hfile.AVG_KEY_LEN = 31
hfile.AVG_VALUE_LEN = 4
hfile.COMPARATOR = org.apache.hadoop.hbase.KeyValue$KeyComparator
Any command-line input or output is written as follows:
$ bin/ycsb load hbase -P workloads/workloada -p columnfamily=f1 -p recordcount=1000000 -p threadcount=4 -s | tee -a workloada.dat
YCSB Client 0.1
Command line: -db com.yahoo.ycsb.db.HBaseClient -P workloads/workloada -p columnfamily=f1 -p recordcount=1000000 -p threadcount=4 -s -load
Loading workload...
New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: " Verify the startup from AWS Management Console".
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