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Apache Oozie Essentials电子书

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8人正在读 | 0人评论 9.8

作       者:Jagat Jasjit Singh

出  版  社:Packt Publishing

出版时间:2015-12-11

字       数:71.2万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Unleash the power of Apache Oozie to create and manage your big data and machine learning pipelines in one go About This Book Teaches you everything you need to know to get started with Apache Oozie from scratch and manage your data pipelines effortlessly Learn to write data ingestion workflows with the help of real-life examples from the author’s own personal experience Embed Spark jobs to run your machine learning models on top of Hadoop Who This Book Is For If you are an expert Hadoop user who wants to use Apache Oozie to handle workflows efficiently, this book is for you. This book will be handy to anyone who is familiar with the basics of Hadoop and wants to automate data and machine learning pipelines. What You Will Learn Install and configure Oozie from source code on your Hadoop cluster Dive into the world of Oozie with Java MapReduce jobs Schedule Hive ETL and data ingestion jobs >Import data from a database through Sqoop jobs in HDFS Create and process data pipelines with Pig, hive *s as per business requirements. Run machine learning Spark jobs on Hadoop Create quick Oozie jobs using Hue Make the most of Oozie’s security capabilities by configuring Oozie’s security In Detail As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities is booming exponentially. This calls for data management. Hadoop caters to this need. Oozie fulfils this necessity for a scheduler for a Hadoop job by acting as a cron to better analyze data. Apache Oozie Essentials starts off with the basics right from installing and configuring Oozie from source code on your Hadoop cluster to managing your complex clusters. You will learn how to create data ingestion and machine learning workflows. This book is sprinkled with the examples and exercises to help you take your big data learning to the next level. You will discover how to write workflows to run your MapReduce, Pig ,Hive, and Sqoop *s and schedule them to run at a specific time or for a specific business requirement using a coordinator. This book has engaging real-life exercises and examples to get you in the thick of things. Lastly, you’ll get a grip of how to embed Spark jobs, which can be used to run your machine learning models on Hadoop. By the end of the book, you will have a good knowledge of Apache Oozie. You will be capable of using Oozie to handle large Hadoop workflows and even improve the availability of your Hadoop environment. Style and approach This book is a hands-on guide that explains Oozie using real-world examples. Each chapter is blended beautifully with fundamental concepts sprinkled in-between case study solution algorithms and topped off with self-learning exercises.
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Apache Oozie Essentials

Table of Contents

Apache Oozie Essentials

Credits

About the Author

About the Reviewers

www.PacktPub.com

Support files, eBooks, discount offers, and more

Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Setting up Oozie

Configuring Oozie in Hortonworks distribution

Installing Oozie using tar ball

Creating a test virtual machine

Building Oozie source code

Summary of the build script

Codehaus Maven move

Download dependency jars

Preparing to create a WAR file

Create a WAR file

Configure Oozie MySQL database

Configure the shared library

Start server testing and verification

Summary

2. My First Oozie Job

Installing and configuring Hue

Oozie concepts

Workflows

Coordinator

Bundles

Book case study

Running our first Oozie job

Types of nodes

Control flow nodes

Action nodes

Oozie web console

The Oozie command line

Summary

3. Oozie Fundamentals

Chapter case study

The Decision node

The Email action

Expression Language functions

Basic EL constants

Basic EL functions

Workflow EL functions

Hadoop EL constants

HDFS EL functions

Email action configuration

Job property file

Submission from the command line

Workflow states

Summary

4. Running MapReduce Jobs

Chapter case study

Running MapReduce jobs from Oozie

The job.properties file

Running the job

Running Oozie MapReduce job

Coordinators

Datasets

Frequency and time

Cron syntax for frequency

Timezone

The <done-flag> tag

Initial instance

My first Coordinator

Coordinator v1 definition

job.properties v1 definition

Coordinator v2 definition

job.properties v2 definition

Checking the job log

Running a MapReduce streaming job

Summary

5. Running Pig Jobs

Chapter case study

The Pig command line

The config-default.xml file

Pig action

Pig Coordinator job v2

Parameters in the Dataset's input and output events

current(int n)

hoursInDay(int n)

daysInMonth(int n)

latest(int n)

Coordinator controls

Pig Coordinator job v3

Summary

6. Running Hive Jobs

Chapter case study

Running a Hive job from the command line

Hive action

Validating Oozie Workflow

Hive 2 action

Parameterization of Coordinator jobs

dateOffset(String baseDate, int instance, String timeUnit)

dateTzOffet(String baseDate, String timezone)

formatTime(String timeStamp, String format)

Summary

7. Running Sqoop Jobs

Chapter case study

Running Sqoop command line

Sqoop action

HCatalog

HCatalog datasets

HCatalog EL functions

HCatalog Coordinator functions

Pig script

The job.properties file

The Sqoop action Coordinator

Running the job

Checking data in the Hive table

Summary

8. Running Spark Jobs

Spark action

Bundles

Data pipelines

Summary

9. Running Oozie in Production

Packaging and continuous delivery

Oozie in secured cluster

Rerun

Rerun Workflow

Rerun Coordinator

Rerun Bundle

Summary

Index

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