Bahaaldine Azarmi - Talend for Big Data
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- Book:Talend for Big Data
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Overview
Write complex processing job codes easily with the help of clear and step by step instructions
Compare, filter, evaluate, and group vast quantities of data using Hadoop Pig
Explore and perform HDFS and RDBMS integration with the Sqoop component
In Detail
Talend, a successful Open Source Data Integration Solution, accelerates the adoption of new big data technologies and efficiently integrates them into your existing IT infrastructure. It is able to do this because of its intuitive graphical language, its multiple connectors to the Hadoop ecosystem, and its array of tools for data integration, quality, management, and governance.
This is a concise, pragmatic book that will guide you through design and implement big data transfer easily and perform big data analytics jobs using Hadoop technologies like HDFS, HBase, Hive, Pig, and Sqoop. You will see and learn how to write complex processing job codes and how to leverage the power of Hadoop projects through the design of graphical Talend jobs using business modeler, meta-data repository, and a palette of configurable components.
Starting with understanding how to process a large amount of data using Talend big data components, you will then learn how to write job procedures in HDFS. You will then look at how to use Hadoop projects to process data and how to export the data to your favourite relational database system.
You will learn how to implement Hive ELT jobs, Pig aggregation and filtering jobs, and simple Sqoop jobs using the Talend big data component palette. You will also learn the basics of Twitter sentiment analysis the instructions to format data with Apache Hive.
Talend for Big Data will enable you to start working on big data projects immediately, from simple processing projects to complex projects using common big data patterns.
What you will learn from this book
Know the structure of the Talend Unified Platform
Work with Talend HDFS components
Implement ELT processing jobs using Talend Hive components
Load, filter, aggregate, and store data using Talend Pig components
Integrate HDFS with RDBMS using Sqoop components
Use the streaming pattern for big data
Learn to reuse the partitioning pattern for big data
Approach
This book is written in a concise and easy-to-understand manner, and acts as a comprehensive guide on data analytics and integration with Talend big data processing jobs.
Who this book is written for
If you are a chief information officer, enterprise architect, data architect, data scientist, software developer, software engineer, or a data analyst who is familiar with data processing projects and who wants to use Talend to get your first big data job executed in a reliable, quick, and graphical way, then Talend for Big Data is perfect for you.
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Copyright 2014 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: February 2014
Production Reference: 2170214
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78216-949-9
www.packtpub.com
Cover Image by Abhishek Pandey (<>)
Author
Bahaaldine Azarmi
Reviewers
Simone Bianchi
Vikram Takkar
Acquisition Editors
Mary Nadar
Llewellyn Rozario
Content Development Editor
Manasi Pandire
Technical Editors
Krishnaveni Haridas
Anand Singh
Copy Editor
Alfida Paiva
Project Coordinator
Ankita Goenka
Proofreader
Mario Cecere
Indexers
Hemangini Bari
Tejal Soni
Production Coordinator
Komal Ramchandani
Cover Work
Komal Ramchandani
Bahaaldine Azarmi is the cofounder of reach5.co. With his past experience of working at Oracle and Talend, he has specialized in real-time architecture using service-oriented architecture products, Big Data projects, and web technologies.
I like to thank my wife, Aurelia, for her support and patience throughout this project.
Simone Bianchi has a degree in Electronic Engineering from Italy, where he is living today, working as a programmer to develop web applications using technologies such as Java, JSP, jQuery, and Oracle. After having a brief experience with the Oracle Warehouse Builder tool, and as soon as the Talend solution came out, he started to extensively use this new tool in all his data migration/integration tasks as well as develop ETL layers in data warehouse projects. He also developed several Talend custom components such as tLogGrid, tDBFInput/Output, which you can download from the TalendForge site, and the ones to access/store data on the Web via SOAP/REST API.
I'd like to thank Packt Publishing to have chosen me to review this book, as well as the very kind people who work there, to have helped me to accomplish my first review at my best.
A special dedication to my father Americo, my mother Giuliana, my sisters Barbara and Monica, for all their support over the years, and finally to my little sweet nephew and niece, Leonardo and Elena, you are my constant source of inspiration.
Vikram Takkar is a freelance Business Intelligence and Data Integration professional with nine years of rich hands-on experience in multiple BI and ETL tools. He has a strong expertise in technologies such as Talend, Jaspersoft, Pentaho, Big Data-MongoDB, Oracle, and MySQL. He has managed and successfully executed multiple projects in data warehousing and data migration developed for both Unix and Windows environments. He has also worked as a Talend Data Integration trainer and facilitated training for various corporate clients in India, Europe, and the United States. He is an impressive communicator with strong leadership, analytical, and problem-solving skills. He is comfortable interacting with people across hierarchical levels for ensuring smooth project execution as per the client's specifications. Apart from this, he is a blogger and publishes articles and videos on open source BI and ETL tools along with supporting technologies on his YouTube channel at www.youtube.com/vtakkar. You can follow him on Twitter @VikTakkar and you can visit his blog at www.vikramtakkar.com.
I would like to thank the Packt Publishing team for again giving me the opportunity to review their book. Earlier, I reviewed their Pentaho and Big Data Analytics book.
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Data volume is growing fast. However, data integration tools are not scalable enough to process such an amount of data, and thus, more and more companies are thinking about starting Big Data projectsdiving into the Hadoop ecosystem projects, understanding each technology, learning MapReduce, Hive SQL, and Pig-Latinthereby becoming more of a burden more than a solution.
Software vendors such as Talend are trying to ease the deployment of Big Data by democratizing the use of Apache Hadoop projects through a set of graphical development components, which doesn't require the developer to be a Hadoop expert to kick off their project.
This book will guide you through a couple of hands-on techniques to get a better understanding of Talend Open Studio for Big Data.
, Getting Started with Talend Big Data , explains the structure of Talend products and then sets up your Talend environment and discovers Talend Studio for the first time.
, Building Our First Big Data Job , explains how we can start creating our first HDFS job and be sure our Talend Studio is integrated with our Hadoop cluster.
, Formatting Data , describes the basics of Twitter Sentiment Analysis and gives an introduction to format data with Apache Hive.
, Processing Tweets with Apache Hive , shows advanced features of Apache Hive, which helps to create the sentiment from extracted tweets.
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