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Access, transform, and integrate data using Talend's open source, extensible toolsAbout This Book
- 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
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, Talend for Big Data is perfect for you.
What You Will Learn- Discover 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
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.
- Sales Rank: #2551821 in Books
- Published on: 2014-02-21
- Released on: 2014-02-21
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .22" w x 7.50" l, .40 pounds
- Binding: Paperback
- 96 pages
About the Author
Bahaaldine Azarmi
Bahaaldine Azarmi is the cofounder of reach5.co. With his past experience of working at Oracle and Talend, he has specialized in realtime architecture using serviceoriented architecture products, Big Data projects, and web technologies.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Not much of contents.
By Kun Ei Kang
I bought the printed book (and eBook) based on the sample chapter and customer review.
I am regretting my purchase. It only has 70 pages of talend big data stuffs. The rest of pages (20 - 30 pages) talks about Cloudera virtual machines thing. I was hoping the book explains the each big data components, but it only shows you how to connect to hadoop and some examples. The book doesn't cover any deeper. This is very beginner book.
To me, this book is very big disappointment, and regret to spend $37 for getting print book. Lessons learned, never buy the print book, but buy eBook first to see if they are any good. :)
0 of 0 people found the following review helpful.
Getting things done with Talend and Hadoop
By Iñigo González
I’ve just finished reading Talend for Big Data, courtesy of Packt Publishing.
I’ve been using Talend for ETL and automation tasks for some years and I wanted to start using it to feed data into a small hadoop cluster we have, so I think I can be able to put myself on this book readers shoes easily.
I’ve enjoyed the book follows a real use case of sentiment analisys using twitter data: I was getting tired of examples word counting / term extraction examples found in other Hadoop texts.
The structure is very straightforward and It resembles closely a real world Big Data integration job:
-The basics: what’s Talend, what’s hadoop, and how to get started (terminology and setup)
-How to get data into a hadoop cluster (there’s a component for that: tHDFDOutput)
-Working with tables (hive) in Talend using Hive.
-Working with data using Pig.
-Loading results back to an SQLdatabase using Apache Sqoop
-And finally, how to industrialize this process.
In the real world you’ll surely choose between Hive and Pig to make your project simpler. Having a chapter for hive and another for pig lets you see and compare both technologies and helps you choose the one you feel more comfortable working with.
I’ve also found very interesting using Apache Sqoop to getting the data out of Hadoop back to the SQL World.
I didn’t know about Sqoop before reading the book and I was tempted to extract the data from Hadoop using a Talend job as a bridge. Dont’ do IT!. Using Sqoop is much better because it can paralelize the load job. It remembers me how to make backups using a disk cabin vs using a server agent (just tell the cabin to do the backup by its own vs copying all the data to a point and move it around).
Surprises:
:: The good ::
* Contexts! I’ve ever thought the best part of Talend are contexts and I find great to see all the examples in the book using contexts since the beginning.
* In chapter 4 we learn how to use UDF (user-defined-functions) with Hive inside Talend. In the book the problem it solves is Hive does not support regular expressions; but It gives us a clue that may allow us to do something with interesting with other kinds of data, like images or audio files.
* The way Talend works with Pig is easier that I expected. Why? because you dont’ need to know anything about Pig latin code to get results. I expected something more complicated. In fact, I thing I’m going to use tPig* components more frequently than the Hive ones.
: The chapter about using Sqoop with Talend. For me, this chapter just justifies buying the book because it saves you a lot of time.
:: The bad ::
* I discovered in the book that Talend doesnt include all the JARs needed to work with Hadoop. This is not a technical problem per se; but a legal one: Talend cannot distribute the hadoop files under their own license. Fortunately the guys from Talend have made available a one-click-fix.
* At first glance I found the book short. Maybe I’m used to technical books with a lot of literature and this book has a very practical how-to-make-things-happen approach. I hope to see a second edition soon with dedicated to Google Big Query (which, by the way, is supported by Talend in the latest release with its own set of components).
Conclusion: concise, hands-on book about data integration with Talend and Hadoop. Highly recommendable even if you just want to extract data from an existing hadoop cluster.
0 of 0 people found the following review helpful.
Nicely covers what I feared to be complexities of dealing with Hadoop as Hive and Pig using Talend - turned to be not true
By A. Zubarev
Talend for Big Data means exactly it! One of the shortest technical books I read, but sure to the point.
This book does not spend your time unwisely, if you happened to suddenly find yourself on a project involving Hadoop (or its ecosystem components) and you know at least some Talend (if not, I recommend a supplementary book that I also reviewed, Talend Open Studio Cookbook by Packt, too) then this is your book. Print it (if you got an eBook) and place a copy by your desk.
The book nicely covers what I feared complexities of dealing with Hadoop as Hive and Pig (a MR generator, not an animal), which actually turned out to be not true, thanks Talend and its 500+ components that cover 90% of what you need out of Big Data is already there for you to use. To my disbelief Talend actually is a very mature and (in paid variant) fully enterprise ready ETL solution.
The book has 7 chapters, each dedicated to a specific goal that accomplishes an exercise with a particular technology piece.
My favorite is #7: Big Data Architecture and Integration Patterns chapter. The last one, but this is the chapter where you get kind of awarded and start benefiting from the material you ingested.
Chapter 6: Aggregate Data with Pig is alot of fun and showed me a new way of interacting with Pig. It turned to be also a much easier way.
As a side note, I am in love with ETL, in general, I think it has the highest ROI out of all the enterprise tools, yet very much fun to work with and what is best - visually documenting!
Chapter 2: Building your First Big Data Job is like your first swim in deep waters - intimidating, but rewarding, full of uncertainty, but excitement and unforgettable.
All the less relevant topics as setting your training system up are shifted to the appendixes, but I recommend actually starting there if you are new to Cloudera's Hadoop (CDH) VM distribution and/or VMPlayer (served in role of your Virtual Machine).
It seemed to me that a reader does not need ANY prior knowledge of neither Talend nor Hadoop to accomplish the tasks in the book.
One suggestion I have to the author is instead of basing the examples on MySQL which seems to be out of favor by the user community MariaDB is the equivalent substitute that with the release of version 10 going to capture a lot of attention.
Another point is the Hadoop distribution preference, it seems that Hortonworks offers more bells and whistles, but it is a catchup game anyways.
It is a 5 out 5 stars book, thank you Bahaaldine and Packt!
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