By Piero Giacomelli
A speedy, clean, developer-oriented dive into the realm of Mahout
- Learn easy methods to organize a Mahout improvement environment
- Start checking out Mahout in a standalone Hadoop cluster
- Learn to discover inventory marketplace path utilizing logistic regression
- Over 35 recipes with real-world examples to assist either expert and the non-skilled builders get the dangle of different positive factors of Mahout
The upward thrust of the net and social networks has created a brand new call for for software program which can research huge datasets which could scale as much as 10 billion rows. Apache Hadoop has been created to address such heavy computational initiatives. Mahout won attractiveness for supplying facts mining category algorithms that may be used with such form of datasets.
"Apache Mahout Cookbook" offers a clean, scope-oriented method of the Mahout global for either novices in addition to complicated clients. The e-book offers an perception on the way to write diversified facts mining algorithms for use within the Hadoop atmosphere and select the easiest one suiting the duty in hand.
"Apache Mahout Cookbook" appears on the a variety of Mahout algorithms on hand, and offers the reader a clean solution-centered procedure on how one can clear up diversified info mining projects. The recipes begin effortless yet get steadily complex. A step by step technique will advisor the developer within the various initiatives keen on mining a big dataset. additionally, you will easy methods to code your Mahout’s information mining set of rules to figure out the simplest one for a selected job. Coupled with this, an entire bankruptcy is devoted to loading info into Mahout from an exterior RDMS process. loads of cognizance has additionally been wear utilizing your info mining set of rules inside of your code with a purpose to be capable to use it in an Hadoop atmosphere. Theoretical points of the algorithms are lined for info reasons, yet each bankruptcy is written to permit the developer to get into the code as speedy and easily as attainable. which means with each recipe, the booklet offers the code for reusing it utilizing Maven in addition to the Maven Mahout resource code.
By the tip of this publication it is possible for you to to code your process to do a number of facts mining projects with various algorithms and to judge and select the easiest ones in your tasks.
What you are going to examine from this book
- Configure from scratch an entire improvement surroundings for Mahout with NetBeans and Maven
- Handle sequencefiles for greater performance
- Query and shop effects into an RDBMS approach with SQOOP
- Use logistic regression to foretell the following step
- Understand textual content mining of uncooked facts with Naïve Bayes
- Create and comprehend clusters
- Customize Mahout to judge diversified cluster algorithms
- Use the mapreduce method of remedy genuine international facts mining problems
"Apache Mahout Cookbook" makes use of over 35 recipes full of illustrations and real-world examples to assist novices in addition to complicated programmers get conversant in the good points of Mahout.
Who this publication is written for
"Apache Mahout Cookbook" is excellent for builders who are looking to have a clean and quick advent to Mahout coding. No past wisdom of Mahout is needed, or even expert builders or procedure directors will enjoy the quite a few recipes presented.
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Extra info for Apache Mahout Cookbook
Once NetBeans finishes downloading the whole package, it will ask if you want to scan and open the project. So click on Ok in the information window and let the IDE import the Maven project. Now, in the Projects tab you should see the following structure: 4. The sources have been downloaded and can be found in the NetBeansProjects folder. 16 Chapter 1 5. Now for compiling these sources using Maven, right-click with your mouse on the Mahout Release Package icon and choose Clean and Build item. 6.
For each line use a counter to create a unique index for the key. 3. For each line read the artist on that line and create the value class. 4. Write the key and the value pair to the sequence file. We open the file using the BufferedReader Java base object. class); 41 Using Sequence Files – When and Why? To create a sequence file you need to declare the Hadoop Configuration and FileSystem type, and the class of the key and value pair. In our case we use the predefined Hadoop classes, the LongWritable and Text classes, corresponding to the long and string types in Java.
So it is time to move to the code to see how to create the sequence file using a more structured Java approach. txt and create a sequence file using the unique ID in the file and the name of the key/value pair. The format of the original file looks like the following: 25231 Radiohead 20372 Pink Floyd 20251 The Beatles 19600 Red Hot Chili Peppers 18867 System of a Down 18671 Metallica 18671 Coldplay 18143 Nirvana 17629 Death Cab for Cutie 17507 Muse 16268 Green Day 16057 Franz Ferdinand 15306 Nine Inch Nails 15258 Led Zeppelin 15114 Tool We would like to use the same format for creating a sequence file.
Apache Mahout Cookbook by Piero Giacomelli