By Piero Giacomelli
A quickly, clean, developer-oriented dive into the realm of Mahout
- Learn how one can 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 cling of the various positive aspects of Mahout
The upward thrust of the net and social networks has created a brand new call for for software program that may study huge datasets that could scale as much as 10 billion rows. Apache Hadoop has been created to deal with such heavy computational projects. Mahout received reputation for offering info mining class algorithms that may be used with such type of datasets.
"Apache Mahout Cookbook" offers a clean, scope-oriented method of the Mahout international for either newbies in addition to complex clients. The ebook offers an perception on find out how to write diversified info mining algorithms for use within the Hadoop setting and select the easiest one suiting the duty in hand.
"Apache Mahout Cookbook" seems to be on the a variety of Mahout algorithms to be had, and provides the reader a clean solution-centered method on the way to clear up diverse facts mining projects. The recipes begin effortless yet get steadily complex. A step by step strategy will advisor the developer within the various projects all for mining a massive dataset. additionally, you will tips on how to code your Mahout’s info mining set of rules to figure out the simplest one for a selected activity. Coupled with this, an entire bankruptcy is devoted to loading information into Mahout from an exterior RDMS approach. loads of cognizance has additionally been wear utilizing your information mining set of rules within your code on the way to be ready to use it in an Hadoop surroundings. Theoretical features of the algorithms are coated 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 ebook offers the code for reusing it utilizing Maven in addition to the Maven Mahout resource code.
By the top of this booklet it is possible for you to to code your technique to do quite a few info mining initiatives with varied algorithms and to guage and select the easiest ones in your tasks.
What you'll study from this book
- Configure from scratch an entire improvement setting for Mahout with NetBeans and Maven
- Handle sequencefiles for higher 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 info with Naïve Bayes
- Create and comprehend clusters
- Customize Mahout to judge diverse cluster algorithms
- Use the mapreduce method of remedy genuine global facts mining problems
"Apache Mahout Cookbook" makes use of over 35 recipes full of illustrations and real-world examples to aid novices in addition to complex programmers get conversant in the positive aspects of Mahout.
Who this booklet is written for
"Apache Mahout Cookbook" is superb for builders who are looking to have a clean and quick advent to Mahout coding. No earlier wisdom of Mahout is needed, or even expert builders or process directors will enjoy the numerous recipes presented.
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Extra info for Apache Mahout Cookbook
Close(); Reading sequence files from code After learning how to create sequence files, it is now time to learn how to read a sequence file. Mahout gives the possibility of reading a sequence file and converting every key/value into a text format. The command is pretty easy. For example, to stream out the file we created in the previous recipes, we could type the following console command: mahout seqdumper -i $WORK_DIR/sequencesfiles/part-0000 -o /mnt/new/lastfm/sequencesfiles/dump This command writes a file called dump in the $WORK_DIR folder from the file part-0000 generated in the previous recipes.
Close(); } } The output of the code is as shown in the following screenshot: 40 Chapter 2 The same output could have been displayed using the hadoop command as follows: hadoop-mahout@hadoop-mahout-laptop:/mnt/new/lastfm/sequencesfiles$ hadoop dfs -text part-0000 This is analogous to the Mahout seqdumper command, but does not require a target output file. The output should be displayed as follows: How it works... As we have seen earlier, the format of a sequence file consists of keys/values pairs.
In the same NetBeans project we created before, we need to add a new Java class as illustrated in the following screenshot: A window will appear, and in the input name text field one should just enter the name of the class, in this case ReadSequenceFileArtist, and click on the Ok button. How to do it… Now that we have our class ready, we simply need to add some code to the main method with the following steps: 1. Text; 43 Using Sequence Files – When and Why? 2. close(); } } 44 Chapter 2 3. csv as shown in the following screenshot: 4.