By Balaswamy Vaddeman
Learn to exploit Apache Pig to strengthen light-weight colossal info functions simply and quick. This publication exhibits you several optimization suggestions and covers each context the place Pig is utilized in immense facts analytics. Beginning Apache Pig exhibits you the way Pig is simple to profit and calls for quite little time to strengthen substantial information applications.The booklet is split into 4 elements: the full beneficial properties of Apache Pig; integration with different instruments; the right way to remedy complicated enterprise difficulties; and optimization of tools.You'll notice issues resembling MapReduce and why it can't meet each enterprise want; the beneficial properties of Pig Latin equivalent to info kinds for every load, shop, joins, teams, and ordering; how Pig workflows might be created; filing Pig jobs utilizing Hue; and dealing with Oozie. you are going to additionally see the best way to expand the framework by means of writing UDFs and customized load, shop, and filter out services. ultimately you are going to disguise various optimization recommendations comparable to accumulating information a couple of Pig script, becoming a member of ideas, parallelism, and the position of knowledge codecs in reliable performance.
What you'll Learn• Use all of the beneficial properties of Apache Pig• combine Apache Pig with different instruments• expand Apache Pig• Optimize Pig Latin code• clear up assorted use situations for Pig LatinWho This e-book Is ForAll degrees of IT pros: architects, giant info fans, engineers, builders, and massive information administrators
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Extra info for Beginning Apache Pig: Big Data Processing Made Easy
Commands Type Command Short Description Example File system fs File system commands Grunt>fs –ls / Shell sh Runs shell programs Grunt>sh ls / Utility exec Runs Pig Latin scripts from the Grunt shell Grunt>exec dumpmovies. pig run Runs Pig Latin scripts from the Grunt shell Grunt>run dumpmovies. pig clear Clears all commands from the Grunt shell Grunt>clear help Displays all command information Grunt>help history Displays previously run statements Grunt> history set Sets a value to a property Set debug ‘on’ quit Quits the Grunt shell Grunt>quit; kill Kills a job Grunt>kill job_201512120001_001 Auto-completion Since the Grunt shell is equipped with the auto-completion feature, you do not need to type out complete commands.
14 Chapter 1 ■ MapReduce and Its Abstractions LocalFlowConnector will help you to create a local flow that can be run on the local file system. You can use HadoopFlowConnector for creating a flow that works on the Hadoop file system. complete() will start executing the flow. 1. Modify the previous Cascading program to filter the word pear. Benefits These are the benefits of Cascading: • Like MapReduce, it can process all types of data, such as structured, semistructured, and unstructured data.
The -paramfile option helps manage lengthy scripts by creating a file containing all the property names and their values. pig; /home/hdfs/ If there are multiple parameters, you can specify all the property names and their values in a file. The file path can also be specified to a Pig script. This is optional. pig; You can specify both the absolute and relative paths. The relative path will be resolved from the current working directory of the local file system. The -param option allows you to provide values for dynamic parameters defined in the script.
Beginning Apache Pig: Big Data Processing Made Easy by Balaswamy Vaddeman