By Balaswamy Vaddeman
Learn to exploit Apache Pig to increase light-weight colossal info purposes simply and speedy. This ebook exhibits you several optimization ideas and covers each context the place Pig is utilized in tremendous information analytics. Beginning Apache Pig indicates you ways Pig is straightforward to profit and calls for fairly little time to increase colossal info applications.The ebook is split into 4 elements: the full gains of Apache Pig; integration with different instruments; how you can remedy advanced company difficulties; and optimization of tools.You'll become aware of themes comparable to MapReduce and why it can't meet each company desire; the positive factors of Pig Latin similar to facts varieties for every load, shop, joins, teams, and ordering; how Pig workflows will be created; filing Pig jobs utilizing Hue; and dealing with Oozie. you are going to additionally see easy methods to expand the framework via writing UDFs and customized load, shop, and clear out capabilities. ultimately you will hide assorted optimization strategies akin to collecting information a couple of Pig script, becoming a member of recommendations, parallelism, and the function of knowledge codecs in strong performance.
What you'll Learn• Use all of the positive aspects of Apache Pig• combine Apache Pig with different instruments• expand Apache Pig• Optimize Pig Latin code• resolve varied use situations for Pig LatinWho This ebook Is ForAll degrees of IT execs: architects, tremendous information lovers, engineers, builders, and massive information administrators
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Extra resources for Beginning Apache Pig: Big Data Processing Made Easy
Now you will learn about other utility commands that are useful for controlling both the Grunt shell and Hadoop jobs. Utility Commands The following are the utility commands. help The help command prints a list of Pig commands or properties with a short description and syntax. grunt> help Commands:
This section shows Pig properties for which you can set values. The set default_parallel command specifies the default number of reducers; in this example, it sets the default number of reducers to 20: Grunt>set default_parallel 20; The set debug command enables and disables debugging in a Pig Latin script. It is set to disable, by default. The following command enables debugging: Grunt>set debug 'on'; To then disable it, use the off option as follows: Grunt> set debug off; This set command allows you to set a name for a job.
Use the registerJar() method of the PigServer method to register a JAR file if it contains any user-defined functions. The following Java code reads data from the input directory and writes it to the output directory. However, observe that the input and output directories are not specified in the Java code; hence, you would have to provide them at runtime. 1. jar file in the build path to check and compile it successfully. Copy the file to one of the cluster nodes to run the program on a cluster.
Beginning Apache Pig: Big Data Processing Made Easy by Balaswamy Vaddeman