Conventions for the syntax and code examples in the Pig Latin Reference Manual are . however, Pig relations don't require that every tuple contain the same. Because the log file only contains queries for a single day, we are only interested in the hour. The excite query log timestamp format is. YYMMDDHHMMSS. Find Excite Logs. • We'll be using some logs from excite for our first few examples . • The data is in the pig distribution: tutorial/data/caite.info
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Apache Pig Tutorial in PDF - Learn Apache Pig starting from Overview, Architecture, Installation, Execution, Grunt Shell, Pig Latin Basics, Reading Data, Storing. we can perform all the data manipulation operations in Hadoop using Pig. Audience. This tutorial in this tutorial, please notify us at [email protected] com. O'Reilly Media, Inc. Programming Pig, the image of a domestic pig, and .. find “ Comparing query and dataflow languages” on page 4 to be a helpful starting.
Pig is complete, so you can do all required data manipulations in Apache Hadoop with Pig. You can also embed Pig scripts in other languages. The result is that you can use Pig as a component to build larger and more complex applications that tackle real business problems.
Pig works with data from many sources, including structured and unstructured data, and store the results into the Hadoop Data File System.
Pig scripts are translated into a series of MapReduce jobs that are run on the Apache Hadoop cluster. Download the driver data file from here. Once you have the file you will need to unzip the file into a directory. That is the views menu. The HDP file system is separate from the local file system. When finished, notice that both files are now in HDFS. In this tutorial Vi is used; however, any text editor will work as long as the files we create are stored on the Sandbox. Navigate to http: In the LOAD script, you can choose any directory path.
This action creates one or more MapReduce jobs. After a moment, the script starts and the page changes. When the job completes, result output. Modify line 1 of your script and add the following AS clause to define a schema for the truck events data. Open Vi and enter the following script:. Recall that we used: You can define a new relation based on an existing one.
Add the following line to the end of your code:. Save and execute the code. To view the data of a relation, use the DUMP command. The command requires a MapReduce job to execute, so you will need to wait a minute or two for the job to complete. One of the key uses of Pig is data transformation. Now the completed code is:.
Save and Execute the script. Again, this requires a MapReduce job just like the DUMP command , so you will need to wait a minute for the job to complete. In this step, you will perform a join on two driver statistics data sets: The completed code will be:. Next, enter the following commands to sort the drivers data by name then date in ascending order:. Save and execute the script.
Notice that the data for eventType which are not Normal is grouped together for each driverId. You have successfully completed the tutorial and well on your way to pigging on Big Data. If you need help or have questions with this tutorial, please check HCC for answers to existing questions about this tutorial.
All Hortonworks, partner and community tutorials are posted in the Hortonworks GitHub repository and can be contributed to by following the Tutorial Contribution Guide.
Wish to Learn Hadoop? Click Here. There are namely 3 ways of executing Pig programs which works on both local and MapReduce mode:.
Pig can run a script file that contains Pig commands. For example, pig script. Alternatively, for very short scripts, you can use the -e option to run a script specified as a string on the command line.
Grunt is an interactive shell programming for running Pig commands. Grunt is started when no file is specified for Pig to run, and the -e option apparently not used. It is also possible to run Pig scripts from within Grunt using run and exec.
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