Nutshell Handbook, the Nutshell Handbook logo, and the O'Reilly logo are registered trademarks of. O'Reilly Media, Inc. Programming Pig, the image of a. With Pig, you can analyze data without having to create a full-fledged Title O' Reilly® Programming Pig; Author(s) Alan F Gates; Publisher: O'Reilly O'Reilly® Programming Pig (Alan F Gates) · The Mirror Site (1) - PDF ( Pages, MB). The next step? Processing and analyzing datasets with the Apache Pig scripting platform. With Pig - Selection from Programming Pig, 2nd Edition [Book].
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Apache Pig: Introduction. • Tool for querying data on Hadoop clusters. • Widely used in the Hadoop world. • Yahoo! estimates that 50% of their Hadoop workload . Apache Pig is a high-level procedural language for querying large semi- structured data sets using Hadoop and the MapReduce Platform. Web site: aracer.mobi Setup your path. Already done, check aracer.mobie. Copy the sample codes/data from. /home/hadoop/pig/examples.
The Apache Pig is a platform for managing large sets of data which consists of high-level programming to analyze the data as per the requirements assigned. Pig mainly consists of the infrastructure to evaluate the complexity of the program.
The advantages of Pig programming is that it can easily handle parallel processes correspondingly managing a very large number of data. The programming on this platform is done by using the textual language Pig Latin. Pig Latin comes with the following features: Simple programming: it is easy to code, execute and manage the program. Better optimization: system can automatically optimize the execution as per the requirement raised. Extensive nature: Used to achieve highly specific processing tasks.
The scalar data types in pig are in the form of int, float, double, long, chararray, and byte array. After generation of the logical plan, the execution of the script goes to physical plan.
Physical plan is the explanation of physical operators, which Pig will use, for the execution of the script. While the generation of any physical plan, the logical operator cogroup is transformed into physical operators, which are — Global Rearrange, Local Rearrange, and Package.
Is Co-group is a group of more than 1 data set?
A group of data sets is referred to as Co-group. In any case, of more than one data set, co-group, groups all the data sets and then joins them based on a common field. That is why; we can say that co-group is obviously a group of more than one data set. Check Out Hadoop Tutorials What are the uses of Apache Pig? Pig operates in situations where the schema is unknown, incomplete, or inconsistent; it is used by all developers who want to use the data before being loaded into the data warehouse.
For building prediction models for behavior, it is used by the website to detect the reply of visitors to a variety of images, ads, articles, etc.
Is PigLatin strongly typed language? Strongly typed language, is characterized where the user should state all the type of variables openly, whereas in Pig, the description of the data, it anticipates the data to approach in the mentioned format.
If the schema is unknown, the script adapts to the actual data types at the runtime. It keeps on working with the data, which may not be up to the expectations. At any given time, cogroup can feature up to relations. What do we understand by the outer bag and inner bag in Pig? The outer bag is just any relation in Pig whereas sny relation within a bag is known as the inner bag.
Grunt Grunt helps the Apache pig shell operations.
The direct working with java APIs can be slow and error prone. It also prevents the usage of Hadoop to Java programmers. The above problem is solved by using the Apache pig. Apache pig is a programming language that simplifies the mutual tasks of working with Hadoop.
Loading data, expressing transformations on the data, and storing the final results etc are the commonly used tasks. Apache pig is a thinner layer.