Hadoop what is pig

Then, these scripts need to be transformed into MapReduce tasks. This is achieved with the help of Pig Engine. By now, we know that Apache Pig is used with Hadoop , and Hadoop is based on the Java programming language. Apache Pig came into the Hadoop world as a boon for all such programmers.

For supporting data operations such as filters, joins, ordering, etc. What is Hadoop? The main reason why programmers have started using Hadoop Pig is that it converts the scripts into a series of MapReduce tasks making their job easy.

Below is the architecture of Pig Hadoop:. Follow the below steps for the Apache Pig installation. Pig Hadoop was developed by Yahoo in the year so that they can have an ad-hoc method for creating and executing MapReduce jobs on huge data sets. The main motive behind developing Pig was to cut down on the time required for development via its multi-query approach.

Pig is a high-level data flow system that renders you a simple language platform popularly known as Pig Latin that can be used for manipulating data and queries. Pig is used by Microsoft, Yahoo and Google, to collect and store large data sets in the form of web crawls, clickstreams, and search logs.

Pig at times finds its usage in ad-hoc analysis and processing of information. Benefit of coding in Pig and Hive is - much fewer lines of code, which reduces the overall development and testing time.

Difference between pig and hive is Pig needs some mental adjustment for SQL users to learn. Pig Latin has many of the usual data processing concepts that SQL has, such as filtering, selecting, grouping, and ordering, but the syntax is a little different from SQL particularly the group by and flatten statements!

Hive is commonly used at Facebook for analytical purposes. Facebook promotes the Hive language. However, Yahoo! Their data engineers use Pig for data processing on their Hadoop clusters. Alternatively, you may choose one among Pig and Hive at your organization, if no standards are set.

Data engineers have better control over the dataflow ETL processes using Pig Latin, especially with procedural language background. Copy file SalesJan Here in this Apache Pig example, the file is in Folder input. If the file is stored in some other location give that name. Open pig. Skip to content. This mode is suitable only for analysis of small datasets using Pig in Hadoop. Map Reduce mode: In this mode, queries written in Pig Latin are translated into MapReduce jobs and are run on a Hadoop cluster cluster may be pseudo or fully distributed.

MapReduce mode with the fully distributed cluster is useful of running Pig on large datasets. Report a Bug. Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

At the present time, Pig's infrastructure layer consists of a compiler that produces sequences of Map-Reduce programs, for which large-scale parallel implementations already exist e.

Pig's language layer currently consists of a textual language called Pig Latin, which has the following key properties:. Apache Pig is released under the Apache 2.