Answer / Mayuri Chaudhary

Pig for Hadoop is a high-level data flow language and an Apache project. Here are some benefits of using Pig: 1) It abstracts the MapReduce programming model, making it easier for developers to write data analysis scripts without having to deal with low-level details such as key-value pairs or splitting and combining tasks. 2) Pig supports a wide variety of data types and operators, allowing for complex transformations and analyses. 3) Pig includes built-in UDFs (User Defined Functions) that can be used to extend the language's functionality. 4) Pig scripts are easier to read and understand than MapReduce programs, making collaboration and debugging more efficient.

What are the relational operators available related to Grouping and joining in Pig language?

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Explain the need for MapReduce while programming in Apache Pig?

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How Pig programming gets converted into MapReduce jobs?

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Pig Features ?

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How do you handle compression in pig?

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Why we use BloomMapFile?

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Why Do We Need Apache Pig?

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What is the difference between store and dumps commands?

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Explain Features of Pig?

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What are the advantages of pig language?

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What are the relational operators available related to combining and splitting in pig language?

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Why should we use ‘orderby’ keyword in pig scripts?

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