For example, Yahoo uses Apache Pig to analyse data gathered from Yahoo search engines and Yahoo News Feeds. Research on large raw data sets like data processing for search platforms.Provides many built-in operators to support data operationsĪpache Pig is used for analyzing and performing tasks involving ad-hoc processing. Performing data operations is a humongous taskĤ. Provides nested data types like tuples, bags, and mapsĤ. It is a low-level data processing paradigmģ. ♣ Tip: In this question, you should explain what were the problems with MapReduce which led to the development of Apache Pig by Yahoo. Highlight the key differences between MapReduce and Apache Pig. Hadoop Interview Questions and Answers | Edurekaġ. Now moving on, let us look at the Apache Pig interview questions. ♣ Tip: Before going through this Apache Pig interview questions, I would suggest you to go through Apache Pig Tutorial to revise your Pig concepts. to read, write, and process large data sets. ♦ Pig Latin provides various built-in operators like join, sort, filter, etc. User Defined Functions (UDF) can be written in different language like Java, Python, Ruby, etc. ♦ Pig allows programmers to write custom functions which is unavailable in Pig. ♦ Apache Pig automatically optimizes the tasks before execution, i.e. It can handle inconsistent schema (in case of unstructured data). ♦Apache Pig follows ETL (Extract Transform Load) process. ♦ Apache Pig has two main components – the Pig Latin language and the Pig Run-time Environment, in which Pig Latin programs are executed. We can perform data manipulation operations very easily in Hadoop using Apache Pig. It is designed to provide an abstraction over MapReduce, reducing the complexities of writing a MapReduce task using Java programming. ♦ Apache Pig is a platform, used to analyze large data sets representing them as data flows. Important points to remember about Apache Pig: We will be happy to answer them, and spread the word to the community of fellow job seekers. In case you have attended Pig interviews previously, we encourage you to add your questions in the comments tab. The list of questions has been carefully put together after much research and under the strict guidance of certified Big Data Hadoop experts who have been working actively in the industry for several years now. I hope you must not have missed the earlier blogs of our Hadoop Interview Question series.Īfter going through the Pig interview questions, you will get an in-depth knowledge of questions that are frequently asked by employers in Hadoop interviews. Looking out for Apache Pig Interview Questions that are frequently asked by employers? Here is the fifth blog of Hadoop Interview Questions series, which covers Apache PIG interview questions.
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