Big Data Pig Assessment Test

Candidates Assessed

17638+

Organizations Served

127+

iMocha’s Big Data Pig programming skills test is the ideal pre-hire test for recruiters and hiring managers to assess candidates objectively. This test is useful for hiring job roles like Big Data Developer in Pig and Big Data Developer. Our test helps to reduce technical screening time by 80%.

About Big Data Pig Assessment Test

Big Data Pig online test assists recruiters and hiring managers to evaluate the Pig skills of Big Data-Pig developer before an interview. Big Data Pig is a platform used for analyzing large data sets which enable for expressing data analysis programs. Pig enables you to write complex data and is a simple SQL-like scripting language. Pig consists of two components - first is the language and the second is the runtime environment. Big Data Pig programming skills test is specially designed to check application, practical skills of a Big Data - Pig developer – as per industry standards.

Apache Pig knowledge test enables employers and recruiters to identify potential Big Data-Pig developers by evaluating working skills and job readiness. For this reason, the emphasis is laid upon evaluating the knowledge of applied skills gained through real work experience, rather than theoretical knowledge.

Are you a jobseeker looking to sharpen your skills?

Test Summary

Apache Pig coding test is designed by our subject matter experts to evaluate the job skills of an applicant and their knowledge about Big Data Pig. Using powerful reporting, you can have a detailed analysis of the test results to help you make a better hiring decision and predict the candidate’s performance.

Pig Big Data assessment test may contain MCQs (Multiple Choice Questions), MAQs (Multiple Answer Questions), Fill in the Blanks, Descriptive, Whiteboard Questions, Audio / Video Questions, AI-LogicBox, Coding Simulations, True or False Questions, etc.

Test Duration: 20 minutes

No. of Questions: 10

Level of Expertise: Entry/Mid/Expert

Useful for hiring

  • Big Data Developer - Pig
  • Big Data Developer

Topics Covered


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Pig Commands

iMocha’s Big Data Pig online test helps recruiters and hiring managers to evaluate candidate’s ability to use Big Data Pig commands

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Optimization in Pig

This test evaluates candidate’s understanding about optimization rules which help to improve performance and efficiency in Big Data

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Pig Scripts

Our test assesses candidate’s ability to run Pig scripts which convert into a series of MapReduce jobs that are run on the Apache Hadoop cluster

Sample Questions

Choose from our 100,000+ question library or add your own questions to make powerful custom tests

Question types:

Multiple Option

Topic:

-

Difficulty:

Easy


Q 1. Assume we use datafu lib in pig:

DEFINE EmptyBagToNullFields datafu.pig.bags.EmptyBagToNullFields();
data = FOREACH (COGROUP input1 BY key, input2 BY key, input3 BY key) GENERATE
    FLATTEN(input1),
      FLATTEN(EmptyBagToNullFields(input2)),
      FLATTEN(EmptyBagToNullFields(input3));

 Which script will define macro similar to above script?
DEFINE myFunction(relation1, key1, relation2, key2, relation3, key3) returns result 
{
    A = GROUP $relation1 BY $key1, $relation2 BY $key2, $relation3 BY $key3;
    $result = FOREACH A GENERATE
        FLATTEN($relation1),
        FLATTEN(EmptyBagToNullFields($relation2)),
        FLATTEN(EmptyBagToNullFields($relation3));
}
DEFINE myFunction(relation1, key1, relation2, key2, relation3, key3) returns result 
{
    A = JOIN $relation1 BY $key1, $relation2 BY $key2, $relation3 BY $key3;
    $result = FOREACH A GENERATE
        FLATTEN($relation1),
        FLATTEN(EmptyBagToNullFields($relation2)),
        FLATTEN(EmptyBagToNullFields($relation3));
}
Cannot replace to have same logic with above script
DEFINE myFunction(relation1, key1, relation2, key2, relation3, key3) returns result 
{
    A = COGROUP $relation1 BY $key1, $relation2 BY $key2, $relation3 BY $key3;
    $result = FOREACH A GENERATE
        FLATTEN($relation1),
        FLATTEN(EmptyBagToNullFields($relation2)),
        FLATTEN(EmptyBagToNullFields($relation3));
}

Question types:

Multiple Option

Topic:

-

Difficulty:

Easy


Q 2. A = load 'Data1' as (name:chararray, team:chararray, position:bag{t:(p:chararray)}, bat:map[]);
B = foreach A generate name, team, position, bat#'batting_average' as batavg;
C = group B by team;
avgC  = foreach C generate group, AVG(B.batavg);
store avgC into 'by_team';
flattenData = foreach B generate name, team, flatten(position) as position, batavg;
D = group flattenData by position parallel 100;
avgD = foreach D generate group, AVG(flattenData.batavg);
store avgD into 'Rank';

How many reduce will run at D relation?
100
Not enough information
Depend on Data1 file
Depend on flattenData relation

Sample Report

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Skill wise performance report by iMocha

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difficulty level
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multiple skills
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Trusted By

Vipin Sharma, Mobile Programming
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“Thanks to Customer Success Team of iMocha, they have shared the best practices of quick test creation & also helped us in training all our recruiters for various functionalities of the tool. Now my team of 25 recruiters has adopted this measure & it has done wonders for our clients.”

Vipin Sharma, Mobile Programming

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