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Welcome to the Introduction to Pig MCQs Page

Dive deep into the fascinating world of Introduction to Pig with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Introduction to Pig, a crucial aspect of Hadoop. In this section, you will encounter a diverse range of MCQs that cover various aspects of Introduction to Pig, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Hadoop.

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Check out the MCQs below to embark on an enriching journey through Introduction to Pig. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Hadoop.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Introduction to Pig. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Introduction to Pig MCQs | Page 4 of 6

Discuss
Answer: (d).All of the mentioned
Q32.
_________ are scanned in the order they are specified on the command line.
Discuss
Answer: (d).Both parameter files and command line parameters
Discuss
Answer: (c).a = load '/mapred/history/done' using HadoopJobHistoryLoader() as (j:map[], m:map[], r:map[]);
b = group a by (j#'PIG_SCRIPT_ID', j#'USER', j#'JOBNAME');
c = foreach b generate group.$1, group.$2, COUNT(a);
d = filter c by $2 > 3;
dump d;
Discuss
Answer: (a).a = load '/mapred/history/done' using HadoopJobHistoryLoader() as (j:map[], m:map[], r:map[]);
b = foreach a generate j#'PIG_SCRIPT_ID' as id, j#'USER' as user, j#'JOBNAME' as script_name,
(Long) j#'SUBMIT_TIME' as start, (Long) j#'FINISH_TIME' as end;
c = group b by (id, user, script_name)
d = foreach c generate group.user, group.script_name, (MAX(b.end) - MIN(b.start)/1000;
dump d;
Discuss
Answer: (c).a = load '/mapred/history/done' using HadoopJobHistoryLoader() as (j:map[], m:map[], r:map[]);
b = foreach a generate j#'PIG_SCRIPT_ID' as id, j#'USER' as user, j#'QUEUE_NAME' as queue;
c = group b by (id, user, queue) parallel 10;
d = foreach c generate group.user, group.queue, COUNT(b);
dump d;
Discuss
Answer: (a).a = load '/mapred/history/done' using HadoopJobHistoryLoader() as (j:map[], m:map[], r:map[]);
b = foreach a generate (Chararray) j#'STATUS' as status, j#'PIG_SCRIPT_ID' as id, j#'USER' as user, j#'JOBNAME' as script_name, j#'JOBID' as job;
c = filter b by status != 'SUCCESS';
dump c;
Discuss
Answer: (b).a = load '/mapred/history/done' using HadoopJobHistoryLoader() as (j:map[], m:map[], r:map[]);
b = foreach a generate j#'PIG_SCRIPT_ID' as id, j#'USER' as user, j#'JOBNAME' as script_name, (Long) r#'NUMBER_REDUCES' as reduces;
c = group b by (id, user, script_name) parallel 10;
d = foreach c generate group.user, group.script_name, MAX(b.reduces) as max_reduces;
e = filter d by max_reduces == 1;
dump e;
Q38.
Pig Latin is _______ and fits very naturally in the pipeline paradigm while SQL is instead declarative.
Discuss
Answer: (b).procedural
Q39.
In comparison to SQL, Pig uses ______________
Discuss
Answer: (d).All of the mentioned
Q40.
Which of the following is an entry in jobconf?
Discuss
Answer: (b).pig.input.dirs
Page 4 of 6

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