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You're reading from  Apache Hive Essentials

Product typeBook
Published inFeb 2015
Reading LevelIntermediate
PublisherPackt
ISBN-139781783558575
Edition1st Edition
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Author (1)
Dayong Du
Dayong Du
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Dayong Du

Dayong Du has all his career dedicated to enterprise data and analytics for more than 10 years, especially on enterprise use case with open source big data technology, such as Hadoop, Hive, HBase, Spark, etc. Dayong is a big data practitioner as well as author and coach. He has published the 1st and 2nd edition of Apache Hive Essential and coached lots of people who are interested to learn and use big data technology. In addition, he is a seasonal blogger, contributor, and advisor for big data start-ups, co-founder of Toronto big data professional association.
Read more about Dayong Du

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Advanced aggregation – GROUPING SETS


Hive has offered the GROUPING SETS keywords to implement advanced multiple GROUP BY operations against the same set of data. Actually, GROUPING SETS is a shorthand way of connecting several GROUP BY result sets with UNION ALL. The GROUPING SETS keyword completes all processes in one stage of jobs, which is more efficient than GROUP BY and UNION ALL having multiple stages. A blank set () in the GROUPING SETS clause calculates the overall aggregation. The following are a few examples to show the equivalence of GROUPING SETS. For better understanding, we can say that the outer level of GROUPING SETS defines on what data UNION ALL is to be implemented. The inner level defines on what data GROUP BY is to be implemented in each UNION ALL.

SELECT name, work_place[0] AS main_place, 
count(employee_id) AS emp_id_cnt 
FROM employee_id
GROUP BY name, work_place[0] GROUPING SETS((name, work_place[0]));
||
SELECT name, work_place[0] AS main_place, 
count(employee_id...
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Apache Hive Essentials
Published in: Feb 2015Publisher: PacktISBN-13: 9781783558575

Author (1)

author image
Dayong Du

Dayong Du has all his career dedicated to enterprise data and analytics for more than 10 years, especially on enterprise use case with open source big data technology, such as Hadoop, Hive, HBase, Spark, etc. Dayong is a big data practitioner as well as author and coach. He has published the 1st and 2nd edition of Apache Hive Essential and coached lots of people who are interested to learn and use big data technology. In addition, he is a seasonal blogger, contributor, and advisor for big data start-ups, co-founder of Toronto big data professional association.
Read more about Dayong Du