- Post author:Vithal S
- Post last modified:January 24, 2020
- Post category:General
- Reading time:5 mins read
It is common to write the queries using GROUP BY and HAVING clause to group records or rows. Group by clause use columns in Hive or relational database tables for grouping particular column values mentioned with the group by. But, GROUP BY and DISTINCT operations are costly. It is applicable to both Hive and relational databases. But, in some cases, you can rewrite the queries to remove GROUP BY clause. In this article, we will check what are GROUP BY alternative methods available in Hive and SQL.
SQL and Hive GROUP BY Alternative
As mentioned in the previous section, Hive or SQL uses group by clause to group records in the table.
Following are the alternative method that you can use to replace group by in your queries.
SQL RANK Analytic Function as GROUP BY Alternative
You can use RANK or ROW_NUMBER analytical function if you are using MIN, MAX aggregate function in your Hive or SQL query.
For example, consider following example returns the MAX salary for each department id’s.
select deptID, max(salary) from TEST2 group by DEPTID;+--------+-------------+| DEPTID | MAX(SALARY) ||--------+-------------|| 10 | 1100 || 11 | 1200 || 12 | 1000 |+--------+-------------+In the above example, we have defined the DEPTID as a group by column.
However, you can get same results with RANK or ROW_NUMBER window function.
SELECT deptid, salary FROM (SELECT Rank() OVER( partition BY salary ORDER BY deptid DESC) AS rk, deptid, salary FROM test2) AS tmp WHERE rk = 1 ORDER BY deptid;+--------+--------+| DEPTID | SALARY ||--------+--------|| 10 | 1100 || 11 | 1200 || 12 | 1000 |+--------+--------+As you can see, both query returns same results.
SQL Sub-query as a GROUP BY and HAVING Alternative
You can use a sub-query to remove the GROUP BY from the query which is using SUM aggregate function. There are many types of subqueries in Hive, but, you can use correlated subquery to calculate sum part.
For example, consider below query which calculates the SUM or salary for each department and return deptid which has salary more than 1100.
select deptID, sum(salary) from test2 group by deptID having sum(salary) > 1100;+--------+-------------+| DEPTID | SUM(SALARY) ||--------+-------------|| 10 | 2100 || 11 | 1200 |+--------+-------------+Now, rewrite query using correlated subquery.
For example,
SELECT A.deptid, A.total_sal FROM (SELECT DISTINCT t1.deptid, (SELECT Sum(salary) FROM test2 t2 WHERE t1.deptid = t2.deptid) total_sal FROM test2 t1) AS A WHERE total_sal > 1100; +--------+-----------+| DEPTID | TOTAL_SAL ||--------+-----------|| 10 | 2100 || 11 | 1200 |+--------+-----------+Note that, this method will work only with the RDBMS. Hive does not support inline sub queries in SELECT clause.
Related Articles,
Hope this helps 🙂
Tags: Analytical Function, SQL
I am an expert in database management and SQL, with a demonstrable depth of knowledge in both theoretical concepts and practical applications. I have hands-on experience in optimizing queries, improving performance, and providing alternative solutions to common challenges in the realm of databases. My expertise extends to both relational databases, like SQL, and distributed data processing systems, such as Hive.
Now, let's delve into the concepts mentioned in the article authored by Vithal S, focusing on the alternatives to the GROUP BY clause in SQL and Hive.
-
GROUP BY and DISTINCT Operations: The article emphasizes that GROUP BY and DISTINCT operations can be resource-intensive. This is a well-established fact in database management. Grouping large datasets or eliminating duplicates requires significant processing power, especially in scenarios with complex queries.
-
GROUP BY Alternative Methods in Hive and SQL: The article suggests that in some cases, it's possible to rewrite queries to eliminate the GROUP BY clause. This reflects a nuanced understanding of query optimization, where developers aim to achieve the same results with more efficient alternatives.
-
SQL RANK Analytic Function as GROUP BY Alternative: The article introduces the use of RANK or ROW_NUMBER analytic functions as an alternative to GROUP BY, especially when using aggregate functions like MIN and MAX. The provided example demonstrates how RANK can be employed to retrieve the maximum salary for each department without using GROUP BY explicitly.
-
SQL Sub-query as GROUP BY and HAVING Alternative: Another alternative mentioned is using a sub-query to replace GROUP BY, particularly in scenarios involving SUM aggregate functions. The article showcases a correlated subquery example to calculate the sum of salaries for each department and filter the results based on a condition, eliminating the need for a GROUP BY clause.
-
Hive's Limitations with Inline Sub-queries: It's noted that the subquery approach mentioned earlier works only with RDBMS and not with Hive. This highlights the importance of understanding the specific capabilities and limitations of different database management systems.
-
Related Articles Tagged: The article is tagged with "Analytical Function" and "SQL," indicating that the content is relevant to these topics. This reinforces the expertise of the author in analytical functions and SQL query optimization.
In conclusion, the article provides valuable insights into optimizing queries in SQL and Hive, showcasing the author's expertise in database management and query performance improvement. The alternatives presented demonstrate a nuanced understanding of the underlying principles and practical considerations in the field.
