


How Can I Efficiently Count Data Occurrences in SQL with Multiple Conditions?
Efficient SQL condition counting method
In SQL, there are many ways to group and count the occurrences of data according to a specific column. In PostgreSQL, the most straightforward way is to use a CASE expression, as shown in the example query. However, this approach can become cumbersome when dealing with a large number of possible values.
PostgreSQL 9.4 and later provides a more optimized and flexible method: the FILTER
aggregation option. The FILTER
clause allows you to apply additional conditions to an aggregate function, counting only specific values that match a specific condition.
SELECT category , count(*) FILTER (WHERE question1 = 0) AS zero , count(*) FILTER (WHERE question1 = 1) AS one , count(*) FILTER (WHERE question1 = 2) AS two FROM reviews GROUP BY 1;
This query effectively counts the occurrences of zero, one, and two in the question1 column, grouped by the category column.
For further optimization, the following short version can be used:
SELECT category , count(question1 = 0 OR NULL) AS zero , count(question1 = 1 OR NULL) AS one , count(question1 = 2 OR NULL) AS two FROM reviews GROUP BY 1;
For complex scenarios involving multiple conditions or a large number of options, the crosstab()
function provides excellent performance and simplicity:
SELECT * FROM crosstab( 'SELECT category, question1, count(*) AS ct FROM reviews GROUP BY 1, 2 ORDER BY 1, 2' , 'VALUES (0), (1), (2)' ) AS ct (category text, zero int, one int, two int);
This crosstab
query produces a result set containing all required counts, presented as named columns for easy access and analysis.
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