How to Optimally Count Occurrences in Grouped Data Using PostgreSQL?

Efficiently count the number of occurrences in PostgreSQL grouped data

PostgreSQL provides a variety of methods to count the occurrences of data in grouped tables. For example, you can use the CASE WHEN statement to count specific values:

<code class="language-sql">SELECT
    sum(CASE WHEN question1 = 0 THEN 1 ELSE 0 END) AS ZERO,
    sum(CASE WHEN question1 = 1 THEN 1 ELSE 0 END) AS ONE,
    sum(CASE WHEN question1 = 2 THEN 1 ELSE 0 END) AS TWO,
    category
FROM reviews
    GROUP BY category</code>

However, when the number of possible values ​​increases, using the CASE WHEN statement becomes increasingly cumbersome. In PostgreSQL 9.4 and later, the aggregate FILTER option provides a cleaner and potentially faster solution:

<code class="language-sql">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;</code>

For brevity, a simplified syntax can be used:

<code class="language-sql">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;</code>

For large option lists, the crosstab() function provides a more performant alternative:

<code class="language-sql">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);</code>

In summary, PostgreSQL provides multiple methods for conditional SQL counting. The FILTER option provides a concise and efficient solution, while the crosstab() function provides the best performance for handling a large number of options.

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