How Can I Optimize GROUP BY Queries to Efficiently Retrieve the Latest Row for Each User?

Optimization Strategies for GROUP BY Query to Retrieve Latest Row per User

Given a table with user messages structured as log_date, user_id, and payload, the task is to efficiently retrieve the latest record for each user before a specific date.

Multicolumn Index

To improve read performance, create a multicolumn index on user_id and log_date:

CREATE INDEX log_combo_idx ON log (user_id, log_date DESC NULLS LAST);

Index-Only Scans with Covering Index

For index-only scans, define a covering index that includes the payload column:

CREATE INDEX log_combo_covering_idx ON log (user_id, log_date DESC NULLS LAST) INCLUDE (payload);

SELECT DISTINCT ON()

For small tables or few rows per user_id, using SELECT DISTINCT ON() can be efficient:

SELECT DISTINCT ON(user_id) log_date, payload
FROM log
WHERE log_date <p><strong>Index Skip Scan Emulation</strong></p><p>For large tables with many rows per user_id, consider emulating an index skip scan using a recursive CTE with LATERAL join:</p><pre class="brush:php;toolbar:false">WITH RECURSIVE cte AS (
   (
   SELECT user_id, log_date, payload
   FROM   log
   WHERE  log_date  c.user_id  -- lateral reference
      AND    log_date <p><strong>Separate Users Table</strong></p><p>If a separate users table exists, simplified solutions are possible:</p><p><strong>LATERAL Join</strong></p><pre class="brush:php;toolbar:false">SELECT u.user_id, l.log_date, l.payload
FROM   users u
CROSS  JOIN LATERAL (
   SELECT l.log_date, l.payload
   FROM   log l
   WHERE  l.user_id = u.user_id         -- lateral reference
   AND    l.log_date <p><strong>Correlated Subquery</strong></p><pre class="brush:php;toolbar:false">SELECT user_id, (combo1).*              -- note parentheses
FROM (
   SELECT u.user_id
        , (SELECT (l.log_date, l.payload)::combo
           FROM   log l
           WHERE  l.user_id = u.user_id
           AND    l.log_date <p>These optimizations improve query performance by utilizing indexes, emulating skip scans, and taking advantage of a separate table for user information.</p>

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