How Can I Optimize Postgres Queries on jsonb Arrays for Improved Performance?

Querying Structures in Arrays using Postgres jsonb

Jsonb arrays can store structured data in Postgres, facilitating queries with nested objects. However, accessing array values with sequential indexes can result in sequential scans.

Proper Indexing for Improved Query Performance

To optimize queries involving jsonb array comparisons, specifically queries like the one provided (checking for events within a certain time range), the following steps can be taken:

• Use jsonb_path_ops Operator Class: This ensures efficient matching for complex jsonb comparisons involving greater than or less than operators.

Basic Approach (Postgres 12 and Later)

SELECT l.*
FROM   locations l
WHERE  l.events @? '$[*] ? (@.event_slug == "test_1")
                         ? (@.end_time.datetime() <p><strong>Advanced Approach Utilizing Materialized Views</strong></p><p>If complex queries still result in poor performance, consider creating a materialized view with normalized relevant attributes:</p>

• Create Event Data Type:

  CREATE TYPE event_type AS (
   , event_slug  text
   , start_time  timestamp
   , end_time    timestamp
  );

• Create Materialized View:

  CREATE MATERIALIZED VIEW loc_event AS
  SELECT l.location_id, e.event_slug, e.end_time  -- start_time not needed
  FROM   locations l, jsonb_populate_recordset(null::event_type, l.events) e;

• Index Materialized View:

  CREATE INDEX loc_event_idx ON loc_event (event_slug, end_time, location_id);

• Query Materialized View:

  SELECT *
  FROM   loc_event
  WHERE  event_slug = 'test_1'
  AND    end_time  >= '2014-10-30 14:04:06 -0400'::timestamptz;

By utilizing the proper operator class and considering advanced approaches like materialized views, you can achieve optimal performance for queries involving comparisons on jsonb array data.

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