When working with PostgreSQL, understanding how queries execute can greatly improve performance tuning and optimization. PostgreSQL provides the EXPLAIN ANALYZE command to help developers analyze query execution plans. However, reading raw execution plans can be challenging. In this post, we will explore how to interpret EXPLAIN ANALYZE output and visualize it using online tools.

Understanding EXPLAIN ANALYZE

The EXPLAIN command in PostgreSQL provides insight into how a query will be executed by the planner. Adding ANALYZE to the command executes the query and provides actual runtime statistics. Here’s an example:

EXPLAIN ANALYZE
SELECT *
FROM orders
JOIN customers ON orders.customer_id = customers.id;

This query joins the orders and customers tables on customer_id. The output will contain details on join strategy, index usage, and execution time.

Example of EXPLAIN ANALYZE Output

Hash Join  (cost=35.00..75.00 rows=1000 width=64) (actual time=0.123..0.456 rows=1000 loops=1)
  Hash Cond: (orders.customer_id = customers.id)
  ->  Seq Scan on orders  (cost=0.00..30.00 rows=1000 width=32) (actual time=0.012..0.045 rows=1000 loops=1)
  ->  Hash  (cost=30.00..30.00 rows=1000 width=32) (actual time=0.098..0.100 rows=1000 loops=1)
        Buckets: 1024  Batches: 1  Memory Usage: 64kB
        ->  Seq Scan on customers  (cost=0.00..30.00 rows=1000 width=32) (actual time=0.015..0.038 rows=1000 loops=1)
Planning Time: 0.345 ms
Execution Time: 0.678 ms

Breaking Down the Output

• Join Type: The Hash Join indicates that PostgreSQL is using a hash-based strategy for joining tables.
• Sequential Scans: Seq Scan on orders and Seq Scan on customers indicate full table scans, which may be inefficient.
• Execution Time: The query took 0.678 ms to execute, which is useful for performance benchmarking.

Visualizing EXPLAIN ANALYZE

While text-based output provides useful insights, visualization tools can make it easier to understand execution plans. Some popular online tools include:

1. Depesz’s EXPLAIN Visualizer

• Copy the EXPLAIN ANALYZE output.
• Paste it into the tool.
• View a color-coded breakdown of query execution.

2. Dalibo’s EXPLAIN Visualizer

• Works similarly to Depesz’s tool.
• Provides graphical representation of execution nodes.

Improving Query Performance

Once you’ve analyzed and visualized the execution plan, consider optimizations such as:

• Adding Indexes: If a sequential scan is detected, adding an index can improve performance.
• Using Proper Join Types: Ensure the best join method is chosen based on data size and indexing.
• Partitioning Large Tables: Helps break down data for efficient scanning.

Conclusion

EXPLAIN ANALYZE is a powerful tool for debugging and optimizing PostgreSQL queries. By using visualization tools, developers can more easily interpret execution plans and make informed optimizations to improve database performance.

Have you used EXPLAIN ANALYZE before? What tools do you use to visualize query execution plans? Let us know in the comments!