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SQL Query Execution Plan & AST Visualizer

Visualize PostgreSQL & MySQL EXPLAIN (ANALYZE, BUFFERS) execution plan trees, detect costly sequential scans, hash join bottlenecks, and get index optimization suggestions.

Quick Answer & Summary

The SQL Query Execution Plan & AST Visualizer is a fast, accurate Developer Tools utility designed to visualize postgresql & mysql explain (analyze, buffers) execution plan trees, detect costly sequential scans, hash join bottlenecks, and get index optimization suggestions. entirely in your browser with zero server data storage.

SQL Query Execution Plan & AST Visualizer

Visualize PostgreSQL & MySQL EXPLAIN (ANALYZE, BUFFERS) trees, detect costly sequential scans and nested loops, and get index suggestions.

Presets:

Visual Plan Execution Tree

Total Cost: 1485.519.45 ms
Seq Scanon orders
Cost: 1485.5Rows: 5200Time: 18.23ms
Filter: (status = 'PROCESSING'::text)

Optimization Checklist (1)

Sequential Table Scan on "orders"

Full table scan detected without an index. The database reads every disk block to find matching rows.

Add a B-Tree index: CREATE INDEX idx_orders_filter ON orders (column_name);

Relational Database Query Planner & Execution Cost Mechanics

Modern RDBMS query optimizers (such as PostgreSQL Cost-Based Optimizer and MySQL Hypergraph Optimizer) transform declarative SQL into an optimal execution tree by evaluating combinatorial scan methods, join algorithms, and sorting strategies.

Core Execution Node Types

  • Seq Scan (Sequential Scan): Reads every heap page sequentially. Fast for small tables (<100 rows), but catastrophic for millions of records.
  • Index Scan / Index Only Scan: Traverses B-Tree index pages. Index Only Scans avoid visiting the table heap entirely if all required columns reside in the index.
  • Hash Join: Constructs an in-memory hash table on the smaller inner relation, then probes it with rows from the outer relation.
  • Nested Loop: Loops over every row of the outer table and performs a lookup on the inner table. Optimal when outer row count is small and inner table is indexed.

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Documentation & Guide

How to Use SQL Query Execution Plan & AST Visualizer

1

Generate EXPLAIN Output

In your database client (psql, DBeaver, pgAdmin), run "EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) SELECT ...;" or MySQL "EXPLAIN FORMAT=JSON SELECT ...;".

2

Paste Plan Into Visualizer

Paste the JSON or text execution plan output into the input editor or choose a built-in preset.

3

Inspect Tree & Cost Nodes

Review the visual execution tree. High-cost nodes and full table scans are highlighted in red and amber badges.

4

Apply Index & Query Optimizations

Follow the generated Optimization Checklist to add missing B-Tree indexes or refresh stale statistics.

Practical Examples & Conversions

Input
EXPLAIN (ANALYZE, FORMAT JSON) SELECT * FROM orders WHERE status = "PROCESSING";
Output
Recommendation: CREATE INDEX idx_orders_status ON orders (status);

Frequently Asked Questions (PAA)

Related Tools & Converters

Authoritative Standards & Citations

Calculations and algorithms on this page are implemented and verified in strict accordance with the following official technical specifications: