---
title: "EXPLAIN clause"
description: "The EXPLAIN clause is a powerful diagnostic tool that shows how DuckDB plans to execute your SQL query."
canonical: "https://motherduck.com/glossary/explain-clause/"
related:
  - title: "EXPLAIN | MotherDuck Docs"
    url: "https://motherduck.com/docs/sql-reference/motherduck-sql-reference/explain/"
  - title: "DuckLake Architecture Deep Dive"
    url: "https://motherduck.com/blog/ducklake-architecture-deep-dive/"
  - title: "Query syntax | MotherDuck Docs"
    url: "https://motherduck.com/docs/sql-reference/duckdb-sql-reference/query-syntax/"
gated_asset:
  title: "DuckLake: The Lakehouse Table Format"
  url: "https://motherduck.com/lp/ducklake-lakehouse-table-format-book-full/"
---

# EXPLAIN clause

> The EXPLAIN clause is a powerful diagnostic tool that shows how DuckDB plans to execute your SQL query.

## Overview
The `EXPLAIN` clause is a powerful diagnostic tool that shows how DuckDB plans to execute your SQL query. When you add `EXPLAIN` before any SQL statement, instead of running the query, DuckDB will display the sequence of operations (known as the query plan) it would use to produce the results.

<glossary-callout guide="duckdb-cheatsheet-full" />

## Basic Usage
The simplest way to use `EXPLAIN` is to prefix it to your query:

```sql
EXPLAIN SELECT * FROM customers WHERE country = 'USA';
```

## EXPLAIN ANALYZE 
DuckDB also supports `EXPLAIN ANALYZE`, which both shows the query plan and actually executes the query, providing additional runtime statistics about how long each operation took and how many rows were processed:

```sql
EXPLAIN ANALYZE 
SELECT customer_name, COUNT(*) 
FROM orders 
GROUP BY customer_name 
HAVING COUNT(*) > 10;
```

## Understanding Query Plans
DuckDB's query plans are displayed as a tree structure, with each operation indented to show its relationship to other operations. The operations are executed from bottom to top, with the results flowing upward through the tree. Key components you'll see include:

- SCAN operations that read data from tables
- FILTER operations that implement WHERE clauses
- JOIN operations that combine tables
- GROUP BY operations that aggregate data
- PROJECTION operations that select specific columns

For example:
```sql
EXPLAIN
SELECT r.region_name, COUNT(*)
FROM customers c
JOIN regions r ON c.region_id = r.id
GROUP BY r.region_name;
```

This will show how DuckDB plans to join the tables, group the results, and count the records for each region.

## DuckDB Specifics
Unlike some databases that use complex notation or require special formatting to read query plans, DuckDB presents its plans in a clear, hierarchical text format that's easy to read. DuckDB's query planner is also designed specifically for analytical workloads, so you'll often see operations optimized for processing large amounts of data in parallel using vectorized execution.