Search Shortcut cmd + k | ctrl + k
- Installation
- Documentation
- Getting Started
- Connect
- Data Import
- Overview
- Data Sources
- CSV Files
- JSON Files
- Overview
- Creating JSON
- Loading JSON
- Writing JSON
- JSON Type
- JSON Functions
- Format Settings
- Installing and Loading
- SQL to / from JSON
- Caveats
- Multiple Files
- Parquet Files
- Partitioning
- Appender
- INSERT Statements
- Client APIs
- Overview
- C
- Overview
- Startup
- Configuration
- Query
- Data Chunks
- Vectors
- Values
- Types
- Prepared Statements
- Appender
- Table Functions
- Replacement Scans
- API Reference
- C++
- CLI
- Dart
- Go
- Java
- Julia
- Node.js (Neo)
- Node.js
- Python
- Overview
- Data Ingestion
- Conversion between DuckDB and Python
- DB API
- Relational API
- Function API
- Types API
- Expression API
- Spark API
- API Reference
- Known Python Issues
- R
- Rust
- Swift
- Wasm
- ADBC
- ODBC
- SQL
- Introduction
- Statements
- Overview
- ANALYZE
- ALTER TABLE
- ALTER VIEW
- ATTACH and DETACH
- CALL
- CHECKPOINT
- COMMENT ON
- COPY
- CREATE INDEX
- CREATE MACRO
- CREATE SCHEMA
- CREATE SECRET
- CREATE SEQUENCE
- CREATE TABLE
- CREATE VIEW
- CREATE TYPE
- DELETE
- DESCRIBE
- DROP
- EXPORT and IMPORT DATABASE
- INSERT
- PIVOT
- Profiling
- SELECT
- SET / RESET
- SET VARIABLE
- SUMMARIZE
- Transaction Management
- UNPIVOT
- UPDATE
- USE
- VACUUM
- LOAD / INSTALL
- Query Syntax
- SELECT
- FROM and JOIN
- WHERE
- GROUP BY
- GROUPING SETS
- HAVING
- ORDER BY
- LIMIT and OFFSET
- SAMPLE
- Unnesting
- WITH
- WINDOW
- QUALIFY
- VALUES
- FILTER
- Set Operations
- Prepared Statements
- Data Types
- Overview
- Array
- Bitstring
- Blob
- Boolean
- Date
- Enum
- Interval
- List
- Literal Types
- Map
- NULL Values
- Numeric
- Struct
- Text
- Time
- Timestamp
- Time Zones
- Union
- Typecasting
- Expressions
- Overview
- CASE Statement
- Casting
- Collations
- Comparisons
- IN Operator
- Logical Operators
- Star Expression
- Subqueries
- Functions
- Overview
- Aggregate Functions
- Array Functions
- Bitstring Functions
- Blob Functions
- Date Format Functions
- Date Functions
- Date Part Functions
- Enum Functions
- Interval Functions
- Lambda Functions
- List Functions
- Map Functions
- Nested Functions
- Numeric Functions
- Pattern Matching
- Regular Expressions
- Struct Functions
- Text Functions
- Time Functions
- Timestamp Functions
- Timestamp with Time Zone Functions
- Union Functions
- Utility Functions
- Window Functions
- Constraints
- Indexes
- Meta Queries
- DuckDB's SQL Dialect
- Samples
- Configuration
- Extensions
- Overview
- Core Extensions
- Community Extensions
- Working with Extensions
- Versioning of Extensions
- Arrow
- AutoComplete
- AWS
- Azure
- Delta
- Excel
- Full Text Search
- httpfs (HTTP and S3)
- Iceberg
- ICU
- inet
- jemalloc
- MySQL
- PostgreSQL
- Spatial
- SQLite
- Substrait
- TPC-DS
- TPC-H
- VSS
- Guides
- Overview
- Data Viewers
- Database Integration
- File Formats
- Overview
- CSV Import
- CSV Export
- Directly Reading Files
- Excel Import
- Excel Export
- JSON Import
- JSON Export
- Parquet Import
- Parquet Export
- Querying Parquet Files
- Network and Cloud Storage
- Overview
- HTTP Parquet Import
- S3 Parquet Import
- S3 Parquet Export
- S3 Iceberg Import
- S3 Express One
- GCS Import
- Cloudflare R2 Import
- DuckDB over HTTPS / S3
- Meta Queries
- Describe Table
- EXPLAIN: Inspect Query Plans
- EXPLAIN ANALYZE: Profile Queries
- List Tables
- Summarize
- DuckDB Environment
- ODBC
- Performance
- Overview
- Environment
- Import
- Schema
- Indexing
- Join Operations
- File Formats
- How to Tune Workloads
- My Workload Is Slow
- Benchmarks
- Python
- Installation
- Executing SQL
- Jupyter Notebooks
- SQL on Pandas
- Import from Pandas
- Export to Pandas
- Import from Numpy
- Export to Numpy
- SQL on Arrow
- Import from Arrow
- Export to Arrow
- Relational API on Pandas
- Multiple Python Threads
- Integration with Ibis
- Integration with Polars
- Using fsspec Filesystems
- SQL Editors
- SQL Features
- Snippets
- Glossary of Terms
- Browse Offline
- Operations Manual
- Overview
- Limits
- Non-Deterministic Behavior
- Embedding DuckDB
- DuckDB's Footprint
- Securing DuckDB
- Development
- DuckDB Repositories
- Testing
- Overview
- sqllogictest Introduction
- Writing Tests
- Debugging
- Result Verification
- Persistent Testing
- Loops
- Multiple Connections
- Catch
- Profiling
- Release Calendar
- Building
- Benchmark Suite
- Internals
- Sitemap
- Why DuckDB
- Media
- FAQ
- Code of Conduct
- Live Demo
Documentation
/ Guides
/ Meta Queries
EXPLAIN ANALYZE: Profile Queries
Prepending a query with EXPLAIN ANALYZE both pretty-prints the query plan,
and executes it, providing run-time performance numbers for every operator, as well as the estimated cardinality (EC) and the actual cardinality.
EXPLAIN ANALYZE SELECT * FROM tbl;
Note that the cumulative wall-clock time that is spent on every operator is shown. When multiple threads are processing the query in parallel, the total processing time of the query may be lower than the sum of all the times spent on the individual operators.
Below is an example of running EXPLAIN ANALYZE on a query:
CREATE TABLE students (name VARCHAR, sid INTEGER);
CREATE TABLE exams (eid INTEGER, subject VARCHAR, sid INTEGER);
INSERT INTO students VALUES ('Mark', 1), ('Joe', 2), ('Matthew', 3);
INSERT INTO exams VALUES (10, 'Physics', 1), (20, 'Chemistry', 2), (30, 'Literature', 3);
EXPLAIN ANALYZE
SELECT name
FROM students
JOIN exams USING (sid)
WHERE name LIKE 'Ma%';
┌─────────────────────────────────────┐
│┌───────────────────────────────────┐│
││ Total Time: 0.0008s ││
│└───────────────────────────────────┘│
└─────────────────────────────────────┘
┌───────────────────────────┐
│ EXPLAIN_ANALYZE │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ 0 │
│ (0.00s) │
└─────────────┬─────────────┘
┌─────────────┴─────────────┐
│ PROJECTION │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ name │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ 2 │
│ (0.00s) │
└─────────────┬─────────────┘
┌─────────────┴─────────────┐
│ HASH_JOIN │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ INNER │
│ sid = sid │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ├──────────────┐
│ EC: 1 │ │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │ │
│ 2 │ │
│ (0.00s) │ │
└─────────────┬─────────────┘ │
┌─────────────┴─────────────┐┌─────────────┴─────────────┐
│ SEQ_SCAN ││ FILTER │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ││ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ exams ││ prefix(name, 'Ma') │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ││ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ sid ││ EC: 1 │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ││ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ EC: 3 ││ 2 │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ││ (0.00s) │
│ 3 ││ │
│ (0.00s) ││ │
└───────────────────────────┘└─────────────┬─────────────┘
┌─────────────┴─────────────┐
│ SEQ_SCAN │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ students │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ sid │
│ name │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ Filters: name>=Ma AND name│
│ <Mb AND name IS NOT NULL │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ EC: 1 │
│ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ ─ │
│ 2 │
│ (0.00s) │
└───────────────────────────┘
See Also
For more information, see the ”Profiling” page.