- Installation
- Documentation
- Getting Started
- Connect
- Data Import and Export
- 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
- Lakehouse Formats
- Client APIs
- Overview
- ADBC
- C
- Overview
- Startup
- Configuration
- Query
- Data Chunks
- Vectors
- Values
- Types
- Prepared Statements
- Appender
- Table Functions
- Replacement Scans
- API Reference
- C++
- CLI
- Overview
- Arguments
- Dot Commands
- Output Formats
- Editing
- Friendly CLI
- Safe Mode
- Autocomplete
- Syntax Highlighting
- Known Issues
- Go
- Java (JDBC)
- Overview
- Connect
- Import Data
- Run Queries
- Handle Results
- Write User Defined Functions
- Profile and Monitor
- Deploy as Native Image
- Troubleshoot
- Node.js (Neo)
- ODBC
- 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
- Overview
- Connect
- Import Data
- Run Queries
- Handle Results
- Write User Defined Functions
- Profile and Monitor
- Troubleshoot
- Wasm
- Tertiary Clients
- 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
- LOAD / INSTALL
- MERGE INTO
- PIVOT
- Profiling
- SELECT
- SET / RESET
- SET VARIABLE
- SHOW and SHOW DATABASES
- SUMMARIZE
- Transaction Management
- UNPIVOT
- UPDATE
- USE
- VACUUM
- 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
- Geometry
- Interval
- List
- Literal Types
- Map
- NULL Values
- Numeric
- Struct
- Text
- Time
- Timestamp
- Time Zones
- Union
- Typecasting
- Variant
- Expressions
- Overview
- CASE Expression
- Casting
- Collations
- Comparisons
- IN Operator
- Logical Operators
- Star Expression
- Subqueries
- TRY
- Functions
- Overview
- Aggregate Functions
- Array Functions
- Bitstring Functions
- Blob Functions
- Date Format Functions
- Date Functions
- Date Part Functions
- Enum Functions
- Geometry 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
- Overview
- Indexing
- Friendly SQL
- Keywords and Identifiers
- Order Preservation
- PostgreSQL Compatibility
- SQL Quirks
- PEG Parser
- Samples
- Configuration
- Extensions
- Overview
- Installing Extensions
- Advanced Installation Methods
- Distributing Extensions
- Versioning of Extensions
- Troubleshooting of Extensions
- Core Extensions
- Overview
- AutoComplete
- Avro
- AWS
- Azure
- Delta
- DuckLake
- Encodings
- Excel
- Full Text Search
- httpfs (HTTP and S3)
- Iceberg
- ICU
- inet
- jemalloc
- Lance
- MotherDuck
- MySQL
- ODBC
- Quack
- PostgreSQL
- Spatial
- SQLite
- TPC-DS
- TPC-H
- UI
- Unity Catalog
- Vortex
- VSS
- Quack Remote Protocol
- Guides
- Overview
- Data Viewers
- Database Integration
- File Formats
- Overview
- CSV Import
- CSV Export
- Directly Reading Files
- Directly Reading DuckDB Databases
- Excel Import
- Excel Export
- JSON Import
- JSON Export
- Parquet Import
- Parquet Export
- Querying Parquet Files
- File Access with the file: Protocol
- Meta Queries
- Describe Table
- EXPLAIN: Inspect Query Plans
- EXPLAIN ANALYZE: Profile Queries
- List Tables
- Summarize
- DuckDB Environment
- 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
- Fastly Object Storage Import
- SeaweedFS Import
- Tigris Import
- ODBC
- Performance
- Overview
- Environment
- Import
- Schema
- Indexing
- Join Operations
- File Formats
- How to Tune Workloads
- My Workload Is Slow
- Out-of-Memory Issues
- Benchmarks
- Working with Huge Databases
- Python
- Installation
- Executing SQL
- Jupyter Notebooks
- marimo 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
- Integration with PyTorch
- Using fsspec Filesystems
- SQL Editors
- SQL Features
- AsOf Join
- Full-Text Search
- Graph Queries
- query and query_table Functions
- Merge Statement for SCD Type 2
- Timestamp Issues
- Snippets
- Creating Synthetic Data
- Dutch Railway Datasets
- Sharing Macros
- Analyzing a Git Repository
- Importing Duckbox Tables
- Copying an In-Memory Database to a File
- Troubleshooting
- Glossary of Terms
- Browsing Offline
- Operations Manual
- Overview
- DuckDB's Footprint
- Installing DuckDB
- Logging
- User Agents
- Securing DuckDB
- Non-Deterministic Behavior
- Limits
- DuckDB Docker Container
- Development
- DuckDB Repositories
- Release Cycle
- Metrics
- Profiling
- Building DuckDB
- Overview
- Build Configuration
- Building Extensions
- Android
- Linux
- macOS
- Raspberry Pi
- Windows
- Python
- R
- Troubleshooting
- Unofficial and Unsupported Platforms
- Benchmark Suite
- Testing
- Internals
- Sitemap
- Live Demo
This page is a reference for all functions and settings provided by the iceberg extension. For task-oriented documentation, see the Overview (reading), Writing to Iceberg, and Iceberg REST Catalogs pages.
Functions that take a table accept either a path to a table's metadata (e.g., 'data/iceberg/lineitem_iceberg') or, when a catalog is attached, a fully qualified table name (e.g., my_catalog.default.my_table).
Common Parameters
The read and metadata table functions below accept the following named parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
allow_moved_paths |
BOOLEAN |
false |
Allows scanning Iceberg tables that are moved |
metadata_compression_codec |
VARCHAR |
'' |
Set to 'gzip' to read gzip-compressed metadata files |
snapshot_from_id |
UBIGINT |
NULL |
Access the snapshot with a specific id |
snapshot_from_timestamp |
TIMESTAMP |
NULL |
Access the snapshot as of a specific timestamp |
version |
VARCHAR |
'?' |
Explicit version string, hint file, or '?' for guessing |
version_name_format |
VARCHAR |
'v%s%s.metadata.json,%s%s.metadata.json' |
Controls how versions are converted to metadata file names |
See Selecting Metadata Versions for details.
Read and Metadata Functions
| Function | Description |
|---|---|
iceberg_scan(table, ⟨options⟩) |
Reads the data of an Iceberg table. Returns the table's columns. |
iceberg_metadata(table, ⟨options⟩) |
Returns one row per manifest entry. Columns: manifest_path, manifest_sequence_number, manifest_content, status, content, file_path, file_format, record_count. |
iceberg_snapshots(table, ⟨options⟩) |
Returns one row per snapshot. Columns: sequence_number, snapshot_id, timestamp_ms, manifest_list. |
iceberg_column_stats(table, ⟨options⟩) |
Returns per-data-file, per-column statistics. Columns include file_path, column_name, column_type, lower_bound, upper_bound, value_count, null_value_count, nan_value_count. |
iceberg_partition_stats(table, ⟨options⟩) |
Returns per-partition-field statistics. Columns include partition_field_name, partition_source_columns, partition_field_transform, lower_bound, upper_bound. |
iceberg_load_table_response(table) |
Advanced, REST-catalog only. Returns the raw catalog LoadTable response: metadata_location, metadata (VARIANT), config (MAP), storage_credentials, request_url. |
SELECT * FROM iceberg_snapshots('data/iceberg/lineitem_iceberg');
SELECT * FROM iceberg_column_stats('my_catalog.default.events');
Table and Schema Property Functions
These functions read and modify Iceberg table properties and Iceberg schema (namespace) properties. They require an attached catalog. See Writing to Iceberg.
| Function | Description |
|---|---|
iceberg_table_properties(table) |
Returns all properties of the table. |
set_iceberg_table_properties(table, properties) |
Sets properties on the table. properties is a MAP(VARCHAR, VARCHAR). |
remove_iceberg_table_properties(table, property_list) |
Removes the listed properties (VARCHAR[]) from the table. |
iceberg_schema_properties(schema) |
Returns all properties of the schema (namespace). |
set_iceberg_schema_properties(schema, properties) |
Sets properties on the schema. |
remove_iceberg_schema_properties(schema, property_list) |
Removes the listed properties from the schema. |
DuckLake Interoperability
| Function | Description |
|---|---|
iceberg_to_ducklake(iceberg_catalog, ducklake_catalog, skip_tables := [...]) |
Performs a metadata-only copy of an attached Iceberg catalog into a DuckLake catalog. The optional skip_tables parameter (VARCHAR[]) excludes tables. |
See Interoperability with DuckLake.
Partition Transform Functions
These scalar functions implement the Iceberg partition transforms. They are most often used in a PARTITIONED BY clause (see Partitioning), but can also be called directly.
| Function | Description |
|---|---|
iceberg_bucket(num_buckets, value) |
Returns the Iceberg bucket partition value (an INTEGER) for value. Supported value types: INTEGER, BIGINT, DECIMAL, DATE, TIME, TIMESTAMP, TIMESTAMP WITH TIME ZONE, TIMESTAMP_NS, VARCHAR, BLOB, UUID. |
iceberg_truncate(width, value) |
Returns the Iceberg truncate partition value for value, with the same type as value. Supported types: INTEGER, BIGINT, DECIMAL, VARCHAR, BLOB. |
SELECT iceberg_bucket(16, 'duckdb');
SELECT iceberg_truncate(10, 1234);
Settings
| Setting | Type | Default | Description |
|---|---|---|---|
unsafe_enable_version_guessing |
BOOLEAN |
false |
Enable globbing the filesystem (if possible) to find the latest metadata version. This may read an uncommitted version, so it is disabled by default. |
iceberg_use_metadata_log |
BOOLEAN |
true |
Use a table's optional metadata-log to preserve atomicity guarantees, at the cost of an additional metadata GET in rare cases. |
ignore_target_file_size_for_partitioned_tables |
BOOLEAN |
false |
Ignore the unsupported write.target-file-size-bytes table property on partitioned tables instead of raising an error. |
ignore_row_group_size_for_partitioned_tables |
BOOLEAN |
false |
Ignore the unsupported write.parquet.row-group-size-bytes table property on partitioned tables instead of raising an error. |
iceberg_via_aws_sdk_for_catalog_interactions |
BOOLEAN |
false |
Use the legacy AWS SDK code path to interact with AWS-based catalogs instead of DuckDB's HTTP client. |