> ## Documentation Index
> Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Lakekeeper catalog

> In this guide, we will walk you through the steps to query your data using ClickHouse and the Lakekeeper Catalog.

export const ExperimentalBadge = () => {
  return <div className="experimentalBadge">
            <div className="experimentalIcon">
            <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
                <path strokeWidth="1.25" d="M5.5 2H10.5" stroke="currentColor" strokeLinecap="round" strokeLinejoin="round" />
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            </svg>
        </div>
            Experimental feature. <u><a href="/docs/docs/beta-and-experimental-features#experimental-features">Learn more.</a></u>
        </div>;
};

<ExperimentalBadge />

<Note>
  Integration with the Lakekeeper Catalog works with Iceberg tables only.
  This integration supports both AWS S3 and other cloud storage providers.
</Note>

ClickHouse supports integration with multiple catalogs (Unity, Glue, REST, Polaris, etc.). This guide will walk you through the steps to query your data using ClickHouse and the [Lakekeeper](https://docs.lakekeeper.io/) catalog.

Lakekeeper is an open-source REST catalog implementation for Apache Iceberg that provides:

* **Rust native** implementation for high performance and reliability
* **REST API** compliance with the Iceberg REST catalog specification
* **Cloud storage** integration with S3-compatible storage

<Note>
  As this feature is experimental, you will need to enable it using:
  `SET allow_experimental_database_iceberg = 1;`
</Note>

<h2 id="local-development-setup">
  Local Development Setup
</h2>

For local development and testing, you can use a containerized Lakekeeper setup. This approach is ideal for learning, prototyping, and development environments.

<h3 id="local-prerequisites">
  Prerequisites
</h3>

1. **Docker and Docker Compose**: Ensure Docker is installed and running
2. **Sample Setup**: You can use the Lakekeeper docker-compose setup

<h3 id="setting-up-local-lakekeeper-catalog">
  Setting up Local Lakekeeper Catalog
</h3>

You can use the official [Lakekeeper docker-compose setup](https://github.com/lakekeeper/lakekeeper/tree/main/examples/minimal) which provides a complete environment with Lakekeeper, PostgreSQL metadata backend, and MinIO for object storage.

**Step 1:** Create a new folder in which to run the example, then create a file `docker-compose.yml` with the following configuration:

```yaml theme={null}
version: '3.8'

services:
  lakekeeper:
    image: quay.io/lakekeeper/catalog:latest
    environment:
      - LAKEKEEPER__PG_ENCRYPTION_KEY=This-is-NOT-Secure!
      - LAKEKEEPER__PG_DATABASE_URL_READ=postgresql://postgres:postgres@db:5432/postgres
      - LAKEKEEPER__PG_DATABASE_URL_WRITE=postgresql://postgres:postgres@db:5432/postgres
      - RUST_LOG=info
    command: ["serve"]
    healthcheck:
      test: ["CMD", "/home/nonroot/lakekeeper", "healthcheck"]
      interval: 1s
      timeout: 10s
      retries: 10
      start_period: 30s
    depends_on:
      migrate:
        condition: service_completed_successfully
      db:
        condition: service_healthy
      minio:
        condition: service_healthy
    ports:
      - 8181:8181
    networks:
      - iceberg_net

  migrate:
    image: quay.io/lakekeeper/catalog:latest-main
    environment:
      - LAKEKEEPER__PG_ENCRYPTION_KEY=This-is-NOT-Secure!
      - LAKEKEEPER__PG_DATABASE_URL_READ=postgresql://postgres:postgres@db:5432/postgres
      - LAKEKEEPER__PG_DATABASE_URL_WRITE=postgresql://postgres:postgres@db:5432/postgres
      - RUST_LOG=info
    restart: "no"
    command: ["migrate"]
    depends_on:
      db:
        condition: service_healthy
    networks:
      - iceberg_net

  bootstrap:
    image: curlimages/curl
    depends_on:
      lakekeeper:
        condition: service_healthy
    restart: "no"
    command:
      - -w
      - "%{http_code}"
      - "-X"
      - "POST"
      - "-v"
      - "http://lakekeeper:8181/management/v1/bootstrap"
      - "-H"
      - "Content-Type: application/json"
      - "--data"
      - '{"accept-terms-of-use": true}'
      - "-o"
      - "/dev/null"
    networks:
      - iceberg_net

  initialwarehouse:
    image: curlimages/curl
    depends_on:
      lakekeeper:
        condition: service_healthy
      bootstrap:
        condition: service_completed_successfully
    restart: "no"
    command:
      - -w
      - "%{http_code}"
      - "-X"
      - "POST"
      - "-v"
      - "http://lakekeeper:8181/management/v1/warehouse"
      - "-H"
      - "Content-Type: application/json"
      - "--data"
      - '{"warehouse-name": "demo", "project-id": "00000000-0000-0000-0000-000000000000", "storage-profile": {"type": "s3", "bucket": "warehouse-rest", "key-prefix": "", "assume-role-arn": null, "endpoint": "http://minio:9000", "region": "local-01", "path-style-access": true, "flavor": "minio", "sts-enabled": true}, "storage-credential": {"type": "s3", "credential-type": "access-key", "aws-access-key-id": "minio", "aws-secret-access-key": "ClickHouse_Minio_P@ssw0rd"}}'
      - "-o"
      - "/dev/null"
    networks:
      - iceberg_net

  db:
    image: bitnami/postgresql:16.3.0
    environment:
      - POSTGRESQL_USERNAME=postgres
      - POSTGRESQL_PASSWORD=postgres
      - POSTGRESQL_DATABASE=postgres
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U postgres -p 5432 -d postgres"]
      interval: 2s
      timeout: 10s
      retries: 5
      start_period: 10s
    volumes:
      - postgres_data:/bitnami/postgresql
    networks:
      - iceberg_net

  minio:
    image: bitnami/minio:2025.4.22
    environment:
      - MINIO_ROOT_USER=minio
      - MINIO_ROOT_PASSWORD=ClickHouse_Minio_P@ssw0rd
      - MINIO_API_PORT_NUMBER=9000
      - MINIO_CONSOLE_PORT_NUMBER=9001
      - MINIO_SCHEME=http
      - MINIO_DEFAULT_BUCKETS=warehouse-rest
    networks: 
      iceberg_net:
        aliases:
          - warehouse-rest.minio
    ports:
      - "9002:9000"
      - "9003:9001"
    healthcheck:
      test: ["CMD", "mc", "ls", "local", "|", "grep", "warehouse-rest"]
      interval: 2s
      timeout: 10s
      retries: 3
      start_period: 15s
    volumes:
      - minio_data:/bitnami/minio/data

  clickhouse:
    image: clickhouse/clickhouse-server:head
    container_name: lakekeeper-clickhouse
    user: '0:0'  # Ensures root permissions
    ports:
      - "8123:8123"
      - "9000:9000"
    volumes:
      - clickhouse_data:/var/lib/clickhouse
      - ./clickhouse/data_import:/var/lib/clickhouse/data_import  # Mount dataset folder
    networks:
      - iceberg_net
    environment:
      - CLICKHOUSE_DB=default
      - CLICKHOUSE_USER=default
      - CLICKHOUSE_DO_NOT_CHOWN=1
      - CLICKHOUSE_PASSWORD=
    depends_on:
      lakekeeper:
        condition: service_healthy
      minio:
        condition: service_healthy

volumes:
  postgres_data:
  minio_data:
  clickhouse_data:

networks:
  iceberg_net:
    driver: bridge
```

**Step 2:** Run the following command to start the services:

```bash theme={null}
docker compose up -d
```

**Step 3:** Wait for all services to be ready. You can check the logs:

```bash theme={null}
docker-compose logs -f
```

<Note>
  The Lakekeeper setup requires that sample data be loaded into the Iceberg tables first. Make sure the environment has created and populated the tables before attempting to query them through ClickHouse. The availability of tables depends on the specific docker-compose setup and sample data loading scripts.
</Note>

<h3 id="connecting-to-local-lakekeeper-catalog">
  Connecting to Local Lakekeeper Catalog
</h3>

Connect to your ClickHouse container:

```bash theme={null}
docker exec -it lakekeeper-clickhouse clickhouse-client
```

Then create the database connection to the Lakekeeper catalog:

```sql theme={null}
SET allow_experimental_database_iceberg = 1;

CREATE DATABASE demo
ENGINE = DataLakeCatalog('http://lakekeeper:8181/catalog', 'minio', 'ClickHouse_Minio_P@ssw0rd')
SETTINGS catalog_type = 'rest', storage_endpoint = 'http://minio:9002/warehouse-rest', warehouse = 'demo'
```

<h2 id="querying-lakekeeper-catalog-tables-using-clickhouse">
  Querying Lakekeeper catalog tables using ClickHouse
</h2>

Now that the connection is in place, you can start querying via the Lakekeeper catalog. For example:

```sql theme={null}
USE demo;

SHOW TABLES;
```

If your setup includes sample data (such as the taxi dataset), you should see tables like:

```response theme={null}
┌─name──────────┐
│ default.taxis │
└───────────────┘
```

<Note>
  If you don't see any tables, this usually means:

  1. The environment hasn't created the sample tables yet
  2. The Lakekeeper catalog service isn't fully initialized
  3. The sample data loading process hasn't completed

  You can check the Spark logs to see the table creation progress:

  ```bash theme={null}
  docker-compose logs spark
  ```
</Note>

To query a table (if available):

```sql theme={null}
SELECT count(*) FROM `default.taxis`;
```

```response theme={null}
┌─count()─┐
│ 2171187 │
└─────────┘
```

<Info>
  **Backticks required**

  Backticks are required because ClickHouse doesn't support more than one namespace.
</Info>

To inspect the table DDL:

```sql theme={null}
SHOW CREATE TABLE `default.taxis`;
```

```response theme={null}
┌─statement─────────────────────────────────────────────────────────────────────────────────────┐
│ CREATE TABLE demo.`default.taxis`                                                             │
│ (                                                                                             │
│     `VendorID` Nullable(Int64),                                                               │
│     `tpep_pickup_datetime` Nullable(DateTime64(6)),                                           │
│     `tpep_dropoff_datetime` Nullable(DateTime64(6)),                                          │
│     `passenger_count` Nullable(Float64),                                                      │
│     `trip_distance` Nullable(Float64),                                                        │
│     `RatecodeID` Nullable(Float64),                                                           │
│     `store_and_fwd_flag` Nullable(String),                                                    │
│     `PULocationID` Nullable(Int64),                                                           │
│     `DOLocationID` Nullable(Int64),                                                           │
│     `payment_type` Nullable(Int64),                                                           │
│     `fare_amount` Nullable(Float64),                                                          │
│     `extra` Nullable(Float64),                                                                │
│     `mta_tax` Nullable(Float64),                                                              │
│     `tip_amount` Nullable(Float64),                                                           │
│     `tolls_amount` Nullable(Float64),                                                         │
│     `improvement_surcharge` Nullable(Float64),                                                │
│     `total_amount` Nullable(Float64),                                                         │
│     `congestion_surcharge` Nullable(Float64),                                                 │
│     `airport_fee` Nullable(Float64)                                                           │
│ )                                                                                             │
│ ENGINE = Iceberg('http://minio:9002/warehouse-rest/warehouse/default/taxis/', 'minio', '[HIDDEN]') │
└───────────────────────────────────────────────────────────────────────────────────────────────┘
```

<h2 id="loading-data-from-your-data-lake-into-clickhouse">
  Loading data from your Data Lake into ClickHouse
</h2>

If you need to load data from the Lakekeeper catalog into ClickHouse, start by creating a local ClickHouse table:

```sql theme={null}
CREATE TABLE taxis
(
    `VendorID` Int64,
    `tpep_pickup_datetime` DateTime64(6),
    `tpep_dropoff_datetime` DateTime64(6),
    `passenger_count` Float64,
    `trip_distance` Float64,
    `RatecodeID` Float64,
    `store_and_fwd_flag` String,
    `PULocationID` Int64,
    `DOLocationID` Int64,
    `payment_type` Int64,
    `fare_amount` Float64,
    `extra` Float64,
    `mta_tax` Float64,
    `tip_amount` Float64,
    `tolls_amount` Float64,
    `improvement_surcharge` Float64,
    `total_amount` Float64,
    `congestion_surcharge` Float64,
    `airport_fee` Float64
)
ENGINE = MergeTree()
PARTITION BY toYYYYMM(tpep_pickup_datetime)
ORDER BY (VendorID, tpep_pickup_datetime, PULocationID, DOLocationID);
```

Then load the data from your Lakekeeper catalog table via an `INSERT INTO SELECT`:

```sql theme={null}
INSERT INTO taxis 
SELECT * FROM demo.`default.taxis`;
```
