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 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
Local Development Setup
For local development and testing, you can use a containerized Lakekeeper setup. This approach is ideal for learning, prototyping, and development environments.
Prerequisites
- Docker and Docker Compose: Ensure Docker is installed and running
- Sample Setup: You can use the Lakekeeper docker-compose setup
Setting up Local Lakekeeper Catalog
You can use the official Lakekeeper docker-compose setup 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:
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: bridgeStep 2: Run the following command to start the services:
docker compose up -dStep 3: Wait for all services to be ready. You can check the logs:
docker-compose logs -fConnecting to Local Lakekeeper Catalog
Connect to your ClickHouse container:
docker exec -it lakekeeper-clickhouse clickhouse-clientThen create the database connection to the Lakekeeper catalog:
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'Querying Lakekeeper catalog tables using ClickHouse
Now that the connection is in place, you can start querying via the Lakekeeper catalog. For example:
USE demo;
SHOW TABLES;If your setup includes sample data (such as the taxi dataset), you should see tables like:
┌─name──────────┐
│ default.taxis │
└───────────────┘To query a table (if available):
SELECT count(*) FROM `default.taxis`;┌─count()─┐
│ 2171187 │
└─────────┘To inspect the table DDL:
SHOW CREATE TABLE `default.taxis`;┌─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]') │
└───────────────────────────────────────────────────────────────────────────────────────────────┘Loading data from your Data Lake into ClickHouse
If you need to load data from the Lakekeeper catalog into ClickHouse, start by creating a local ClickHouse table:
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:
INSERT INTO taxis
SELECT * FROM demo.`default.taxis`;