Add Nessie catalog support in docs

[somratdutta]

Summary

Checklist

• Delete items not relevant to your PR
• URL changes should add a redirect to the old URL via https://github.com/ClickHouse/clickhouse-docs/blob/main/docusaurus.config.js
• If adding a new integration page, also add an entry to the integrations list here: https://github.com/ClickHouse/clickhouse-docs/blob/main/docs/integrations/index.mdx

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[somratdutta]

Testing Instructions

This PR depends on a recently merged fix that is not yet available as a Docker image. Below are comprehensive testing instructions to validate the changes locally using Nessie as the REST catalog backend.

Prerequisites

Download the appropriate ClickHouse binary from the build artifacts based on your platform. For macOS on Apple Silicon, use the arm_darwin build.

Environment Setup

1. Initialize ClickHouse Server

   chmod +x clickhouse
   ./clickhouse server

2. Deploy Supporting Infrastructure

   Create a docker-compose.yaml file with the following configuration:

   services:
     jupyter:
       image: quay.io/jupyter/pyspark-notebook:2024-10-14
       depends_on:
         minio:
           condition: service_healthy
       command: start-notebook.sh --NotebookApp.token=''
       volumes:
         - ./notebooks:/home/jovyan/examples/
       ports:
         - "8888:8888"
   
     nessie:
       image: ghcr.io/projectnessie/nessie:latest
       ports:
         - "19120:19120"
       environment:
         - nessie.version.store.type=IN_MEMORY
         - nessie.catalog.default-warehouse=warehouse
         - nessie.catalog.warehouses.warehouse.location=s3://my-bucket/
         - nessie.catalog.service.s3.default-options.endpoint=http://minio:9000/
         - nessie.catalog.service.s3.default-options.access-key=urn:nessie-secret:quarkus:nessie.catalog.secrets.access-key
         - nessie.catalog.service.s3.default-options.path-style-access=true
         - nessie.catalog.service.s3.default-options.auth-type=STATIC
         - nessie.catalog.secrets.access-key.name=admin
         - nessie.catalog.secrets.access-key.secret=password
         - nessie.catalog.service.s3.default-options.region=us-east-1
         - nessie.server.authentication.enabled=false
   
     minio:
       image: quay.io/minio/minio
       ports:
         - "9002:9000"
         - "9003:9001"
       environment:
         - MINIO_ROOT_USER=admin
         - MINIO_ROOT_PASSWORD=password
         - MINIO_REGION=us-east-1
       healthcheck:
         test: ["CMD", "mc", "ready", "local"]
         interval: 5s
         timeout: 10s
         retries: 5
         start_period: 30s
       entrypoint: >
         /bin/sh -c "
         minio server /data --console-address ':9001' &
         sleep 10;
         mc alias set myminio http://localhost:9000 admin password;
         mc mb myminio/my-bucket --ignore-existing;
         tail -f /dev/null"

Data Ingestion via PySpark

Create the notebook notebooks/PySpark-Nessie.ipynb to establish test data using PySpark with Nessie and Apache Iceberg:

from pyspark.sql import SparkSession

# Initialize SparkSession with Nessie, Iceberg, and S3 configuration
spark = (
    SparkSession.builder.appName("Nessie-Iceberg-PySpark")
    .config('spark.jars.packages', 'org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.5.0,software.amazon.awssdk:bundle:2.24.8,software.amazon.awssdk:url-connection-client:2.24.8')
    .config("spark.sql.extensions", "org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions")
    .config("spark.sql.catalog.nessie", "org.apache.iceberg.spark.SparkCatalog")
    .config("spark.sql.catalog.nessie.uri", "http://nessie:19120/iceberg/main/")
    .config("spark.sql.catalog.nessie.warehouse", "s3://my-bucket/")
    .config("spark.sql.catalog.nessie.type", "rest")
    .getOrCreate()
)

# Create a namespace in Nessie
spark.sql("CREATE NAMESPACE IF NOT EXISTS nessie.demo").show()

# Create a table in the `nessie.demo` namespace using Iceberg
spark.sql(
    """
    CREATE TABLE IF NOT EXISTS nessie.demo.sample_table (
        id BIGINT,
        name STRING
    ) USING iceberg
    """
).show()

# Insert data into the sample_table
spark.sql(
    """
    INSERT INTO nessie.demo.sample_table VALUES
    (1, 'Alice'),
    (2, 'Bob')
    """
).show()

# Query the data from the table
spark.sql("SELECT * FROM nessie.demo.sample_table").show()

# Stop the Spark session
spark.stop()

Integration Testing

After executing the notebook, connect to ClickHouse and validate the DataLakeCatalog integration with Nessie:

./clickhouse client

Execute the following SQL commands to verify functionality:

-- Enable experimental Iceberg support
SET allow_experimental_database_iceberg = 1;

-- Configure DataLakeCatalog with Nessie REST catalog backend
CREATE DATABASE demo 
ENGINE = DataLakeCatalog('http://localhost:19120/iceberg', 'admin', 'password') 
SETTINGS 
    catalog_type = 'rest', 
    storage_endpoint = 'http://localhost:9002/my-bucket', 
    warehouse = 'warehouse';

-- Verify table discovery
SHOW TABLES FROM demo;

-- Validate data retrieval
SELECT * FROM demo.`demo.sample_table`;

Expected Results

The integration should successfully:

• Discover the Iceberg table: demo.sample_table
• Query the table returning the test dataset:

  ┌─id─┬─name──┐
  │  2 │ Bob   │
  │  1 │ Alice │
  └────┴───────┘