Introduction

In this article, we are going to look into setting up a datawarehouse(Clickhouse). This is perticularly useful for someone who is getting started with analytics,data engineering or sql. Clickhouse has good documentation and it also provides some sample datasets to explore the datawarehouse. I am going to cover the following in this article:

1. Setting up Clickhouse using docker
2. Create a connection with Clickhouse local instance using DBeaver
3. Loading a sample dataset

prerequisite

• You should have docker desktop setup on your machine.
• Docker daemon should be up and running.
• DBeaver should be installed on your machine.

Steps to setup Clickhouse

1. docker pull clickhouse/clickhouse-server - Download the ClickHouse server Docker image from the repository.
2. mkdir ~/Documents/<User>/Volumes/clickhouse - Create a directory in your Documents folder to store ClickHouse data and logs.
3. cd ~/Documents/<User>/Volumes/clickhouse - Navigate to the newly created directory.
4. mkdir -p clickhouse_data - Make a subdirectory to store ClickHouse data files.
5. mkdir -p clickhouse_logs - Make another subdirectory to store ClickHouse log files.
6. docker run -d -v /Users/<user>/Documents/Experiment/clickhouse/clickhouse_data:/var/lib/clickhouse -v /Users/<user>/Documents/Experiment/clickhouse/clickhouse_logs:/var/log/clickhouse-server -p 8123:8123 -p 9000:9000 --name clickhouse-server --ulimit nofile=262144:262144 clickhouse/clickhouse-server - Run the ClickHouse server in a Docker container, mapping your data and log directories to the container, and setting the necessary ports and file limits.
7. docker ps - Validate if the container is running.

Establish Connection in DBeaver

• Open DBeaver and Create a new connection:
  • Click on Database > New Database Connection.
  • Select ClickHouse from the list of available database drivers.
  • Click Next.
• Configure the Connection:
  • Click on connect by URL option and provide jdbc:clickhouse://localhost:8123/default in the input
  • database: default
  • user: default
  • password: We have not provided it so leave it blank. This is for local development and testing. Not meant for production setup.
• Test the Connection:
  • Click on Test Connection to ensure that the connection to the ClickHouse server is successful.
  • If the connection is successful, click Finish to save the connection.

Setup Sample Data

• For importing the data, change the socket_timeout property under driver properties in dbeaver. It is available under edit connection menu. Set the value to 300000 to make sure import works as expected.

We are going to import NYC taxi data and it is documented on the official site as well.

• Create a new sql script on DBeaver and use the following commands in the same order as below:

CREATE TABLE trips (
    trip_id             UInt32,
    pickup_datetime     DateTime,
    dropoff_datetime    DateTime,
    pickup_longitude    Nullable(Float64),
    pickup_latitude     Nullable(Float64),
    dropoff_longitude   Nullable(Float64),
    dropoff_latitude    Nullable(Float64),
    passenger_count     UInt8,
    trip_distance       Float32,
    fare_amount         Float32,
    extra               Float32,
    tip_amount          Float32,
    tolls_amount        Float32,
    total_amount        Float32,
    payment_type        Enum('CSH' = 1, 'CRE' = 2, 'NOC' = 3, 'DIS' = 4, 'UNK' = 5),
    pickup_ntaname      LowCardinality(String),
    dropoff_ntaname     LowCardinality(String)
)
ENGINE = MergeTree
PRIMARY KEY (pickup_datetime, dropoff_datetime);

INSERT INTO trips
SELECT
    trip_id,
    pickup_datetime,
    dropoff_datetime,
    pickup_longitude,
    pickup_latitude,
    dropoff_longitude,
    dropoff_latitude,
    passenger_count,
    trip_distance,
    fare_amount,
    extra,
    tip_amount,
    tolls_amount,
    total_amount,
    payment_type,
    pickup_ntaname,
    dropoff_ntaname
FROM gcs(
    'https://storage.googleapis.com/clickhouse-public-datasets/nyc-taxi/trips_{0..2}.gz',
    'TabSeparatedWithNames'
);

Validate the insertion using the following query:

SELECT count()
FROM trips;

Next Steps

• You can use this datawarehouse to perform ETL.
• Ingest data from a data lake created on cloud.
• Practice SQL using any avaialble dataset.

I am going to cover few other features as i explore more. Happy learning.

References:

1. https://clickhouse.com/docs/en/install
2. https://hub.docker.com/r/clickhouse/clickhouse-server/
3. https://clickhouse.com/docs/en/getting-started/example-datasets/nyc-taxi