Data
ClickHouse
ClickHouse — open source distributed column-oriented DBMS

Add credentials

  1. Create a new pipeline or open an existing pipeline.
  2. Expand the left side of your screen to view the file browser.
  3. Scroll down and click on a file named io_config.yaml.
  4. Enter the following keys and values under the key named default (you can have multiple profiles, add it under whichever is relevant to you)
version: 0.1.1
default:
  CLICKHOUSE_DATABASE: ...
  CLICKHOUSE_HOST: ...
  CLICKHOUSE_INTERFACE: http
  CLICKHOUSE_PASSWORD: ...
  CLICKHOUSE_PORT: 8123
  CLICKHOUSE_USERNAME: ...

Using SQL block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block.
  3. Select SQL.
  4. Under the Data provider dropdown, select ClickHouse.
  5. Under the Profile dropdown, select default (or the profile you added credentials underneath).
  6. Enter the optional table name of the table to write to.
  7. Under the Write policy dropdown, select Replace or Append (please see SQL blocks guide for more information on write policies).
  8. Enter in this test query: SELECT 1.
  9. Run the block.

Using Python block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block (the code snippet below is for a data loader).
  3. Select Generic (no template).
  4. Enter this code snippet (note: change the config_profile from default if you have a different profile):
from mage_ai.data_preparation.repo_manager import get_repo_path
from mage_ai.io.clickhouse import ClickHouse
from mage_ai.io.config import ConfigFileLoader
from os import path
from pandas import DataFrame

if 'data_loader' not in globals():
    from mage_ai.data_preparation.decorators import data_loader


@data_loader
def load_data_from_clickhouse(**kwargs) -> DataFrame:
    query = 'SELECT 1'
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    return ClickHouse.with_config(ConfigFileLoader(config_path, config_profile)).load(query)
  1. Run the block.