Data
ClickHouse
Data
ClickHouse

Add credentials
- Create a new pipeline or open an existing pipeline.
- Expand the left side of your screen to view the file browser.
- Scroll down and click on a file named
io_config.yaml
. - 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
- Create a new pipeline or open an existing pipeline.
- Add a data loader, transformer, or data exporter block.
- Select
SQL
. - Under the
Data provider
dropdown, selectClickHouse
. - Under the
Profile
dropdown, selectdefault
(or the profile you added credentials underneath). - Enter the optional table name of the table to write to.
- Under the
Write policy
dropdown, selectReplace
orAppend
(please see SQL blocks guide for more information on write policies). - Enter in this test query:
SELECT 1
. - Run the block.
Using Python block
- Create a new pipeline or open an existing pipeline.
- Add a data loader, transformer, or data exporter block (the code snippet below is for a data loader).
- Select
Generic (no template)
. - Enter this code snippet (note: change the
config_profile
fromdefault
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)
- Run the block.