Skip to main content

airflow-clickhouse-plugin - Airflow plugin to execute ClickHouse commands and queries

Project description

Airflow ClickHouse Plugin

Provides ClickHouseHook and ClickHouseOperator for Apache Airflow based on mymarilyn/clickhouse-driver.

Features

  1. SQL queries are templated.
  2. Can run multiple SQL queries per single ClickHouseOperator.
  3. Result of the last query of ClickHouseOperator instance is pushed to XCom.
  4. Executed queries are logged in a pretty form.
  5. Uses effective native ClickHouse TCP protocol thanks to clickhouse-driver. Does not support HTTP protocol.

Installation

pip install -U airflow-clickhouse-plugin

Usage

See examples below.

ClickHouseOperator Reference

To import ClickHouseOperator use: from airflow.operators.clickhouse_operator import ClickHouseOperator

Supported kwargs:

  • sql: templated query (if argument is a single str) or queries (if iterable of str's).
  • clickhouse_conn_id: connection id. Connection schema (all properties are optional, defaults correspond to the default ClickHouse configuration):
    • host, default: localhost;
    • port, default: 9000 (default native ClickHouse protocol port);
    • database, default: default;
    • user, default: default;
    • password, default: '' (empty).
  • parameters: passed to clickhouse-driver execute method.
    • If multiple queries are provided via sql then the parameters are passed to all of them.
    • Parameters are not templated.
  • database: if present, overrides database defined by connection.
  • Other kwargs (including the required task_id) are inherited from Airflow BaseOperator.

The result of the last query is pushed to XCom.

ClickHouseHook Reference

To import ClickHouseHook use: from airflow.hooks.clickhouse_hook import ClickHouseHook

Supported kwargs of constructor (__init__ method):

  • clickhouse_conn_id: connection id. See connection schema above.
  • database: if present, overrides database defined by connection.

Supports all of the methods of the Airflow BaseHook including:

  • get_records(sql: str, parameters: dict=None): returns result of the query as a list of tuples. Materializes all the records in memory.
  • get_first(sql: str, parameters: dict=None): returns the first row of the result. Does not load the whole dataset into memory because of using execute_iter.
  • run(sql, parameters): runs a single query (specified argument of type str) or multiple queries (if iterable of str). parameters can have any form supported by execute method of clickhouse-driver.
    • If single query is run then returns its result. If multiple queries are run then returns the result of the last of them.
    • If multiple queries are given then parameters are passed to all of them.
    • Materializes all the records in memory (uses simple execute but not execute_iter).
      • To achieve results streaming by execute_iter use it directly via hook.get_conn().execute_iter(…) (see execute_iter reference).
    • Every run call uses a new connection which is closed when finished.
  • get_conn(): returns the underlying clickhouse_driver.Client instance.

Examples

ClickHouseOperator

from airflow import DAG
from airflow.operators.clickhouse_plugin import ClickHouseOperator
from airflow.operators.python_operator import PythonOperator
from airflow.utils.dates import days_ago

with DAG(
        dag_id='update_income_aggregate',
        start_date=days_ago(2),
) as dag:
    ClickHouseOperator(
        task_id='update_income_aggregate',
        database='default',
        sql=(
            "INSERT INTO aggregate "
                "SELECT eventDt, sum(price * qty) AS income FROM sales "
                "WHERE eventDt = '{{ ds }}' GROUP BY eventDt",
            "OPTIMIZE TABLE aggregate ON CLUSTER {{ var.value.cluster_name }} "
                "PARTITION toDate('{{ execution_date.format('%Y-%m-01') }}')",
            "SELECT sum(income) FROM aggregate "
                "WHERE eventDt BETWEEN "
                "'{{ execution_date.start_of('month').to_date_string() }}'"
                "AND '{{ execution_date.end_of('month').to_date_string() }}'",
            # result of the last query is pushed to XCom
        ),
        clickhouse_conn_id='clickhouse_test',
    ) >> PythonOperator(
        task_id='print_month_income',
        provide_context=True,
        python_callable=lambda task_instance, **_:
            # pulling XCom value and printing it
            print(task_instance.xcom_pull(task_ids='update_income_aggregate')),
    )

ClickHouseHook

from airflow import DAG
from airflow.hooks.clickhouse_hook import ClickHouseHook
from airflow.hooks.mysql_hook import MySqlHook
from airflow.operators.python_operator import PythonOperator
from airflow.utils.dates import days_ago


def mysql_to_clickhouse():
    mysql_hook = MySqlHook()
    ch_hook = ClickHouseHook()
    records = mysql_hook.get_records('SELECT * FROM some_mysql_table')
    ch_hook.run('INSERT INTO some_ch_table VALUES', records)


with DAG(
        dag_id='mysql_to_clickhouse',
        start_date=days_ago(2),
) as dag:
    dag >> PythonOperator(
        task_id='mysql_to_clickhouse',
        python_callable=mysql_to_clickhouse,
    )

Important note: don't try to insert values using ch_hook.run('INSERT INTO some_ch_table VALUES (1)') literal form. clickhouse-driver requires values for INSERT query to be provided via parameters due to specifics of the native ClickHouse protocol.

Default connection

By default the hook and operator use connection_id='clickhouse_default'.

How to run tests

From the root project directory: python -m unittest discover -s tests

Contributors

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

airflow-clickhouse-plugin-0.5.3.tar.gz (6.3 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file airflow-clickhouse-plugin-0.5.3.tar.gz.

File metadata

  • Download URL: airflow-clickhouse-plugin-0.5.3.tar.gz
  • Upload date:
  • Size: 6.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.44.0 CPython/3.7.7

File hashes

Hashes for airflow-clickhouse-plugin-0.5.3.tar.gz
Algorithm Hash digest
SHA256 dbda68f98174a78a78c0d68740ff1c94106bf664060ad3a36f0fb818851904d9
MD5 611cb61f3005599c10e061340c9302ac
BLAKE2b-256 6ec3d17b3beed00e797fc92fdcaa8c485fb6d17a36c141a965ace71fa5f92b6e

See more details on using hashes here.

File details

Details for the file airflow_clickhouse_plugin-0.5.3-py3-none-any.whl.

File metadata

  • Download URL: airflow_clickhouse_plugin-0.5.3-py3-none-any.whl
  • Upload date:
  • Size: 8.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.44.0 CPython/3.7.7

File hashes

Hashes for airflow_clickhouse_plugin-0.5.3-py3-none-any.whl
Algorithm Hash digest
SHA256 9be4a50f041652ca30a353298717842ecc2d053427b51a5b5e44190b8b83a19d
MD5 8d72c7765e5bb4e1e4cbcded9eb25475
BLAKE2b-256 b0dba5ea1eb901b548cb747c1a2bbb10efea9a8956c0f2a5247993151c2697c7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page