分布式调度框架。
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

94 lines
3.5 KiB

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
A example workflow for task datax.
This example will create a workflow named `task_datax`.
`task_datax` is true workflow define and run task task_datax.
You can create data sources `first_mysql` and `first_mysql` through UI.
It creates a task to synchronize datax from the source database to the target database.
"""
from pydolphinscheduler.core.process_definition import ProcessDefinition
from pydolphinscheduler.tasks.datax import CustomDataX, DataX
# datax json template
JSON_TEMPLATE = {
"job": {
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "usr",
"password": "pwd",
"column": ["id", "name", "code", "description"],
"splitPk": "id",
"connection": [
{
"table": ["source_table"],
"jdbcUrl": ["jdbc:mysql://127.0.0.1:3306/source_db"],
}
],
},
},
"writer": {
"name": "mysqlwriter",
"parameter": {
"writeMode": "insert",
"username": "usr",
"password": "pwd",
"column": ["id", "name"],
"connection": [
{
"jdbcUrl": "jdbc:mysql://127.0.0.1:3306/target_db",
"table": ["target_table"],
}
],
},
},
}
],
"setting": {
"errorLimit": {"percentage": 0, "record": 0},
"speed": {"channel": 1, "record": 1000},
},
}
}
with ProcessDefinition(
name="task_datax_example",
tenant="tenant_exists",
) as pd:
# This task synchronizes the data in `t_ds_project`
# of `first_mysql` database to `target_project` of `second_mysql` database.
# You have to make sure data source named `first_mysql` and `second_mysql` exists
# in your environment.
task1 = DataX(
name="task_datax",
datasource_name="first_mysql",
datatarget_name="second_mysql",
sql="select id, name, code, description from source_table",
target_table="target_table",
)
# You can custom json_template of datax to sync data. This task create a new
# datax job same as task1, transfer record from `first_mysql` to `second_mysql`
task2 = CustomDataX(name="task_custom_datax", json=str(JSON_TEMPLATE))
pd.run()