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Version: 2.3.7

config


Intro to config file

In SeaTunnel, the most important thing is the config file, through which users can customize their own data synchronization requirements to maximize the potential of SeaTunnel. So next, I will introduce you how to configure the config file.

The main format of the config file is hocon, for more details you can refer to HOCON-GUIDE, BTW, we also support the json format, but you should keep in mind that the name of the config file should end with .json.

We also support the SQL format, please refer to SQL configuration for more details.

Example​

Before you read on, you can find config file examples Here from the binary package's config directory.

Config File Structure​

The config file is similar to the below one:

hocon​

env {
job.mode = "BATCH"
}

source {
FakeSource {
result_table_name = "fake"
row.num = 100
schema = {
fields {
name = "string"
age = "int"
card = "int"
}
}
}
}

transform {
Filter {
source_table_name = "fake"
result_table_name = "fake1"
fields = [name, card]
}
}

sink {
Clickhouse {
host = "clickhouse:8123"
database = "default"
table = "seatunnel_console"
fields = ["name", "card"]
username = "default"
password = ""
source_table_name = "fake1"
}
}

multi-line support​

In hocon, multiline strings are supported, which allows you to include extended passages of text without worrying about newline characters or special formatting. This is achieved by enclosing the text within triple quotes """ . For example:

var = """
Apache SeaTunnel is a
next-generation high-performance,
distributed, massive data integration tool.
"""
sql = """ select * from "table" """

json​


{
"env": {
"job.mode": "batch"
},
"source": [
{
"plugin_name": "FakeSource",
"result_table_name": "fake",
"row.num": 100,
"schema": {
"fields": {
"name": "string",
"age": "int",
"card": "int"
}
}
}
],
"transform": [
{
"plugin_name": "Filter",
"source_table_name": "fake",
"result_table_name": "fake1",
"fields": ["name", "card"]
}
],
"sink": [
{
"plugin_name": "Clickhouse",
"host": "clickhouse:8123",
"database": "default",
"table": "seatunnel_console",
"fields": ["name", "card"],
"username": "default",
"password": "",
"source_table_name": "fake1"
}
]
}

As you can see, the config file contains several sections: env, source, transform, sink. Different modules have different functions. After you understand these modules, you will see how SeaTunnel works.

env​

Used to add some engine optional parameters, no matter which engine (Zeta, Spark or Flink), the corresponding optional parameters should be filled in here.

Note that we have separated the parameters by engine, and for the common parameters, we can configure them as before. For flink and spark engine, the specific configuration rules of their parameters can be referred to JobEnvConfig.

source​

Source is used to define where SeaTunnel needs to fetch data, and use the fetched data for the next step. Multiple sources can be defined at the same time. The supported source can be found in Source of SeaTunnel. Each source has its own specific parameters to define how to fetch data, and SeaTunnel also extracts the parameters that each source will use, such as the result_table_name parameter, which is used to specify the name of the data generated by the current source, which is convenient for follow-up used by other modules.

transform​

When we have the data source, we may need to further process the data, so we have the transform module. Of course, this uses the word 'may', which means that we can also directly treat the transform as non-existent, directly from source to sink. Like below.

env {
job.mode = "BATCH"
}

source {
FakeSource {
result_table_name = "fake"
row.num = 100
schema = {
fields {
name = "string"
age = "int"
card = "int"
}
}
}
}

sink {
Clickhouse {
host = "clickhouse:8123"
database = "default"
table = "seatunnel_console"
fields = ["name", "age", "card"]
username = "default"
password = ""
source_table_name = "fake"
}
}

Like source, transform has specific parameters that belong to each module. The supported transform can be found in Transform V2 of SeaTunnel

sink​

Our purpose with SeaTunnel is to synchronize data from one place to another, so it is critical to define how and where data is written. With the sink module provided by SeaTunnel, you can complete this operation quickly and efficiently. Sink and source are very similar, but the difference is reading and writing. So please check out Supported Sinks.

Other​

You will find that when multiple sources and multiple sinks are defined, which data is read by each sink, and which is the data read by each transform? We introduce two key configurations called result_table_name and source_table_name. Each source module will be configured with a result_table_name to indicate the name of the data source generated by the data source, and other transform and sink modules can use source_table_name to refer to the corresponding data source name, indicating that I want to read the data for processing. Then transform, as an intermediate processing module, can use both result_table_name and source_table_name configurations at the same time. But you will find that in the above example config, not every module is configured with these two parameters, because in SeaTunnel, there is a default convention, if these two parameters are not configured, then the generated data from the last module of the previous node will be used. This is much more convenient when there is only one source.

Config Variable Substitution​

In config file we can define some variables and replace it in run time. This is only support hocon format file.

env {
job.mode = "BATCH"
job.name = ${jobName}
parallelism = 2
}

source {
FakeSource {
result_table_name = ${resName}
row.num = ${rowNum}
string.template = ${strTemplate}
int.template = [20, 21]
schema = {
fields {
name = ${nameType}
age = "int"
}
}
}
}

transform {
sql {
source_table_name = "fake"
result_table_name = "sql"
query = "select * from "${resName}" where name = '"${nameVal}"' "
}

}

sink {
Console {
source_table_name = "sql"
username = ${username}
password = ${password}
}
}

In the above config, we define some variables, like ${rowNum}, ${resName}. We can replace those parameters with this shell command:

./bin/seatunnel.sh -c <this_config_file> 
-i jobName='this_is_a_job_name'
-i resName=fake
-i rowNum=10
-i strTemplate=['abc','d~f','hi']
-i nameType=string
-i nameVal=abc
-i username=seatunnel=2.3.1
-i password='$a^b%c.d~e0*9('
-m local

Then the final submitted config is:

env {
job.mode = "BATCH"
job.name = "this_is_a_job_name"
parallelism = 2
}

source {
FakeSource {
result_table_name = "fake"
row.num = 10
string.template = ["abc","d~f","h i"]
int.template = [20, 21]
schema = {
fields {
name = string
age = "int"
}
}
}
}

transform {
sql {
source_table_name = "fake"
result_table_name = "sql"
query = "select * from fake where name = 'abc' "
}

}

sink {
Console {
source_table_name = "sql"
username = "seatunnel=2.3.1"
password = "$a^b%c.d~e0*9("
}
}

Some Notes:

  • Quota with ' if the value has special character such as (
  • If the replacement variables is in " or ', like resName and nameVal, you need add "
  • The value can't have space ' ', like -i jobName='this is a job name' , this will be replaced to job.name = "this"
  • If you want to use dynamic parameters, you can use the following format: -i date=$(date +"%Y%m%d").

What's More​

If you want to know the details of the format configuration, please see HOCON.