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Version: 1.x

Quick start

We take an application that receives data through a socket, divides the data into multiple fields, and outputs the processing results as an example to quickly demonstrate the use of seatunnel.

Step 1: Prepare the Spark runtime environment

If you are familiar with Spark or have prepared the Spark runtime environment, you can ignore this step, Spark does not require any special configuration.

Please download Spark first, and select Spark version >= 2.x.x. After downloading and decompressing, you can submit tasks in Spark deploy-mode = local mode without any configuration. If you expect the task to run on a Standalone cluster or a Yarn or Mesos cluster, please refer to the [Spark Deployment Documentation] on the Spark official website (

Step 2: Download seatunnel

Go to the seatunnel installation package download page and download the latest version of seatunnel-<version>.zip

Or directly download the specified version (take 1.1.2 as an example):

wget -O

After downloading, unzip:

unzip seatunnel-<version>.zip
ln -s seatunnel-<version> seatunnel

Step 3: Configure seatunnel

Edit config/, specify the required environment configuration such as SPARK_HOME (the directory downloaded and decompressed by Spark in Step 1)

Edit config/application.conf, which determines the way and logic of data input, processing, and output after seatunnel is started.

spark {
# seatunnel defined streaming batch duration in seconds
spark.streaming.batchDuration = 5 = "seatunnel"
spark.ui.port = 13000

input {
socketStream {}

filter {
split {
fields = ["msg", "name"]
delimiter = ","

output {
stdout {}

Step 4: Start the netcat server for sending data

nc -l -p 9999

Step 5: Start seatunnel

cd seatunnel
./bin/ --master local[4] --deploy-mode client --config ./config/application.conf

Step 6: Input at the nc terminal

Hello World, Gary

The seatunnel log prints out:

|raw_message |msg |name|
|Hello World, Gary|Hello World|Gary|


seatunnel is simple and easy to use, and there are richer data processing functions waiting to be discovered. The data processing case presented in this paper, No code, compilation, packaging required, simpler than the official Quick Example.

For more seatunnel configuration examples, see:

Configuration Example 1: Streaming Streaming Computing

The above configuration is the default [Streaming Configuration Template], which can be run directly. The command is as follows:

cd seatunnel
./bin/ --master local[4] --deploy-mode client --config ./config/streaming.conf.template

Configuration example 2: Batch offline batch

The above configuration is the default [offline batch configuration template], which can be run directly. The command is as follows:

cd seatunnel
./bin/ --master local[4] --deploy-mode client --config ./config/batch.conf.template

Configuration Example 3: Structured Streaming Streaming

The above configuration is the default [Structured Streaming configuration template], and the Kafka input source needs to be configured to run, the command is as follows:

cd seatunnel
./bin/ --master local[4] --deploy-mode client --config ./config/batch.conf.template