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Version: 2.3.8

SQL UDF

UDF of SQL transform plugin

Description

Use UDF SPI to extend the SQL transform functions lib.

UDF API

package org.apache.seatunnel.transform.sql.zeta;

public interface ZetaUDF {
/**
* Function name
*
* @return function name
*/
String functionName();

/**
* The type of function result
*
* @param argsType input arguments type
* @return result type
*/
SeaTunnelDataType<?> resultType(List<SeaTunnelDataType<?>> argsType);

/**
* Evaluate
*
* @param args input arguments
* @return result value
*/
Object evaluate(List<Object> args);
}

UDF Implements Example

Add these dependencies and provided scope to your maven project:


<dependencies>
<dependency>
<groupId>org.apache.seatunnel</groupId>
<artifactId>seatunnel-transforms-v2</artifactId>
<version>2.3.2</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.seatunnel</groupId>
<artifactId>seatunnel-api</artifactId>
<version>2.3.2</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>com.google.auto.service</groupId>
<artifactId>auto-service</artifactId>
<version>1.0.1</version>
<scope>provided</scope>
</dependency>
</dependencies>

Add a Java Class implements of ZetaUDF like this:


@AutoService(ZetaUDF.class)
public class ExampleUDF implements ZetaUDF {
@Override
public String functionName() {
return "EXAMPLE";
}

@Override
public SeaTunnelDataType<?> resultType(List<SeaTunnelDataType<?>> argsType) {
return BasicType.STRING_TYPE;
}

@Override
public Object evaluate(List<Object> args) {
String arg = (String) args.get(0);
if (arg == null) return null;
return "UDF: " + arg;
}
}

Package the UDF project and copy the jar to the path: ${SEATUNNEL_HOME}/lib. And if your UDF use third party library, you also need put it to ${SEATUNNEL_HOME}/lib.
If you use cluster mode, you need put the lib to all your node's ${SEATUNNEL_HOME}/lib folder and re-start the cluster.

Example

The data read from source is a table like this:

idnameage
1Joy Ding20
2May Ding21
3Kin Dom24
4Joy Dom22

We use UDF of SQL query to transform the source data like this:

transform {
Sql {
source_table_name = "fake"
result_table_name = "fake1"
query = "select id, example(name) as name, age from fake"
}
}

Then the data in result table fake1 will update to

idnameage
1UDF: Joy Ding20
2UDF: May Ding21
3UDF: Kin Dom24
4UDF: Joy Dom22

Changelog

new version

  • Add UDF of SQL Transform Connector