Java 类名:com.alibaba.alink.operator.batch.dataproc.SplitBatchOp
Python 类名:SplitBatchOp
将输入数据按比例拆分为两部分。
名称 | 中文名称 | 描述 | 类型 | 是否必须? | 取值范围 | 默认值 |
---|---|---|---|---|---|---|
fraction | 拆分到左端的数据比例 | 拆分到左端的数据比例 | Double | ✓ | 0.0 <= x <= 1.0 | |
randomSeed | 随机数种子 | 随机数种子 | Integer | null |
from pyalink.alink import * import pandas as pd useLocalEnv(1) df_data = pd.DataFrame([['Ohio', 2001, 1.7], ['Ohio', 2002, 3.6], ['Nevada', 2001, 2.4], ['Nevada', 2002, 2.9]]) batch_data = BatchOperator.fromDataframe(df_data, schemaStr='f1 string, f2 bigint, f3 double') spliter = SplitBatchOp().setFraction(0.5) spliter.linkFrom(batch_data) spliter.lazyPrint(-1) spliter.getSideOutput(0).lazyPrint(-1) BatchOperator.execute()
import org.apache.flink.types.Row; import com.alibaba.alink.operator.batch.BatchOperator; import com.alibaba.alink.operator.batch.dataproc.SplitBatchOp; import com.alibaba.alink.operator.batch.source.MemSourceBatchOp; import org.junit.Test; import java.util.Arrays; import java.util.List; public class SplitBatchOpTest { @Test public void testSplitBatchOp() throws Exception { List <Row> df_data = Arrays.asList( Row.of("Ohio", 2001, 1.7), Row.of("Ohio", 2002, 3.6), Row.of("Nevada", 2001, 2.4), Row.of("Nevada", 2002, 2.9) ); BatchOperator <?> batch_data = new MemSourceBatchOp(df_data, "f1 string, f2 int, f3 double"); BatchOperator <?> spliter = new SplitBatchOp().setFraction(0.5); spliter.linkFrom(batch_data); spliter.lazyPrint(-1); spliter.getSideOutput(0).lazyPrint(-1); BatchOperator.execute(); } }
f1 | f2 | f3 |
---|---|---|
Ohio | 2001 | 1.7000 |
Nevada | 2002 | 2.9000 |
f1 | f2 | f3 |
---|---|---|
Ohio | 2002 | 3.6000 |
Nevada | 2001 | 2.4000 |