Java 类名：com.alibaba.alink.operator.batch.dataproc.SampleWithSizeBatchOp
Python 类名：SampleWithSizeBatchOp

功能介绍

对数据按个数进行随机抽样，每个样本都以相同的概率被抽到。

参数说明

名称 中文名称 描述 类型 是否必须？ 取值范围 默认值
size 采样个数 采样个数 Integer ✓
withReplacement 是否放回 是否有放回的采样，默认不放回 Boolean false

代码示例

Python 代码

  1. from pyalink.alink import *
  3. import pandas as pd
  5. useLocalEnv(1)
  7. df = pd.DataFrame([
  8.   ["0,0,0"],
  9.   ["0.1,0.1,0.1"],
  10.   ["0.2,0.2,0.2"],
  11.   ["9,9,9"],
  12.   ["9.1,9.1,9.1"],
  13.   ["9.2,9.2,9.2"]
  14. ])
  16. inOp = BatchOperator.fromDataframe(df, schemaStr='Y string')
  18. sampleOp = SampleWithSizeBatchOp() \
  19.   .setSize(2) \
  20.   .setWithReplacement(False)
  22. inOp.link(sampleOp).print()

Java 代码

  1. import org.apache.flink.types.Row;
  3. import com.alibaba.alink.operator.batch.BatchOperator;
  4. import com.alibaba.alink.operator.batch.dataproc.SampleWithSizeBatchOp;
  5. import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
  6. import org.junit.Test;
  8. import java.util.Arrays;
  9. import java.util.List;
  11. public class SampleWithSizeBatchOpTest {
  12.     @Test
  13.     public void testSampleWithSizeBatchOp() throws Exception {
  14.         List <Row> df = Arrays.asList(
  15.             Row.of("0,0,0"),
  16.             Row.of("0.1,0.1,0.1"),
  17.             Row.of("0.2,0.2,0.2"),
  18.             Row.of("9,9,9"),
  19.             Row.of("9.1,9.1,9.1"),
  20.             Row.of("9.2,9.2,9.2")
  21.         );
  22.         BatchOperator <?> inOp = new MemSourceBatchOp(df, "Y string");
  23.         BatchOperator <?> sampleOp = new SampleWithSizeBatchOp()
  24.             .setSize(2)
  25.             .setWithReplacement(false);
  26.         inOp.link(sampleOp).print();
  27.     }
  28. }

运行结果

| Y | | —- |

| 0,0,0 |

| 0.2,0.2,0.2 |