Java 类名：com.alibaba.alink.operator.stream.dataproc.SampleStreamOp
Python 类名：SampleStreamOp

功能介绍

  • 随机采样是对数据进行随机抽样，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 | | —- | —- | —- | —- | —- | —- | —- |

| ratio | 采样比例 | 采样率，范围为[0, 1] | Double | ✓ | [0.0, 1.0] | |

| 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_data = pd.DataFrame([
  8.     ["-0.6264538 0.1836433"],
  9.     ["-0.8356286 1.5952808"],
  10.     ["0.3295078 -0.8204684"],
  11.     ["0.4874291 0.7383247"],
  12.     ["0.5757814 -0.3053884"],
  13.     ["1.5117812 0.3898432"],
  14.     ["-0.6212406 -2.2146999"],
  15.     ["11.1249309 9.9550664"],
  16.     ["9.9838097 10.9438362"],
  17.     ["10.8212212 10.5939013"],
  18.     ["10.9189774 10.7821363"],
  19.     ["10.0745650 8.0106483"],
  20.     ["10.6198257 9.9438713"],
  21.     ["9.8442045 8.5292476"],
  22.     ["9.5218499 10.4179416"],
  23. ])
  25. data = StreamOperator.fromDataframe(df_data, schemaStr='features string')
  27. sampleOp = SampleStreamOp().setRatio(0.3)
  29. data.link(sampleOp).print()
  31. StreamOperator.execute()

Java 代码

  1. import org.apache.flink.types.Row;
  3. import com.alibaba.alink.operator.stream.StreamOperator;
  4. import com.alibaba.alink.operator.stream.dataproc.SampleStreamOp;
  5. import com.alibaba.alink.operator.stream.source.MemSourceStreamOp;
  6. import org.junit.Test;
  8. import java.util.Arrays;
  9. import java.util.List;
  11. public class SampleStreamOpTest {
  12.     @Test
  13.     public void testSampleStreamOp() throws Exception {
  14.         List <Row> df_data = Arrays.asList(
  15.             Row.of("-0.6264538 0.1836433"),
  16.             Row.of("-0.8356286 1.5952808"),
  17.             Row.of("0.3295078 -0.8204684"),
  18.             Row.of("0.4874291 0.7383247"),
  19.             Row.of("0.5757814 -0.3053884"),
  20.             Row.of("1.5117812 0.3898432"),
  21.             Row.of("-0.6212406 -2.2146999"),
  22.             Row.of("11.1249309 9.9550664"),
  23.             Row.of("9.9838097 10.9438362"),
  24.             Row.of("10.8212212 10.5939013"),
  25.             Row.of("10.9189774 10.7821363"),
  26.             Row.of("10.0745650 8.0106483"),
  27.             Row.of("10.6198257 9.9438713"),
  28.             Row.of("9.8442045 8.5292476"),
  29.             Row.of("9.5218499 10.4179416")
  30.         );
  31.         StreamOperator <?> data = new MemSourceStreamOp(df_data, "features string");
  32.         StreamOperator <?> sampleOp = new SampleStreamOp().setRatio(0.3);
  33.         data.link(sampleOp).print();
  34.         StreamOperator.execute();
  35.     }
  36. }

运行结果

| features | | —- |

| 10.9189774 10.7821363 |

| 10.0745650 8.0106483 |