固定条数随机采样 (SampleWithSizeBatchOp)

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

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df = pd.DataFrame([
  ["0,0,0"],
  ["0.1,0.1,0.1"],
  ["0.2,0.2,0.2"],
  ["9,9,9"],
  ["9.1,9.1,9.1"],
  ["9.2,9.2,9.2"]
])

inOp = BatchOperator.fromDataframe(df, schemaStr='Y string')

sampleOp = SampleWithSizeBatchOp() \
  .setSize(2) \
  .setWithReplacement(False)

inOp.link(sampleOp).print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.dataproc.SampleWithSizeBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;

import java.util.Arrays;
import java.util.List;

public class SampleWithSizeBatchOpTest {
	@Test
	public void testSampleWithSizeBatchOp() throws Exception {
		List <Row> df = Arrays.asList(
			Row.of("0,0,0"),
			Row.of("0.1,0.1,0.1"),
			Row.of("0.2,0.2,0.2"),
			Row.of("9,9,9"),
			Row.of("9.1,9.1,9.1"),
			Row.of("9.2,9.2,9.2")
		);
		BatchOperator <?> inOp = new MemSourceBatchOp(df, "Y string");
		BatchOperator <?> sampleOp = new SampleWithSizeBatchOp()
			.setSize(2)
			.setWithReplacement(false);
		inOp.link(sampleOp).print();
	}
}

运行结果

Y
0,0,0
0.2,0.2,0.2