SQL操作：Distinct (DistinctBatchOp)

Java 类名：com.alibaba.alink.operator.batch.sql.DistinctBatchOp

Python 类名：DistinctBatchOp

功能介绍

对批式数据进行sql的DISTINCT操作。

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

代码示例

Python 代码

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df = pd.DataFrame([
    ['Ohio', 2000, 1.5],
    ['Ohio', 2001, 1.7],
    ['Ohio', 2002, 3.6],
    ['Nevada', 2001, 2.4],
    ['Nevada', 2002, 2.9],
    ['Nevada', 2003, 3.2]
])

batch_data = BatchOperator.fromDataframe(df, schemaStr='f1 string, f2 bigint, f3 double')

batch_data.select('f1').link(DistinctBatchOp()).print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import com.alibaba.alink.operator.batch.sql.DistinctBatchOp;
import org.junit.Test;

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

public class DistinctBatchOpTest {
	@Test
	public void testDistinctBatchOp() throws Exception {
		List <Row> df = Arrays.asList(
			Row.of("Ohio", 2000, 1.5),
			Row.of("Ohio", 2001, 1.7),
			Row.of("Ohio", 2002, 3.6),
			Row.of("Nevada", 2001, 2.4),
			Row.of("Nevada", 2002, 2.9),
			Row.of("Nevada", 2003, 3.2)
		);
		BatchOperator <?> batch_data = new MemSourceBatchOp(df, "f1 string, f2 int, f3 double");
		batch_data.select("f1").link(new DistinctBatchOp()).print();
	}
}

运行结果

f1
Nevada
Ohio