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 |