Java 类名:com.alibaba.alink.operator.batch.feature.OverWindowBatchOp
Python 类名:OverWindowBatchOp
功能介绍
批式OverWindow特征构造组件。
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 |
---|---|---|---|---|---|---|
clause | 运算语句 | 运算语句 | String | ✓ | ||
orderBy | 排序列 | 排序列 | String | ✓ | ||
groupCols | 分组列名数组 | 分组列名,多列,可选,默认不选 | String[] | null | ||
reservedCols | 算法保留列名 | 算法保留列 | String[] | null |
代码示例
Python 代码
from pyalink.alink import *
import pandas as pd
useLocalEnv(1)
df = pd.DataFrame([
[2, 8, 2.2],
[2, 7, 3.3],
[5, 6, 4.4],
[5, 6, 5.5],
[7, 5, 6.6],
[1, 8, 1.1],
[1, 9, 1.0],
[7, 5, 7.7],
[9, 5, 8.8],
[9, 4, 9.8],
[19, 4, 8.8]])
data = BatchOperator.fromDataframe(df, schemaStr="f0 bigint, f1 bigint, f2 double")
OverWindowBatchOp().setOrderBy("f0, f1 desc").setClause("count_preceding(*) as cc").linkFrom(data).print()
Java 代码
import org.apache.flink.types.Row;
import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.feature.OverWindowBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class OverWindowBatchOpTest {
@Test
public void testOverWindowBatchOp() throws Exception {
List <Row> df = Arrays.asList(
Row.of(2, 8, 2.2),
Row.of(2, 7, 3.3),
Row.of(5, 6, 4.4),
Row.of(5, 6, 5.5),
Row.of(7, 5, 6.6),
Row.of(1, 8, 1.1),
Row.of(1, 9, 1.0),
Row.of(7, 5, 7.7),
Row.of(9, 5, 8.8),
Row.of(9, 4, 9.8)
);
BatchOperator <?> data = new MemSourceBatchOp(df, "f0 int, f1 int, f2 double");
new OverWindowBatchOp().setOrderBy("f0, f1 desc").setClause("count_preceding(*) as cc").linkFrom(data).print();
}
}
运行结果
| f0 | f1 | f2 | cc | | —- | —- | —- | —- |
| 1 | 9 | 1.0000 | 0 |
| 1 | 8 | 1.1000 | 1 |
| 2 | 8 | 2.2000 | 2 |
| 2 | 7 | 3.3000 | 3 |
| 5 | 6 | 4.4000 | 4 |
| 5 | 6 | 5.5000 | 5 |
| 7 | 5 | 6.6000 | 6 |
| 7 | 5 | 7.7000 | 7 |
| 9 | 5 | 8.8000 | 8 |
| 9 | 4 | 9.8000 | 9 |