Java 类名:com.alibaba.alink.operator.stream.dataproc.vector.VectorSliceStreamOp
Python 类名:VectorSliceStreamOp
功能介绍
对于流数据,取出 Vector 中的若干列,组成一个新的Vector。
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 | | —- | —- | —- | —- | —- | —- | —- |
| selectedCol | 选中的列名 | 计算列对应的列名 | String | ✓ | 所选列类型为 [DENSE_VECTOR, SPARSE_VECTOR, STRING, VECTOR] | |
| indices | 需要被提取的索引数组 | 需要被提取的索引数组 | int[] | | | null |
| outputCol | 输出结果列 | 输出结果列列名,可选,默认null | String | | | null |
| reservedCols | 算法保留列名 | 算法保留列 | String[] | | | null |
| numThreads | 组件多线程线程个数 | 组件多线程线程个数 | Integer | | | 1 |
代码示例
Python 代码
from pyalink.alink import *
import pandas as pd
useLocalEnv(1)
df = pd.DataFrame([
["1:3,2:4,4:7", 1],
["0:3,5:5", 3],
["2:4,4:5", 4]
])
data = StreamOperator.fromDataframe(df, schemaStr="vec string, id bigint")
vecSlice = VectorSliceStreamOp().setSelectedCol("vec").setOutputCol("vec_slice").setIndices([1,2,3])
vecSlice.linkFrom(data).print()
StreamOperator.execute()
Java 代码
import org.apache.flink.types.Row;
import com.alibaba.alink.operator.stream.StreamOperator;
import com.alibaba.alink.operator.stream.dataproc.vector.VectorSliceStreamOp;
import com.alibaba.alink.operator.stream.source.MemSourceStreamOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class VectorSliceStreamOpTest {
@Test
public void testVectorSliceStreamOp() throws Exception {
List <Row> df = Arrays.asList(
Row.of("1:3,2:4,4:7", 1),
Row.of("0:3,5:5", 3),
Row.of("2:4,4:5", 4)
);
StreamOperator <?> data = new MemSourceStreamOp(df, "vec string, id int");
StreamOperator <?> vecSlice = new VectorSliceStreamOp().setSelectedCol("vec").setOutputCol("vec_slice")
.setIndices(new int[] {1, 2, 3});
vecSlice.linkFrom(data).print();
StreamOperator.execute();
}
}
运行结果
| vec | id | vec_slice | | —- | —- | —- |
| 1:3,2:4,4:7 | 1 | $3$0:3.0 1:4.0 |
| 0:3,5:5 | 3 | |
| 2:4,4:5 | 4 | $3$1:4.0 |