文本分解 (TokenizerStreamOp)

Java 类名：com.alibaba.alink.operator.stream.nlp.TokenizerStreamOp
Python 类名：TokenizerStreamOp

功能介绍

对文本按空白符进行切分操作。

使用方式

文本列通过参数 selectedCol 指定，输出列通过 outputCol 指定。

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 [STRING] | |

| 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([
    [0, 'That is an English Book!'],
    [1, 'Do you like math?'],
    [2, 'Have a good day!']
])
inOp1 = BatchOperator.fromDataframe(df, schemaStr='id long, text string')
op = TokenizerBatchOp().setSelectedCol("text")
op.linkFrom(inOp1).print()
inOp2 = StreamOperator.fromDataframe(df, schemaStr='id long, text string')
op2 = TokenizerStreamOp().setSelectedCol("text")
op2.linkFrom(inOp2).print()
StreamOperator.execute()

Java 代码

import org.apache.flink.types.Row;
import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.nlp.TokenizerBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import com.alibaba.alink.operator.stream.StreamOperator;
import com.alibaba.alink.operator.stream.nlp.TokenizerStreamOp;
import com.alibaba.alink.operator.stream.source.MemSourceStreamOp;
import org.junit.Test;
import java.util.Arrays;
import java.util.List;
public class TokenizerStreamOpTest {
    @Test
    public void testTokenizerStreamOp() throws Exception {
        List <Row> df = Arrays.asList(
            Row.of(0, "That is an English Book!"),
            Row.of(1, "Do you like math?"),
            Row.of(2, "Have a good day!")
        );
        BatchOperator <?> inOp1 = new MemSourceBatchOp(df, "id int, text string");
        BatchOperator <?> op = new TokenizerBatchOp().setSelectedCol("text");
        op.linkFrom(inOp1).print();
        StreamOperator <?> inOp2 = new MemSourceStreamOp(df, "id int, text string");
        StreamOperator <?> op2 = new TokenizerStreamOp().setSelectedCol("text");
        op2.linkFrom(inOp2).print();
        StreamOperator.execute();
    }
}

运行结果

批运行结果

| id | text | | —- | —- |

| 0 | that is an english book! |

| 1 | do you like math? |

| 2 | have a good day! |

流运行结果

| id | text | | —- | —- |

| 0 | that is an english book! |

| 2 | have a good day! |

| 1 | do you like math? |