Java 类名：com.alibaba.alink.pipeline.dataproc.IndexToString
Python 类名：IndexToString

功能介绍

基于StringIndexer模型，将一列整数映射为字符串。

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
modelName 模型名字 模型名字 String ✓
selectedCol 选中的列名 计算列对应的列名 String ✓
modelFilePath 模型的文件路径 模型的文件路径 String null
outputCol 输出结果列 输出结果列列名，可选，默认null String null
overwriteSink 是否覆写已有数据 是否覆写已有数据 Boolean false
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
modelStreamFilePath 模型流的文件路径 模型流的文件路径 String null
modelStreamScanInterval 扫描模型路径的时间间隔 描模型路径的时间间隔，单位秒 Integer 10
modelStreamStartTime 模型流的起始时间 模型流的起始时间。默认从当前时刻开始读。使用yyyy-mm-dd hh:mm:ss.fffffffff格式，详见Timestamp.valueOf(String s) String null

代码示例

Python 代码

  1. from pyalink.alink import *
  3. import pandas as pd
  5. useLocalEnv(1)
  7. df_data = pd.DataFrame([
  8.     ["football"],
  9.     ["football"],
  10.     ["football"],
  11.     ["basketball"],
  12.     ["basketball"],
  13.     ["tennis"],
  14. ])
  16. train_data = BatchOperator.fromDataframe(df_data, schemaStr='f0 string')
  17. data = StreamOperator.fromDataframe(df_data, schemaStr='f0 string')
  19. stringIndexer = StringIndexer() \
  20.     .setModelName("string_indexer_model") \
  21.     .setSelectedCol("f0") \
  22.     .setOutputCol("f0_indexed") \
  23.     .setStringOrderType("frequency_asc").fit(train_data)
  25. batch_model = stringIndexer.transform(train_data)
  26. indexed = stringIndexer.transform(data)
  28. indexToStrings = IndexToStringPredictStreamOp(batch_model) \
  29.     .setSelectedCol("f0_indexed") \
  30.     .setOutputCol("f0_indxed_unindexed")
  32. indexToStrings.linkFrom(indexed).print()
  33. StreamOperator.execute()

Java 代码

  1. import org.apache.flink.types.Row;
  3. import com.alibaba.alink.operator.batch.BatchOperator;
  4. import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
  5. import com.alibaba.alink.operator.stream.StreamOperator;
  6. import com.alibaba.alink.operator.stream.dataproc.IndexToStringPredictStreamOp;
  7. import com.alibaba.alink.operator.stream.source.MemSourceStreamOp;
  8. import com.alibaba.alink.pipeline.dataproc.StringIndexer;
  9. import com.alibaba.alink.pipeline.dataproc.StringIndexerModel;
  10. import org.junit.Test;
  12. import java.util.Arrays;
  13. import java.util.List;
  15. public class IndexToStringTest {
  16.     @Test
  17.     public void testIndexToString() throws Exception {
  18.         List <Row> df_data = Arrays.asList(
  19.             Row.of("football"),
  20.             Row.of("football"),
  21.             Row.of("football"),
  22.             Row.of("basketball"),
  23.             Row.of("basketball"),
  24.             Row.of("tennis")
  25.         );
  26.         BatchOperator <?> train_data = new MemSourceBatchOp(df_data, "f0 string");
  27.         StreamOperator <?> data = new MemSourceStreamOp(df_data, "f0 string");
  28.         StringIndexerModel stringIndexer = new StringIndexer()
  29.             .setModelName("string_indexer_model")
  30.             .setSelectedCol("f0")
  31.             .setOutputCol("f0_indexed")
  32.             .setStringOrderType("frequency_asc").fit(train_data);
  33.         BatchOperator batch_model = stringIndexer.transform(train_data);
  34.         StreamOperator indexed = stringIndexer.transform(data);
  35.         StreamOperator <?> indexToStrings = new IndexToStringPredictStreamOp(batch_model)
  36.             .setSelectedCol("f0_indexed")
  37.             .setOutputCol("f0_indxed_unindexed");
  38.         indexToStrings.linkFrom(indexed).print();
  39.         StreamOperator.execute();
  40.     }
  41. }

运行结果

| f0 | f0_indexed | f0_indxed_unindexed | | —- | —- | —- |

| football | 2 | football |

| football | 2 | football |

| football | 2 | football |

| basketball | 1 | basketball |

| basketball | 1 | basketball |

| tennis | 0 | tennis |