Java 类名：com.alibaba.alink.operator.batch.source.TsvSourceBatchOp
Python 类名：TsvSourceBatchOp

功能介绍

读Tsv文件，Tsv文件是以tab为分隔符。文件来源可以是本地，oss，http，hdfs等。

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
filePath 文件路径 文件路径 String ✓
schemaStr Schema Schema。格式为”colname coltype[, colname2, coltype2[, …]]”，例如”f0 string, f1 bigint, f2 double” String ✓
ignoreFirstLine 是否忽略第一行数据 是否忽略第一行数据 Boolean false
skipBlankLine 是否忽略空行 是否忽略空行 Boolean true

代码示例

Python 代码

  1. from pyalink.alink import *
  3. import pandas as pd
  5. useLocalEnv(1)
  7. df = pd.DataFrame([
  8.                 ["0L", "1L", 0.6],
  9.                 ["2L", "2L", 0.8],
  10.                 ["2L", "4L", 0.6],
  11.                 ["3L", "1L", 0.6],
  12.                 ["3L", "2L", 0.3],
  13.                 ["3L", "4L", 0.4]
  14.         ])
  16. source = BatchOperator.fromDataframe(df, schemaStr='uid string, iid string, label double')
  18. filepath = "/tmp/abc.tsv"
  19. tsvSink = TsvSinkBatchOp()\
  20.     .setFilePath(filepath)\
  21.     .setOverwriteSink(True)
  23. source.link(tsvSink)
  25. BatchOperator.execute()
  27. tsvSource = TsvSourceBatchOp().setFilePath(filepath).setSchemaStr("f string")
  28. tsvSource.print()

Java 代码

  1. package javatest.com.alibaba.alink.batch.source;
  3. import org.apache.flink.types.Row;
  5. import com.alibaba.alink.operator.batch.BatchOperator;
  6. import com.alibaba.alink.operator.batch.sink.TsvSinkBatchOp;
  7. import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
  8. import com.alibaba.alink.operator.batch.source.TsvSourceBatchOp;
  9. import org.junit.Test;
  11. import java.util.Arrays;
  12. import java.util.List;
  14. public class TsvSourceBatchOpTest {
  15.     @Test
  16.     public void testTsvSourceBatchOp() throws Exception {
  17.         List <Row> df = Arrays.asList(
  18.             Row.of("0L", "1L", 0.6),
  19.             Row.of("2L", "2L", 0.8),
  20.             Row.of("2L", "4L", 0.6),
  21.             Row.of("3L", "1L", 0.6),
  22.             Row.of("3L", "2L", 0.3),
  23.             Row.of("3L", "4L", 0.4)
  24.         );
  25.         BatchOperator <?> source = new MemSourceBatchOp(df, "uid string, iid string, label double");
  26.         String filepath = "/tmp/abc.tsv";
  27.         BatchOperator <?> tsvSink = new TsvSinkBatchOp()
  28.             .setFilePath(filepath)
  29.             .setOverwriteSink(true);
  30.         source.link(tsvSink);
  31.         BatchOperator.execute();
  32.         BatchOperator <?> tsvSource = new TsvSourceBatchOp().setFilePath(filepath).setSchemaStr("f string");
  33.         tsvSource.print();
  34.     }
  35. }

运行结果

| f | | —- |

| 0L |

| 2L |

| 3L |

| 3L |

| 2L |

| 3L |