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CSV转列数据 (CsvToColumns)

Java 类名:com.alibaba.alink.pipeline.dataproc.format.CsvToColumns

Python 类名:CsvToColumns

功能介绍

将数据格式从 Csv 转成 Columns

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
csvCol CSV列名 CSV列的列名 String
schemaStr Schema Schema。格式为“colname coltype[, colname2, coltype2[, …]]”,例如“f0 string, f1 bigint, f2 double” String
csvFieldDelimiter 字段分隔符 字段分隔符 String “,”
handleInvalid 解析异常处理策略 解析异常处理策略,可选为ERROR(抛出异常)或者SKIP(输出NULL) String “ERROR”, “SKIP” “ERROR”
quoteChar 引号字符 引号字符 Character “"”
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([
    ['1', '{"f0":"1.0","f1":"2.0"}', '$3$0:1.0 1:2.0', 'f0:1.0,f1:2.0', '1.0,2.0', 1.0, 2.0],
    ['2', '{"f0":"4.0","f1":"8.0"}', '$3$0:4.0 1:8.0', 'f0:4.0,f1:8.0', '4.0,8.0', 4.0, 8.0]])

data = BatchOperator.fromDataframe(df, schemaStr="row string, json string, vec string, kv string, csv string, f0 double, f1 double")
 
op = CsvToColumns()\
    .setCsvCol("csv")\
    .setSchemaStr("f0 double, f1 double")\
    .setReservedCols(["row"])\
    .setSchemaStr("f0 double, f1 double")\
    .transform(data)

op.print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import com.alibaba.alink.pipeline.dataproc.format.CsvToColumns;
import org.junit.Test;

import java.util.Arrays;
import java.util.List;

public class CsvToColumnsTest {
	@Test
	public void testCsvToColumns() throws Exception {
		List <Row> df = Arrays.asList(
			Row.of("1", "{\"f0\":\"1.0\",\"f1\":\"2.0\"}", "$3$0:1.0 1:2.0", "f0:1.0,f1:2.0", "1.0,2.0", 1.0, 2.0)
		);
		BatchOperator <?> data = new MemSourceBatchOp(df,
			"row string, json string, vec string, kv string, csv string, f0 double, f1 double");
		BatchOperator op = new CsvToColumns()
			.setCsvCol("csv")
			.setSchemaStr("f0 double, f1 double")
			.setReservedCols("row")
			.setSchemaStr("f0 double, f1 double")
			.transform(data);
		op.print();
	}
}

运行结果

row f0 f1
1 1.0 2.0
2 4.0 8.0