CSV转列数据 (CsvToColumnsBatchOp)

Java 类名：com.alibaba.alink.operator.batch.dataproc.format.CsvToColumnsBatchOp

Python 类名：CsvToColumnsBatchOp

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	✓	所选列类型为 [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 = CsvToColumnsBatchOp()\
    .setCsvCol("csv")\
    .setSchemaStr("f0 double, f1 double")\
    .setReservedCols(["row"])\
    .linkFrom(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.dataproc.format.CsvToColumnsBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;

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

public class CsvToColumnsBatchOpTest {
	@Test
	public void testCsvToColumnsBatchOp() 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),
			Row.of("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)
		);
		BatchOperator <?> data = new MemSourceBatchOp(df,
			"row string, json string, vec string, kv string, csv string, f0 double, f1 double");
		BatchOperator <?> op = new CsvToColumnsBatchOp()
			.setCsvCol("csv")
			.setSchemaStr("f0 double, f1 double")
			.setReservedCols("row")
			.linkFrom(data);
		op.print();
	}
}

运行结果

row	f0	f1
1	1.0	2.0
2	4.0	8.0