Java 类名:com.alibaba.alink.operator.batch.dataproc.format.ColumnsToCsvBatchOp
Python 类名:ColumnsToCsvBatchOp
功能介绍
将数据格式从 Columns 转成 Csv
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 | ||
| selectedCols | 选中的列名数组 | 计算列对应的列名列表 | String[] | null |
代码示例
Python 代码
from pyalink.alink import *import pandas as pduseLocalEnv(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 = ColumnsToCsvBatchOp()\.setSelectedCols(["f0", "f1"])\.setReservedCols(["row"])\.setCsvCol("csv")\.setSchemaStr("f0 double, f1 double")\.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.ColumnsToCsvBatchOp;import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;import org.junit.Test;import java.util.Arrays;import java.util.List;public class ColumnsToCsvBatchOpTest {@Testpublic void testColumnsToCsvBatchOp() 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 ColumnsToCsvBatchOp().setSelectedCols("f0", "f1").setReservedCols("row").setCsvCol("csv").setSchemaStr("f0 double, f1 double").linkFrom(data);op.print();}}
运行结果
| row | csv | | —- | —- |
| 1 | 1.0,2.0 |
| 2 | 4.0,8.0 |
