列数据转JSON (ColumnsToJsonStreamOp)

Java 类名：com.alibaba.alink.operator.stream.dataproc.format.ColumnsToJsonStreamOp

Python 类名：ColumnsToJsonStreamOp

功能介绍

将数据格式从 Columns 转成 Json

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
jsonCol	JSON列名	JSON列的列名	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”
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 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 = StreamOperator.fromDataframe(df, schemaStr="row string, json string, vec string, kv string, csv string, f0 double, f1 double")

op = ColumnsToJsonStreamOp()\
    .setSelectedCols(["f0", "f1"])\
    .setReservedCols(["row"])\
    .setJsonCol("json")\
    .linkFrom(data)

op.print()

StreamOperator.execute()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.stream.StreamOperator;
import com.alibaba.alink.operator.stream.dataproc.format.ColumnsToJsonStreamOp;
import com.alibaba.alink.operator.stream.source.MemSourceStreamOp;
import org.junit.Test;

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

public class ColumnsToJsonStreamOpTest {
	@Test
	public void testColumnsToJsonStreamOp() 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)
		);
		StreamOperator <?> data = new MemSourceStreamOp(df,
			"row string, json string, vec string, kv string, csv string, f0 double, f1 double");
		StreamOperator <?> op = new ColumnsToJsonStreamOp()
			.setSelectedCols("f0", "f1")
			.setReservedCols("row")
			.setJsonCol("json")
			.linkFrom(data);
		op.print();
		StreamOperator.execute();
	}
}

运行结果

row	json
1	{“f0”:“1.0”,“f1”:“2.0”}
2	{“f0”:“4.0”,“f1”:“8.0”}