Java 类名:com.alibaba.alink.operator.batch.dataproc.format.ColumnsToJsonBatchOp
Python 类名:ColumnsToJsonBatchOp
将数据格式从 Columns 转成 Json
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 |
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 = ColumnsToJsonBatchOp()\ .setSelectedCols(["f0", "f1"])\ .setReservedCols(["row"])\ .setJsonCol("json")\ .linkFrom(data) op.print()
import org.apache.flink.types.Row; import com.alibaba.alink.operator.batch.BatchOperator; import com.alibaba.alink.operator.batch.dataproc.format.ColumnsToJsonBatchOp; import com.alibaba.alink.operator.batch.source.MemSourceBatchOp; import org.junit.Test; import java.util.Arrays; import java.util.List; public class ColumnsToJsonBatchOpTest { @Test public void testColumnsToJsonBatchOp() 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 ColumnsToJsonBatchOp() .setSelectedCols("f0", "f1") .setReservedCols("row") .setJsonCol("json") .linkFrom(data); op.print(); } }
row | json |
---|---|
1 | {“f0”:“1.0”,“f1”:“2.0”} |
2 | {“f0”:“4.0”,“f1”:“8.0”} |