我有一个csv文件:
name,age,phonenumbers
Tom,20,"[{number:100200, area_code:555},{number:100300, area_code:444}]"
Harry,20,"[{number:100400, area_code:555},{number:100500, area_code:666}]"
如何将Spark中的此文件加载到Person对象的人员的RDD /数据集中:
class Person {
String name;
Integer age;
List<Phone> phonenumbers;
class Phone {
int number;
int area_code;
}
}
答案 0 :(得分:1)
不幸的是,嵌套对象的列名在示例中没有引号。真的是这样吗?因为如果他们有引号(例如格式良好的JSON),那么您可以非常轻松地使用 var context = VSS.getWebContext();
var workClient = TFS_Work.getClient();
var teamContext = { projectId: context.project.id, teamId: context.team.id, project: "", team: "" };
_iterationId = VSS.getConfiguration().iterationId;
_witClient = VSS_Service.getCollectionClient(TFS_Wit_WebApi.WorkItemTrackingHttpClient);
workClient.getTeamDaysOff(teamContext, _iterationId).then(process);
函数,如下所示:
from_json
如果情况并非如此,那么您需要使用自己的逻辑将字符串转换为实际的嵌套对象,例如:
import org.apache.spark.sql.functions._
import org.apache.spark.sql.types._
val schema = new ArrayType(new StructType()
.add("number", IntegerType)
.add("area_code", IntegerType), false)
val converted = input.withColumn("phones", from_json('phonenumbers, schema))