Spark Scala:按近位置和时间范围加入两个数据帧

Spark Scala : Join two Dataframes by near position and time range

我有两个数据框:

  1. 一个数据帧DF1,结构如下:(ID, StartDate, EndDate, Position)

  2. 一个 Dataframe DF2 看起来像:(DateTime, Position)

我想使用这些数据帧创建一个新数据帧,其中包含每个 DF1(ID)、DF2 中的行数,其中 DF2(DateTime) 在 DF1(StartDate) 和 DF1(EndDate) 和 DF2 之间(位置)靠近 DF1(位置)

我们可以假设我有一个 udf 函数 isNearUDF(pos1,pos2) 可以完成比较位置的工作。

我目前正在尝试通过我的数据帧之间的连接来执行此操作,但这似乎不是正确的解决方案

编辑 2:

这是一个 MVCE:

def isInRadius(lat1:Double,lon1:Double,lat2:Double,lon2:Double,dist:Double):Boolean={
  val distance = 0// calculate distance between lon/lat positions

  return distance<=dist
}

val DF1 = sc.parallelize(Array(
  ("ID1", "2018-02-27T13:47:59.416+01:00", "2018-03-01T16:02:00.632+01:00", "25.13297154663", "55.13297154663"),
  ("ID2", "2018-02-25T13:47:59.416+01:00", "2018-02-07T16:02:00.632+01:00", "26.13297154663", "55.13297154663"),
  ("ID3", "2018-02-24T13:47:59.416+01:00", "2018-02-02T16:02:00.632+01:00", "25.13297154663", "55.13297154663")
// ...
)).toDF("ID", "CreationDate","EndDate","Lat1","Lon1")

val DF2 = sc.parallelize(Array(
  ("2018-02-27T13:47:59.416+01:00","25.13297154663", "55.13297154663"),
  ("2018-02-27T13:47:59.416+01:00","25.1304663", "54.10663"),
  ("2018-02-27T13:47:59.416+01:00","25.1354663", "55.132904663")
  // ...
)).toDF("DateTime","Lat2","Lon2")

val isInRadiusUdf = udf(isInRadius _)

val DF3 = DF1.join(DF2,$"DateTime">=$"CreationDate" && $"DateTime"<=$"EndDate" /*&& isInRadiusUdf($"Lat1",$"Lon1",$"Lat2",$"Lon2",lit(10))*/)

display(DF3)

这适用于日期,但需要很长时间。 当我添加 isInRadius 条件时,出现错误:

SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: org.apache.spark.sql.DataFrameReader

尝试将您的函数定义更改为:

def isInRadius : Double => Double => Double => Double => Double = lat1 => long1 => lat2 => long2 => dist {
  val distance = // calculate distance between lon/lat positions

  return distance<=dist
}

在尝试了各种可能的解决方案并得到奇怪的结果后,我终于通过简单地重新启动我的 Spark 集群(Databricks Notebook)来解决我的问题 我完全不知道问题出在哪里,但 MVCE 的代码现在可以工作了。