1

我有一个关于 Sparks Dataframe 1.6 中的窗口操作的问题。

假设我有下表:

id|MONTH  |number
1  201703  2
1  201704  3
1  201705  7
1  201706  6

目前我正在使用 rowsBetween 函数:

val window = Window.partitionBy("id")
  .orderBy(asc("MONTH"))
  .rowsBetween(-2, 0)

randomDF.withColumn("counter", sum(col("number")).over(window))

这给了我以下结果:

id|MONTH  |number |counter
1  201703  2       2
1  201704  3       5
1  201705  7       12
1  201706  6       16

我不想实现的是在没有前置行时设置默认值(例如在 lag() 和 lead() 中)。例如:'0' 这样我得到的结果如下:

id|MONTH  |number |counter
1  201703  2       0
1  201704  3       0
1  201705  7       12
1  201706  6       16

我已经查看了文档,但 Spark 1.6 不允许这样做,我想知道是否有某种解决方法。

非常感谢 !

4

2 回答 2

2

像这样的东西怎么样:

  • 添加额外lag的步骤
  • 用替换值case

代码

val rowsRdd: RDD[Row] = spark.sparkContext.parallelize(
  Seq(
    Row(1, 1, 201703, 2),
    Row(2, 1, 201704, 3),
    Row(3, 1, 201705, 7),
    Row(4, 1, 201706, 6)))

val schema: StructType = new StructType()
  .add(StructField("sortColumn",     IntegerType,  false))
  .add(StructField("id",     IntegerType,  false))
  .add(StructField("month",  IntegerType, false))
  .add(StructField("number",  IntegerType, false))

val df0: DataFrame = spark.createDataFrame(rowsRdd, schema)

val prevRows = 2

val window = Window.partitionBy("id")
  .orderBy(col("month"))
  .rowsBetween(-prevRows, 0)

val window2 = Window.partitionBy("id")
  .orderBy(col("month"))

val df2 = df0.withColumn("counter", sum(col("number")).over(window))
val df3 = df2.withColumn("myLagTmp", lag(lit(1), prevRows).over(window2))
val df4 = df3.withColumn("counter", expr("case when myLagTmp is null then 0 else counter end")).drop(col("myLagTmp"))
df4.sort("sortColumn").show()
于 2018-02-15T14:31:30.577 回答
0

感谢@astro_asz 的回答,我想出了以下解决方案:

val numberRowsBetween = 2
val window1 = Window.partitionBy("id").orderBy("MONTH")
val window2 = Window.partitionBy("id")
      .orderBy(asc("MONTH"))
      .rowsBetween(-(numberRowsBetween - 1), 0)

randomDF.withColumn("counter", when(lag(col("number"), numberRowsBetween , 0).over(window1) === 0, 0)
                .otherwise(sum(col("number")).over(window2)))

此解决方案会将“0”作为默认值。

于 2018-02-16T13:42:34.077 回答