为什么 Window 函数会因 "Window function X does not take a frame specification" 而失败？

Question

我正在尝试在 pyspark 1.4.1

但主要是出现错误或意外结果。这是一个我认为应该可行的非常简单的示例：

from pyspark.sql.window import Window
import pyspark.sql.functions as func

l = [(1,101),(2,202),(3,303),(4,404),(5,505)]
df = sqlContext.createDataFrame(l,["a","b"])

wSpec = Window.orderBy(df.a).rowsBetween(-1,1)

df.select(df.a, func.rank().over(wSpec).alias("rank"))  
    ==> Failure org.apache.spark.sql.AnalysisException: Window function rank does not take a frame specification.

df.select(df.a, func.lag(df.b,1).over(wSpec).alias("prev"), df.b, func.lead(df.b,1).over(wSpec).alias("next"))  
    ===>  org.apache.spark.sql.AnalysisException: Window function lag does not take a frame specification.;


wSpec = Window.orderBy(df.a)

df.select(df.a, func.rank().over(wSpec).alias("rank"))
    ===> org.apache.hadoop.hive.ql.exec.UDFArgumentTypeException: One or more arguments are expected.

df.select(df.a, func.lag(df.b,1).over(wSpec).alias("prev"), df.b, func.lead(df.b,1).over(wSpec).alias("next")).collect()

    [Row(a=1, prev=None, b=101, next=None), Row(a=2, prev=None, b=202, next=None), Row(a=3, prev=None, b=303, next=None)]

如您所见，如果我添加 rowsBetween 框架规范，rank() 和 lag/lead() window 函数都无法识别它："Window function does not take a frame specification".

如果我至少省略 rowsBetween 帧规范 lag/lead() 不会抛出异常，但 return 出乎意料的（对我来说）结果：总是 None。 rank() 仍然无法处理不同的异常。

任何人都可以帮助我正确设置 window 功能吗？

更新

好吧，这看起来像是一个 pyspark 错误。我在纯 Spark (Scala, spark-shell) 中准备了相同的测试：

import sqlContext.implicits._
import org.apache.spark.sql._
import org.apache.spark.sql.types._

val l: List[Tuple2[Int,Int]] = List((1,101),(2,202),(3,303),(4,404),(5,505))
val rdd = sc.parallelize(l).map(i => Row(i._1,i._2))
val schemaString = "a b"
val schema = StructType(schemaString.split(" ").map(fieldName => StructField(fieldName, IntegerType, true)))
val df = sqlContext.createDataFrame(rdd, schema)

import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions._

val wSpec = Window.orderBy("a").rowsBetween(-1,1)
df.select(df("a"), rank().over(wSpec).alias("rank"))
    ==> org.apache.spark.sql.AnalysisException: Window function rank does not take a frame specification.;

df.select(df("a"), lag(df("b"),1).over(wSpec).alias("prev"), df("b"), lead(df("b"),1).over(wSpec).alias("next"))
    ===> org.apache.spark.sql.AnalysisException: Window function lag does not take a frame specification.;


val wSpec = Window.orderBy("a")
df.select(df("a"), rank().over(wSpec).alias("rank")).collect()
    ====> res10: Array[org.apache.spark.sql.Row] = Array([1,1], [2,2], [3,3], [4,4], [5,5])

df.select(df("a"), lag(df("b"),1).over(wSpec).alias("prev"), df("b"), lead(df("b"),1).over(wSpec).alias("next"))
    ====> res12: Array[org.apache.spark.sql.Row] = Array([1,null,101,202], [2,101,202,303], [3,202,303,404], [4,303,404,505], [5,404,505,null])

即使 rowsBetween 不能在 Scala 中应用，rank() 和 lag()/lead() 都可以在省略 rowsBetween 时正常工作。

Answer 1

据我所知，有两个不同的问题。 Window Hive GenericUDAFRank, GenericUDAFLag and GenericUDAFLead 根本不支持框架定义，因此您看到的错误是预期的行为。

关于以下 PySpark 代码的问题

wSpec = Window.orderBy(df.a)
df.select(df.a, func.rank().over(wSpec).alias("rank"))

看起来和我的问题有关 and should be addressed by SPARK-9978。到目前为止，您可以通过将 window 定义更改为此来使其工作：

wSpec = Window.partitionBy().orderBy(df.a)

为什么 Window 函数会因 "Window function X does not take a frame specification" 而失败？

Why do Window functions fail with "Window function X does not take a frame specification"?

apache-spark

pyspark

apache-spark-sql

window-functions

pyspark-sql