根据与另一个 DataFrame 的列值匹配的列值子集 SparkR DataFrame

Question

我有两个 SparkR DataFrame，newHiresDF 和 salesTeamDF。我想根据 salesTeamDF$name 中 newHiresDF$name 的值获得 newHiresDF 的一个子集，但我想不出一种方法来做到这一点。以下是我尝试的代码。

#Create DataFrames
newHires <- data.frame(name = c("Thomas", "George", "Bill", "John"),
    surname = c("Smith", "Williams", "Brown", "Taylor"))
salesTeam <- data.frame(name = c("Thomas", "Bill", "George"),
    surname = c("Martin", "Clark", "Williams"))
newHiresDF <- createDataFrame(newHires)
salesTeamDF <- createDataFrame(salesTeam)
display(newHiresDF)

#Try to subset newHiresDF based on name values in salesTeamDF
#All of the below result in errors
NHsubset1 <- filter(newHiresDF, newHiresDF$name %in% salesTeamDF$name)
NHsubset2 <- filter(newHiresDF, intersect(select(newHiresDF, 'name'), 
    select(salesTeamDF, 'name')))
NHsubset3 <- newHiresDF[newHiresDF$name %in% salesTeamDF$name,] #This is how it would be done in R

#What I'd like NHsubset to look like:
    name  surname
1 Thomas    Smith
2 George Williams
3   Bill    Brown

如果您愿意，PySpark 代码也可以使用。

Answer 1

想出了一个事后看来很简单的解决方案：只需使用 merge。

NHsubset <- merge(newHiresDF, select(salesTeamDF, 'name'))

根据与另一个 DataFrame 的列值匹配的列值子集 SparkR DataFrame

Subsetting SparkR DataFrame based on column values matching another DataFrame's column values

apache-spark

pyspark

spark-dataframe

sparkr