问题
I have a Spark dataframe in R as follows
head(df)
Lat1 Lng1 Lat2 Lng2
23.123 24.234 25.345 26.456
... ... ... ...
The DataFrame
contains two points Latitude and Longitude
I would like to calculate the Geo distance between the nodes in each row and add it to a new column.
In R I am using distCosine
function from geosphere
library.
df$dist = distCosine(cbind(df$lng1,df$lat1),cbind(df$lng2,df$lat2))
I am wondering how I should calculate it in SparkR.
SparkR produces the following error,
Error in as.integer(length(x) > 0L) :
cannot coerce type 'S4' to vector of type 'integer'
回答1:
You cannot use standard R function directly on Spark DataFrames
. If you use a recent Spark release you can you can use dapply
but it is a bit verbose and slowish:
df <- createDataFrame(data.frame(
lat1=c(23.123), lng1=c(24.234), lat2=c(25.345), lng2=c(26.456)))
new_schema <- do.call(
structType, c(schema(df)$fields(), list(structField("dist", "double", TRUE))))
attach_dist <- function(df) {
df$dist <- geosphere::distCosine(
cbind(df$lng1, df$lat1), cbind(df$lng2, df$lat2))
df
}
dapply(df, attach_dist, new_schema) %>% head()
lat1 lng1 lat2 lng2 dist
1 23.123 24.234 25.345 26.456 334733.4
In practice I would rather use the formula directly. It will be much faster, all required functions are already available and it is not very complicated:
df %>% withColumn("dist", acos(
sin(toRadians(df$lat1)) * sin(toRadians(df$lat2)) +
cos(toRadians(df$lat1)) * cos(toRadians(df$lat2)) *
cos(toRadians(df$lng1) - toRadians(df$lng2))
) * 6378137) %>% head()
lat1 lng1 lat2 lng2 dist
1 23.123 24.234 25.345 26.456 334733.4
来源:https://stackoverflow.com/questions/42764388/geo-distance-calculation-using-sparkr