bupaR: Error in data.frame Arguments imply different number of rows

Question

I am currently trying to use bupaR to generate some R visuals in power BI for process mining. Currently I have a dataset with over 120k rows. There are not rows with empty timestamps. The code I am using is the following:

library(bupaR)
library(DiagrammeR)

GeneralData <- dataset
GeneralData$LASTUPDATE <- as.POSIXct(GeneralData$LASTUPDATE, tz = "GMT", format = c("%d-%m-$Y %H:%M:%S"))
x <- GeneralData %>%
        eventlog(
            activity_id =  "STATUS",
            case_id = "CONTRACTID",
            resource_id =  "CAT",
            activity_instance_id =  "Index",
            lifecycle_id =  "CTYPE",
            timestamp = "LASTUPDATE"
        ) %>% process_map(performance(median, "days"), render=FALSE)

export_graph(x, "result.png", file_type = "png")

Whenever I try to run this, I receive the following message:

Error in data.frame(id = 1:n, type = type, label = label, stringsAsFactors = FALSE) : Arguments imply different number of rows: 2, 0 Calls: %>% ... create_node_df -> -> list2 -> data.frame.

How can I solve this? if I don't try to measure the amount of time used for each step of the process, the code works fine:

library(bupaR)
library(DiagrammeR)
Query1 <- dataset
Query1$LASTUPDATE <- as.POSIXct(Query1$LASTUPDATE, tz="GMT", format = c("%Y-%m-$d %H:%M:%S"))
x <- Query1 %>%
    eventlog(
        activity_id="STATUS",
        case_id="CONTRACTID",
        resource_id="CAT",
        activity_instance_id= "Index",
        lifecycle_id="CTYPE",
        timestamp="LASTUPDATE"
    ) 
y <- process_map(x, render=FALSE)
export_graph(y, "result.png", file_type = "png")

I can't figure out why this isn't working.