Accessing rows in XDF File

Question

I am solving the exercise 2 from https://github.com/MicrosoftLearning/20773_Analyzing-Big-Data-with-Microsoft-R/blob/master/Instructions/20773A_LAB_AK_04.md. The code creates the function which calculates the zone time etc. I do not understand why one can access variables and rows in the XDF File by for example departureYear <- dataList[[departureYearVarIndex]][i] inside the function, but if I try to do the same just from the subset file:

rxOptions(reportProgress = 1)
flightDelayDataSubsetFile <- "\\\\LON-RSVR\\Data\\flightDelayDataSubset.xdf"
flightDelayDataSubset <- rxDataStep(inData = mergedFlightDelayData,
    outFile = flightDelayDataSubsetFile, overwrite = TRUE,
    rowSelection = rbinom(.rxNumRows, size = 1, prob = 0.005)
)

like e.g. flightDelayDataSubset[[1]][1] it tells me "Error...this S4 class is not subsettable".

How to access the elements in XDF file? Why does it work in the function, but not manually for an existing file? I probably ask the wrong question because I do not understand how this function works. The functions argument dataList is given as a vector of XDF File Columns

transformFunc = standardizeTimes,
        transformVars = c("Year", "Month", "DayofMonth", "DepTime", "ActualElapsedTime", "OriginTimeZone")

. In the function it is treated as a list [[]] instead dataList[[arrivalTimeVarIndex]]. I am totally confused how it works. The question is probably, how this function knows which argument relates to which argument in the

transformVars = c("Year", "Month", "DayofMonth", "DepTime", "ActualElapsedTime", "OriginTimeZone")?

The function looks like this:

standardizeTimes <- function (dataList) {
    # Check to see whether this is a test chunk
    if (.rxIsTestChunk) {
        return(dataList)
    }

# Create a new vector for holding the standardized departure time
# and add it to the list of variable values
departureTimeVarIndex <- length(dataList) + 1
dataList[[departureTimeVarIndex]] <- rep(as.numeric(NA), times = .rxNumRows)
names(dataList)[departureTimeVarIndex] <- "StandardizedDepartureTime"

# Do the same for standardized arrival time
arrivalTimeVarIndex <- length(dataList) + 1
dataList[[arrivalTimeVarIndex]] <- rep(as.numeric(NA), times = .rxNumRows)
names(dataList)[arrivalTimeVarIndex] <- "StandardizedArrivalTime"
departureYearVarIndex <- 1
departureMonthVarIndex <- 2
departureDayVarIndex <- 3
departureTimeStringVarIndex <- 4
elapsedTimeVarIndex <- 5
departureTimezoneVarIndex <- 6

# Iterate through the rows and add the standardized arrival and departure times
for (i in 1:.rxNumRows) {
    # Get the local departure time details
    departureYear <- dataList[[departureYearVarIndex]][i]
    departureMonth <- dataList[[departureMonthVarIndex]][i]
    departureDay <- dataList[[departureDayVarIndex]][i]
    departureHour <- trunc(as.numeric(dataList[[departureTimeStringVarIndex]][i]) / 100)
    departureMinute <- as.numeric(dataList[[departureTimeStringVarIndex]][i]) %% 100
    departureTimeZone <- dataList[[departureTimezoneVarIndex]][i]

    # Construct the departure date and time, including timezone
    departureDateTimeString <- paste(departureYear, "-", departureMonth, "-", departureDay, " ", departureHour, ":", departureMinute, sep="")
    departureDateTime <- as.POSIXct(departureDateTimeString, tz = departureTimeZone)

    # Convert to UTC and store it
    standardizedDepartureDateTime <- format(departureDateTime, tz="UTC")
    dataList[[departureTimeVarIndex]][i] <- standardizedDepartureDateTime

    # Calculate the arrival date and time
    # Do this by adding the elapsed time to the departure time
    # The elapsed time is stored as the number of minutes (an integer)
    elapsedTime = dataList[[5]][i]
    standardizedArrivalDateTime <- format(as.POSIXct(standardizedDepartureDateTime) + minutes(elapsedTime))

        # Store it
        dataList[[arrivalTimeVarIndex]][i] <- standardizedArrivalDateTime
    }

    # Return the data including the new variables
    return(dataList)
}

flightDelayDataTimeZonesFile <- "\\\\LON-RSVR\\Data\\flightDelayDataTimezones.xdf"
flightDelayDataTimeZones <- rxDataStep(inData = flightDelayDataSubset,
    outFile = flightDelayDataTimeZonesFile, overwrite = TRUE,
    transformFunc = standardizeTimes,
    transformVars = c("Year", "Month", "DayofMonth", "DepTime", "ActualElapsedTime", "OriginTimeZone"),
    transformPackages = c("lubridate")
)

Hong Ooi Hong Ooi · Accepted Answer · 2019-02-14T11:19:13

My dplyrXdf package lets you index and subset Xdf files like they are data frames. Specifically it defines [[ and $ methods to extract columns from the file (but not [, because of implementation issues)

Accessing rows in XDF File

1 Answers