52 lines
1.4 KiB
R
52 lines
1.4 KiB
R
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library(foreach)
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library(RSQLite)
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# Define a simple iterator for a query result, which is
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# just a wrapper around the fetch function
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iquery <- function(con, statement, ..., n=1) {
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rs <- dbSendQuery(con, statement, ...)
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nextEl <- function() {
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d <- fetch(rs, n)
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if (nrow(d) == 0) {
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dbClearResult(rs)
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stop('StopIteration')
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}
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d
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}
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obj <- list(nextElem=nextEl)
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class(obj) <- c('abstractiter', 'iter')
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obj
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}
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# Create an SQLite instance
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m <- dbDriver('SQLite')
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# Initialize a new database to a tempfile and copy a data frame
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# into it repeatedly to get more data to process
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tfile <- tempfile()
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con <- dbConnect(m, dbname=tfile)
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data(USArrests)
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dbWriteTable(con, 'USArrests', USArrests)
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for (i in 1:99)
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dbWriteTable(con, 'USArrests', USArrests, append=TRUE)
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# Create an iterator to issue the query, selecting the fields of interest
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qit <- iquery(con, 'select Murder, Assault, Rape from USArrests', n=50)
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# Define a combine function for the partial results
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comb <- function(...) {
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n <- foreach(a=list(...), .combine='+') %do% a$n
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means <- foreach(a=list(...), .combine='+') %do% ((a$n / n) * a$means)
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list(n=n, means=means)
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}
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# Compute the mean of each of those fields, 50 records at a time
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r <- foreach(d=qit, .combine=comb, .multicombine=TRUE) %dopar%
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list(n=nrow(d), means=mean(d))
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print(r)
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# Clean up
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dbDisconnect(con)
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file.remove(tfile)
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