Databases
StackOverflow2013
Postsdbo
POWhy is the parallel package slower than just using apply?
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POWhy is the parallel package slower than just using apply?
    primarykey
    data
    text
    <p>I am trying to determine when to use the <code>parallel</code> package to speed up the time necessary to run some analysis. One of the things I need to do is create matrices comparing variables in two data frames with differing number of rows. I asked a question as to an efficient way of doing on <a href="https://stackoverflow.com/questions/14485040/is-there-an-efficient-way-of-comparing-two-data-frames">StackOverflow</a> and wrote about tests on my <a href="http://jason.bryer.org/posts/2013-01-24/Comparing_Two_Data_Frames.html" rel="nofollow noreferrer">blog</a>. Since I am comfortable with the best approach I wanted to speed up the process by running it in parallel. The results below are based upon a 2ghz i7 Mac with 8gb of RAM. I am surprised that the <code>parallel</code> package, the <code>parSapply</code> funciton in particular, is worse than just using the <code>apply</code> function. The code to replicate this is below. Note that I am currently only using one of the two columns I create but eventually want to use both.</p> <p><a href="http://jason.bryer.org/images/ParalleVsApplyTiming.png" rel="nofollow noreferrer">Execution Time http://jason.bryer.org/images/ParalleVsApplyTiming.png</a></p> <pre><code>require(parallel) require(ggplot2) require(reshape2) set.seed(2112) results &lt;- list() sizes &lt;- seq(1000, 30000, by=5000) pb &lt;- txtProgressBar(min=0, max=length(sizes), style=3) for(cnt in 1:length(sizes)) { i &lt;- sizes[cnt] df1 &lt;- data.frame(row.names=1:i, var1=sample(c(TRUE,FALSE), i, replace=TRUE), var2=sample(1:10, i, replace=TRUE) ) df2 &lt;- data.frame(row.names=(i + 1):(i + i), var1=sample(c(TRUE,FALSE), i, replace=TRUE), var2=sample(1:10, i, replace=TRUE)) tm1 &lt;- system.time({ df6 &lt;- sapply(df2$var1, FUN=function(x) { x == df1$var1 }) dimnames(df6) &lt;- list(row.names(df1), row.names(df2)) }) rm(df6) tm2 &lt;- system.time({ cl &lt;- makeCluster(getOption('cl.cores', detectCores())) tm3 &lt;- system.time({ df7 &lt;- parSapply(cl, df1$var1, FUN=function(x, df2) { x == df2$var1 }, df2=df2) dimnames(df7) &lt;- list(row.names(df1), row.names(df2)) }) stopCluster(cl) }) rm(df7) results[[cnt]] &lt;- c(apply=tm1, parallel.total=tm2, parallel.exec=tm3) setTxtProgressBar(pb, cnt) } toplot &lt;- as.data.frame(results)[,c('apply.user.self','parallel.total.user.self', 'parallel.exec.user.self')] toplot$size &lt;- sizes toplot &lt;- melt(toplot, id='size') ggplot(toplot, aes(x=size, y=value, colour=variable)) + geom_line() + xlab('Vector Size') + ylab('Time (seconds)') </code></pre>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. USCommunity
    1. USjbryer
    plurals
    1. PL
      singulars
      1. LTLinked
    1. PL
      singulars
      1. LTLinked
    2. PL
      singulars
      1. LTLinked
    3. PL
      singulars
      1. LTDuplicate
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    2. PO
      singulars
      1. PTAnswer
    3. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POWhy is the parallel package slower than just using apply?
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. POWhy is the parallel package slower than just using apply?
      1. This table or related slice is empty.
      1. VTUpMod
    3. VO
      singulars
      1. POWhy is the parallel package slower than just using apply?
      1. This table or related slice is empty.
      1. VTUpMod
    1. CO(+1) nice formulation and I find it interesting! (apart from the blog plug :) )
      singulars
      1. POWhy is the parallel package slower than just using apply?
      1. USArun
    2. COSorry, didn't mean it as a plug :-) Was just trying to provide all the information I currently have.
      singulars
      1. POWhy is the parallel package slower than just using apply?
      1. USjbryer
    3. COI was only joking :).
      singulars
      1. POWhy is the parallel package slower than just using apply?
      1. USArun
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload