Processing large datasets
In cases where I have to parse through large datasets that will not fit into R's memory, I will grab relevant data using SQL and then analyze said data using R. There are several packages designed to do this, like [1] and [2] below, that allow you to query a database using SQL and end up with that data in an R data.frame. [1] http://cran.cnr.berkeley.edu/web/packages/RMySQL/index.html [2] http://cran.cnr.berkeley.edu/web/packages/RSQLite/index.html
On Wed, May 25, 2011 at 12:29 AM, Roman Naumenko <roman at bestroman.com> wrote:
Hi R list, I'm new to R software, so I'd like to ask about it is capabilities. What I'm looking to do is to run some statistical tests on quite big tables which are aggregated quotes from a market feed. This is a typical set of data. Each day contains millions of records (up to 10 non filtered). 2011-05-24 ? ? ?750 ? ? Bid ? ? DELL ? ?14130770 ? ? ? ?400 15.4800 ? ? ? ? BATS ? ?35482391 ? ? ? ?Y ? ? ? 1 ? ? ? 1 ? ? ? 0 ? ? ? 0 2011-05-24 ? ? ?904 ? ? Bid ? ? DELL ? ?14130772 ? ? ? ?300 15.4800 ? ? ? ? BATS ? ?35482391 ? ? ? ?Y ? ? ? 1 ? ? ? 0 ? ? ? 0 ? ? ? 0 2011-05-24 ? ? ?904 ? ? Bid ? ? DELL ? ?14130773 ? ? ? ?135 15.4800 ? ? ? ? BATS ? ?35482391 ? ? ? ?Y ? ? ? 1 ? ? ? 0 ? ? ? 0 ? ? ? 0 I'll need to filter it out first based on some criteria. Since I keep it mysql database, it can be done through by query. Not super efficient, checked it already. Then I need to aggregate dataset into different time frames (time is represented in ms from midnight, like 35482391). Again, can be done through a databases query, not sure what gonna be faster. Aggregated tables going to be much smaller, like thousands rows per observation day. Then calculate basic statistic: mean, standard deviation, sums etc. After stats are calculated, I need to perform some statistical hypothesis tests. So, my question is: what tool faster for data aggregation and filtration on big datasets: mysql or R? Thanks, --Roman N. ? ? ? ?[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
=============================================== Jon Daily Technician =============================================== #!/usr/bin/env outside # It's great, trust me.