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...a more memory-efficient way to load this data? * Are there R modules that can store large data-sets in a more memory-efficient way? Can anyone relate their experiences with them? For reference, here's the Python script I used to measure Python's memory usage: import os def show_mem(): statm = open('/proc/%d/statm' % os.getpid()).read() print 'VIRT = %s, RSS = %s' % tuple(statm.split(' ')[:2]) def read_data(fname): servlets = [] timestamps = [] elapsed = [] for line in open(fname, 'r'): s, t, e = line.strip().split(' ') servlets.append...

...n png() : No png support in this version of R Can anyone tell me how to compile png support on solaris/unix? The new bitmap() device already does what I need but it requires ghostscript program installed. Please respond to my email in addition to the list. Thanks. Li Dongfeng ldf at statms.stat.pku.edu.cn Dept Statistics http://statms.stat.pku.edu.cn/~ldf Peking University -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or &quo...

...Department of Epidemiology, Biostatistics, & Occupational Health McGill University http://www.biostat.mcgill.ca/moodie -------------- next part -------------- A non-text attachment was scrubbed... Name: Meta-analysis of continuous outcomes combining individual patient data and aggregate data-StatMed.pdf Type: application/pdf Size: 202242 bytes Desc: Meta-analysis of continuous outcomes combining individual patient data and aggregate data-StatMed.pdf URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20121005/90f048a6/attachment-0002.pdf>

...roc/2191/maps -rw------- 1 root root 0 Nov 8 10:09 /proc/2191/mem lrwx------ 1 root root 0 Nov 8 10:09 /proc/2191/root -> / -r--r--r-- 1 root root 0 Nov 8 10:09 /proc/2191/stat -r--r--r-- 1 root root 0 Nov 8 10:09 /proc/2191/statm -r--r--r-- 1 root root 0 Nov 8 10:09 /proc/2191/status /proc/2191/fd: total 0 lrwx------ 1 root root 64 Nov 8 10:09 0 -> socket:[6186417] lrwx------ 1 root root 64 Nov 8 10:09 1 -> /dev/null lrwx------ 1 root root 64 Nov 8...

Two ideas, one more controversial than the other. First: auto-killing bloated workers.?My current app has some memory leakage that wasn''t really visible on our older passenger setup, since the auto-scaling meant that bloated workers got killed periodically. In a perfect world, we''d find and patch all of the leaks, but in the meantime (and as a safety net) I''d like to get

...--r--r-- 1 root root 0 Oct 8 16:54 maps -rw------- 1 root root 0 Oct 8 16:54 mem lrwx------ 1 root root 0 Oct 8 16:54 root -> / -r--r--r-- 1 root root 0 Oct 8 16:53 stat -r--r--r-- 1 root root 0 Oct 8 16:54 statm -r--r--r-- 1 root root 0 Oct 8 16:54 status [root@image:~/test]# The implications should be obvious. Once a compromise has taken place, nothing can be trusted, the operating system included. A module such as this could be placed in /lib/modules/<kernel_ver>/default to force...

...-- 1 root root 0 Oct 25 11:40 maps -rw------- 1 root root 0 Oct 25 11:40 mem lrwxrwxrwx 1 root root 0 Oct 25 11:40 root -> // -r--r--r-- 1 root root 0 Oct 25 11:40 stat -r--r--r-- 1 root root 0 Oct 25 11:40 statm -r--r--r-- 1 root root 0 Oct 25 11:40 status ls -l /proc/11026/fd total 0 dr-x------ 2 root root 0 Oct 25 10:39 ./ dr-xr-xr-x 3 root root 0 Oct 25 10:39 ../ lrwx------ 1 root root 64 Oct 25 11:39 0 -> /dev/null lrwx------...