similar to: rsync freezes when copying several million files

The Asterisk Development Team has announced the release of Asterisk 11.9.0. This release is available for immediate download at http://downloads.asterisk.org/pub/telephony/asterisk The release of Asterisk 11.9.0 resolves several issues reported by the community and would have not been possible without your participation. Thank you! The following are the issues resolved in this release: Bugs

The Asterisk Development Team has announced the release of Asterisk 11.9.0. This release is available for immediate download at http://downloads.asterisk.org/pub/telephony/asterisk The release of Asterisk 11.9.0 resolves several issues reported by the community and would have not been possible without your participation. Thank you! The following are the issues resolved in this release: Bugs

Hi Anyone have experience with very large datasets and the Bayesian Network package, bnlearn? In my experience R doesn't react well to very large datasets. Is there a way to divide up the dataset into pieces and incrementally learn the network with the pieces? This would also be helpful incase R crashes, because I could save the network after learning each piece. Thank you.

It took approximately five days, having single process using one core CPU and 6GB of memory to build this giant 607GB single Xapian index, containing 219 million of unique documents (web sites). So far I did not found any other implementation that would enable me to build such a single index containing over 200 million documents, while testing Lucene, Solr, MySQL, Hadoop and Oracle. Probably

Hi there, I have a data frame DF with 40 millions strings and their frequency. I am searching for strings with a given pattern and I am trying to speed up this part of my code. I try many options but so far I am not satisfied. I tried: - grepl and subset are equivalent in term of processing time grepl(paste0("^",pattern),df$Strings) subset(df,

Xapian Index 253 million documents = 704G I just build my largest single Xapian index with 253 million unique documents on single server using single hard disk, less that 8G RAM and single processor 2.0 GHz. I do not see any search performance decreases in searching my indexes between 100 million and 250 million, which indicates a good scalability of Xapian and it looks like, I can push it easily

Hi all, did not find much info in lists about subj. I have ztdummy working properly because I can use conferences without any errors. But when I try to use trunk=yes, I get the following: Sep 2 21:20:51 WARNING[1137720112]: chan_iax2.c:6422 build_user: Unable to support trunking on user home' without zaptel timing Sep 2 21:20:51 WARNING[1137720112]: chan_iax2.c:6246 build_peer: Unable to

lol - yep when news of this first broke I thought thats actually a very good idea to have implemented, though it sounds the way Trixbox implemented it may have been unsecure. Maybe someone else can come up with a better way of implementing this. If the data was all randomised there's no harm in doing this; some basic infomration like; Hours of uptime Reboots Number of extensions Number of

Comparison of Dovecot, Uwash, Courier, Cyrus and M-Box: http://www.isode.com/whitepapers/mbox-benchmark.html

Quoting Ruga <ruga at protonmail.com>: > Comparison of Dovecot, Uwash, Courier, Cyrus and M-Box: > http://www.isode.com/whitepapers/mbox-benchmark.html Wow. That comparison is only 11.5 years old. The "default" file system of reiserfs and gcc-3.3 were dead giveaways. I suspect Dovecot's changed a tad since that test. =R=

I'm trying to use rsync to get a live backup of 2 million files, about 50 gb, max depth of 5 directory levels. I'm on a gigabit lan so I'm passing -W, but it's still incredibly slow. What else can I do to speed things up? Perhaps there's a good way to filter out files older than X so only newer files are checked?. Will rsync 3.0.0 make a big difference for large trees?

i found two article said that rsync -a --delete empty/ a1/ will much more faster than rm when deleting millions files: http://linuxnote.net/jianingy/en/linux/a-fast-way-to-remove-huge-number-of-files.html http://www.quora.com/File-Systems/How-can-someone-rapidly-delete-400-000-files but my test gets opposite result, and i think it's impossible on theory. i use the command 'for i in

*Fukuoka Ruby Award* http://www.f-rubyaward.com/index_en.html The Government of Fukuoka Japan, together with the Fukuoka Ruby Award Selection Committee, is excited to announce the opening of the 2010 Fukuoka Ruby Award Competition. The competition is free to enter. The grand prize is 1 million yen (approximately $10,000). Applications may be submitted Online at

Hi, I have about half million binary features, and would like to find a model to estimate the continous response. According to the inference, I can express predictors and response by linear model. (ie. Design matrix: large sparse matrix with 0/1. Response: Continous number) Since it is not a classification problem, someone suggested me to try random forest in R. However, in the randomForest help

If someone posted already, forgive me I get the digest. http://www.tgdaily.com/content/view/43480/108/ Scientists get a million Linux kernels to run at once Scientists at Sandia National Laboratories in Livermore, have run more than a million Linux kernels as virtual machines. (how long before shared hosts use this....lol) The technique will allow them to effectively observe behaviour found

Hi. I am trying to recursively rsync a directory containing 13 million files. Right now this is killing my server, in terms of memory usage. I've upgraded from rsync 2.6.9 to 3.0.3 on both ends, but memory usage is still too high. I killed the rsync process when it reached 256 MB in size. I only have 1 GB of RAM in this server. We've planned an outage to upgrade it to 3 GB, but

Hi, I used postfix always_bcc to backup mail. And up to now the backup account has half million mails in cur/, when I first time tried to receive the mail by outlook, it failed , no responds. Does any one has some good idea to deal with this problem? Thanks

On 10/04/2016 2:03 PM, Fabien Tarrade wrote: > Hi there, > > I have a data frame DF with 40 millions strings and their frequency. I > am searching for strings with a given pattern and I am trying to speed > up this part of my code. I try many options but so far I am not > satisfied. I tried: > - grepl and subset are equivalent in term of processing time >

Hi Fabien, I was going to send this last night, but I thought it was too simple. Runs in about one millisecond. df<-data.frame(freq=runif(1000), strings=apply(matrix(sample(LETTERS,10000,TRUE),ncol=10), 1,paste,collapse="")) match.ind<-grep("DF",df$strings) match.ind [1] 2 11 91 133 169 444 547 605 734 943 Jim On Mon, Apr 11, 2016 at 5:27 AM, Fabien Tarrade

On Tue, 21 Feb 2017 09:49:39 -0500 KT Walrus wrote: > I just read this blog: https://mrotaru.wordpress.com/2013/10/10/scaling-to-12-million-concurrent-connections-how-migratorydata-did-it/ <https://mrotaru.wordpress.com/2013/10/10/scaling-to-12-million-concurrent-connections-how-migratorydata-did-it/> about scaling to 12 Million Concurrent Connections on a single server and it got me