Thanks ! I will experiment. I have Windows 7 (64 bit) with 4GB RAM - so I suspect that 2GB is the most I can specify anyway.
Is there a 32-bit versus 64-bit official releases of the command line shell? On Fri, Feb 3, 2012 at 10:48 AM, Alexey Pechnikov <pechni...@mobigroup.ru>wrote: > You can try page size 8192 and cache size 128000. > Note: is required vacuuming after changing page size on existing database. > > Inserting/updating big indexed tables may be slow. In last SQLite versions > a index creating performance is optimized and so indexing fully populated > table is a good idea when it's possible. > > Don't use b-tree index for text fields. Use instead FTS4 extension or > integer > hash value to index text fields. Note: index compression is not supported > by > SQLite. > > 100+ Gb table and database is not too much for SQLite. I think you have > problems with big indexed tables but not with big tables. Big cache or > RAM drive or SSD disk may increase index updating speed. When a index > is larger than cache size (for parameters above cache size will be > 128 000 *8 192 bytes) all index moditications is very disk expensive > operations. > > P.S. Do not use cache size > 2Gb on 32-bit hosts. > > 2012/2/3 Udi Karni <uka...@gmail.com>: > > Marcus - thanks. I will experiment with those 2 PRAGMAs. > > > > Meanwhile - I was trying to update some columns in a table with 130 > million > > rows and got this error - > > > > "Error: out of memory" > > > > I am not sure why. I thought the "UPDATE" just writes out new rows and > > maybe a journal of the old rows for recoverability - but I am not sure > why > > it would need very much memory. > > > > Be that as it may - and with regard to your suggestion - and in light of > > this error message - given that I only have 4GB of RAM on my PC - is this > > really enough RAM to handle tables of this size ? Or am I giving Sqlite > an > > unreasonably small amount of resources and it's time for a serious > hardware > > upgrade? > > > > Thanks, > > > > Udi > > > > On Thu, Feb 2, 2012 at 10:03 PM, Marcus Grimm <mgr...@medcom-online.de > >wrote: > > > >> > Given how clever and compelling Sqlite is - I am testing how it > scales to > >> > tables in the 100GB / 200 million row range. This is for a strictly > "read > >> > only" application - but first the tables must be populated in a one > time > >> > process. As is often the case with Big Data - the data is a little > dirty > >> - > >> > so the process involves importing - selecting - counting - inspecting > - > >> > updating some rows - deleting some rows - selecting - counting - > >> > inspecting, etc. until clean. > >> > > >> > Placing the Sqlite database on a traditional C: drive - IO was too > slow. > >> > At > >> > 15 MB/sec - reading a 50GB table would take an hour. So I moved it to > >> > external Raid array where I ran across an interesting find. IO wasn't > >> that > >> > much faster - until I vaccuumed the database - which increase IO 10X > to > >> > 150 > >> > MB/sec - with the same CPU utilization. > >> > > >> > This is good news for the final implementation of this read-only > database > >> > - > >> > but still a dilemma at the data load phase. After a ".vaccuum" - > issueing > >> > a > >> > single DML against a table - even a DELETE which deletes no rows at > all - > >> > causes IO to drop back down to 15 MB/sec - on the table I'm selecting > / > >> > DMLing - which makes the data loading / cleansing phase very long. > >> > > >> > So I have 2 questions - > >> > > >> > (1) Why would simple DML cause such an extreme slowdown as compared > with > >> > "post vaccuum" speeds ? > >> > > >> > (2) Any knobs to turn to try and maintain the higher speeds post DML - > >> > without resorting to ".vaccuum" ? > >> > >> > >> You didn't tell if you already set the usual tricks to speed up > >> your load phase. That would be to increase the page cache and try > >> with reduced syncs. > >> See > >> PRAGMA cache_size > >> PRAGMA synchronous > >> > >> In particular the page cache should be increased dramatically > >> for huge DB files. > >> > >> Marcus > >> > >> > > >> > Thanks, > >> > > >> > Udi > >> > _______________________________________________ > >> > sqlite-users mailing list > >> > sqlite-users@sqlite.org > >> > http://sqlite.org:8080/cgi-bin/mailman/listinfo/sqlite-users > >> > > >> > >> > >> _______________________________________________ > >> sqlite-users mailing list > >> sqlite-users@sqlite.org > >> http://sqlite.org:8080/cgi-bin/mailman/listinfo/sqlite-users > >> > > _______________________________________________ > > sqlite-users mailing list > > sqlite-users@sqlite.org > > http://sqlite.org:8080/cgi-bin/mailman/listinfo/sqlite-users > > > > -- > Best regards, Alexey Pechnikov. > http://pechnikov.tel/ > _______________________________________________ > sqlite-users mailing list > sqlite-users@sqlite.org > http://sqlite.org:8080/cgi-bin/mailman/listinfo/sqlite-users > _______________________________________________ sqlite-users mailing list sqlite-users@sqlite.org http://sqlite.org:8080/cgi-bin/mailman/listinfo/sqlite-users
