I have a single SQLite 2-column table with a primary TEXT key and a value, like so (id TEXT PRIMARY KEY, value TEXT). One process adds new records periodically, perhaps 1-10 per minute. The database currently has 850,000 entries and is 7.3GB large on disk.
I also need to perform bulk queries, which appear to be very slow. On an average desktop PC, for instance, a "SELECT COUNT(*)" takes over 5 minutes. If I want to do a dump of the table, as in "SELECT value FROM ...." I'll quickly get "database is locked" errors. Googling revealed that those are because a long running select keeps a cursor, and thus readlock on the entire database. I have since rewritten the query using multiple SELECT * FROM ... LIMIT a, b where b = 50 and a = 0, 50, 100, 150, ..... However, it takes 20 hours to fully extract the table's 850,000 records, with only minimal per record processing. My question: is this performance expected, or am I doing something wrong? Is there a quick way to count and/or dump an approximate snapshot of a single 2-column table such as the one shown above, even while keeping the database available for concurrent writes? I'm using Ubuntu 12.10 with 3.7.9-2ubuntu1.1 libsqlite3 using the Python binding. - Godmar _______________________________________________ sqlite-users mailing list firstname.lastname@example.org http://sqlite.org:8080/cgi-bin/mailman/listinfo/sqlite-users