I now tried it with Lucene and the index creating is much *faster*. =) Also tested again both ways:
1. Importing without index: 120 sec + Indexing 80 sec 2. Importing with index: 340 sec + extracted 274.139 records (686 records/sec) - 274.139 records -> loaded 274.13 8 vertices (686 vertices/sec) Total time: 339809ms [0 warnings, 0 errors] So is Lucene actually faster when building up the index afterwards? Or is my computer really that crappy so that my 100% cpu usage really harming the benchmark? They query from above was done in ~25 sec, so it's also a bit faster. Can that be true? Am Montag, 18. August 2014 17:23:40 UTC+2 schrieb Enrico Risa: > > Hi Curtis > > can you post the result of > > explain select * from Abstract where appln_abstract LIKE "%of a pipe of > the pipe%" > > Thanks > Enrico > > > 2014-08-18 17:19 GMT+02:00 'Curtis Mosters' via OrientDB < > [email protected] <javascript:>>: > >> I'm still testing around with OrientDB. Today I realized that OrientDB is >> 3 times slower on the same data, with the same indexer compared to MySQL. >> How can that be? >> >> So there are ~250k entries. FULLTEXT indexer are used on both db's. (from >> https://github.com/orientechnologies/orientdb/wiki/Indexes) >> >> And the test query is: >> select * from Abstract where appln_abstract LIKE "%of a pipe of the >> pipe%" >> >> in OrientDB: 34 sec >> in MySQL: 14 sec >> >> I tested this on them both 3 times and this is the average. >> >> Any ideas? >> >> -- >> >> --- >> You received this message because you are subscribed to the Google Groups >> "OrientDB" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to [email protected] <javascript:>. >> For more options, visit https://groups.google.com/d/optout. >> > > -- --- You received this message because you are subscribed to the Google Groups "OrientDB" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
