Hi Curtis

the LIKE operator doesn't use the FULLTEXT index.

Could you retry the query with the CONTAINSTEXT
operator. It should be faster because rely on the FULLTEXT index

http://www.orientechnologies.com/docs/1.7.8/orientdb.wiki/SQL-Where.html
see here

Enrico


2014-08-18 20:47 GMT+02:00 'Curtis Mosters' via OrientDB <
[email protected]>:

> 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]>:
>>
>>> 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?
>>>
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