>To get clarity, are you saying the 33% speedup is the gain of the
>non-Indexed vs. Indexed table, or due to setting that cache size on the
>already in-memory DB?  (The latter would be worrying).


Ryan, It seemed unaffected by cache size. The slight gain in speed (~0.2 secs) 
for the 2 million inserts was the result of having the full database in memory 
versus SSD based. There was almost no difference for the 111 million inserts.



________________________________
From: sqlite-users <sqlite-users-boun...@mailinglists.sqlite.org> on behalf of 
R Smith <rsm...@rsweb.co.za>
Sent: Monday, December 18, 2017 3:19:31 PM
To: sqlite-users@mailinglists.sqlite.org
Subject: Re: [sqlite] What happens if an in memory database runs out of memory

A big cache on an in-memory DB is a bit like insisting to sit inside a
row-boat while on a big ship. It has zero effect in helping you float
better - it's probably slightly worse even, considering the cache
computation cycles could have been avoided.

To get clarity, are you saying the 33% speedup is the gain of the
non-Indexed vs. Indexed table, or due to setting that cache size on the
already in-memory DB?  (The latter would be worrying).


On 2017/12/18 4:48 PM, curmudgeon wrote:
> You're definitely right about me wasting my time Simon. I loaded my entire
> database (1 GB) into memory and set cache_size = -8192 for an 8 GB cache
> size (using win64). I then ran my test (inserting the results of a query,
> returning 111 million bigints, into a non-indexed single column table) and
> there was no real difference. For lesser inserts (2 million) the speedup was
> around 33% but would hardly be noticeable to the end user.
>
> I daresay it would've been more noticeable if my laptop had a hard drive but
> the moral of the story is get yourself an SSD and leave sqlite to take care
> of the hard stuff.
>
>
>
> --
> Sent from: http://sqlite.1065341.n5.nabble.com/
> _______________________________________________
> sqlite-users mailing list
> sqlite-users@mailinglists.sqlite.org
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