Hi,
I am currently experiencing trouble getting my new mysql 5-servers
running as slaves on my old 4.1.13-master.
Looks like I'll have to dump the whole 30GB-database and import it on
the new servers :( At this moment I
do no see any oppurtunity to do this before the weekend since the
longest time I can block any of our production
systems is only 2-3 hours between midnight and 2am :(
I am still curious if Innodb could handle the load of my updates on the
heavy-traffic-tables since its disk-bound and
does transactions.
What I would probably need is an in-memory-table without any kind of
locking - at least not table-locks! But there
is no such engine in mysql. When a cluster can handle that (although it
has the transaction-overhead) it would probably be
perfect for since it even adds high availability in a very easy way...
Jan
Jan Kirchhoff schrieb:
sheeri kritzer schrieb:
No problem:
Firstly, how are you measuring your updates on a single table? I took
a few binary logs, grepped out for things that changed the table,
counting the lines (using wc) and then dividing by the # of seconds
the binary logs covered. The average for one table was 108 updates
per second.
I'm very intrigued as to how you came up with 2-300 updates per second
for one table. . . did you do it that way? If not, how did you do it?
(We are a VERY heavily trafficked site, having 18,000 people online
and active, and that accounts for the 108 updates per second. So if
you have more traffic than that. . .wow!)
Thanks for your hardware/database information. I will look at that
close tomorrow since I want to go home for today - it's already 9 pm
over here... I need beer ;)
We are not running a webservice here (actually we do, too, but thats
on other systems). This is part of our database with data of major
stock exchanges worldwide that we deliver realtime data for.
Currently that are around 900,000 quotes, during trading hours they
change all the time... We have much more updates than selects on the
main database.
Our Application that receives the datastream writes blocks (INSERT ...
ON DUPLICATE KEY UPDATE...) with all records that changed since the
last write. It gives me debug output like "[timestamp] Wrote 19427
rows in 6 queries" every 30 seconds - and that are numbers that I can
rely on.
Jan
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