Hi All
please help me to reduce mysqld cpu load.
mysql 4.1 running on solaris 10 with 4gb ram. front end apps is php (apache
server). everyday mysql reach about 100% cpu load. can one help to fix this
issue...
thank you.
Cheers
Faizal S
GSM : 9840118673
Blog: http://oradbapro.blogspot.com
Set up a local firewall that denies connections to TCP port 3306. Your load
will drop like a stone.
Alternatively, find out what's happening on the server, and start optimizing
from there.
On Tue, Mar 30, 2010 at 8:54 AM, F.A.I.Z.A.L sac.fai...@gmail.com wrote:
Hi All
please help me to
Hi,
I've used mainly of the older versions of MySQL. However am looking to port
a application across to MySQL 5. My question is when would one decide to
use a Stored Procedure over a query written at the application level ?
Cheers
Neil
Hello,
I have been pondering this for a while, but never really looked deeply
into the problem.
I have 96 dimensional points and I would like to pose queries such as:
'give me all points that are within such a radius of this one'. The gis
extensions to mysql might support such type of query. The
Geert-Jan Brits wrote:
You're most likely talking about something like consine-similarity on
N-dimensional vectors.
http://en.wikipedia.org/wiki/Cosine_similarity
http://stackoverflow.com/search?q=cosine+similarity
Cool links ! Although it is not why I need it for. I'm really talking
about an
Johan De Meersman wrote:
Well... a point in an n-dimensional space, is a location that has a
defined value for each of it's n dimensions. If you have a value for
each of your 96 dimensions, you have a point.
Well, it's fairly simple. If you have two points with 96 values in each.
Hi!
SQL Maestro Group announces the release of PHP Generator for MySQL
10.3, a GUI frontend that allows you to generate high-quality PHP
scripts for the selected MySQL tables, views and queries for the
further working with these objects through the web.
Hi there,
I currently store some information about a users daily habits in a table.
The table has 4 fields per day, and another 4 fields as the keys. This
table, depending on the month, can be from (4 keys + (28 days * 4 fields per
day)) fields, to (4 keys + (31 days * 4 fields per day)) fields
Not only should you definitely have one record per day, instead of one record
per month, you should think about normalizing your structure further. Try
these articles for tips on how to design a database structure:
http://dev.mysql.com/tech-resources/articles/intro-to-normalization.html and
I'm not sure why, but it seems that some people, I don't mean to imply
that you are one of them, think there is some magic MySQL can preform to
find points with in a given radius using the GIS extension. There is no
magic. They simply use the well known math required to determine what
points
Your first table layout is horrible, the second one is only marginally
better. You should read up on database normalization.
I have no idea what id, id2 and type are but since they seem like they
are the same for every 'f' and every day, I am pretty sure they all
relate directly to the user
Today I installed MySQL 5.1.45-1 on my production server and it
recommended that I run the following:
/usr/bin/mysql_secure_installation
When I ran this, it simply guided me to do the following:
- set root password
- disable remote login for root
- remove 'anonymous' user accounts
- delete
Perhaps you could give us a (generalized) description of your use-case, so
we can better grasp what you want to achieve, and how you want to use it.
i.e: since I can't imagine/ envison a real 'eucledian distance' over 96
dimensions I bet you're talking a generalized distance function over N
Hello Chris,
The use case I'
m talking about is actually a typical usecase for GIS applications: give
me the x closest points to this one. E.g: give me the 10 points closest
to (1,2,79) or in my case: give me the 100 points closest to
(x1,x96). A query like yours might be possible and might
Geert-Jan Brits wrote:
Perhaps you could give us a (generalized) description of your use-case, so
we can better grasp what you want to achieve, and how you want to use it.
i.e: since I can't imagine/ envison a real 'eucledian distance' over 96
dimensions I bet you're talking a generalized
Here is an idea, I'm not going to code this one:) It's still not an
ideal solution because it has to make assumptions about your data set.
Execute the algorithm I outlined previously with a very small r value,
if you didn't find the number of points you are looking for, increase r
and modify
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