I have a site where users browse through search results. It will be useful to remember which results the user has viewed, and mark them as Viewed.
Problem: To implement such a Recently Viewed list feature, which is the recommended approach?
Use a RDBMS like MySQL. Everytime a user clicks on a link, fire an AJAX call to the server to insert a new row into a table views with columns id, user_id, item_id, timestamp. Before any search results are displayed, each item will have its id checked against the table views to determine if that listing will be marked as viewed.
(If this helps, my PHP framework Laravel can use either the database or redis as the Session driver instead of using cookies)
Use a in-memory data store like Redis. I do not have experience with redis/memcached, the reason for thinking of using this is because of the large number of writes to the viewed table, and reads are mainly selected by the primary key (is there the concept of index in Redis?)
Thank you for any suggestions and opinions, especially from those who are experienced with the 2 technologies.
There is no rule of thumb when it comes to choose between the technologies you mention, at least not without a more comprehensive context (e.g. server load, amount of visits, amount of data, database write vs read ratio, etc), because none of them is all around "better" than the other, they are just different tools.
One MySQL INSERT per page view is very unlikely to pose even the slightlest hit in performance unless you count on having tens of thousands of concurrent (that is, visiting the site simultaneously, at the exact same time) users. I would suggest: focus on MySQL, since that seems to be what you know best, because you'll move faster and get whatever you are working on done earlier. You will always be able to switch to a different method later on if it really eventually becomes a bottleneck.
That being said: if you feel adventurous and time is not a problem:
redis would be an excellent fit for what you are trying to do.
Esentially you would have a sorted set per each user containing
itemids with timestamps as the score. This is easy to retrieve (name
each key after the user id, e.g. user:$userid:recentviews), easy to
paginate (ZREVRANGE would get you the most recent x views) and easy
to expire (ZREMRANGEBYRANK by a range between 0 and a timestamp of
now-30 days to remove all entries older than 30 days, for instance)
and should be relatively memory efficient compared to its MySQL
counter part. Don't worry if this all sounds like gibberish now, once you learn redis it's all actually very intuitive.
Memcached is designed strictly as a cache and not as a data-store, and as a result it's a bit inflexible with its data types (you would most likely have to store json strings and parse/string-ify them as you go, which has the added inconvenient of not being able to edit the list partially without retrieving it entirely first) and as opposed to redis it doesn't persist data to disk, so I would personally not recommend it for your recent views system. It may fit if your recent views data is volatile and small, but I don't think memcached is significantly faster than redis anyway.
If you do have the time, I would recommend searching and reading more about redis and memcached until you have a good picture of what they are and how they are used; only then you will be able to do an informed decision. But as I mentioned earlier, keep in mind that unless your needs are rather extraordinary MySQL may do the job just fine with no performance issues.
I have something similar to this, but it should work for what you're trying to get at. Couldn't you just store the pages they visit by including a file to each page. If you have a session.php file or something similar that is included on each page you can put the following code into that
$insert = mysql_query("INSERT INTO views VALUES
('$user_id','$itemid','$timestamp')");
(id should be auto incremented in database)
That will insert the page and it's id that they're currently on. You will need to define the page id in that page. For me that's easy because I use something like profile.php?id=1. Then for where you display the search results..
$checkid = mysql_query("SELECT * FROM views WHERE user_id='$userid' & itemid='$itemid');
$views = mysql_num_rows($checkid);
if($views > 1){
$viewed = "false";
}else{
$viewed = "true";
}
Then on your page you show the results you could have something like
if($viewed = "true"){
echo "You have viewed this page $views time(s)";
}elseif($viewed = "false"){
echo "You have not yet viewed this page";
}
If you run into something that doesn't make sense tell me, I'm running on not many hours of sleep! Haha (and I'm not exactly a PHP whiz)
Related
Well this is kind of a question of how to design a website which uses less resources than normal websites. Mobile optimized as well.
Here it goes: I was about to display a specific overview of e.g. 5 posts (from e.g. a blog). Then if I'd click for example on the first post, I'd load this post in a new window. But instead of connecting to the Database again and getting this specific post with the specific id, I'd just look up that post (in PHP) in my array of 5 posts, that I've created earlier, when I fetched the website for the first time.
Would it save data to download? Because PHP works server-side as well, so that's why I'm not sure.
Ok, I'll explain again:
Method 1:
User connects to my website
5 Posts become displayed & saved to an array (with all its data)
User clicks on the first Post and expects more Information about this post.
My program looks up the post in my array and displays it.
Method 2:
User connects to my website
5 Posts become displayed
User clicks on the first Post and expects more Information about this post.
My program connects to MySQL again and fetches the post from the server.
First off, this sounds like a case of premature optimization. I would not start caching anything outside of the database until measurements prove that it's a wise thing to do. Caching takes your focus away from the core task at hand, and introduces complexity.
If you do want to keep DB results in memory, just using an array allocated in a PHP-processed HTTP request will not be sufficient. Once the page is processed, memory allocated at that scope is no longer available.
You could certainly put the results in SESSION scope. The advantage of saving some DB results in the SESSION is that you avoid DB round trips. Disadvantages include the increased complexity to program the solution, use of memory in the web server for data that may never be accessed, and increased initial load in the DB to retrieve the extra pages that may or may not every be requested by the user.
If DB performance, after measurement, really is causing you to miss your performance objectives you can use a well-proven caching system such as memcached to keep frequently accessed data in the web server's (or dedicated cache server's) memory.
Final note: You say
PHP works server-side as well
That's not accurate. PHP works server-side only.
Have you think in saving the posts in divs, and only make it visible when the user click somewhere? Here how to do that.
Put some sort of cache between your code and the database.
So your code will look like
if(isPostInCache()) {
loadPostFromCache();
} else {
loadPostFromDatabase();
}
Go for some caching system, the web is full of them. You can use memcached or a static caching you can made by yourself (i.e. save post in txt files on the server)
To me, this is a little more inefficient than making a 2nd call to the database and here is why.
The first query should only be pulling the fields you want like: title, author, date. The content of the post maybe a heavy query, so I'd exclude that (you can pull a teaser if you'd like).
Then if the user wants the details of the post, i would then query for the content with an indexed key column.
That way you're not pulling content for 5 posts that may never been seen.
If your PHP code is constantly re-connecting to the database you've configured it wrong and aren't using connection pooling properly. The execution time of a query should be a few milliseconds at most if you've got your stack properly tuned. Do not cache unless you absolutely have to.
What you're advocating here is side-stepping a serious problem. Database queries should be effortless provided your database is properly configured. Fix that issue and you won't need to go down the caching road.
Saving data from one request to the other is a broken design and if not done perfectly could lead to embarrassing data bleed situations where one user is seeing content intended for another. This is why caching is an option usually pursued after all other avenues have been exhausted.
This question has been asked a THOUSAND times... so it's not unfair if you decide to skip reading/answering it, but I still thought people would like to see and comment on my approach...
I'm building a site which requires an activity feed, like FourSquare.
But my site has this feature for the eye-candy's sake, and doesn't need the stuff to be saved forever.
So, I write the event_type and user_id to a MySQL table. Before writing new events to the table, I delete all the older, unnecessary rows (by counting the total number of rows, getting the event_id lesser than which everything is redundant, and deleting those rows). I prune the table, and write a new row every time an event happens. There's another user_text column which is NULL if there is no user-generated text...
In the front-end, I have jQuery that checks with a PHP file via GET every x seconds the user has the site open. The jQuery sends a request with the last update "id" it received. The <div> tags generated by my backend have the "id" attribute set as the MySQL row id. This way, I don't have to save the last_received_id in memory, though I guess there's absolutely no performance impact from storing one variable with a very small int value in memory...
I have a function that generates an "update text" depending on the event_type and user_id I pass it from the jQuery, and whether the user_text column is empty. The update text is passed back to jQuery, which appends the freshly received event <div> to the feed with some effects, while simultaneously getting rid of the "tail end" event <div> with an effect.
If I (more importantly, the client) want to, I can have an "event archive" table in my database (or a different one) that saves up all those redundant rows before deleting. This way, event information will be saved forever, while not impacting the performance of the live site...
I'm using CodeIgniter, so there's no question of repeated code anywhere. All the pertinent functions go into a LiveUpdates class in the library and model respectively.
I'm rather happy with the way I'm doing it because it solves the problem at hand while sticking to the KISS ideology... but still, can anyone please point me to some resources, that show a better way to do it? A Google search on this subject reveals too many articles/SO questions, and I would like to benefit from the experience any other developer that has already trawled through them and found out the best approach...
If you use proper indexes there's no reason you couldn't keep all the events in one table without affecting performance.
If you craft your polling correctly to return nothing when there is nothing new you can minimize the load each client has on the server. If you also look into push notification (the hybrid delayed-connection-closing method) this will further help you scale big successfully.
Finally, it is completely unnecessary to worry about variable storage in the client. This is premature optimization. The performance issues are going to be in the avalanche of connections to the web server from many users, and in the DB, tables without proper indexes.
About indexes: An index is "proper" when the most common query against a table can be performed with a seek and a minimal number of reads (like 1-5). In your case, this could be an incrementing id or a date (if it has enough precision). If you design it right, the operation to find the most recent update_id should be a single read. Then when your client submits its ajax request to see if there is updated content, first do a query to see if the value submitted (id or time) is less than the current value. If so, respond immediately with the new content via a second query. Keeping the "ping" action as lightweight as possible is your goal, even if this incurs a slightly greater cost for when there is new content.
Using a push would be far better, though, so please explore Comet.
If you don't know how many reads are going on with your queries then I encourage you to explore this aspect of the database so you can find it out and assess it properly.
Update: offering the idea of clients getting a "yes there's new content" answer and then actually requesting the content was perhaps not the best. Please see Why the Fat Pings Win for some very interesting related material.
Let's say you have a search form, with multiple select fields, let's say a user selects from a dropdown an option, but before he submits the data I need to display the count of the rows in the database .
So let's say the site has at least 300k(300.000) visitors a day, and a user selects options from the form at least 40 times a visit, that would mean 12M ajax requests + 12M count queries on the database, which seems a bit too much .
The question is how can one implement a fast count (using php(Zend Framework) and MySQL) so that the additional 12M queries on the database won't affect the load of the site .
One solution would be to have a table that stores all combinations of select fields and their respective counts (when a product is added or deleted from the products table the table storing the count would be updated). Although this is not such a good idea when for 8 filters (select options) out of 43 there would be +8M rows inserted that need to be managed.
Any other thoughts on how to achieve this?
p.s. I don't need code examples but the idea itself that would work in this scenario.
I would probably have an pre-calculated table - as you suggest yourself. Import is that you have an smart mechanism for 2 things:
Easily query which entries are affected by which change.
Have an unique lookup field for an entire form request.
The 8M entries wouldn't be very significant if you have solid keys, as you would only require an direct lookup.
I would go trough the trouble to write specific updates for this table on all places it is necessary. Even with the high amount of changes, this is still efficient. If correctly done you will know which rows you need to update or invalidate when inserting/updating/deleting the product.
Sidenote:
Based on your comment. If you need to add code on eight places to cover all spots can be deleted - it might be a good time to refactor and centralize some code.
there are few scenarios
mysql has the query cache, you dun have to bother the caching IF the update of table is not that frequently
99% user won't bother how many results that matched, he/she just need the top few records
use the explain - if you notice explain will return how many rows going to matched in the query, is not 100% precise, but should be good enough to act as rough row count
Not really what you asked for, but since you have a lot of options and want to count the items available based on the options you should take a look at Lucene and its faceted search. It was made to solve problems like this.
If you do not have the need to have up to date information from the search you can use a queue system to push updates and inserts to Lucene every now and then (so you don't have to bother Lucene with couple of thousand of updates and inserts every day).
You really only have three options, and no amount of searching is likely to reveal a fourth:
Count the results manually. O(n) with the total number of the results at query-time.
Store and maintain counts for every combination of filters. O(1) to retrieve the count, but requires O(2^n) storage and O(2^n) time to update all the counts when records change.
Cache counts, only calculating them (per #1) when they're not found in the cache. O(1) when data is in the cache, O(n) otherwise.
It's for this reason that systems that have to scale beyond the trivial - that is, most of them - either cap the number of results they'll count (eg, items in your GMail inbox or unread in Google Reader), estimate the count based on statistics (eg, Google search result counts), or both.
I suppose it's possible you might actually require an exact count for your users, with no limitation, but it's hard to envisage a scenario where that might actually be necessary.
I would suggest a separate table that caches the counts, combined with triggers.
In order for it to be fast you make it a memory table and you update it using triggers on the inserts, deletes and updates.
pseudo code:
CREATE TABLE counts (
id unsigned integer auto_increment primary key
option integer indexed using hash key
user_id integer indexed using hash key
rowcount unsigned integer
unique key user_option (user, option)
) engine = memory
DELIMITER $$
CREATE TRIGGER ai_tablex_each AFTER UPDATE ON tablex FOR EACH ROW
BEGIN
IF (old.option <> new.option) OR (old.user_id <> new.user_id) THEN BEGIN
UPDATE counts c SET c.rowcount = c.rowcount - 1
WHERE c.user_id = old.user_id and c.option = old.option;
INSERT INTO counts rowcount, user_id, option
VALUES (1, new.user_id, new.option)
ON DUPLICATE KEY SET c.rowcount = c.rowcount + 1;
END; END IF;
END $$
DELIMITER ;
Selection of the counts will be instant, and the updates in the trigger should not take very long either because you're using a memory table with hash indexes which have O(1) lookup time.
Links:
Memory engine: http://dev.mysql.com/doc/refman/5.5/en/memory-storage-engine.html
Triggers: http://dev.mysql.com/doc/refman/5.5/en/triggers.html
A few things you can easily optimise:
Cache all you can allow yourself to cache. The options for your dropdowns, for example, do they need to be fetched by ajax calls? This page answered many of my questions when I implemented memcache, and of course memcached.org has great documentation available too.
Serve anything that can be served statically. Ie, options that don't change frequently could be stored in a flat file as array via cron every hour for example and included with script at runtime.
MySQL with default configuration settings is often sub-optimal for any serious application load and should be tweaked to fit the needs, of the task at hand. Maybe look into memory engine for high performance read-access.
You can have a look at these 3 great-but-very-technical posts on materialized views, as a matter of fact that whole blog is truly a goldmine of performance tips for mysql.
GOod-luck
Presumably you're using ajax to make the call to the back end that you're talking about. Use some kind of a chached flat file as an intermediate for the data. Set an expire time of 5 seconds or whatever is appropriate. Name the data file as the query key=value string. In the ajax request if the data file is older than your cooldown time, then refresh, if not, use the value stored in your data file.
Also, you might be underestimating the strength of the mysql query cache mechanism. If you're using mysql query cache, I doubt there would be any significant performance dip over doing it the way I just described. If the query was being query cached by mysql then virtually the only slowdown effect would be from the network layer between your application and mysql.
Consider what role replication can play in your architecture. If you need to scale out, you might consider replicating your tables from InnoDB to MyISAM. The MyISAM engine automatically maintains a table count if you are doing count(*) queries. If you are doing count(col) where queries, then you need to rely heavily on well designed indicies. In that case you your count queries might take shape like so:
alter table A add index ixA (a, b);
select count(a) using from A use index(ixA) where a=1 and b=2;
I feel crazy for suggesting this as it seems that no-one else has, but have you considered client-side caching? JavaScript isn't terrible at dealing with large lists, especially if they're relatively simple lists.
I know that your ideal is that you have a desire to make the numbers completely accurate, but heuristics are your friend here, especially since synchronization will never be 100% -- a slow connection or high latency due to server-side traffic will make the AJAX request out of date, especially if that data is not a constant. IF THE DATA CAN BE EDITED BY OTHER USERS, SYNCHRONICITY IS IMPOSSIBLE USING AJAX. IF IT CANNOT BE EDITED BY ANYONE ELSE, THEN CLIENT-SIDE CACHING WILL WORK AND IS LIKELY YOUR BEST OPTION. Oh, and if you're using some sort of port connection, then whatever is pushing to the server can simply update all of the other clients until a sync can be accomplished.
If you're willing to do that form of caching, you can also cache the results on the server too and simply refresh the query periodically.
As others have suggested, you really need some sort of caching mechanism on the server side. Whether it's a MySQL table or memcache, either would work. But to reduce the number of calls to the server, retrieve the full list of cached counts in one request and cache that locally in javascript. That's a pretty simple way to eliminate almost 12M server hits.
You could probably even store the count information in a cookie which expires in an hour, so subsequent page loads don't need to query again. That's if you don't need real time numbers.
Many of the latest browser also support local storage, which doesn't get passed to the server with every request like cookies do.
You can fit a lot of data into a 1-2K json data structure. So even if you have thousands of possible count options, that is still smaller than your typical image. Just keep in mind maximum cookie sizes if you use cookie caching.
I have a site where the users can view quite a large number of posts. Every time this is done I run a query similar to UPDATE table SET views=views+1 WHERE id = ?. However, there are a number of disadvantages to this approach:
There is no way of tracking when the pageviews occur - they are simply incremented.
Updating the table that often will, as far as I understand it, clear the MySQL cache of the row, thus making the next SELECT of that row slower.
Therefore I consider employing an approach where I create a table, say:
object_views { object_id, year, month, day, views }, so that each object has one row pr. day in this table. I would then periodically update the views column in the objects table so that I wouldn't have to do expensive joins all the time.
This is the simplest solution I can think of, and it seems that it is also the one with the least performance impact. Do you agree?
(The site is build on PHP 5.2, Symfony 1.4 and Doctrine 1.2 in case you wonder)
Edit:
The purpose is not web analytics - I know how to do that, and that is already in place. There are two purposes:
Allow the user to see how many times a given object has been shown, for example today or yesterday.
Allow the moderators of the site to see simple view statistics without going into Google Analytics, Omniture or whatever solution. Furthermore, the results in the backend must be realtime, a feature which GA cannot offer at this time. I do not wish to use the Analytics API to retrieve the usage data (not realtime, GA requires JavaScript).
Quote : Updating the table that often will, as far as I understand it, clear the MySQL cache of the row, thus making the next SELECT of that row slower.
There is much more than this. This is database killer.
I suggest u make table like this :
object_views { object_id, timestamp}
This way you can aggregate on object_id (count() function).
So every time someone view the page you will INSERT record in the table.
Once in a while you must clean the old records in the table. UPDATE statement is EVIL :)
On most platforms it will basically mark the row as deleted and insert a new one thus making the table fragmented. Not to mention locking issues .
Hope that helps
Along the same lines as Rage, you simply are not going to get the same results doing it yourself when there are a million third party log tools out there. If you are tracking on a daily basis, then a basic program such as webtrends is perfectly capable of tracking the hits especially if your URL contains the ID's of the items you want to track... I can't stress this enough, it's all about the URL when it comes to these tools (Wordpress for example allows lots of different URL constructs)
Now, if you are looking into "impression" tracking then it's another ball game because you are probably tracking each object, the page, the user, and possibly a weighted value based upon location on the page. If this is the case you can keep your performance up by hosting the tracking on another server where you can fire and forget. In the past I worked this using SQL updating against the ID and a string version of the date... that way when the date changes from 20091125 to 20091126 it's a simple query without the overhead of let's say a datediff function.
First just a quick remark why not aggregate the year,month,day in DATETIME, it would make more sense in my mind.
Also I am not really sure what is the exact reason you are doing that, if it's for a marketing/web stats purpose you have better to use tool made for that purpose.
Now there is two big family of tool capable to give you an idea of your website access statistics, log based one (awstats is probably the most popular), ajax/1pixel image based one (google analytics would be the most popular).
If you prefer to build your own stats database you can probably manage to build a log parser easily using PHP. If you find parsing apache logs (or IIS logs) too much a burden, you would probably make your application ouput some custom logs formated in a simpler way.
Also one other possible solution is to use memcached, the daemon provide some kind of counter that you can increment. You can log view there and have a script collecting the result everyday.
If you're going to do that, why not just log each access? MySQL can cache inserts in continuous tables quite well, so there shouldn't be a notable slowdown due to the insert. You can always run Show Profiles to see what the performance penalty actually is.
On the datetime issue, you can always use GROUP BY MONTH( accessed_at ) , YEAR( accessed_at) or WHERE MONTH(accessed_at) = 11 AND YEAR(accessed_at) = 2009.
How to increase the performance for mysql database because I have my website hosted in shared server and they have suspended my account because of "too many queries"
the stuff asked "index" or "cache" or trim my database
I don't know what does "index" and cache mean and how to do it on php
thanks
What an index is:
Think of a database table as a library - you have a big collection of books (records), each with associated data (author name, publisher, publication date, ISBN, content). Also assume that this is a very naive library, where all the books are shelved in order by ISBN (primary key). Just as the books can only have one physical ordering, a database table can only have one primary key index.
Now imagine someone comes to the librarian (database program) and says, "I would like to know how many Nora Roberts books are in the library". To answer this question, the librarian has to walk the aisles and look at every book in the library, which is very slow. If the librarian gets many requests like this, it is worth his time to set up a card catalog by author name (index on name) - then he can answer such questions much more quickly by referring to the catalog instead of walking the shelves. Essentially, the index sets up an 'alternative ordering' of the books - it treats them as if they were sorted alphabetically by author.
Notice that 1) it takes time to set up the catalog, 2) the catalog takes up extra space in the library, and 3) it complicates the process of adding a book to the library - instead of just sticking a book on the shelf in order, the librarian also has to fill out an index card and add it to the catalog. In just the same way, adding an index on a database field can speed up your queries, but the index itself takes storage space and slows down inserts. For this reason, you should only create indexes in response to need - there is no point in indexing a field you rarely search on.
What caching is:
If the librarian has many people coming in and asking the same questions over and over, it may be worth his time to write the answer down at the front desk. Instead of checking the stacks or the catalog, he can simply say, "here is the answer I gave to the last person who asked that question".
In your script, this may apply in different ways. You can store the results of a database query or a calculation or part of a rendered web page; you can store it to a secondary database table or a file or a session variable or to a memory service like memcached. You can store a pre-parsed database query, ready to run. Some libraries like Smarty will automatically store part or all of a page for you. By storing the result and reusing it you can avoid doing the same work many times.
In every case, you have to worry about how long the answer will remain valid. What if the library got a new book in? Is it OK to use an answer that may be five minutes out of date? What about a day out of date?
Caching is very application-specific; you will have to think about what your data means, how often it changes, how expensive the calculation is, how often the result is needed. If the data changes slowly, it may be best to recalculate and store the result every time a change is made; if it changes often but is not crucial, it may be sufficient to update only if the cached value is more than a certain age.
Setup a copy of your application locally, enable the mysql query log, and setup xdebug or some other profiler. The start collecting data, and testing your application. There are lots of guides, and books available about how to optimize things. It is important that you spend time testing, and collecting data first so you optimize the right things.
Using the data you have collected try and reduce the number of queries per page-view, Ideally, you should be able to get everything you need in less 5-10 queries.
Look at the logs and see if you are asking for the same thing twice. It is a bad idea to request a record in one portion of your code, and then request it again from the database a few lines later unless you are sure the value is likely to have changed.
Look for queries embedded in loop, and try to refactor them so you make a single query and simply loop on the results.
The select * you mention using is an indication you may be doing something wrong. You probably should be listing fields you explicitly need. Check this site or google for lots of good arguments about why select * is evil.
Start looking at your queries and then using explain on them. For queries that are frequently used make sure they are using a good index and not doing a full table scan. Tweak indexes on your development database and test.
There are a couple things you can look into:
Query Design - look into more advanced and faster solutions
Hardware - throw better and faster hardware at the problem
Database Design - use indexes and practice good database design
All of these are easier said than done, but it is a start.
Firstly, sack your host, get off shared hosting into an environment you have full control over and stand a chance of being able to tune decently.
Replicate that environment in your lab, ideally with the same hardware as production; this includes things like RAID controller.
Did I mention that you need a RAID controller. Yes you do. You can't achieve decent write performance without one - which needs a battery backed cache. If you don't have one, each write needs to physically hit the disc which is ruinous for performance.
Anyway, back to read performance, once you've got the machine with the same spec RAID controller (and same discs, obviously) as production in your lab, you can try to tune stuff up.
More RAM is usually the cheapest way of achieving better performance - make sure that you've got MySQL configured to use it - which means tuning storage-engine specific parameters.
I am assuming here that you have at least 100G of data; if not, just buy enough ram that your entire DB fits in ram then read performance is essentially solved.
Software changes that others have mentioned such as optimising queries and adding indexes are helpful too, but only once you've got a development hardware environment that enables you to usefully do performance work - i.e. measure performance of your application meaningfully - which means real hardware (not VMs), which is consistent with the hardware environment used in production.
Oh yes - one more thing - don't even THINK about deploying a database server on a 32-bit OS, it's a ruinous waste of good ram.
Indexing is done on the database tables in order to speed queries. If you don't know what it means you have none. At a minumum you should have indexes on every foriegn key and on most fileds that are used frequently in the where clauses of your queries. Primary keys should have indexes automatically assuming you set them up to begin with which I would find unlikely in someone who doesn't know what an index is. Are your tables normalized?
BTW, since you are doing a division in your math (why I haven't a clue), you should Google integer math. You may neot be getting correct results.
You should not select * ever. Instead, select only the data you need for that particular call. And what is your intention here?
order by votes*1000+((1440 - ($server_date - date))/60)2+visites600 desc
You may have poorly-written queries, and/or poorly written pages that run too many queries. Could you give us specific examples of queries you're using that are ran on a regular basis?
sure
this query to fetch the last 3 posts
select * from posts where visible = 1 and date > ($server_date - 86400) and dont_show_in_frontpage = 0 order by votes*1000+((1440 - ($server_date - date))/60)*2+visites*600 desc limit 3
what do you think?