I'm working with a programmer who doesn't want me touching his database...
I would like work with a database instead of hard coding my content but don't want the sites performance to suffer.
Is it bad practice to query two different databases on one page?
If its not a problem is there a limit to how many databases you can query per page?
PS the site is php/mysql
me touching his database
That's probably because there is a layered architecture in place and you're not supposed to be talking to the database directly.
Otherwise, if you've come already to the division - "my" database, "his" markup, it's a recipe for disaster.
Is it bad practice to query two different databases on one page?
No, if there is a real need to do it. Yes, if only because somebody declared the database their property and you've got to have your own.
No its not a problem, in some scenarios it's even a pretty good approach.
It depends on if the databases are holding related data. If they are related, it makes sense to keep them in once database. The programmer could then give you a user account with limited access so that you can't corrupt other things.
There is some cost to making a new connection, but it will likely be negligible if you are doing a number of queries.
Can you have a separate schema in his DB? If so, then you could save some connection building /destruction time.
Will you be storing data/relational data in the DB? If not, can you get away with include("file.php")
All that being said it's not a bad practice to have multiple DBs on a page you just need a good reason to do it.
i routinely hit a estimate database and a reference database aka customer live in texas, closest office is 150 miles away.
Related
I'm currently developping an application which allows doctors to dinamically generate invoices. The fact is, each doctors requires 6 differents database tables, and there could be like 50 doctors connected at the same time and working with the database (writing and reading) at the same time.
What I wanted to know is if the construction of my application fits. For each doctors, I create a personnal Sqlite3 database (all database are secure) which only him can connect to. I'll have like 200 Sqlite database, but is there any problems ? I thought it could be better than using a big MySQL database for everyone.
Is this solution viable ? Will I have problems to deal with ? I never did such an application with so many users, but I thought it could be the best solution
Firstly, to answer your question: no, you probably will not have any significant problems if a single sqlite database is used only by one person (user) at a time. If you highly value certain edge cases, like the ability to move some users/databases to another server, this might be a very good solution.
But it is not a terribly good design. The usual way is to have all data in the same database, and tables having a field which identifies which rows belong to which users. The application code is responsible for maintaining security (i.e. not to let users see data which doesn't belong to them), and indexes in the database (which you should use in all cases, even in your own design) are responsible for making it fast.
There are a large number of tutorials which could help you to make a better database design; a random google result is http://www.profsr.com/sql/sqless02.htm .
I see programmers putting a lot of information into databases that could otherwise be put in a file that holds arrays. Instead of arrays, they'll use many tables of SQL which, I believe, is slower.
CitrusDB has a table in the database called "holiday". This table consists of just one date column called "holiday_date" that holds dates that are holidays. The idea is to let the user add holidays to the table. Citrus and the programmers I work with at my workplace will prefer to put all this information in tables because it is "standard".
I don't see why this would be true unless you are allowing the user, through a user interface, to add holidays. I have a feeling there's something I'm missing.
Sometimes you want to design in a bit of flexibility to a product. What if your product is released in a different country with different holidays? Just tweak the table and everything will work fine. If it's hard coded into the application, or worse, hard coded in many different places through the application, you could be in a world of pain trying to get it to work in the new locale.
By using tables, there is also a single way of accessing this information, which probably makes the program more consistent, and easier to maintain.
Sometimes efficiency/speed is not the only motivation for a design. Maintainability, flexibility, etc are very important factors.
The main advantage I have found of storing 'configuration' in a database, rather than in a property file, or a file full of arrays, is that the database is usually centrally stored, whereas a server may often be split across a farm of several, or even hundreds of servers.
I have implemented, in a corporate environment, such a solution, and the power of being able to change configuration at a single point of access, knowing that it will immediately be propagated to all servers, without the concern of a deployment process is actually very powerful, and one that we have come to rely on quite heavily.
The actual dates of some holidays change every year. The flexibility to update the holidays with a query or with a script makes putting it in the database the easiest way. One could easily implement a script that updates the holidays each year for their country or region when it is stored in the database.
Theoretically, databases are designed and tuned to provide faster access to data than doing a disk read from a file. In practice, for small to mid-sized applications this difference is minuscule. Best practices, however, are typically oriented at larger scale. By implementing best practices on your small application, you create one that is capable of scaling up.
There is also the consideration of the accessibility of the data in terms of other aspects of the project. Where is most of the data in a web-based application? In the database. Thus, we try to keep ALL the data in the database, or as much as is feasible. That way, in the future, if you decide that now you need to join the holiday dates again a list of events (for example), all the data is in a single place. This segmenting of disparate layers creates tiers within your application. When each tier can be devoted to exclusive handling of the roles within its domain (database handles data, HTML handles presentation, etc), it is again easier to change or scale your application.
Last, when designing an application, one must consider the "hit by a bus principle". So you, Developer 'A', put the holidays in a PHP file. You know they are there, and when you work on the code it doesn't create a problem. Then.... you get hit by a bus. You're out of commission. Developer 'B' comes along, and now your boss wants the holiday dates changed - we don't get President's Day off any more. Um. Johnny Next Guy has no idea about your PHP file, so he has to dig. In this example, it sounds a little trivial, maybe a little silly, but again, we always design with scalability in mind. Even if you KNOW it isn't going to scale up. These standards make it easier for other developers to pick up where you left off, should you ever leave off.
The answer lays in many realms. I used to code my own software to read and write to my own flat-file database format. For small systems, with few fields, it may seem worth it. Once you learn SQL, you'll probably use it for even the smallest things.
File parsing is slow. String readers, comparing characters, looking for character sequences, all take time. SQL Databases do have files, but they are read and then cached, both more efficiently.
Updating & saving arrays require you to read all, rebuild all, write all, save all, then close the file.
Options: SQL has many built-in features to do many powerful things, from putting things in order to only returning x through y results.
Security
Synchronization - say you have the same page accessed twice at the same time. PHP will read from your flatfile, process, and write at the same time. They will overwrite each other, resulting in dataloss.
The amount of features SQL provides, the ease of access, the lack of things you need to code, and plenty other things contribute to why hard-coded arrays aren't as good.
The answer is it depends on what kind of lists you are dealing with. It seems that here, your list consists of a small, fixed set of values.
For many valid reasons, database administrators like having value tables for enumerated values. It helps with data integrity and for dealing wtih ETL, as two examples for why you want it.
At least in Java, for these kinds of short, fixed lists, I usually use Enums. In PHP, you can use what seems to be a good way of doing enums in PHP.
The benefit of doing this is the value is an in-memory lookup, but you can still get data integrity that DBAs care about.
If you need to find a single piece of information out of 10, reading a file vs. querying a database may not give a serious advantage either way. Reading a single piece of data from hundreds or thousands, etc, has a serious advantage when you read from a database. Rather than load a file of some size and read all the contents, taking time and memory, querying from the database is quick and returns exactly what you query for. It's similar to writing data to a database vs text files - the insert into the database includes only what you are adding. Writing a file means reading the entire contents and writing them all back out again.
If you know you're dealing with very small numbers of values, and you know that requirement will never change, put data into files and read them. If you're not 100% sure about it, don't shoot yourself in the foot. Work with a database and you're probably going to be future proof.
This is a big question. The short answer would be, never store 'data' in a file.
First you have to deal with read/write file permission issues, which introduces security risk.
Second, you should always plan on an application growing. When the 'holiday' array becomes very large, or needs to be expanded to include holiday types, your going to wish it was in the DB.
I can see other answers rolling in, so I'll leave it at that.
Generally, application data should be stored in some kind of storage (not flat files).
Configuration/settings can be stored in a KVP storage (such as Redis) then access it via REST API.
I am writing a PHP application in ZF. Customers will use it to sell their products to final customers. Customers will host their application on my server or they could use their own. Most of them will host this application on my server.
I could design one database for all customers at once, so every customer will use the same database, but of course products etc. will be assigned to particular customer. Trivial.
I could use separate database for every customer, so the database structure will be simpler. I will then probably use separate subdomains and maybe even file location, but that is just a detail.
Which solution will have better performance and how big will be the difference? Which one would you choose?
I would use a separate database for each customer. It makes backup and scaling easier. If you ever get a large customer that needs some custom changes to the schema, you can do it easily.
If one customer needs you to restore their data, with a single database it is trivial. On a shared db, much harder.
And that if large customer ever gets a lot of traffic, you can easily put them on another server with minimal changes.
If one site gets compromised, you don't have all of teh data for everyone in one place, the damage is mitigated to just the site that was hacked.
I'd definitely recommend going with 1 db per customer if possible.
Personally, I would go with multiple databases - i.e. a database for each client.
As I understand it all your clients will be using just an instance of your application so these instances should have their own databases.
If you go with a single database, you are creating a great potential security risk. One client compromising the login details to the db server would automatically compromise data of all your clients.
Also a single security vulnerability (a SQL injection attack) could destroy data of all clients (with multiple dbs you could still have time to fix the security hole and release a patch before all other sites are attacked).
You don't want to have an army of 1000000 mad clients instead of just 1 angry client.
Multiple databases also give you a greater possibility of load balancing (you can have the dbs spread across more servers).
Performance wise you're basically start with a 'sharding' approach. Because of this, the sharding performance strategy will be piece of cake.
The downside is that you could argue you're losing some (undefined) bit of overhead in the duplication.
One pitfall is that you might not notice performance issues in major components as quickly. This is because they are so scattered, so they might not be visible on your radar. Load testing is the way to get ahead of this.
To some extent this is a question of personal opinion. There are pros and cons of both models.
Personally, and because of the "they could use their own" comment, I would go with a seperate database per customer. This gives you
The ability to move customer data around when necessary. For example moving a single customer onto a different servers/setups depending on things like load.
If something goes wrong you only impact one customer and not everybody.
You can spread DB load across multiple DB servers if necessary.
If a customer comes to you with a specific requirement you can more easily cater for this without impact other customers.
From a performance perspective, to be honest I don't think there is any real performace gain in either model. That said this does of course depend on the structure of your DB and the hardware it runs on.
Don't choose multiple databases solution, if your needs can be fulfilled with one database. Because multiple databases will lead to big burden in long run, and your system will become highly complicated and unmanageable as you grow.
Using proper relationship you can go long way
A Client model can have many Products // why multiple databases?
Performance can achieved in either ways, just going multiple dbs will NOT benefit in that direction
I have a pretty large social network type site I have working on for about 2 years (high traffic and 100's of files) I have been experimenting for the last couple years with tweaking things for max performance for the traffic and I have learned a lot. Now I have a huge task, I am planning to completely re-code my social network so I am re-designing mysql DB's and everything.
Below is a photo I made up of a couple mysql tables that I have a question about. I currently have the login table which is used in the login process, once a user is logged into the site they very rarely need to hit the table again unless editing a email or password. I then have a user table which is basicly the users settings and profile data for the site. This is where I have questions, should it be better performance to split the user table into smaller tables? For example if you view the user table you will see several fields that I have marked as "setting_" should I just create a seperate setting table? I also have fields marked with "count" which could be total count of comments, photo's, friends, mail messages, etc. So should I create another table to store just the total count of things?
The reason I have them all on 1 table now is because I was thinking maybe it would be better if I could cut down on mysql queries, instead of hitting 3 tables to get information on every page load I could hit 1.
Sorry if this is confusing, and thanks for any tips.
alt text http://img2.pict.com/b0/57/63/2281110/0/800/dbtable.jpg
As long as you don't SELECT * FROM your tables, having 2 or 100 fields won't affect performance.
Just SELECT only the fields you're going to use and you'll be fine with your current structure.
should I just create a seperate setting table?
So should I create another table to store just the total count of things?
There is not a single correct answer for this, it depends on how your application is doing.
What you can do is to measure and extrapolate the results in a dev environment.
In one hand, using a separate table will save you some space and the code will be easier to modify.
In the other hand you may lose some performance ( and you already think ) by having to join information from different tables.
About the count I think it's fine to have it there, although it is always said that is better to calculate this kind of stuff, I don't think for this situation it hurt you at all.
But again, the only way to know what's better your you and your specific app, is to measuring, profiling and find out what's the benefit of doing so. Probably you would only gain 2% of improvement.
You'll need to compare performance testing results between the following:
Leaving it alone
Breaking it up into two tables
Using different queries to retrieve the login data and profile data (if you're not doing this already) with all the data in the same table
Also, you could implement some kind of caching strategy on the profile data if the usage data suggests this would be advantageous.
You should consider putting the counter-columns and frequently updated timestamps in its own table --- every time you bump them the entire row is written.
I wouldn't consider your user table terrible large in number of columns, just my opinion. I also wouldn't break that table into multiple tables unless you can find a case for removal of redundancy. Perhaps you have a lot of users who have the same settings, that would be a case for breaking the table out.
Should take into account the average size of a single row, in order to find out if the retrieval is expensive. Also, should try to use indexes as while looking for data...
The most important thing is to design properly, not just to split because "it looks large". Maybe the IP or IPs could go somewhere else... depends on the data saved there.
Also, as the socialnetworksite using this data also handles auth and autorization processes (guess so), the separation between login and user tables should offer a good performance, 'cause the data on login is "short enough", while the access to the profile could be done only once, inmediately after the successful login. Just do the right tricks to improve DB performance and it's done.
(Remember to visualize tables as entities, name them as an entity, not as a collection of them)
Two things you will want to consider when deciding whether or not you want to break up a single table into multiple tables is:
MySQL likes small, consistent datasets. If you can structure your tables so that they have fixed row lengths that will help performance at the potential cost of disk space. One thing that from what I can tell is common is taking fixed length data and putting it in its own table while the variable length data will go somewhere else.
Joins are in most cases less performant than not joining. If the data currently in your table will normally be accessed all at the same time then it may not be worth splitting it up as you will be slowing down both inserts and quite potentially reads. However, if there is some data in that table that does not get accessed as often then that would be a good candidate for moving out of the table for performance reasons.
I can't find a resource online to substantiate this next statement but I do recall in a MySQL Performance talk given by Jay Pipes that he said the MySQL optimizer has issues once you get more than 8 joins in a single query (MySQL 5.0.*). I am not sure how accurate that magic number is but regardless joins will usually take longer than queries out of a single table.
Okay, so I'm sure plenty of you have built crazy database intensive pages...
I am building a page that I'd like to pull all sorts of unrelated database information from. Here are some sample different queries for this one page:
article content and info
IF the author is a registered user, their info
UPDATE the article's view counter
retrieve comments on the article
retrieve information for the authors of the comments
if the reader of the article is signed in, query for info on them
etc...
I know these are basically going to be pretty lightning quick, and that I could combine some; but I wanted to make sure that this isn't abnormal?
How many fairly normal and un-heavy queries would you limit yourself to on a page?
As many as needed, but not more.
Really: don't worry about optimization (right now). Build it first, measure performance second, and IFF there is a performance problem somewhere, then start with optimization.
Otherwise, you risk spending a lot of time on optimizing something that doesn't need optimization.
I've had pages with 50 queries on them without a problem. A fast query to a non-large (ie, fits in main memory) table can happen in 1 millisecond or less, so you can do quite a few of those.
If a page loads in less than 200 ms, you will have a snappy site. A big chunk of that is being used by latency between your server and the browser, so I like to aim for < 100ms of time spent on the server. Do as many queries as you want in that time period.
The big bottleneck is probably going to be the amount of time you have to spend on the project, so optimize for that first :) Optimize the code later, if you have to. That being said, if you are going to write any code related to this problem, write something that makes it obvious how long your queries are taking. That way you can at least find out you have a problem.
I don't think there is any one correct answer to this. I'd say as long as the queries are fast, and the page follows a logical flow, there shouldn't be any arbitrary cap imposed on them. I've seen pages fly with a dozen queries, and I've seen them crawl with one.
Every query requires a round-trip to your database server, so the cost of many queries grows larger with the latency to it.
If it runs on the same host there will still be a slight speed penalty, not only because a socket is between your application but also because the server has to parse your query, build the response, check access and whatever else overhead you got with SQL servers.
So in general it's better to have less queries.
You should try to do as much as possible in SQL, though: don't get stuff as input for some algorithm in your client language when the same algorithm could be implemented without hassle in SQL itself. This will not only reduce the number of your queries but also help a great deal in selecting only the rows you need.
Piskvor's answer still applies in any case.
Wordpress, for instance, can pull up to 30 queries a page. There are several things you can use to stop MySQL pull down - one of them being memchache - but right now and, as you say, if it will be straightforward just make sure all data you pull is properly indexed in MySQL and don't worry much about the number of queries.
If you're using a Framework (CodeIgniter for example) you can generally pull data for the page creation times and check whats pulling your site down.
As other have said, there is no single number. Whenever possible please use SQL for what it was built for and retrieve sets of data together.
Generally an indication that you may be doing something wrong is when you have a SQL inside a loop.
When possible Use joins to retrieve data that belongs together versus sending several statements.
Always try to make sure your statements retrieve exactly what you need with no extra fields/rows.
If you need the queries, you should just use them.
What I always try to do, is to have them executed all at once at the same place, so that there is no need for different parts (if they're separated...) of the page to make database connections. I figure it´s more efficient to store everything in variables than have every part of a page connect to the database.
In my experience, it is better to make two queries and post-process the results than to make one that takes ten times longer to run that you don't have to post-process. That said, it is also better to not repeat queries if you already have the result, and there are many different ways this can be achieved.
But all of that is oriented around performance optimization. So unless you really know what you're doing (hint: most people in this situation don't), just make the queries you need for the data you need and refactor it later.
I think that you should be limiting yourself to as few queries as possible. Try and combine queries to mutlitask and save time.
Premature optimisation is a problem like people have mentioned before, but that's where you're crapping up your code to make it run 'fast'. But people take this 'maxim' too far.
If you want to design with scalability in mind, just make sure whatever you do to load data is sufficiently abstracted and calls are centralized, this will make it easier when you need to implement a shared memory cache, as you'll only have to change a few things in a few places.