In the previous post I outlined the system’s specs and use cases. We also selected the primary use case we should start from – that is filtering screen.

The complexity with DB design here is that we want maximum flexibility on the one hand and we don’t want to lose much in performance on the other hand.
Let’s recap what data about student we should store:

1. Phone
2. Password
3. Email
4. ICQ
5. Name
6. Surname
7. Patronymic
8. Gender
9. Birthday
10. Faculty
11. Course
12. Group
13. Clubs
14. Tags
15. OK to send SMS (true/false)

Items 1-9 and #15 are scalar values and can be easily stored in User table as fields of the correspondent type. While Faculty, Course, Group and Clubs are either N-M (Clubs) or 1-N relations. So obvious way to handle them is to create tables and cross-table for N-M relation. Tags can be also represented as N-M relation.
It seems OK until we don’t want to extend the system by adding some more fields. But even without extensibility in mind, we should create 3 separate tables (for courses, faculties and clubs). However if we look closer at these, we’ll see that all of them are kind of groups and we can create a kind of hierarchy:

• University
  • Faculty
    • Course
      • Group
  • Club
    • Section

So we can consider everything to be group. With this approach we also store information about relations between these groups.
With such approach we can add more types of groups in the future if needed. Or this solution can be ported to another domain model (e.g. school or business organization) without changes in the structure. We should only define, which groups are required for user. In this case Faculty, course and group are required. However, knowing the group, we can get both course and faculty. But I’m not sure if that is a good idea because this way we’ll have to make several queries to the DB in order to get faculty instead of one.
Here’s the DB scheme we came up with:

Database design

Filtering it

Let’s try to compose some simple queries to test if our DB can cope with them.

1. Let’s get all male users who’re elder than 18:
   1. SELECT * FROM User WHERE gender=‘male’ AND birthday <= ’1992-03-19 23:59:59′

   Date for the birthday is set to the 18 years back from now. Everyone who was born before or on 19 of March 1992 will fall into the condition. And gender is obvious.

2. Let’s try to get all male that have first names starting with ‘K’ and who study on the first or second course:
   1. SELECT u.* FROM User u INNER JOIN UserGroup ug ON u.userID=ug.userID WHERE u.gender=‘male’ AND u.name LIKE ‘K%’ AND ug.groupID IN (5,6)

   Suppose that in Group table we have groups for the first course and second course and they have Ids 5 and 6 respectively.

3. Let’s try to search for all who is on the 3rd course and is also in Geeks’ Club:
   1. SELECT u.* FROM User u INNER JOIN UserGroup ug ON u.userID=ug.userID WHERE ug.groupID IN (7, 15)

   7 is ID of the group “3rd course” and 15 is ID of the group “Geeks’ Club”.
   We have the problem with the last query It will find all users who either studies on the 3rd course or attends Geeks’ Club. However we need 3rd course and Geeks’ club.
   There are two possible solutions here. One is SQL-based, another is PHP-based.

   1. 1.SQL-based:
      1. SELECT * FROM User WHERE userID IN (SELECT userID FROM UserGroup WHERE userID IN(SELECT userID FROM UserGroup WHERE groupID=15) AND groupID=7)

      Here we select users who have group=15. Then from these users we select the ones who have group=7 as well, and finally we select user records that correspond the userIDs found.
      I think, the variant with INNER JOIN is also possible here (at least, joining results of the groups filtering instead of sub-querying). It just takes some time to figure it out and it has to deal more with optimization than with the principle of filtering.
      Anyway, the more groups we have here, the more complex this query becomes.
      UPDATE: Here I’ve been advised to use the following query which is more simple and efficient:

      1. SELECT
      2.   u.*
      3. FROM
      4.   USER u
      5. INNER JOIN
      6.   UserGroup ug1
      7. ON
      8.   u.id = ug1.userID AND ug1.groupID=7
      9. INNER JOIN
      10.   UserGroup ug2
      11. ON
      12.   u.id = ug2.userID AND ug2.groupID=15

      I think this is the best way of making such queries. Great thanks to ScallioXTX

   2. PHP-based. Basically, the principle is the same:
      1. $group7 = getUsersForGroup(7);
      2. $group15 = getUsersForGroup(15);
      3. $userIDs = array_intersect($group7, $group15);
      4. $users = getUsersByIDs($userIDs);

      getUsersForGroup actually executes the query:

      1. SELECT userID FROM UserGroup WHERE groupID=[GROUP]

      getUsersByID executes the following query:

      1. SELECT * FROM User WHERE userID IN ([ids])

      array_intersect is a PHP function that returns the values present in all given arrays, returns the intersection of sets.
      For example, if we give it 3 arrays:
      (1, 5, 8, 15)
      (5, 8, 15, 19)
      (1, 5, 15, 25)
      it will return (5, 15).
      In this case we execute several little queries instead of one big. In MySQL this often gives benefits in performance.

So that’s our filtering approach.

There is one thing to add here. If we have group #1 and #2 and group#2 is a child of #1. And user selected to filter users which are both in #1 and #2, then we should perform a little optimization and search only for #2 because that will be the correct answer to the query. This situation is stupid, but we should act smart even in a stupid queries

Maybe there are better solutions. We’re open to them! Moreover, we realize that there are more experienced developers that already solved such problem. Help us

Tomorrow we have a meeting where we’ll be discussing the architecture, classes etc. I’ll upload our results on the weekends or early next week. This depends on the amount of work done during the meeting.
Stay tuned! Subscribe to my blog’s RSS, share your opinions/suggestions in comments and don’t miss the next post in this series!

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In November 2008 I’ve got a nice project, that resulted in a complex search engine, that specializes in clothing. I can’t give the link now, but will do when site officially launches. Key features of such service are:

• Large number of users, which search with various parameters, rate items, leave comments, create articles etc.
• Large database, that is updated frequently

Sure, the site is running on a dedicated server, sure I use caching, but optimal DB is a key to success.

MyISAM or InnoDB?

Since we need reliability, I created different tests, search the internet etc. My main question was – what to use MyISAM or InnoDB? I found the post on the MySQL Perfomance Blog (also this and this) and came to the conclusion, that when SELECT’ing, InnoDB is definitely faster (or, at least, is not slower). In addition, it provides constraints mechanism and allows transactions. The only thing it doesn’t have is FULLTEXT search. One more disadvantage is slower inserts. However, 80% of DB usage in this project are SELECT queries without FULLTEXT. For the fulltext search I created MyISAM table with fields I need and it works fine. The project is finished, but there will be phase 2 and I’m thinking of introducing Sphinx there. Anybody has experience with it?
So I came up with InnoDB storage engine.

Optimizing structure

Next important step is DB structure. I’ll give some background info about the project so you could better understand what I’m talking about. The site collects info from different UK shops. Then users can rate them, add some tags, create articles (called “looks”) and link that articles to the products they’re writing about. And the same (tags, comments, rating) applies to the looks. Here we come across with an interesting question. We can create structure of different types for this:

• Create 2 separate cross-tables for linking Rating to Look or Product
• Create one cross-table and add additional field “type” there to differentiate between Product and Look entities

See both variants in the following images:

Normalized variant

Denormalized version

• If there are 0-2 ratings linked to entity, then normalized variant is better
• If there are 3-5 ratings linked to entity, then denormalized variant is slightly (less than 1%) better
• If there are 6-8 ratings linked to the entity, the normalized variant wins again

I did these tests for different situations similar to this one, in each test I generated random records and randomly linked them with each other. Number of record in Product, Look tables was 10000, in Rating – 20000. Number of records in cross tables varies because the linkings are random.
So I came up with normalizing everything like it should be done according to the DB theory.

The only exclusion of this rule is the following situation. In this project you can add different alternatives to the product. Each alternative is “better” or “cheaper” or “different” etc. And since the only case when these alternatives are pulled from DB is when user views the product, they are pulled altogether, so it is better to keep them in the same table.

Conclusion

• InnoDB turns out to behave better under the high load, it supports transactions and maintains constraints. All that helps to develop better and never leave orphan records.
• Using normalization techniques you usually get better performance
• Create tests and test everything if you are going to do something great

Further reading

• Database Normalization
• MySQL Performance Blog

P.S. I’m looking forward to see your comments on implementation techniques in the high-loaded websites, your thoughts about the InnoDB vs MyISAM question and anything else you can think of

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Yes, really it matters. Each call starts after the previous one ends and it takes long to finish them all. But each web application handles the concurrent requests by nature. So I started a forum thread to clarify this. And sebas recommended me to use CDbHttpSession instead of standard one. Yes, I knew, that storing sessions in DB speeds up the application, but I thought that is because of more effective search. And it turns out, that besides more effective search it gives one more DB benefit – concurrent access to the session storage. That’s actually the reason #1 why we usually use databases instead of files
So here is a quick trick, that solves the problem:

It creates a new table YiiSession and uses it for session data. This time the JS test above runs much faster. Try it yourself!

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Nearly every large application has some configuration parameters – site admin email, cache time for different blocks, number of latest news, number of items per search or catalogue page etc.

Standard Way

Yii comes with the built-in mechanism for this. You can create a file with an associative array of all your variables, like this:

Then put it somewhere, for example in /protected/config/params.php and configure your application to use it:

Usage is simple, just refer to it as to array:

This is quite convenient when you just want to save some constants. End-user will not be able to change this from admin in any way. Sure, you can create the interface for editing this config and update the file, but much more flexible way is to store the configuration in DB.

The Database Way

To make the life easier, I’ve created an extension, that can be used as an application component. Extension can be downloaded from the Yii extension page. Here I’ll give an overview of it’s work.

First thing to note, it implements IApplicationComponent, so it should implement init() method where initialization is performed. In this method we check if there are any parameters to load. If so – we try to load them. If there is an exception, it means, that no table is present, so we create it and initialize the parameters that should be preloaded with null values

If parameter is requested, in the __get() method we reuse the parent’s (CAttributesCollection) contains() method, which checks if we have this parameter in the collection already. If so – we simply return it. If not – we call the loadParam() method, it loads if from DB and adds to the component collection. If there is no attribute, it throws an exception. We catch it in the __get() and call the parent::__get(). Here is the code:

Setter method simply updates the collection. We check if the parameter is already present in DB. If so – we update it. If not – we create it. And, if everything was OK, we add the parameter to the internal collection ($this->add($name,$value)):

When configuring the extension or using load() or purge() method, we can specify parameters either as array or as comma-separated string. This is achieved by the preprocessing method, which also converts parameter names to lowercase and they are case insensitive (if this is required by the caseSensitive property, it must be set to true). Here is it:

And, finally, load and purge methods:

Usage Instructions

Using the extension is simple. Like any extension, you should unzip it to the /protected/extensions/ folder and then set it up as an application component. To do this, you should add it with any name to the components array in the application configuration:

‘par’ is the ID of the component, you will refer to it in any place of the application by it’s ID:

That’s it! Enjoy!

UPDATE: Updated on March, 5 2009 according to the Jonah’s comments an this discussion. Version 3 is planned with great functionality

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In December I’ve got a project, that required sophisticated and quite complex DB and that DB was subject to change greatly during first development phase. Before that project I was using Sparx Enterprise Architect both for application design and DB design. But, frankly speaking, it’s not good at databases, especially MySQL. So I decided to pick up a new DB modelling tool.

Requirements

My requirements to it were:

• Convenient entering of the attributes and their types. When I have an idea, I want it to be recorded fast, I don’t want to spend time clicking different “add” and “save” buttons in order to enter table attributes
• Full MySQL features (including all types of indexes) and main storage engines support (MyISAM, InnoDB, MEMORY)
• Visual tables layout like in MS Access
• Maintaining table joins and involved indexes, visual creation of table connections
• SQL export
• Free!

On the way to perfection…

I went through this list and installed and tried around 10 different tools and I didn’t like any of them. One has no visual modelling, other has inconvenient input, third has both, but doesn’t support a number of MySQL features. So finally I ended up with MySQL Workbench. It gives me all I need and even more.

Yes! It’s really perfect

Here you may find a list of features together with versions comparison. You can read it yourself and I want to describe why I liked it:

Nice design

Yes, it matters. When you use Windows95-like program, you can’t feel as good as if you’re using excellent-designed one. Here is a screen:

Model Overview

Creating DB

I liked their “schema approach”. When you create DB, you set the schema default encoding and all the tables in DB are automatically created in this encoding. Sure, you can change it for each table, but this is very helpful. I’ve also set up mydefault storage engine – InnoDB (MyISAM is default). This setting can be found in a seconds; everything is in it’s place (Tools -> Options -> MySQL).
So now I can create my table without remembering that I should change some settings each time I create new table. That’s my first requirement.

Creating tables

I liked their template approach to the generic field names. Near every table has ID field. In my name conventions (since I’m using Yii framework, I follow their), ID field name is [tableName]ID. So I go to the Tools -> Options -> Model and set there:

• Primary key pattern – %table%ID
• Primary key default type – INT(11)
• Foreign key defaults (since I’m using InnoDB, which takes care of data integrity, I set this. I’ll tell more about this in my future posts about MySQL&InnoDB)

Three little settings, but it makes my life much more simple! Actually, you can set up the naming of the auto-generated index fields, but I don’t use it, I create all tables I need myself. However, Workbench can create cross table for Many-to-Many relation for you.
Now I create the table (collation and engine are set automatically), go to the “fields” tab (tabs are in the bottom – I had problems finding them first time) and have my ID field created. Unfortunately, I can’t say that I want first letter in lower-case, so I correct it manually. Then start adding fields. It is very simple. First you double click on the empty row where should one name of the field, enter your name, press TAB, enter the field type (I usually enter 1-3 letters and press “Down” key, it selects correct type), press TAB again and you’re on the next field! So you just keep populating your attributes really fast! Then just tick NN (not null) and AI (auto increment) checkboxes and your table scheme is done. All indexes are set up on the next tab – Indexes except PRIMARY KEY. ID field is PRIMARY KEY by default. To add more fields there, select field and tick PRIMARY KEY checkbox in the right part of the tab.

Visual layout

Consider we created tables we need, now we advance to the scheme and connections. Double click “Add Diagram” in the top of the screen and you’re there. In the centre of the right pane you have tables you created. If you drag table from that list to your diagram, you’ll see big dot near it’s name. That’s also very convenient when you have a number of tables. Sure, here you can snap to grid, show/hide it, but that’s not so impressive.

Visual grouping

And this feature is mega-great! When you have huge DB, you can group tables using coloured layers:

ER Diagram with coloured layers for grouping

Visual connections

Yes, it allows you to connect tables like you want. 1-1,1-N and N-M relations. If you prefer to create foreign keys automatically, yo can use these types of joins. I prefer to create all tables and fields and then connect it. So I click on the last icon in the left toolbar, select foreign key, then click “Pick referenced columns” and finally select the primary key I link to. I’m done. All InnoDB connections are automatically created.

Creating relationship using existing columns

SQL export

Sure, SQL export is not new or impressive feature, but MySQL Workbench allows you not only to create SQL for the scheme, but also to create ALTER DB script for the CREATE DB script already created. For example, you designed a great DB, exported to SQL query, installed on server and then your client wants changes. You open MySQL Workbench project, make necessary changes and then create ALTER script. Very convenient thing

Integration with Yii

One clever guy (unikly) created the Yii shell command, that allows to use mwb file instead of DB connection when creating Yii DB models. This command is available on the Yii extensions page. As for me, it’s a very big plus.

A fly in the ointment

I’ve noticed several bad things in this software:

• When DB becomes huge, you need a good machine to work with it comfortably. It takes too much resources
• Some interface elements are not evident (In the DB overview screen lowest part has tabs both on the top and on the bottom. Top tabs – switch between tables, bottom tabs – switch between table’s sections (properties, fields, indexes)
• When creating joins, it doesn’t maintain the uniqueness of foreign indexes names. Take a close look at the export script (and watch for constraints and auto-created foreign keys) when it fails in phpMyAdmin (or other tool)

Disclaimer: Screenshots are taken from MySQL Workbench site, I was lazy to take my own ones.

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