Why database should be taught before programming in universities

Learn Database before Coding

Often students from initial semester ask me how do we store our data in our programming project? When students join university to learn about computer science and technology they are usually taught programming first in courses like introduction to programming. As part of coursework students are required to work on a project. Majority of the projects, in fact almost all projects involve data handling and that data needs to be stored somewhere.

Problem students face

As a novice students don’t know how to store data. One option is to store data in plain text files if filing is taught to them but in that case their project becomes too complex for them. In my opinion, file formats is an advanced topic for students that have just started learning how to program. So, students get stuck where and how to store data. They create variables and arrays to store data in memory but that is not very useful until they have option to store their data somewhere permanently that they can retrieve later. Otherwise, every time they run their project they have to feed data from the beginning.

Teach Database before Programming

If universities modify their courses and add database in first semester and replace programming course with it then it would be easier for students to get started in computer science degree. Introduction to database is relatively easier course then programming and students will know what is database, how to store data in database, and how to retrieve it later using SQL. Then in next semester if they do a programming course then it will require only one lecture to teach them how to access database from your code and how to store and retrieve data. That will not only make their projects more valuable but will make more sense to them and they can take it to advance level in forthcoming courses.

Your Take?

What is your opinion? Please, let me know in the comments.

MySQL Installation and Configuration

Since I have been involved with MySQL development for last several years, so I constantly look for good resources related to MySQL. I found a very good article on this at IIS site (http://learn.iis.net/page.aspx/610/walkthrough—set-up-mysql-51-for-php-applications/). I thought I should refer that to my blog. I am providing whole article as it is here.

Overview

This article provides a basic step by step guide on how to install and configure MySQL on the Windows Operating System. For more detailed instructions about installing and configuring MySQL on Windows refer to the official MySQL documentation.

Downloading and Installing MySQL

The MySQL binaries and installer can be downloaded from the official MySQL site. The instructions in this article are based on MySQL version 5.1 Community Edition installed with the Windows MSI installer.

Run the installer and choose the installation option. For a majority of the cases, the typical installation is sufficient:

However, if you want to control which components get installed or if you want to use a non-default installation path then choose the “Custom” option.

When the installation is complete, make sure to check the box to “Configure the MySQL Server now”. This will launch the “MySQL Server Instance Configuration Wizard” that will guide you through the configuration process for the MySQL instance.

Configuring MySQL instance

Follow these steps in the “MySQL Server Instance Configuration Wizard” to optimize the MySQL configuration for the kind of tasks you expect it to perform.

On the first page of the wizard choose “Detailed Configuration”:

On the next page choose the server type option:

Choose the “Database Usage” option:

The Database usage options control what kind of database storage engine is used on the server:

  • MyISAM – Optimized for high performance SELECT operations. It has low overhead in terms of memory usage and disk utilization, but at the cost of not supporting transactions
  • InnoDB – Provides fully ACID transactional capabilities, but at the cost of more aggressive usage of disk space and memory

For an in-depth comparison of these database engines, refer to MySQL Storage Engine Architecture. As a general recommendation – if the web applications on your server require multi-statement transactions, advanced isolation levels and row-level locking, foreign key constraints, or otherwise have a requirement for ACID features — use InnoDB. Otherwise, use MyISAM.

Next choose the number of concurrent connections to the server:

On the next page choose networking options :

If you have mysql and web server on the same machine you may consider not enabling TCP/IP networking and instead use named pipes. Note though that some PHP applications may require TCP connection to MySQL. Refer to the application’s documentation to confirm if it supports named pipes connection to MySQL.

Choose the default charset to use when creating new databases:

Next ensure that MySQL will be configured as a Windows Service:

Optionally, you can add the MySQL Bin directory to the Windows PATH environment variable. That will make it easier to launch MySQL tools from the command line.

Finally provide the password for the database administrative account, which in called “root” in MySQL. Make sure that you leave the “Create an Anonymous Account” checkbox cleared:

On the next page click “Execute” to apply all the configuration settings and to start the MySQL service:

Now you can logon to MySQL by opening a command line window and typing:

mysql -u root -p
Enter password: ******If MySQL was configured correctly then the MySQL prompt will be shown:

Welcome to the MySQL monitor. Commands end with ; or \g.
Your MySQL connection id is 3
Server Version 5.1.32-community MySQL Community Server (GPL)
Type ‘help;’ or ‘\h’ for help. Type ‘\c’ to clear the buffer.
mysql>

MySQL Query Cache

MySQL query cache is good to cache select queries and their results and improve some performance of your database applications. So I thought I should write a quick tutorial to quickly set up the query cache without going into the details. So here what you have to do to enable query cache on MySQL.

If you want to enable query cache without restarting the MySQL server then just run the following command on MySQL prompt/client:

set global query_cache_size=67108864;


This will set MySQL query cache size to around 64MB and also enable the query cache. You can set it to any value you desire. You can then check the status later by running following commands on MySQL prompt/client:

SHOW VARIABLES LIKE ‘%query_cache%’;

SHOW STATUS LIKE ‘%qcache%’;


These commands will show some useful information about the query cache like if query cache is enabled, how much memory is being used, how many queries are currently in cache, cache hit rate etc.

This is really a quick way to enable query cache. For details see MySQL documentation http://dev.mysql.com/tech-resources/articles/mysql-query-cache.html

Multiple MySQL on single host

Sometimes we need to run multiple MySQL servers on single machine. That is mostly required in testing environments to test different aspects with different configurations. In this way one can test server without affecting others. So, if you want to run multiple MySQL you can use MySQL Sandbox which eases the whole process of installing and configuring the server. Here how will you do it.

First of all you need to install MySQL Sandbox. You can download it from https://launchpad.net/mysql-sandbox.

Then you need tar balls of MySQL server. You can download it from MySQL site.

After installing MySQL Sandbox you can run following script to install MySQL.

make_sandbox /path/to/mysql-X.X.XX-osinfo.tar.gz

This script will tell you some information like port, user name, and password which you can use to login to MySQL after installation. After confirmation it will install and run MySQL. That’s it! You are up and running.

If you want to install another MySQL you can just run the following command.

make_sandbox /path/to/mysql-X.X.XX-osinfo.tar.gz –check_port

The –check_port option checks the first available port so it can install and run on that port. By default it will use the MySQL version as port. For example if you have MySQL version 4.1.20 it will run MySQL on port 4120. And if it is not available then it will try 4121.

MySQL Sandbox provides other useful scripts to manage the server. So installing and running multiple MySQL, even different versions, is that easy 🙂

You can find the complete documentation at http://forge.mysql.com/wiki/MySQL_Sandbox#Single_server_sandbox.

Breaking problem into code

Let us consider an example. If you have two boxes say BoxA and BoxB, and there are few balls of different colors, let’s say 5 balls (red, blue, green, yellow, and white) in BoxA, and you want to move one ball, say red ball from BoxA to BoxB. What will be the steps? If you can make a flow chart of it then its good, but if you find it difficult to make a flow chart of it then you need to do some hard work to become a programmer.

I asked this to someone and guess how he solved it. Here is his solution. Take out all balls from BoxA, then pick the red ball, put it in BoxB, and then put all remaining balls back in BoxA.

Fine! it worked. But why would you take out all balls if you can only take out red ball and move it to next box?

Let’s move this to programming side. In the above mentioned scenario we will have two database tables, boxes, and balls. boxes will have boxid as PK, name, and other details. Keep it simple so we don’t get lost in other details. balls table has ballid as PK, name, boxid as FK, and other details. boxes table has two records with 1 and BoxA as its boxid and name. balls table will have 5 records with id between 1 to 5 and red, blue, green, yellow, and white as their names, and all balls will have 1 in boxid field which is FK to boxes table.

Now if we adopt the first solution then it will run following queries (these are pseudo queries not actual SQL queries):

– select all balls where boxid=1 (so we can have a list of all balls before deleting them from database)
– delete from balls where boxid=1
– insert into balls values ballid=1, name=red ball, boxid=2
– insert into balls values
(ballid=2, name=blue ball, boxid=1)
(ballid=3, name=green ball, boxid=1)
(ballid=4, name=yellow ball, boxid=1)
(ballid=5, name=white ball, boxid=1)

Or even worse if we use multiple insert queries. It will run from 4 to 7 queries.

Now let’s see what happens if we just perform operation on the red ball and don’t touch other balls.

– update balls set boxid=2 where ballid=1; /* ball with id 1 is the red ball */

Wow, just one query and we’re done! We saved 3 to 6 queries. Imagine this scenario for a high traffic website or any other application, we can improve the performance with a big difference by just implementing correct logic to solve a problem.

Database indexes and locks

I was discussing with my friend on the issue I have discussed in my post Referential Integrity (http://mjawaid.wordpress.com/2009/04/01/referential-integrity/) and Mapping tables (http://mjawaid.wordpress.com/2009/04/02/mapping-tables/). My friend told me the scenario that when we create multiple indexes on the table we will get deadlocks. The reason he told me was the bucket lock, or in other words gap lock. Actually what server does is that due to multiple indexes when you lock any one record it locks multiple records, since it searches indexes and all the records it encounters during search, it locks them. That what I understood he was trying to say. I wasn’t convinced and thought of trying to create few tables with indexes and test them. For test I used MySQL4 and InnoDB engine, since the issue we were facing was on it.

So I created five tables indxtest1, indxtest2, indxtest3, indxtest4, and indxtest5.

CREATE TABLE `indxtest1` (

`id` bigint(20) NOT NULL auto_increment,

`name` varchar(255) default NULL,

`fk` bigint(20) default NULL,

PRIMARY KEY (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=latin1 CHECKSUM=1 DELAY_KEY_WRITE=1 ROW_FORMAT=DYNAMIC

CREATE TABLE `indxtest2` (

`id` bigint(20) NOT NULL auto_increment,

`name` varchar(255) default NULL,

`fk` bigint(20) default NULL,

PRIMARY KEY (`id`),

KEY `NewIndex1` (`fk`)

) ENGINE=InnoDB DEFAULT CHARSET=latin1 CHECKSUM=1 DELAY_KEY_WRITE=1 ROW_FORMAT=DYNAMIC

CREATE TABLE `indxtest3` (

`id` bigint(20) NOT NULL auto_increment,

`name` varchar(255) default NULL,

`fk` bigint(20) default NULL,

PRIMARY KEY (`id`),

KEY `NewIndex1` (`id`,`fk`)

) ENGINE=InnoDB DEFAULT CHARSET=latin1 CHECKSUM=1 DELAY_KEY_WRITE=1 ROW_FORMAT=DYNAMIC

CREATE TABLE `indxtest4` (

`id` bigint(20) NOT NULL auto_increment,

`name` varchar(255) default NULL,

`fk` bigint(20) NOT NULL default ‘0’,

PRIMARY KEY (`id`,`fk`)

) ENGINE=InnoDB DEFAULT CHARSET=latin1 CHECKSUM=1 DELAY_KEY_WRITE=1 ROW_FORMAT=DYNAMIC

CREATE TABLE `indxtest5` (

`id` bigint(20) NOT NULL auto_increment,

`name` varchar(255) default NULL,

`fk` bigint(20) default NULL,

PRIMARY KEY (`id`),

KEY `FK_indxtest4` (`fk`),

CONSTRAINT `FK_indxtest4` FOREIGN KEY (`fk`) REFERENCES `indxtest5parent` (`id`) ON DELETE SET NULL

) ENGINE=InnoDB DEFAULT CHARSET=latin1 CHECKSUM=1 DELAY_KEY_WRITE=1 ROW_FORMAT=DYNAMIC

And another table indxtest5parent as parent for indxtest5.

CREATE TABLE `indxtest5parent` (

`id` bigint(20) NOT NULL auto_increment,

`test` varchar(255) default NULL,

PRIMARY KEY (`id`)

) ENGINE=InnoDB DEFAULT CHARSET=latin1 CHECKSUM=1 DELAY_KEY_WRITE=1 ROW_FORMAT=DYNAMIC

Let me explain what is the difference between the tables. All tables except the indxtest5parent contain three fields: id, name, and fk. Don’t confuse fk with a foreign key. Id is the primary key in all tables. The main difference between the tables is the indexing on the fk field.

The indxtest1 has no index on fk.

The indxtest2 has an index on fk, so fk is indexed.

The indxtest3 has a multi-field-index on id and fk combined, in addition to primary key index on id.

The indxtest4 has a composite primary key id, fk. Therefore there is a primary key index on id and fk i.e multi-field-index.

The indxtest5 has a foreign key fk mapping to id field of indxtest5parent. So it has foreign key index on fk.

After that I inserted some data in these tables, around just 10 records. I inserted that few records since I wasn’t testing performance with huge data, instead I was just testing that how records are searched in table with indexes, multiple indexes, and without indexes, which is useful in knowing how records are locked, implicitly when updating or explicitly.

So all tables look almost like this after inserting data:

id

name

fk

1

One

10

2

Two

12

3

three

13

4

Four

14

5

Five

15

6

Six

15

7

seven

14

8

eight

13

9

Nine

12

10

Ten

10

Now run the following queries on all tables:

select * from indxtest1 where id = 1;

select * from indxtest2 where id = 1;

select * from indxtest3 where id = 1;

select * from indxtest4 where id = 1;

select * from indxtest5 where id = 1;

These all queries will result in same output, i.e the first record of the table. This is very simple, and since result was filtered using the primary key in the where clause so it scanned only one record during search. We can see this by running following queries:

explain select * from indxtest1 where id = 1;

explain select * from indxtest2 where id = 1;

explain select * from indxtest3 where id = 1;

explain select * from indxtest4 where id = 1;

explain select * from indxtest5 where id = 1;

You will notice that in result the rows column will show 1, that means only one record was scanned during the search.

Now let’s filter the result using the fk field in the where clause:

select * from indxtest1 where fk = 10;

select * from indxtest2 where fk = 10;

select * from indxtest3 where fk = 10;

select * from indxtest4 where fk = 10;

select * from indxtest5 where fk = 10;

All these queries will return the same result, two records with id in 1 and 10. But how many records were scanned during search? To find out the answer run the following queries:

explain select * from indxtest1 where fk = 10;

explain select * from indxtest2 where fk = 10;

explain select * from indxtest3 where fk = 10;

explain select * from indxtest4 where fk = 10;

explain select * from indxtest5 where fk = 10;

In the rows column you will notice that for the indxtest1 table it scanned 10 records. That is reasonable since there was no indexing. Now let’s see for indxtest2 table, 2 records were scanned. This is also reasonable since fk was indexed. So far so good. Now for indxtest3 table 10 records were scanned. Hmm… ok we will discuss this in a moment. Let’s check other queries first. For indxtest4 table 10 records were scanned, and for indxtest5 table only 2 records were scanned. Result for indxtest5 table is also reasonable since it has a foreign key index on it.

Now what are the cases with indxtest3 and indxtest4? If you notice both tables have a multi-column index. According to MySQL documentation:

MySQL uses multiple-column indexes in such a way that queries are fast when you specify a known quantity for the first column of the index in a WHERE clause, even if you do not specify values for the other columns. (http://dev.mysql.com/doc/refman/4.1/en/multiple-column-indexes.html)

It is clearly stated in the documentation that when second column is specified, MySQL will not use the index, or even if second column is used with first column with OR condition, it will not use the index. That’s why queries on indxtest3 and indxtest4 scanned all 10 records during search/select.

Now what is the effect of indexing on locking? According to MySQL documentation:

A locking read, an UPDATE, or a DELETE generally set record locks on every index record that is scanned in the processing of the SQL statement. (http://dev.mysql.com/doc/refman/4.1/en/innodb-locks-set.html)

And what is record lock?

Record lock: This is a lock on an index record. (http://dev.mysql.com/doc/refman/4.1/en/innodb-record-level-locks.html)

Few more points from MySQL documentation (http://dev.mysql.com/doc/refman/4.1/en/innodb-locks-set.html):

1 – For SELECT ... FOR UPDATE or SELECT ... IN SHARE MODE, locks are acquired for scanned rows.

2 – SELECT ... FROM ... FOR UPDATE sets exclusive next-key locks on all index records the search encounters.

3 – UPDATE ... WHERE ... sets an exclusive next-key lock on every record the search encounters.

4 – DELETE FROM ... WHERE ... sets an exclusive next-key lock on every record the search encounters.

Conclusion

So, according to MySQL documentation, either we are explicitly locking records (first two points) or locks are implicit (last two points), locks will be acquired on records the search encounters. So if indexing is proper no locks will be acquired on rows on which we don’t want to. Even MySQL documentation says that:

It is important to create good indexes so that your queries do not unnecessarily need to scan many rows. (http://dev.mysql.com/doc/refman/4.1/en/innodb-locks-set.html)

Scanning many records will result in lock on those records due to which deadlocks can occur, performance can be degraded, or anything bad can happen.

If you are going to test the above scenario then you will also notice the performance differences between the queries if you have reasonable number of records in tables.