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Database Normalization
Normalization is the process of organizing data in a database. This includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency.
Redundant data wastes disk space and creates maintenance problems. If data that exists in more than one place must be changed, the data must be changed in exactly the same way in all locations. A customer address change is much easier to implement if that data is stored only in the Customers table and nowhere else in the database.
What is an “inconsistent dependency”? While it is intuitive for a user to look in the Customers table for the address of a particular customer, it may not make sense to look there for the salary of the employee who calls on that customer. The employee’s salary is related to, or dependent on, the employee and thus should be moved to the Employees table. Inconsistent dependencies can make data difficult to access because the path to find the data may be missing or broken.
There are a few rules for database normalization. Each rule is called a “normal form.” If the first rule is observed, the database is said to be in “first normal form.” If the first three rules are observed, the database is considered to be in “third normal form.” Although other levels of normalization are possible, third normal form is considered the highest level necessary for most applications.
As with many formal rules and specifications, real world scenarios do not always allow for perfect compliance. In general, normalization requires additional tables and some customers find this cumbersome. If you decide to violate one of the first three rules of normalization, make sure that your application anticipates any problems that could occur, such as redundant data and inconsistent dependencies.
The following descriptions include examples.
First Normal Form
- Eliminate repeating groups in individual tables.
- Create a separate table for each set of related data.
- Identify each set of related data with a primary key.
Do not use multiple fields in a single table to store similar data. For example, to track an inventory item that may come from two possible sources, an inventory record may contain fields for Vendor Code 1 and Vendor Code 2.
What happens when you add a third vendor? Adding a field is not the answer; it requires program and table modifications and does not smoothly accommodate a dynamic number of vendors. Instead, place all vendor information in a separate table called Vendors, then link inventory to vendors with an item number key, or vendors to inventory with a vendor code key.
Second Normal Form
- Create separate tables for sets of values that apply to multiple records.
- Relate these tables with a foreign key.
Records should not depend on anything other than a table’s primary key (a compound key, if necessary). For example, consider a customer’s address in an accounting system. The address is needed by the Customers table, but also by the Orders, Shipping, Invoices, Accounts Receivable, and Collections tables. Instead of storing the customer’s address as a separate entry in each of these tables, store it in one place, either in the Customers table or in a separate Addresses table.
Third Normal Form
- Eliminate fields that do not depend on the key.
Values in a record that are not part of that record’s key do not belong in the table. In general, any time the contents of a group of fields may apply to more than a single record in the table, consider placing those fields in a separate table.
For example, in an Employee Recruitment table, a candidate’s university name and address may be included. But you need a complete list of universities for group mailings. If university information is stored in the Candidates table, there is no way to list universities with no current candidates. Create a separate Universities table and link it to the Candidates table with a university code key.
EXCEPTION: Adhering to the third normal form, while theoretically desirable, is not always practical. If you have a Customers table and you want to eliminate all possible interfield dependencies, you must create separate tables for cities, ZIP codes, sales representatives, customer classes, and any other factor that may be duplicated in multiple records. In theory, normalization is worth pursing. However, many small tables may degrade performance or exceed open file and memory capacities.
It may be more feasible to apply third normal form only to data that changes frequently. If some dependent fields remain, design your application to require the user to verify all related fields when any one is changed.
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Other Normalization Forms
Fourth normal form, also called Boyce Codd Normal Form (BCNF), and fifth normal form do exist, but are rarely considered in practical design. Disregarding these rules may result in less than perfect database design, but should not affect functionality.
Normalizing an Example Table
These steps demonstrate the process of normalizing a fictitious student table.
- Unnormalized table:
Student# Advisor Adv-Room Class1 Class2 Class3 1022 Jones 412 101-07 143-01 159-02 4123 Smith 216 201-01 211-02 214-01 - First Normal Form: No Repeating GroupsTables should have only two dimensions. Since one student has several classes, these classes should be listed in a separate table. Fields Class1, Class2, and Class3 in the above records are indications of design trouble.Spreadsheets often use the third dimension, but tables should not. Another way to look at this problem is with a one-to-many relationship, do not put the one side and the many side in the same table. Instead, create another table in first normal form by eliminating the repeating group (Class#), as shown below:
Student# Advisor Adv-Room Class# 1022 Jones 412 101-07 1022 Jones 412 143-01 1022 Jones 412 159-02 4123 Smith 216 201-01 4123 Smith 216 211-02 4123 Smith 216 214-01 - Second Normal Form: Eliminate Redundant DataNote the multiple Class# values for each Student# value in the above table. Class# is not functionally dependent on Student# (primary key), so this relationship is not in second normal form.The following two tables demonstrate second normal form:Students:
Student# Advisor Adv-Room 1022 Jones 412 4123 Smith 216 Registration:
Student# Class# 1022 101-07 1022 143-01 1022 159-02 4123 201-01 4123 211-02 4123 214-01 - Third Normal Form: Eliminate Data Not Dependent On KeyIn the last example, Adv-Room (the advisor’s office number) is functionally dependent on the Advisor attribute. The solution is to move that attribute from the Students table to the Faculty table, as shown below:Students:
Student# Advisor 1022 Jones 4123 Smith Faculty:
Name Room Dept Jones 412 42 Smith 216 42
Difference between String and StringBuffer/StringBuilder
Well, the most important difference between String and StringBuffer/StringBuilder is that String object is immutable whereas StringBuffer/StringBuilder objects are mutable.
By immutable, we mean that the value stored in the String object cannot be changed. Then the next question that comes to our mind is “If String is immutable then how am I able to change the contents of the object whenever I wish to?” . Well, to be precise it’s not the same String object that reflects the changes you do. Internally a new String object is created to do the changes.
So suppose you declare a String object:
String myString = “Hello”;
Next, you want to append “Guest” to the same String. What do you do?
myString = myString + ” Guest”;
When you print the contents of myString the output will be “Hello Guest”. Although we made use of the same object(myString), internally a new object was created in the process. So, if you were to do some string operation involving an append or trim or some other method call to modify your string object, you would really be creating those many new objects of class String.
Now isn’t that a performance issue?
Yes, it definitely is.
Then how do you make your string operations efficient?
By using StringBuffer or StringBuilder.
How would that help?
Well, since StringBuffer/StringBuilder objects are mutable, we can make changes to the value stored in the object. What this effectively means is that string operations such as append would be more efficient if performed using StringBuffer/StringBuilder objects than String objects.
Finally, whats the difference between StringBuffer and StringBuilder?
StringBuffer and StringBuilder have the same methods with one difference and that’s of synchronization. StringBuffer is synchronized( which means it is thread safe and hence you can use it when you implement threads for your methods) whereas StringBuilder is not synchronized( which implies it isn’t thread safe).
So, if you aren’t going to use threading then use the StringBuilder class as it’ll be more efficient than StringBuffer due to the absence ofsynchronization.
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