A list of frequently asked JDBC interview questions with answers are given below.
1) What is JDBC?
JDBC is a Java API that is used to connect and execute query to the database. JDBC API uses jdbc drivers to connects to the database.
2) What is SQL?
SQL(Structured Query Language ) is a computer language for database, it includes facilities for database creation, deletion, fetching rows and modifying rows etc.It can be used to storing, manipulating and retrieving data stored in relational database.
SQL is the standard language for Relation Database System. All relational database management systems like MySQL, MS Access, Oracle, Sybase, Informix, postgres and SQL Server use SQL as standard database language.
SQL is an ANSI (American National Standards Institute) standard but there are many different versions of the SQL language.
Also, they are using different dialects, such as:
- MS SQL Server using T-SQL,
- Oracle using PL/SQL,
- MS Access version of SQL is called JET SQL (native format) etc.
3) What does SQL allow?
- Allows users to access data in relational database management systems.
- Allows users to describe the data.
- Allows users to define the data in database and manipulate that data.
- Allows to embed within other languages using SQL modules, libraries & pre-compilers.
- Allows users to create and drop databases and tables.
- Allows users to create view, stored procedure, functions in a database.
- Allows users to set permissions on tables, procedures, and views
4) What are the steps in executing a SQL Query?
When you are executing an SQL command for any RDBMS, the system determines the best way to carry out your request and SQL engine figures out how to interpret the task.
There are various components included in the process. These components are Query Dispatcher, Optimization Engines, Classic Query Engine and SQL Query Engine, etc. Classic query engine handles all non-SQL queries but SQL query engine won’t handle logical files.
Following is a simple diagram showing SQL Architecture:
5) What are the different SQl commands used?
The standard SQL commands to interact with relational databases are CREATE, SELECT, INSERT, UPDATE, DELETE and DROP. These commands can be classified into groups based on their nature:
6) What is RDBMS?
A Relational database management system (RDBMS) is a database management system (DBMS) that is based on the relational model as introduced by E. F. Codd. RDBMS is the basis for SQL operations, and for all modern database systems like MS SQL Server, IBM DB2, Oracle, MySQL, and Microsoft Access.
7) What is table?
The data in RDBMS is stored in database objects called tables. The table is a collection of related data entries and it consists of columns and rows.
Remember, a table is the most common and simplest form of data storage in a relational database. Following is the example of a CUSTOMERS table.
+----+----------+-----+-----------+----------+ | ID | NAME | AGE | ADDRESS | SALARY | +----+----------+-----+-----------+----------+ | 1 | Ramesh | 32 | Ampara | 2000.00 | | 2 | Nihal | 25 | Dehiwala | 1500.00 | | 3 | Ranil | 23 | Kottawa | 2000.00 | | 4 | Chamara | 25 | Maharagama| 6500.00 | | 5 | Harin | 27 | Horana | 8500.00 | | 6 | Kamal | 22 | Madampe | 4500.00 | | 7 | Mahinda | 24 | Nawinna | 10000.00 | +----+----------+-----+-----------+----------+
8) What is field?
Every table is broken up into smaller entities called fields. The fields in the CUSTOMERS table consist of ID, NAME, AGE, ADDRESS and SALARY. A field is a column in a table that is designed to maintain specific information about every record in the table.
9) What is record or row?
A record, also called a row of data, is each individual entry that exists in a table. For example there are 7 records in the above CUSTOMERS table. Following is a single row of data or record in the CUSTOMERS table:
+----+----------+-----+-----------+----------+ | 1 | Ramesh | 32 | Ampara | 2000.00 | +----+----------+-----+-----------+----------+
A record is a horizontal entity in a table.
10) What is column?
A column is a vertical entity in a table that contains all information associated with a specific field in a table.
For example, a column in the CUSTOMERS table is ADDRESS, which represents location description and would consist of the following:
+-----------+ | ADDRESS | +-----------+ | Ampara | | Dehiwala | | Kottawa | | Maharagama| | Horana | | Madampe | | Nawinna | +----+------+
11) What is NULL value?
A NULL value in a table is a value in a field that appears to be blank, which means a field with a NULL value is a field with no value.
It is very important to understand that a NULL value is different than a zero value or a field that contains spaces. A field with a NULL value is one that has been left blank during record creation.
12) what are SQL Constraints ?
Constraints are the rules enforced on data columns on table. These are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the database.
Constraints could be column level or table level. Column level constraints are applied only to one column where as table level constraints are applied to the whole table.
Following are commonly used constraints available in SQL:
- NOT NULL Constraint: Ensures that a column cannot have NULL value.
- DEFAULT Constraint: Provides a default value for a column when none is specified.
- UNIQUE Constraint: Ensures that all values in a column are different.
- PRIMARY Key: Uniquely identified each rows/records in a database table.
- FOREIGN Key: Uniquely identified a rows/records in any another database table.
- CHECK Constraint: The CHECK constraint ensures that all values in a column satisfy certain conditions.
- INDEX: Use to create and retrieve data from the database very quickly.
13) what are Data Integrity ?
The following categories of the data integrity exist with each RDBMS:
- Entity Integrity: There are no duplicate rows in a table.
- Domain Integrity: Enforces valid entries for a given column by restricting the type, the format, or the range of values.
- Referential integrity: Rows cannot be deleted, which are used by other records.
- User-Defined Integrity: Enforces some specific business rules that do not fall into entity, domain or referential integrity.
14) Database Normalization
Database normalization is the process of efficiently organizing data in a database. There are two reasons of the normalization process:
- Eliminating redundant data, for example, storing the same data in more than one tables.
- Ensuring data dependencies make sense.
Both of these are worthy goals as they reduce the amount of space a database consumes and ensure that data is logically stored. Normalization consists of a series of guidelines that help guide you in creating a good database structure.
Normalization guidelines are divided into normal forms; think of form as the format or the way a database structure is laid out. The aim of normal forms is to organize the database structure so that it complies with the rules of first normal form, then second normal form, and finally third normal form.
It’s your choice to take it further and go to fourth normal form, fifth normal form, and so on, but generally speaking, third normal form is enough.
15) Briefly Explain the First Normal Form (1NF) ?
First normal form (1NF) sets the very basic rules for an organized database:
- Define the data items required, because they become the columns in a table. Place related data items in a table.
- Ensure that there are no repeating groups of data.
- Ensure that there is a primary key.
First Rule of 1NF:
You must define the data items. This means looking at the data to be stored, organizing the data into columns, defining what type of data each column contains, and finally putting related columns into their own table.
For example, you put all the columns relating to locations of meetings in the Location table, those relating to members in the MemberDetails table, and so on.
Second Rule of 1NF:
The next step is ensuring that there are no repeating groups of data. Consider we have the following table.
CREATE TABLE CUSTOMERS( ID INT NOT NULL, NAME VARCHAR (20) NOT NULL, AGE INT NOT NULL, ADDRESS CHAR (25), ORDERS VARCHAR(155) );
So if we populate this table for a single customer having multiple orders, then it would be something as follows:
But as per 1NF, we need to ensure that there are no repeating groups of data. So let us break above table into two parts and join them using a key as follows:
CREATE TABLE CUSTOMERS( ID INT NOT NULL, NAME VARCHAR (20) NOT NULL, AGE INT NOT NULL, ADDRESS CHAR (25), PRIMARY KEY (ID) ); This table would have the following record:
CREATE TABLE ORDERS( ID INT NOT NULL, CUSTOMER_ID INT NOT NULL, ORDERS VARCHAR(155), PRIMARY KEY (ID) );
This table would have the following records
Third Rule of 1NF:
The final rule of the first normal form, create a primary key for each table which we have already created.
16) Briefly Explain the Database – Second Normal Form (2NF)?
Second normal form states that it should meet all the rules for 1NF and there must be no partial dependencies of any of the columns on the primary key:
Consider a customer-order relation and you want to store customer ID, customer name, order ID and order detail, and date of purchase:
CREATE TABLE CUSTOMERS( CUST_ID INT NOT NULL, CUST_NAME VARCHAR (20) NOT NULL, ORDER_ID INT NOT NULL, ORDER_DETAIL VARCHAR (20) NOT NULL, SALE_DATE DATETIME, PRIMARY KEY (CUST_ID, ORDER_ID) );
This table is in first normal form, in that it obeys all the rules of first normal form. In this table, the primary key consists of CUST_ID and ORDER_ID. Combined, they are unique assuming same customer would hardly order same thing.
However, the table is not in second normal form because there are partial dependencies of primary keys and columns. CUST_NAME is dependent on CUST_ID, and there’s no real link between a customer’s name and what he purchased. Order detail and purchase date are also dependent on ORDER_ID, but they are not dependent on CUST_ID, because there’s no link between a CUST_ID and an ORDER_DETAIL or their SALE_DATE.
To make this table comply with second normal form, you need to separate the columns into three tables.
First, create a table to store the customer details as follows:
CREATE TABLE CUSTOMERS( CUST_ID INT NOT NULL, CUST_NAME VARCHAR (20) NOT NULL, PRIMARY KEY (CUST_ID) );
Next, create a table to store details of each order:
CREATE TABLE ORDERS( ORDER_ID INT NOT NULL, ORDER_DETAIL VARCHAR (20) NOT NULL, PRIMARY KEY (ORDER_ID) );
Finally, create a third table storing just CUST_ID and ORDER_ID to keep track of all the orders for a customer:
CREATE TABLE CUSTMERORDERS( CUST_ID INT NOT NULL, ORDER_ID INT NOT NULL, SALE_DATE DATETIME, PRIMARY KEY (CUST_ID, ORDER_ID) );
17) Briefly Explain the Database – Third Normal Form (3NF)?
A table is in third normal form when the following conditions are met:
- It is in second normal form.
- All non-primary fields are dependent on the primary key.
The dependency of non-primary fields is between the data. For example, in the below table, street name, city, and state are unbreakably bound to the zip code.
CREATE TABLE CUSTOMERS( CUST_ID INT NOT NULL, CUST_NAME VARCHAR (20) NOT NULL, DOB DATE, STREET VARCHAR(200), CITY VARCHAR(100), STATE VARCHAR(100), ZIP VARCHAR(12), EMAIL_ID VARCHAR(256), PRIMARY KEY (CUST_ID) );
The dependency between zip code and address is called a transitive dependency. To comply with third normal form, all you need to do is move the Street, City, and State fields into their own table, which you can call the Zip Code table:
CREATE TABLE ADDRESS( ZIP VARCHAR(12), STREET VARCHAR(200), CITY VARCHAR(100), STATE VARCHAR(100), PRIMARY KEY (ZIP) );
Next, alter the CUSTOMERS table as follows:
CREATE TABLE CUSTOMERS( CUST_ID INT NOT NULL, CUST_NAME VARCHAR (20) NOT NULL, DOB DATE, ZIP VARCHAR(12), EMAIL_ID VARCHAR(256), PRIMARY KEY (CUST_ID) );
The advantages of removing transitive dependencies are mainly twofold. First, the amount of data duplication is reduced and therefore your database becomes smaller.
The second advantage is data integrity. When duplicated data changes, there’s a big risk of updating only some of the data, especially if it’s spread out in a number of different places in the database. For example, if address and zip code data were stored in three or four different tables, then any changes in zip codes would need to ripple out to every record in those three or four tables.