File organization defines how data records are stored in a database file, impacting how data is retrieved, inserted, updated, or deleted. Proper file organization is essential for optimizing database performance.

This lesson explores below types of file organizations, illustrating their features, advantages, disadvantages, and how records are managed.

1. Sequential File Organization
2. Heap File Organization
3. Hash File Organization
4. Clustered File Organization
5. B+ Tree File Organization
6. ISAM (Indexed Sequential Access Method)

Types of File Organization

1. Sequential File Organization

In sequential file organization, records are stored in a sequential order based on a specific key field (e.g., primary key). When new records are added, they are placed in the correct order, maintaining the sequence.

How It Works

• Data is inserted in sorted order.
• Searching requires a sequential scan or binary search if the data is indexed.

Advantages

• Efficient for range queries and batch processing.
• Easy to read data in a predefined order.

Disadvantages

• Insertion and deletion are costly as they require reordering records.
• Performance degrades with frequent updates.

Example

In the below diagram, we have records in the R1, R3, R5, R4, sequence.

If we want to insert R2, we need to insert it between R1 and R3.

2. Heap File Organization

Heap files are unordered, meaning new records are inserted wherever space is available. No sorting or indexing is applied, making this the simplest form of file organization.

How It Works

• Records are placed in the first available space in the file.
• Searching requires a full scan of the file.

Advantages

• Simple and efficient for insertion.
• Minimal overhead for maintenance.

Disadvantages

• Searching and updating are slow due to the lack of order.
• Data retrieval is inefficient for large datasets.

Example

In the below diagram, we have the first empty slot available in the first block.

If we want to insert the new record R2, we can insert it in the first block as shown in diagram below.

3. Hash File Organization

In hash file organization, a hash function is used to calculate the address of a record based on a key field. Records are stored in buckets corresponding to hash values.

How It Works

• A hash function maps a key to a bucket.
• Collisions are resolved using techniques like chaining or open addressing.

Advantages

• Fast access for equality searches.
• Efficient insertion and deletion.

Disadvantages

• Not suitable for range queries.
• Collisions may degrade performance.

Example

Hash function: Key MOD 5

• Adding Record (ID: 106): 106 MOD 5 = 1 → Placed in Bucket 1. Here, Collision occurred as 2 values have the same hash value. So, we can use methods like chaining to resolve the collision. We will learn to resolve collision in upcoming chapters of this course.

4. Clustered File Organization

In clustered file organization, records with similar values are stored together physically. This organization is often based on clustering indexes.

How It Works

• Data is grouped based on a clustering key.
• Records are stored sequentially within each group.

Advantages

• Faster range queries and sequential access.
• Improves I/O efficiency for related data.

Disadvantages

• Complex to maintain during insertions and updates.
• Not suitable for datasets without natural groupings.

Example

In the below diagram, cluster A contains Alice, and Alex, cluster B contains Bob, and Ben and cluster C contains the Charlie record.

If we add a new record "Anna" in cluster A, it will look like as shown below.

We will cover B+ Tree File Organization and ISAM (Indexed Sequential Access Method) methods in the upcoming lessons of this chapter.

In the next lesson, we will explore Access Methods, covering topics like clustered vs. non-clustered storage and hashing mechanisms in greater detail.