- Sequential organization: In this method, records are stored in a contiguous block on the storage device in a fixed order, typically based on a primary key. This method is simple and efficient for processing data in order, but can be slow for random access or updating.
- Indexed organization: In this method, records are stored in a contiguous block, but an index is created to allow for faster access to specific records. This index is typically based on the primary key of the record. Indexed organization allows for faster random access and updating, but requires additional storage space for the index.
- Hashed organization: In this method, records are distributed across the storage device based on a hash function. This allows for fast access to records based on the primary key, but can be inefficient for range queries or accessing records in a specific order.
- Clustered organization: In this method, related records are stored together in the same block or page of the storage device. This can improve performance for queries that retrieve related records, but can be inefficient for queries that access records from different clusters.
The choice of file organization method depends on the specific requirements of the database system and the types of queries that will be performed on the data.
Objective of file organization
- Efficient storage: File organization aims to minimize the amount of storage space required to store data. This can be achieved through techniques such as data compression, data encoding, and data encryption.
- Quick and easy data retrieval: The organization of files should be such that the retrieval of data is fast and easy. This can be achieved by using techniques such as indexing, hashing, and clustering.
- Data security: File organization should ensure that data is protected from unauthorized access, modification, or deletion. This can be achieved by using techniques such as access control and encryption.
- Data consistency: File organization should ensure that data is consistent and accurate. This can be achieved through techniques such as data validation and data verification.
- Data sharing: File organization should allow multiple users to access the same data simultaneously without causing data inconsistencies or other issues. This can be achieved through techniques such as file locking and transaction processing.
Sequential File Organization is a method of file organization where records are stored in a sequence, one after another. This method can be implemented in two ways: Pile File Method and Sorted File Method.
In the Pile File Method, records are inserted into the file in the order in which they are inserted into the table. When a record needs to be updated or deleted, it is searched for in the memory blocks and then marked for deletion, and the new record is inserted.
In the Sorted File Method, new records are always inserted at the end of the file, and then the file is sorted in ascending or descending order based on a primary key or any other key. When a record needs to be modified, it is updated, and then the file is sorted again, and the updated record is placed in the right place.
Overall, Sequential File Organization is a simple and easy method of file organization, but it can become inefficient when dealing with large files, as searching and sorting can become time-consuming operations.
Heap file organization
In heap file organization, when a new record is to be inserted, it is stored at the end of the file. If the current block is full, a new block is allocated, and the new record is stored in it. The location of the new block can be selected by the DBMS, and it need not be the next block in sequence.
One disadvantage of heap file organization is that it is inefficient for searching or modifying individual records. In order to find a specific record, the file must be searched sequentially from the beginning. This can be time-consuming for large databases. However, it is a good method for bulk insertion of large amounts of data into a database.
Hash File Organization
Hash File Organization uses a hashing algorithm to determine the record’s storage location in the file, based on its key value. Each record has a unique key value, and this value is used to determine the storage location in the file.
In this method, the file is divided into a fixed number of blocks, and each block has a unique address. A hash function is applied to the record’s key value, which provides the address of the block in which the record is to be stored. If there is already a record in that block, then the file manager uses a collision resolution technique to store the new record.
Collision resolution techniques include linear probing, chaining, and double hashing. Linear probing involves searching for the next available slot in the same block. Chaining involves creating a linked list of records that hash to the same block. Double hashing uses a second hash function to compute an alternative address for the record.
Hash File Organization is efficient for large databases, as the records can be accessed quickly based on their key values. However, it is not suitable for range searches or for searching records based on non-key fields. Additionally, the hash function must be carefully designed to avoid collisions and ensure an even distribution of records across the file.
B+ File Organization
In a B+ tree, each node can have multiple children, and all nodes at the same level are linked together in a linked list. The B+ tree has a root node, which is the topmost node, and all leaf nodes are at the same level. The records are stored only in the leaf nodes, and each leaf node contains a pointer to the next leaf node in the linked list.
The B+ tree is designed to minimize the number of disk accesses required to find a record. Each node of the B+ tree is stored in a disk block, and the size of the disk block is chosen to be the same as the size of a memory page. When a search is performed, the B+ tree is traversed, and only the required nodes are read from the disk. This minimizes the number of disk accesses required to find a record.
B+ file organization is very efficient for range queries, as the records are stored in sorted order in the leaf nodes, and the B+ tree is designed to minimize the number of disk accesses required to traverse the tree. It is also efficient for insertion and deletion of records, as the B+ tree can be easily rebalanced to maintain its balanced structure.
In summary, B+ file organization provides efficient access to records, especially for range queries, and is widely used in modern database systems.