This document discusses different types of file organization, including heap file organization, hash file organization, sequential file organization, and multitable clustering file organization. Heap file organization stores records sequentially with a key field. Hash file organization uses hashing techniques like cut key, folded key, and division remainder to organize records. Sequential file organization stores records in sorted order based on a search key. Multitable clustering file organization stores frequently joined tables together in the same file or cluster for efficient retrieval.

1. File Organization

2. Group Members:
Sadman Naib 16701044
Sharif Himu 16701034
Maruf Sikder 16701047
Arpan Barua 16701003
Touhiduzzaman Akash 16701017
Group no : 4

3. File Organization
File organization refers primarily to the logical
arrangement of data in a file system.
Advantages:
1.Backup
2.Data retrieval
3.Editing
4.Remote Access

4. Types of File Organizations
 Heap File organization
 Hash File organization
 Sequential File organization
 Multitable Clustering File organization

5. Heap file organization

6. I. Also called pile method.
II. There will be a single file for each relation.
III. Insertion done by stacking method. (insert at 1st position if
empty than 2nd position if empty.)
IV. There will be a field in each record known as key (as
0,1,2,3…..).
V. If we want to remove any record than we have to delete its
key that is logically deleted.
VI. If we want to delete a record physically than we have to use
garbage collection that will locate all unnecessary record and
remove it.

7. Hash File Organization

8. I. Records are organized using a technique called
hashing.
II. 3 types of Hash function.
 cut key hashing.
 Folded key hashing.
 Division remainder hashing.

9. Cut key hashing
• Last number
of a value will
be used as a
hash key
Folded key hashing
• Addition of
numbers of a
value will be
used as a hash
key.
Division remainder
hashing
• Remainder of division
of a number divided
by any definite
number will be used
as a hash key.

10. Sequential File Organization(SFO):
 A sequential file is designed for efficient processing of records
in sorted order based on some search key.
 A search key is any attribute or set of attributes; it need not
be the primary key or even the super key.
 It allows records to be read in sorted order; that can be useful
for display purposes, as well as for certain query-processing
algorithms.
 The design is very simple compared other file organization.
There is no much effort involved to store the data.

11. How SFO works :
 Records are stored one after another as are inserted into the
tables. This method is called pile file method. When a new
record is inserted ,it is placed at the end of the file. In the case
of any modification or deletion of record, the record will be
searched in the memory blocks. Once it is found, it will be
marked for deleting and new blocks of record is entered.
 In the second method, records are sorted each time they are
inserted into the system. This method is called sorted file
method .Sorting of records may be based on the primary key
or on any other columns.Whenever a new record is inserted, it
will be inserted at the end of the file and then it will sort based
on key value and placed at the correct position.

12. Multitable Clustering File
Organization
 In this method two or more table which are
frequently used to join and get the results are
stored in the same file called clusters.

13. Example

14. Applicable situation
● There is a frequent need for joining the tables with
same condition. Also, these joins will result in only
few records from both tables.
● If tables are joined once in a while or full table scan
of any one the table in involved in the query, then we
do not cluster the tables.
● If there is 1: M relationship between the tables, then
we can cluster the tables.

15. Classification
● Indexed Clusters: - Here records are grouped based on the
cluster key and stored together.
● Hash Clusters: - This is also similar to indexed cluster. Here
instead of storing the records based on the cluster key, we
generate the hash key value for the cluster key and store the
records with same hash key value together in the memory
disk.

16. Advantages
● This method is best suited when there is frequent
request for joining the tables with same joining
condition.
● When there is a 1:M mapping between the tables, it
results efficiently.

17. Disadvantages
● This method is not suitable for very large databases since the
performance of this method on them is low.
● We cannot use this clusters, if there is any change is joining
condition. If the joining condition changes, the traversing the
file takes lot of time.
● This method is not suitable for less frequently joined tables
or tables with 1:1 conditions.

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