Comp 335 File Structures Reclaiming and Reusing File Space Techniques for File Maintenance

Considerations for File Modification Modifications take place in three forms:  Record Addition  Record Deletion  Record Update ADDITIONS  If a file only has additions, no problems, just continue to append to the end of file. DELETIONS  Theses leave “holes” in the file. You do not want to always “pack” the file. We must come up with a way to use these holes. UPDATING  Only a problem if variable length records are used. What if the modification results in a smaller record? Larger record?

Reclaiming File Space DELETIONS and UPDATES can lead to a severely fragmented file. FILE COMPACTION is an option. Records can be marked as deleted and then the OS can run a compaction on the file. The compaction can be done in two ways: a) move records up into unused space or b) a file copy which simply skips over deleted records. Considering large files with millions of records, file compactions are usually done once a day or week.

Dynamic Space Reclamations It would be nice if file space could be reclaimed on the fly and just simply reuse the space (holes) without having to do file compaction. This can be done fairly efficiently with both fixed and variable length record files using a stack.

Fixed length Record Files Dynamically Reusing Space One way would be to “logically” delete records. A “logical” deletion is a flag kept in a record header which simply marks whether or not this record is deleted. The records could be searched and the first record found which is deleted could simply be reused. This could be EXTREMELY SLOW! O(n) algorithm. Not to mention the possibility of MANY SEEKS!

Fixed length Record Files Dynamically Reusing Space It would be nice to find immediately where a space (hole) is in the file ( if indeed there is available space) and go directly to this location. A very fast technique to use is to link all available holes together and to implement this list as a stack.

Fixed length Record Files Dynamically Reusing Space Add a “top” pointer to the file header. This will point to the top of the linked list of available spaces in the file. Each record will need to include a header which will contain a delete flag and a next pointer.

Variable length Record Files Dynamically Reusing Space Same basic technique will be utilized but there are some problems which arise with VL record files that do not occur with FL record files. Problems: Cannot use RRN to get to a “hole”, must use actual address Size of the holes are different Fragmentation is a problem, holes can get so small that they cannot be reused.

Variable length Record Files Dynamically Reusing Space Ordering of the “avail” (available space) list becomes an issue. Three Techniques could be used:  First Fit  Best Fit  Worst Fit

First Fit Strategy Adding a new “hole” to list:  The new hole is added to front of list – O(1) Reusing space  Find first space which fits (searching an unordered list) – O(n)

Best Fit Strategy List must be ordered in ascending order. Adding a new “hole” to the list:  Insertion into an ordered linked list – O(n) Reusing Space  Searching an ordered list but is not in an array – O(n) This technique can also lead to fast fragmentation. Since we using the best or closest fit, any unused space could possibly be too small to be reused.

Worst Fit Strategy List must be placed in descending order. Adding a new “hole” to the list:  Insertion into an ordered list not in an array – O(n) Reusing space  Take the top of the avail list because this is either the worst fit or no fit. O(1) This technique is frequently used because of two reasons: 1) fragmentation is usually delayed because unused space in a reclamation can probably be reused and 2) reusing the space is fast.

Other Points about File Maintenance How do you handle updates to records in files?  Fixed length records – no problem, just reuse that same space. Variable length records – handle as a deletion and then an add. Coalescing – to delay fragmentation, coalescing can be used; this technique searches the file for places in the file where there are two or more “adjacent” holes and will combine them into one hole.