As the data source develops with time, we now have 3 choices:
- Choose hash perform depending on present file size. Obtain overall performance destruction because document develops.
- Choose hash perform depending on anticipated file size. Space is wasted initially.
- Periodically re-organize hash framework because document develops. Demands choosing brand new hash perform, recomputing just about all addresses and generating new bucket assignments. Costly, and shuts down database.
Some hashing techniques allow the hash function to be modified dynamically to accommodate the growth or shrinking of the database. These are called dynamic hash functions.
- Extendable hashing is one form of dynamic hashing.
- Extendable hashing splits and coalesces buckets as database size changes.
- This imposes some performance overhead, but space efficiency is maintained.
- As reorganization is on one bucket at a time, overhead is acceptably low.
Example of Dynamic Hashing
- Hash function generates values over a large range — typicallyb-bit integers, withb = 32.
- At any time use only a prefix of the hash function to index into a table of bucket addresses.
- Let the length of the prefix bei bits, 0=i = 32.
- Bucket address table size = 2i. Initiallyi = 0
- Value ofi grows and shrinks as the size of the database grows and shrinks.
- Multiple entries in the bucket address table may point to a bucket.
- Thus, actual number of buckets is < 2i
- Extendable hashing provides performance that does not degrade as the file grows.
- Minimal space overhead - no buckets need be reserved for future use. Bucket address table only contains one pointer for each hash value of current prefix length.
- Extra level of indirection in the bucket address table
- Added complexity
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