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Hashing

Hashing. Motivation. The primary goal is to locate the desired record in a single access of disk. Sequential search: O(N) B+ trees: O( log k N) Hashing: O(1) In hashing, the key of a record is transformed into an address and the record is stored at that address.

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Hashing

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  1. Hashing

  2. Motivation • The primary goal is to locate the desired record in a single access of disk. • Sequential search: O(N) • B+ trees: O(logkN) • Hashing: O(1) • In hashing, the key of a record is transformed into an address and the record is stored at that address. • Hash-based indexes are best for equality selections. Cannot support range searches. • Static and dynamic hashing techniques exist. CENG 351

  3. Hash-based Index • Data entries are kept in buckets (an abstract term) • Each bucket is a collection of one primary block and zero or more overflow blocks. • Given a search key value, k, we can find the bucket where the data entry k* is stored as follows: • Use a hash function, denoted by h • The value of h(k) is the address for the desired bucket. h(k) should distribute the search key values uniformly over the collection of buckets CENG 351

  4. Hash Functions • Key mod N: • N is the size of the table, better if it is prime. • Folding: • e.g. 123|456|789: add them and take mod. • Truncation: • e.g. 123456789 map to a table of 1000 addresses by picking 3 digits of the key. • Squaring: • Square the key and then truncate • Radix conversion: • e.g. 1 2 3 4 treat it to be base 11, truncate if necessary. CENG 351

  5. Static Hashing • Primary Area: # primary pages fixed, allocated sequentially, never de-allocated; (say M buckets). • A simple hash function: h(k) = f(k) mod M • Overflow area: disjoint from the primary area. It keeps buckets which hold records whose key maps to a full bucket. • Adding the address of an overflow bucket to a primary area bucket is called chaining. • Collisiondoes not cause a problem as long as there is still room in the mapped bucket. Overflow occurs during insertion when a record is hashed to the bucket that is already full. CENG 351

  6. Example • Assume f(k) = k. Let M = 5. So, h(k) = k mod 5 • Bucket factor = 3 records. Insert records with keys: 12, 35, 44, 60, 6, 46,57,33,62,17 35 60 6 46 17 12 57 62 33 overflow 44 Primary area CENG 351

  7. # of records in the file # of spaces in primary area Load Factor (Packing density) • To limit the amount of overflow we allocate more space to the primary area than we need (i.e. the primary area will be, say, 70% full) • Load Factor = => Lf = n M * Bkfr CENG 351

  8. Effects of Lf and Bkfr • Performance can be enhanced by the choice of bucket size and load factor. • In general, a smaller load factor means • less overflow and a faster fetch time; • but more wasted space. • A larger Bkfr means • less overflow in general, • but slower fetch. CENG 351

  9. Insertion and Deletion • Insertion: New records are inserted at the end of the chain. • Deletion: Two ways are possible: • Mark the record to be deleted • Consolidate sparse buckets when deleting records. • In the 2nd approach: • When a record is deleted, fill its place with the last record in the chain of the current bucket. • Deallocate the last bucket when it becomes empty. CENG 351

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