A Grouping Aggregation Method of Olap Based on Functional Dependency
A functional dependency and relational technology, applied in database models, database indexes, multi-dimensional databases, etc., can solve the problems of increasing memory access delay for group computing, high CPU computing cost, and increasing hash table space, so as to reduce storage and computing. Overhead, the effect of reducing computational cost
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[0031] Such as figure 1 As shown, the database usually uses the hash group aggregation calculation method. The attribute group corresponding to the GROUP BY clause is used as the hash key value (hash key) to perform hash mapping through the hash function, and is mapped to the unique bucket in the hash table, the bucket Several hash records are stored in , and the hash records are composed of hash key values and aggregation calculation units. Since different hash key values may correspond to the same bucket under the mapping of the hash function, the hash key value needs to be kept in the hash table for comparison and as a grouping attribute of the output result.
[0032] The efficiency of hash group aggregation calculation depends on the storage access efficiency of hash table and the calculation efficiency of hash detection. In an in-memory database, the smaller the hash table, the higher the cache hit rate of the hash table memory access, and the lower the memory access...
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