Hash Map Value Identifier Storage for Database Memory Optimization
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Solution Overview
Problem
Conventional database systems face inefficiencies in storing and retrieving data records due to time-consuming retrieval processes, especially as the number of data records grows, and existing hash maps are memory-intensive.
Innovation Solution
The use of a hash map-based system that stores value identifiers directly in a bucket list without corresponding values, allowing for direct memory access and collision resolution techniques using a dual memory structure configuration, enabling efficient insertion and retrieval of value identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional database systems traverse the entire dictionary to retrieve data records, then the retrieval process can handle any number of data records, but the retrieval time increases significantly as the number of data records grows
Solution Approach 1:
The dictionary is segmented into multiple buckets, with each bucket containing a subset of value identifiers. The hash map divides the retrieval space into manageable segments, allowing the system to search only relevant portions rather than traversing the entire dictionary sequentially.
Solution Approach 2:
Value identifiers are pre-organized into buckets and indexed in the hash map before retrieval operations occur. This preliminary organization enables direct access to relevant data segments during query execution, eliminating the need for full dictionary traversal at retrieval time.
2Speed
If conventional hash maps store complete data records to enable fast retrieval, then retrieval speed improves, but memory consumption increases significantly
Solution Approach 1:
The invention extracts only the essential identifying information (value identifiers) from complete data records and stores these extracted identifiers in the hash map and buckets. The full data records remain stored separately in the database, allowing fast identification through the hash map while minimizing memory usage for the indexing structure.
Solution Approach 2:
Instead of storing complete data records in the hash map, the system creates simplified copies consisting only of value identifiers. These compact copies serve as indexes that enable fast retrieval operations without duplicating the full data payload in memory.
Data Source
AI summary
The subject matter disclosed herein provides methods for inserting and retrieving value identifiers from a dictionary encoded database using hash maps. A first value identifier and a first value can be accessed from a dictionary storing one or more value identifiers and one or more values. Each value identifier can correspond to a different value. The hash map and the first value can be used to determine a first index in a bucket list for inserting the first value identifier. The bucket list can have one or more indices. Each index can store at least one value identifier. The hash map can include a vector of one or more pointers. Each pointer can refer to at least one of the indices. Based on the determining, the first value identifier can be inserted at the first index without inserting the first value. Related apparatus, systems, techniques, and articles are also described.