Character Encoding Dictionaries for On-Demand Query Decoding
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Solution Overview
Problem
Database management systems face inefficiencies in query processing due to the need for pre-creation of dictionaries for various encoding schemes, leading to memory overhead and processing resource wastage, especially when not all encoding schemes are needed for query processing.
Innovation Solution
Implementing a method to dynamically create and cache dictionaries on-demand based on specific encoding schemes required by queries, allowing for efficient reuse of dictionaries and reducing memory consumption through cache management policies like LRU.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dictionaries for various encoding schemes are pre-created, then query processing can be performed, but memory overhead and processing resource wastage increase
Solution Approach 1:
The system performs preliminary action by pre-creating dictionaries for various encoding schemes and storing them in the buffer pool, but only when there is sufficient available memory. This allows query processing to proceed efficiently without requiring dictionary creation at query time, while controlling memory overhead through available memory checks.
Solution Approach 2:
The system changes the parameter of dictionary storage by moving dictionaries from permanent table storage to buffer pool caching, and by dynamically adjusting which encoding schemes have pre-created dictionaries based on available memory. This transforms the static memory allocation into a dynamic parameter that adapts to system conditions.
2Adaptability or versatility
If dictionaries are pre-created for all encoding schemes, then any query can be processed, but processing resources are wasted on unused encoding schemes
Solution Approach 1:
The system applies partial action by pre-creating dictionaries only for the most commonly used encoding schemes (such as UTF-8, ASCII, and EBCDIC) rather than all possible encoding schemes. This provides adequate support for typical queries while avoiding the resource wastage of creating and maintaining dictionaries for rare or unused encoding schemes.
Solution Approach 2:
The buffer pool serves multiple functions: it acts as cache for pre-created dictionaries, stores compressed column data, and provides workspace for query execution. This multi-functionality allows the system to support multiple encoding schemes through a single universal caching mechanism rather than requiring separate dedicated storage for each encoding scheme.
3Quantity of substance
If dictionaries are created on-demand, then memory consumption is reduced, but query processing speed decreases
Solution Approach 1:
The system performs preliminary action by pre-creating dictionaries for commonly used encoding schemes and caching them in the buffer pool before queries are executed. This eliminates the need for dictionary creation at query time for these common schemes, maintaining high query processing speed while using memory only when beneficial.
Solution Approach 2:
The system makes the dictionary caching strategy dynamic by checking available memory before pre-creating dictionaries and using cache management policies to evict less frequently used dictionaries when memory pressure occurs. This dynamic approach allows the system to adapt between memory consumption and query speed based on current system conditions.
4Adaptability or versatility
If multiple encoding schemes are supported, then data migration and encoding changes are possible, but dictionary management complexity increases
Solution Approach 1:
The buffer pool serves as a universal caching mechanism for dictionaries of multiple encoding schemes, replacing the need for separate management structures for each encoding. This single universal cache handles UTF-8, ASCII, EBCDIC, and other encoding schemes uniformly, reducing management complexity while maintaining support for multiple encodings.
Solution Approach 2:
The buffer pool acts as an intermediary layer between the compressed column data and the various encoding schemes. Instead of managing dictionaries for each encoding scheme directly, the system uses the buffer pool as a mediator that handles dictionary creation, caching, and retrieval for all encoding schemes, simplifying the overall management architecture.
Data Source
AI summary
In an approach for character encoding, a processor receives a first query involving an attribute, wherein the first query utilizes a value encoded in accordance with a first encoding scheme. A processor identifies a table comprising values of the attribute in a compressed format. A processor creates at least one dictionary associated with the attribute, wherein the at least one new dictionary associated with the attribute maps a compressed value to a corresponding uncompressed value. A processor executes the first query by invoking a conversion operation in a query plan of the first query for decoding one or more queried values of the attribute. A processor fills the at least one new dictionary with one or more decoded query values to create at least one full dictionary. A processors stores the at least one full dictionary in a cache using a predefined cache management policy of the cache.