![]() Examples include Oracle's shared pool/library cache, and SQL Server's and Sybase's SQL/Procedure caches.ĭata caches are the most easily understood memory cache of databases, with the contents being (surprise!), application data. The amount of CPU savings from such caches can indeed be very large. The goal of code caches is to reuse repetitive SQL and procedural code statements so only soft parsing (parsing without access plan generation, other miscellaneous steps, and loading into the cache) is done. Working from the bottom up, metadata caches are standard across nearly all relational systems and hold system reference data, with examples being Oracle's dictionary cache (contained within its shared pool), the MySQL table cache, and the MySQL InnoDB storage engine's dictionary cache.Ĭode caches are used to primarily lessen the impact of "hard parse" activity where, after SQL and stored code statements are initially executed and checked both syntactically and for security, the sometimes costly process of generating access plans is performed. There are more memory structures used by databases, but the three mentioned above represent the bulk of a RDBMS system's RAM demands. Metadata caches that keep reference data such as object structure information, security information, and more.Code caches that retain often-executed SQL or procedural code.Data caches that hold often-referenced application data.Generally speaking, there are normally three types of global caches used by RDBMS systems: Database Vendor Memory Caching StrategiesĪ detailed discussion of how the popular database vendors implement their caching strategies could easily result in a lengthy work, so we will just quickly look at the subject in a broad way. This paper compares the memory caching strategies used by a number of database vendors with MySQL, and then focuses on the MySQL query cache with a discussion of why its unique approach to memory caching can pay handsome performance dividends when correctly used by database administrators and performance analysts. While certainly not free, accessing application data, query plans, or database metadata in RAM is normally much quicker than repetitively retrieving that same information from disk or building it from scratch. All robust relational database management systems utilize memory caching to help improve the overall responsiveness of their underlying engine.
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