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Showing posts from October, 2017

Understanding database [3] : Buffer algorithms

Understanding database 3 : Buffer algorithms As we use buffers to boost up our performance, it is also necessary for us to choose a suitable algorithm for our buffer to follow. With formal expression, the ‘ access pattern ’  is the key of ensuring the number of I/Os to be controlled, which has a massive impact on the performance of execution. We introduce the formula for read efficiency here, noted as (number of page requests - physical I/Os) /(number of page requests) And we should also aim for above 0 .8 or 80% for an adequate efficiency. We have 4 basic policies to decide for replacing frames within a buffer, including First in first out (FIFO) ->oldest leaves Least recently used (LRU)          <--------------------------- most common ->frame with oldest access leaves Most recently used (MRU) ->frame with freshest access leaves Least frequently used (LFU) ->frame with least access count leaves Most database management systems wo

Understanding database [2] : Buffer Manager

Understanding database 2 : Buffer manager Continuing from the previous chapter, we will now talk more about how the buffer would work when a request to the database is executed. We consider there are frames of data which consists of records that are being stored in the buffer pool, some filled and some empty. The database management system would send a message to the buffer manager when it needs to request a page from disk, and the buffer may or may not have the requested page within the buffer. The page consists of records, and is being stored as frames in the pool. If our requested page is not in the pool, we will first look for an empty frame. If we could grab an empty one, great, but if not, we will have to replace one of the frames for the current execution. The frame must not be ‘ pinned ’ , namely it must not be in use at the moment. The pinning of a frame arrives when the page is in the pool(may exist already before, or it may have just been pulled in to the pool).

Understanding database [1] : Storage layers

Note: This series of posts are more for the personal interpretation of uni taught materials, please make corrections if anything is appearing to be incorrect or unclear. _____ Understanding database : Storage layers For a database, its obvious that we will have to store data within some storing sheds which may allow us to access previous information that we have recorded. For gamers, its really often that we may see the word RAM, or HDD and SSD which are terms that represent data storing mediums. We often HDD as secondary storage, as it is relatively cheaper,slower but more stable than RAM. Moreover, tertiary storage also exists in the form of tapes etc. They are one step more cheaper than secondary storage. We may classify our secondary storage as disks. The data within disks are stored in units, and at the same time being retrieved in units as well. We call these units the disk pages. We may consider the accessing latency as a pyramid : from the top its cache, with th