free barcode generator in asp.net c# THE ANATOMY OF A DATABASE SYSTEM in Font

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CHAPTER 2 THE ANATOMY OF A DATABASE SYSTEM
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+-----------+-------------------+ | last_name | certificate_level | +-----------+-------------------+ | BELL | P | | BELL | S | | BELL | Y | | BELL | P | | BELL | S | +-----------+-------------------+ 5 rows in set (0.61 sec)
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mysql> SELECT SQL_CACHE professionals.last_name, certifications.certificate_level FROM professionals JOIN certifications ON professionals.unique_no = certifications.unique_no WHERE professionals.med_class > 1 AND certifications.last_name = 'Bell'; +-----------+-------------------+ | last_name | certificate_level | +-----------+-------------------+ | BELL | P | | BELL | S | | BELL | Y | | BELL | P | | BELL | S | +-----------+-------------------+ 5 rows in set (0.61 sec) mysql>
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The caching and buffers subsystem is responsible for ensuring that the most frequently used data (or structures, as you will see) are available in the most efficient manner possible. In other words, the data must be resident or ready to read at all times. The caches dramatically increase the response time for requests for that data because the data is in memory and thus no additional disk access is necessary to retrieve it. The cache subsystem was created to encapsulate all of the caching and buffering into a loosely coupled set of library functions. Although you will find the caches implemented in several different source code files, they are considered part of the same subsystem. A number of caches are implemented in this subsystem. Most of the cache mechanisms use the same or similar concept of storing data as structures in a linked list. The caches are implemented in different portions of the code to tailor the implementation to the type of data that is being cached. Let s look at each of the caches.
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CHAPTER 2 THE ANATOMY OF A DATABASE SYSTEM
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The table cache was created to minimize the overhead in opening, reading, and closing tables (the .FRM files on disk). For this reason, the table cache is designed to store metadata about the tables in memory. This makes it much faster for a thread to read the schema of the table without having to reopen the file every time. Each thread has its own list of table cache structures. This permits the threads to maintain their own views of the tables so that if one thread is altering the schema of a table (but has not committed the changes) another thread may use that table with the original schema. The structure used is a simple one that includes all of the metadata information for a table. The structures are stored in a linked list in memory and associated with each thread.
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Record Cache
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The record cache was created to enhance sequential reads from the storage engines. Thus the record cache is usually only used during table scans. It works like a read-ahead buffer by retrieving a block of data at a time, thus resulting in fewer disk accesses during the scan. Fewer disk accesses generally equates to improved performance. Interestingly, the record cache is also used in writing data sequentially by writing the new (or altered) data to the cache first and then writing the cache to disk when full. In this way write performance is improved as well. This sequential behavior (called locality of reference) is the main reason the record cache is most often used with the MyISAM storage engine, although it is not limited to MyISAM. The record cache is implemented in an agnostic manner that doesn t interfere with the code used to access the storage engine API. Developers don t have to do anything to take advantage of the record cache as it is implemented within the layers of the API.
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Key Cache
The key cache is a buffer for frequently used index data. In this case, it is a block of data for the index file (B-tree) and is used exclusively for MyISAM tables (the .MYI files on disk). The indexes themselves are stored as linked lists within the key cache structure. A key cache is created when a MyISAM table is opened for the first time. The key cache is accessed on every index read. If an index is found in the cache, it is read from there; otherwise, a new index block must be read from disk and placed into the cache. However, the cache has a limited size and is tunable by changing the key_cache_block_size configuration variable. Thus not all blocks of the index file will fit into memory. So how does the system keep track of which blocks have been used The cache implements a monitoring system to keep track of how frequent the index blocks are used. The key cache has been implemented to keep track of how warm the index blocks are. Warm in this case refers to how many times the index block has been accessed over time. Values for warm include BLOCK_COLD, BLOCK_WARM, and BLOCK_HOT. As the blocks cool off and new blocks become warm, the cold blocks are purged and the warm blocks added. This strategy is a least recently used (LRU) page-replacement strategy the same algorithm used for virtual memory management and disk buffering in operating systems that has been proven to be remarkably efficient even in the face of much more sophisticated page-replacement algorithms. In a similar way, the key cache keeps track of the index blocks that have changed (called getting dirty ). When a dirty block is purged, its data is written back to the index file on disk before being replaced. Conversely, when a clean block is purged it is simply removed from memory.
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