Storage Retrieval

Download Database Tuning: Principles, Experiments, and by Dennis Shasha, Philippe Bonnet PDF

By Dennis Shasha, Philippe Bonnet

Tuning your database for optimum functionality capacity greater than following a number of brief steps in a vendor-specific consultant. for optimum development, you wish a large and deep wisdom of uncomplicated tuning ideas, the facility to assemble facts in a scientific method, and the ability to make your procedure run speedier. this can be an paintings in addition to a technological know-how, and Database Tuning: rules, Experiments, and Troubleshooting ideas may also help you advance transportable abilities that might let you track a large choice of database structures on a mess of and working structures. additional, those talents, mixed with the scripts supplied for validating effects, are precisely what you must evaluation competing database items and to decide on the appropriate one. * ahead by way of Jim grey, with invited chapters by way of Joe Celko and Alberto Lerner* contains business contributions through invoice McKenna (RedBrick/Informix), Hany Saleeb (Oracle), Tim Shetler (TimesTen), Judy Smith (Deutsche Bank), and Ron Yorita (IBM)* Covers the total process surroundings: undefined, working method, transactions, indexes, queries, desk layout, and alertness research* comprises experiments (scripts to be had at the author's website) that can assist you confirm a system's effectiveness on your personal atmosphere* offers unique subject matters, together with info warehousing, internet help, major reminiscence databases, really good databases, and monetary time sequence* Describes performance-monitoring ideas that can assist you realize and troubleshoot difficulties

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Additional resources for Database Tuning: Principles, Experiments, and Troubleshooting Techniques

Example text

Further, different reads by a single transaction to the same data will not be repeatable, that is, they may return different values. Writes may overwrite the dirty data of other transactions. A transaction holds a write lock on x while writing x, then releases the lock immediately thereafter. 2. Degree l~read uncommitted: Reads may read dirty data and will not be repeatable. Writes may not overwrite other transactions' dirty data. 3. Degree2~read committed: Read~ may access only committed data, but reads are still not repeatable because an access to a data item x at time T2 may read from a different committed transaction than the earlier access to x at TI.

The net result is that sending a 1-kilobyte packet will be little more expensive than sending a 1-byte packet. This implies that it is good to send large chunks of data rather than small ones. The cost of parsing, performing semantic analysis, and selecting access paths for even simple queries is significant (more than 10,000 instructions on most systems). This suggests that often executed queries should be compiled. Suppose that a program in a standard programming language such as C++, Java, perl, COBOL, or PL/1 makes calls to a database system.

EXAMPLE: AIRLINE RESERVATIONS A reservation involves three steps. 1. Retrieve the list of seats available. 2. Determine which seat the customer wants. 3. Secure that seat. If all this were encapsulated in a single transaction, then that transaction would hold the lock on the list of seats in a given plane while a reservations agent talks to a customer. At busy times, many other customers and agents might be made to wait. To avoid this intolerable situation, airline reservation systems break up the act of booking a seat into two transactions and a nontransactional interlude.

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