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Answering queries using cached data in a key-based data storage environment

IP.com Disclosure Number: IPCOM000015093D
Original Publication Date: 2002-Oct-03
Included in the Prior Art Database: 2003-Jun-20
Document File: 1 page(s) / 39K

Publishing Venue

IBM

Abstract

Answering Queries using Cached Data in a Key-Based Data Storage Environment Traditional query answering always tries to answer queries by using data in database which in a multitier environment requires cached data to be flushed back to database before answering queries . We implement a new strategy to answer queries of specific patterns by looking directly into the cached data for applications when every data entity is with its unique key. This improves query performance as no overhead is needed in flushing back the cached data. Caching data is a common strategy used in client-server computing which is usually a 2 tier environment. Multitier computing environment is a new computing paradigm evolved from 2 tier environment. In contrast, we detect particular query patterns in order to answer these queries using cached data in a key-based data storage environment. The proposed solution is targeted for a multi-tier computing environment where the middle tier server caches data and every data entity in the cache and backend database system is with its unique key. The cache system in the middle tier needs to maintain parent-child relationships of data entities. The solution enhances the capability of the middle tier by solving queries directly looking in cached data, and it consists of the

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Answering queries using cached data in a key-based data storage environment

Answering Queries using Cached Data in a Key-Based Data Storage Environment

Traditional query answering always tries to answer queries by using data in database which in a multitier environment requires cached data to be flushed back to database before answering queries . We implement a new strategy to answer queries of specific patterns by looking directly into the cached data for applications when every data entity is with its unique key. This improves query performance as no overhead is needed in flushing back the cached data.

Caching data is a common strategy used in client-server computing which is usually a 2 tier environment. Multitier computing environment is a new computing paradigm evolved from 2 tier environment. In contrast, we detect particular query patterns in order to answer these queries using cached data in a key-based data storage environment.

The proposed solution is targeted for a multi-tier computing environment where the middle tier server caches data and every data entity in the cache and backend database system is with its unique key. The cache system in the middle tier needs to maintain parent-child relationships of data entities. The solution enhances the capability of the middle tier by solving queries directly looking in cached data, and it consists of the
following steps: 1) detecting the following patterns of queries:

-- queries for retrieving data entity wi...