Ingres Algorithm Distributed Database

0 Distributed database E Relational envelope and select assemblv site Distributed execution of reducer S, Assembly site 92 - t-l D ' Superset of database I needed to compute QD Step 3 4 Fig. 6. Main steps of query processing algorithm. ACM Transactions on Database Systems, Vol. 6, No. 4, December 1981.

Distributed Ingres' distributed query optimization algorithm deterministically explores the search space of possible plans by making local optimization decisions at each step. Distributed Ingres supports horizontal fragmentation. The objective function is a weighted combination of total time cost and response time.

In this research, the performance of the centralized and the distributed INGRES algorithm is studied in distributed database environment. Distributed INGRES takes into consideration both communication costs and local processing costs, allowing relations to be fragmented among multiple sites 2. Consider an input query Q

In addition, the algorithm can optimize separately for two models of a communi- cation network representing respectively ARPANET and ETHERNET like networks. This algorithm is being implemented as part of the INGRES data base system. KEYWORDS AND PHRASES Distributed databases,. relational model, distributed

distributed databases environment. Keywords Query Optimization, caching, query execution, Hill Climbing Algorithm, Ingres Algorithm. 1. Introduction . Given a query, there are many plans that a database management system DBMS can take to process the query and produce result. All these plans are equivalent in terms

Distributed-INGRES dynamically generates query execution plans at run-time using the available information e.g. number of records returned in the intermediate results. R, SDD-1 and Genetic algorithm GA 21 did not consider horizontal or vertical fragments, while Distributed-INGRES and our New Genetic Algorithm

Distributed DBMS Features 70's and 80's, three main prototypes - SDD-1, distributed INGRES, and R Main components of a distributed DBMS - Defining data placement and fragmentation - Distributed catalog - Distributed query optimization today - Distributed transactions next lecture

reliability. Distributed database systems DDBS and distributed computing systems DCS differ in the resources to be shared. DCS share hard disks and printers etc. while DDBS distribute data, where the data as well as operations on the data items are equally important 3 . Since data are geographically distributed in such a distributed

Distributed query processing involves the retrieving of data from physically distributed databases that provide the view of a single logical database to users. It has a number of objectives as listed below. This section introduces three global query optimization algorithms, namely, distributed INGRES algorithm, R algorithm and SDD-1

These methods include the algorithms used in SDD-1, in Distributed INGRES, and those proposed by Hevner-Yao. A general framework for query optimization is also discussed. The objective function of most of the distributed query optimization strategies is the minimization of the use of network resources.