Query optimization could be static or dynamic. In this paper, we review static and several dynamic optimization strategies for autonomous and non-autonomous distributed database system. In a static optimization strategy, a given query is parsed, validated, optimized once and stored in the database. Dynamic optimization strategy works in bottom-up

In this work we present a multiple query optimization on homogeneous distributed database application through dynamic programming for semi optimal solution. Keywards: Distributedinformation retrieval (DIR), Multiple query optimization” (MQO)

Apr 25, 2019 · In this work we present a multiple query optimization on homogeneous distributed database application through dynamic programming for semi optimal solution.

Our experimental results show that this reformulation of non-inner joins as complex predicates can improve optimization time by orders of magnitude, com-pared to known algorithms dealing with complex join pred-icates and non-inner joins. Once again, this gives dynamic programming a distinct advantage over current memoization techniques. 1.

Cost difference between evaluation plans for a query can be enormous • E.g. seconds vs. days in some cases Steps in cost-based query optimization 1. Generate logically equivalent expressions using equivalence rules 2. Annotate resultant expressions to get alternative query plans 3. Choose the cheapest plan based on estimated cost

• Output: A good physical query plan • Basic query optimization algorithm – Enumerate alternative plans (logical and physical) – Compute estimated cost of each plan • Compute number of I/Os •Optionally take into account other resources – Choose plan with lowest cost – This is called cost-based optimization

Mar 1, 2000 · In this paper, we present and thoroughly evaluate a new class of query optimization algorithms that are based on a principle that we call iterative dynamic programming, or IDP for short.

Jul 7, 2011 · Extensive research has been done for query optimization in distributed databases. Numerous optimization strategies like static, dynamic and randomized strategies have been proposed for determining an optimal plan.

Nov 15, 2004 · Introduction The “multiple query optimization” (MQO) prob- lem has been studied in the database literature since 1980s. MQO tries to reduce the execution cost of a group of queries by performing common tasks only once, whereas traditional query optimization consid- ers a single query at a time.

Query optimization in distributed databases explicitly needed in many aspects of the optimization process, often making it imperative for the optimizer to consult underlying data sources while doing cost based optimization.