Distributed Database Systems

4.

Distributed Query Processing

4.1.

Overview of Query Processing

4.1.1.

Query Decomposition

4.1.2.

Data Localization

4.1.3.

Global Query Optimization

4.1.4.

Local Query Optimization

4.1.5.

Query Execution

4.2.

Query Decomposition Steps

4.2.1.

Parsing and Validation

4.2.2.

Query Normalization

4.2.3.

Semantic Analysis

4.2.4.

Simplification and Restructuring

4.2.5.

Query Graph Generation

4.2.6.

Algebraic Optimization

4.3.

Data Localization

4.3.1.

Mapping Global Queries to Local Fragments

4.3.2.

Fragment Query Generation

4.3.3.

Localization Program

4.3.4.

Fragment Substitution

4.4.

Global Query Optimization

4.4.1.

Objective Function

4.4.1.1.

4.4.1.2.

4.4.1.3.

Communication Costs

4.4.1.4.

4.4.2.

Search Space of Execution Plans

4.4.2.1.

Plan Enumeration

4.4.2.2.

Heuristic Approaches

4.4.2.3.

Dynamic Programming

4.4.3.

Optimization Strategies

4.4.3.1.

Centralized Optimization

4.4.3.2.

Distributed Optimization

4.4.3.3.

Hybrid Optimization

4.4.4.

4.4.4.1.

Statistical Cost Models

4.4.4.2.

Parametric Cost Models

4.5.

Local Query Optimization

4.5.1.

Local Plan Generation

4.5.2.

Local Cost Estimation

4.5.3.

Local Execution Strategies

4.6.

Distributed Join Strategies

4.6.1.

Nested Loop Join

4.6.2.

Sort-Merge Join

4.6.3.

4.6.4.

Semijoin Operation

4.6.4.1.

Reducing Data Transfer

4.6.4.2.

Semijoin Variants

4.6.4.3.

4.6.5.

Ship Operations

4.6.5.1.

Ship Whole Relations

4.6.5.2.

4.6.5.3.

4.6.6.

4.6.7.

Parallel Join Execution

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3. Data Distribution Design

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5. Distributed Transaction Management