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Concepts of Query Processing in ADBMS.pptx
1. CONCEPTS OF QUERY PROCESSING
OVERVIEW OF KEY CONCEPTS IN QUERY EXECUTION AND OPTIMIZATION
2. INTRODUCTIONTO QUERY PROCESSING
• Query processing involves the steps and techniques used to translate a high-level query,
typically written in a declarative query language like SQL, into a series of operations that
can be executed by the database management system (DBMS) to retrieve the desired
data.
• Query processing plays a crucial role in database management systems (DBMS) for
several reasons like Efficiency, Performance Optimization, Scalability, Security,
Predictability etc.
• Steps involved in the query processing are Parsing,Translation, Optimization and
Execution.
3. CONVERTING SQL QUERIES INTO RELATIONAL ALGEBRA
• Converting high-level SQL queries into low-level relational algebra expressions involves
several steps, each transforming the query into a more structured and executable form.
• The steps of the process are Parsing,Translation, Logical Query Plan (Relational Algebra),
Optimization, Execution Plan Generation and Execution.
• These steps ensure that a high-level SQL query is systematically converted into low-level
relational algebra, optimized for performance, and executed efficiently by the DBMS.
4. RELATIONAL ALGEBRA OPERATORS
• Relational algebra is a theoretical foundation for manipulating relational databases, and it
comprises a set of operators that take one or two relations as input and produce a new
relation as output. Here’s an overview of the basic relational algebra operators: Selection
( )
σ , Projection (π), Union ( ), Difference ( ), Cartesian Product (×), Join ( ),
∪ − ⨝
Intersection ( ), Rename (
∩ )
ρ , Division (÷).
• These operators form the backbone of relational database query languages and enable
complex data retrieval and manipulation operations. Understanding these operators is
essential for working with relational databases effectively.
5. BASIC ALGORITHMS FOR EXECUTING QUERY OPERATIONS
• Executing query operations in a database involves various algorithms designed to
efficiently process and retrieve data. Here we are going to know some of the basic
algorithms used for executing query operations: Selection Algorithms, Projection
Algorithms, Join Algorithms,Aggregation Algorithms, Set Operations Algorithms and
Cartesian Product Algorithm.
• The key algorithms for the fundamental operations of selection, projection, and join in
relational databases: Selection Algorithms - Linear Search, Binary Search and Index-Based
Selection; Projection Algorithms - Tuple-by-Tuple and Sort-Based Projection; Join
Algorithms - Nested-Loop Join, Block Nested-Loop Join, Index Nested-Loop Join and
Merge Join and Hash Join.
6. QUERY TREES AND QUERY GRAPHS
• Query trees are tree-like structures that represent the sequence of operations needed to execute
a query in a relational database.They visually illustrate the order in which various relational algebra
operations are applied.
• Characteristics - Nodes: Each node represents a relational algebra operation (e.g., selection,
projection, join).Leaves:The leaf nodes represent base relations (tables). Edges: Edges indicate the
flow of data from one operation to the next.
• Query graphs are graphical representations used in query optimization to visualize the
relationships between different parts of a query.They show the flow of data between various query
operations and can help in understanding how different operations interact.
• Characteristics - Nodes: Each node represents a relation (table) or intermediate result. Edges:
Edges represent the operations (e.g., joins, selections) that connect these relations.
7. HEURISTIC OPTIMIZATION OF QUERY TREE
• Heuristic optimization in the context of database systems refers to the use of rule-based
techniques to improve the performance of query processing. Rather than finding the
absolutely optimal execution plan, heuristic optimization aims to find a good enough plan
quickly by applying a set of predefined rules or heuristics.
• Here are some common heuristics used in query optimization: Pushing Selections,
Combining Cartesian Products and Joins, Projection Pushdown, Join Reordering,
Aggregation and Grouping Early, Using Indexes and Eliminating Redundant Operations.
8. FUNCTIONAL DEPENDENCIES
• Functional dependencies are a fundamental concept in the context of relational
databases.They describe relationships between attributes in a relation (table), indicating
that one attribute (or a set of attributes) uniquely determines another attribute (or a set
of attributes).
• A functional dependency, denoted as , exists between two sets of attributes
𝑋→𝑌 𝑋
and in a relation if and only if, for any two tuples 1 and 2 in , whenever
𝑌 𝑅 𝑡 𝑡 𝑅
1[ ]= 2[ ], it must also hold that 1[ ]= 2[ ].In other words, if two tuples have
𝑡 𝑋 𝑡 𝑋 𝑡 𝑌 𝑡 𝑌
the same values for attributes in , they must also have the same values for attributes in
𝑋
.
𝑌
9. NORMAL FORMS
• Database normalization is the process of organizing the attributes and tables of a
relational database to minimize redundancy and dependency. It involves dividing large
tables into smaller, related tables and defining relationships between them to enhance
data integrity and reduce redundancy.
• Normalization involves organizing a database's attributes and tables to minimize
redundancy and dependency.The process is carried out in stages, each corresponding to
a specific normal form. Here's a brief overview of the common normal forms: First
Normal Form (1NF), Second Normal Form (2NF),Third Normal Form (3NF) and Boyce-
Codd Normal Form (BCNF).
10. CONCLUSION
• Optimization is a critical aspect of query processing in database management systems
(DBMS) for several reasons. Here's why optimization holds such immense importance in
ensuring query efficiency: Performance Improvement, Scalability, Cost Reduction, Improved
User Experience, Data Integrity and Accuracy and Energy Efficiency.
• Optimization is indispensable in query processing because it directly impacts performance,
scalability, cost, user experience, data integrity, and energy efficiency. By transforming queries
into the most efficient execution plans, optimization ensures that databases operate
effectively and sustainably, delivering faster and more reliable results.In a world where data
volumes are constantly growing, and user expectations are higher than ever, query
optimization is the key to maintaining efficient, responsive, and cost-effective database
systems.
11. THANKYOU
Presented by (MCA 1-D) Presented to
Aaradhya Dixit Dr. Komal Ma’am
Abhishek Joshi ADBMS
Sagar K 1st
Semester
Lovenesh Sharma
Sakshi Dadheech
Mudit Jha
![FUNCTIONAL DEPENDENCIES
• Functional dependencies are a fundamental concept in the context of relational
databases.They describe relationships between attributes in a relation (table), indicating
that one attribute (or a set of attributes) uniquely determines another attribute (or a set
of attributes).
• A functional dependency, denoted as , exists between two sets of attributes
𝑋→𝑌 𝑋
and in a relation if and only if, for any two tuples 1 and 2 in , whenever
𝑌 𝑅 𝑡 𝑡 𝑅
1[ ]= 2[ ], it must also hold that 1[ ]= 2[ ].In other words, if two tuples have
𝑡 𝑋 𝑡 𝑋 𝑡 𝑌 𝑡 𝑌
the same values for attributes in , they must also have the same values for attributes in
𝑋
.
𝑌](https://image.slidesharecdn.com/conceptsofqueryprocessing-250408160502-620c6c8f/85/Concepts-of-Query-Processing-in-ADBMS-pptx-8-320.jpg)
