SlideShare a Scribd company logo
1. Query Processing
2. Translating SQL queries into RA
3. Evaluation Plan

4. Query Execution
5. Query Optimization
6. Translation Rules
7. Cost Estimations
1. Query Processing
1. Query Processing
▪ Aim of query processing
- to find information in one or more databases,
- and deliver it to the user quickly and efficiently.
- to choose the most cost effective.
▪ Translation of queries
- into expressions that can be used at physical level of file system.
- Includes query optimization and query evaluation.
1. Query Processing
1. Query Processing
▪ Typical steps when processing a high-level query (e.g. SQL query)
Query tree
internal representation
of the query
Execution strategy
how to retrieve
results of query
2. Translating SQL queries into RA
2. Translating SQL queries into RA
▪ Translate query into its internal form.
- This is then translated into Relational Algebra(RA).
- The parser checks syntax, verifies relations.
▪ A RA expression may have many equivalent expressions.
▪ Example
Σbalance<2500(πbalance(account))
Is equivalent to
Πbalance(σbalance<2500(account))

Each relational algebra operation can be evaluated using one of
several different algorithms. Correspondingly, a relational-algebra
expression can be evaluated in many ways.
3. Evaluation Plan
3. Evaluation Plan
▪ Annotated expression specifying detailed evaluation strategy.
▪ Example
Use an index on balance to find accounts with balance < 2500,
Or perform complete relation scan and discard accounts with balance ≥ 2500.
Initial canonical query tree
Book (access#, title)
Member (ticket#, name)
Loan(loanedbook,loanedto)

Select member.name
rom book, loan, member
where book.title = "dracula"
and member.ticket# = loan.loanedto
and loan.loanedbook = book.access#
4. Query Execution
4. Query Execution
For each operation (join, select, project, aggregation …)
- Typical algorithms (e.g. Binary search for simple selection)
- Specific or not to storage structure and access paths
Book (access#, title)
Member (ticket#, name)
Loan(loanedbook,loanedto)

Select member.name
From book, loan, member
where book.title = "dracula"
and member.ticket# = loan.loanedto
and loan.loanedbook = book.access#
4. Query Execution
4. Query Execution
Ad

More Related Content

Similar to 1 query processing (20)

Ch-2-Query-Process.pptx advanced database
Ch-2-Query-Process.pptx advanced databaseCh-2-Query-Process.pptx advanced database
Ch-2-Query-Process.pptx advanced database
tasheebedane
 
700442110-advanced database Ch-2-Query-Process.pptx
700442110-advanced database Ch-2-Query-Process.pptx700442110-advanced database Ch-2-Query-Process.pptx
700442110-advanced database Ch-2-Query-Process.pptx
tasheebedane
 
Query processing
Query processingQuery processing
Query processing
Ravinder Kamboj
 
LECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptx
LECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptxLECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptx
LECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptx
AthosBeatus
 
Concepts of Query Processing in ADBMS.pptx
Concepts of Query Processing in ADBMS.pptxConcepts of Query Processing in ADBMS.pptx
Concepts of Query Processing in ADBMS.pptx
AaradhyaDixit6
 
Query optimization and performance
Query optimization and performanceQuery optimization and performance
Query optimization and performance
fika sweety
 
Query optimization and performance
Query optimization and performanceQuery optimization and performance
Query optimization and performance
fika sweety
 
Query optimization and processing for advanced database systems
Query optimization and processing for advanced database systemsQuery optimization and processing for advanced database systems
Query optimization and processing for advanced database systems
meharikiros2
 
ch02-240507064009-ac337bf1 .ppt
ch02-240507064009-ac337bf1             .pptch02-240507064009-ac337bf1             .ppt
ch02-240507064009-ac337bf1 .ppt
iamayesha2526
 
CH5_Query Processing and Optimization.pdf
CH5_Query Processing and Optimization.pdfCH5_Query Processing and Optimization.pdf
CH5_Query Processing and Optimization.pdf
amariyarana
 
Overview of query evaluation
Overview of query evaluationOverview of query evaluation
Overview of query evaluation
avniS
 
QueryProcessingAndOptimization-Part 1.pptx
QueryProcessingAndOptimization-Part 1.pptxQueryProcessingAndOptimization-Part 1.pptx
QueryProcessingAndOptimization-Part 1.pptx
ISHAAGARWAL75
 
Mc seminar
Mc seminarMc seminar
Mc seminar
Ankit Anand
 
DB LECTURE 5 QUERY PROCESSING.pptx
DB LECTURE 5 QUERY        PROCESSING.pptxDB LECTURE 5 QUERY        PROCESSING.pptx
DB LECTURE 5 QUERY PROCESSING.pptx
grahamoyigo19
 
Presentación Oracle Database Migración consideraciones 10g/11g/12c
Presentación Oracle Database Migración consideraciones 10g/11g/12cPresentación Oracle Database Migración consideraciones 10g/11g/12c
Presentación Oracle Database Migración consideraciones 10g/11g/12c
Ronald Francisco Vargas Quesada
 
Query Decomposition and data localization
Query Decomposition and data localization Query Decomposition and data localization
Query Decomposition and data localization
Hafiz faiz
 
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...
Thanh Tran
 
Expressive Querying of Semantic Databases with Incremental Query Rewriting
Expressive Querying of Semantic Databases with Incremental Query RewritingExpressive Querying of Semantic Databases with Incremental Query Rewriting
Expressive Querying of Semantic Databases with Incremental Query Rewriting
Alexandre Riazanov
 
Distributed DBMS - Unit 6 - Query Processing
Distributed DBMS - Unit 6 - Query ProcessingDistributed DBMS - Unit 6 - Query Processing
Distributed DBMS - Unit 6 - Query Processing
Gyanmanjari Institute Of Technology
 
Lecture 5.pptx
Lecture 5.pptxLecture 5.pptx
Lecture 5.pptx
Shafii8
 
Ch-2-Query-Process.pptx advanced database
Ch-2-Query-Process.pptx advanced databaseCh-2-Query-Process.pptx advanced database
Ch-2-Query-Process.pptx advanced database
tasheebedane
 
700442110-advanced database Ch-2-Query-Process.pptx
700442110-advanced database Ch-2-Query-Process.pptx700442110-advanced database Ch-2-Query-Process.pptx
700442110-advanced database Ch-2-Query-Process.pptx
tasheebedane
 
LECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptx
LECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptxLECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptx
LECTURE_06_DATABASE PROCESSING & OPTIMAZATION.pptx
AthosBeatus
 
Concepts of Query Processing in ADBMS.pptx
Concepts of Query Processing in ADBMS.pptxConcepts of Query Processing in ADBMS.pptx
Concepts of Query Processing in ADBMS.pptx
AaradhyaDixit6
 
Query optimization and performance
Query optimization and performanceQuery optimization and performance
Query optimization and performance
fika sweety
 
Query optimization and performance
Query optimization and performanceQuery optimization and performance
Query optimization and performance
fika sweety
 
Query optimization and processing for advanced database systems
Query optimization and processing for advanced database systemsQuery optimization and processing for advanced database systems
Query optimization and processing for advanced database systems
meharikiros2
 
ch02-240507064009-ac337bf1 .ppt
ch02-240507064009-ac337bf1             .pptch02-240507064009-ac337bf1             .ppt
ch02-240507064009-ac337bf1 .ppt
iamayesha2526
 
CH5_Query Processing and Optimization.pdf
CH5_Query Processing and Optimization.pdfCH5_Query Processing and Optimization.pdf
CH5_Query Processing and Optimization.pdf
amariyarana
 
Overview of query evaluation
Overview of query evaluationOverview of query evaluation
Overview of query evaluation
avniS
 
QueryProcessingAndOptimization-Part 1.pptx
QueryProcessingAndOptimization-Part 1.pptxQueryProcessingAndOptimization-Part 1.pptx
QueryProcessingAndOptimization-Part 1.pptx
ISHAAGARWAL75
 
DB LECTURE 5 QUERY PROCESSING.pptx
DB LECTURE 5 QUERY        PROCESSING.pptxDB LECTURE 5 QUERY        PROCESSING.pptx
DB LECTURE 5 QUERY PROCESSING.pptx
grahamoyigo19
 
Presentación Oracle Database Migración consideraciones 10g/11g/12c
Presentación Oracle Database Migración consideraciones 10g/11g/12cPresentación Oracle Database Migración consideraciones 10g/11g/12c
Presentación Oracle Database Migración consideraciones 10g/11g/12c
Ronald Francisco Vargas Quesada
 
Query Decomposition and data localization
Query Decomposition and data localization Query Decomposition and data localization
Query Decomposition and data localization
Hafiz faiz
 
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-S...
Thanh Tran
 
Expressive Querying of Semantic Databases with Incremental Query Rewriting
Expressive Querying of Semantic Databases with Incremental Query RewritingExpressive Querying of Semantic Databases with Incremental Query Rewriting
Expressive Querying of Semantic Databases with Incremental Query Rewriting
Alexandre Riazanov
 
Lecture 5.pptx
Lecture 5.pptxLecture 5.pptx
Lecture 5.pptx
Shafii8
 

More from Mr Patrick NIYISHAKA (20)

Summary
SummarySummary
Summary
Mr Patrick NIYISHAKA
 
3 summary
3 summary3 summary
3 summary
Mr Patrick NIYISHAKA
 
2 ddb architecture
2 ddb architecture2 ddb architecture
2 ddb architecture
Mr Patrick NIYISHAKA
 
1 ddb
1 ddb1 ddb
1 ddb
Mr Patrick NIYISHAKA
 
2 countermeasures
2 countermeasures2 countermeasures
2 countermeasures
Mr Patrick NIYISHAKA
 
2 countermeasures
2 countermeasures2 countermeasures
2 countermeasures
Mr Patrick NIYISHAKA
 
3 summary
3 summary3 summary
3 summary
Mr Patrick NIYISHAKA
 
1 db security
1 db security1 db security
1 db security
Mr Patrick NIYISHAKA
 
4 summary
4 summary4 summary
4 summary
Mr Patrick NIYISHAKA
 
3 summary
3 summary3 summary
3 summary
Mr Patrick NIYISHAKA
 
2 con control
2 con control2 con control
2 con control
Mr Patrick NIYISHAKA
 
1 con exe
1 con exe1 con exe
1 con exe
Mr Patrick NIYISHAKA
 
1 basic concepts
1 basic concepts1 basic concepts
1 basic concepts
Mr Patrick NIYISHAKA
 
2 recovery
2 recovery2 recovery
2 recovery
Mr Patrick NIYISHAKA
 
3 transaction
3 transaction3 transaction
3 transaction
Mr Patrick NIYISHAKA
 
3 summary
3 summary3 summary
3 summary
Mr Patrick NIYISHAKA
 
1 query processing
1 query processing1 query processing
1 query processing
Mr Patrick NIYISHAKA
 
2 optimization
2 optimization2 optimization
2 optimization
Mr Patrick NIYISHAKA
 
2 collision
2 collision2 collision
2 collision
Mr Patrick NIYISHAKA
 
4 summary
4 summary4 summary
4 summary
Mr Patrick NIYISHAKA
 
Ad

Recently uploaded (20)

2025-05-Q4-2024-Investor-Presentation.pptx
2025-05-Q4-2024-Investor-Presentation.pptx2025-05-Q4-2024-Investor-Presentation.pptx
2025-05-Q4-2024-Investor-Presentation.pptx
Samuele Fogagnolo
 
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfThe Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
Abi john
 
Dev Dives: Automate and orchestrate your processes with UiPath Maestro
Dev Dives: Automate and orchestrate your processes with UiPath MaestroDev Dives: Automate and orchestrate your processes with UiPath Maestro
Dev Dives: Automate and orchestrate your processes with UiPath Maestro
UiPathCommunity
 
AI and Data Privacy in 2025: Global Trends
AI and Data Privacy in 2025: Global TrendsAI and Data Privacy in 2025: Global Trends
AI and Data Privacy in 2025: Global Trends
InData Labs
 
Greenhouse_Monitoring_Presentation.pptx.
Greenhouse_Monitoring_Presentation.pptx.Greenhouse_Monitoring_Presentation.pptx.
Greenhouse_Monitoring_Presentation.pptx.
hpbmnnxrvb
 
How Can I use the AI Hype in my Business Context?
How Can I use the AI Hype in my Business Context?How Can I use the AI Hype in my Business Context?
How Can I use the AI Hype in my Business Context?
Daniel Lehner
 
Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...
Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...
Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...
BookNet Canada
 
Big Data Analytics Quick Research Guide by Arthur Morgan
Big Data Analytics Quick Research Guide by Arthur MorganBig Data Analytics Quick Research Guide by Arthur Morgan
Big Data Analytics Quick Research Guide by Arthur Morgan
Arthur Morgan
 
tecnologias de las primeras civilizaciones.pdf
tecnologias de las primeras civilizaciones.pdftecnologias de las primeras civilizaciones.pdf
tecnologias de las primeras civilizaciones.pdf
fjgm517
 
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc
 
TrsLabs - Fintech Product & Business Consulting
TrsLabs - Fintech Product & Business ConsultingTrsLabs - Fintech Product & Business Consulting
TrsLabs - Fintech Product & Business Consulting
Trs Labs
 
Generative Artificial Intelligence (GenAI) in Business
Generative Artificial Intelligence (GenAI) in BusinessGenerative Artificial Intelligence (GenAI) in Business
Generative Artificial Intelligence (GenAI) in Business
Dr. Tathagat Varma
 
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager API
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPath Community Berlin: Orchestrator API, Swagger, and Test Manager API
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager API
UiPathCommunity
 
Complete Guide to Advanced Logistics Management Software in Riyadh.pdf
Complete Guide to Advanced Logistics Management Software in Riyadh.pdfComplete Guide to Advanced Logistics Management Software in Riyadh.pdf
Complete Guide to Advanced Logistics Management Software in Riyadh.pdf
Software Company
 
Quantum Computing Quick Research Guide by Arthur Morgan
Quantum Computing Quick Research Guide by Arthur MorganQuantum Computing Quick Research Guide by Arthur Morgan
Quantum Computing Quick Research Guide by Arthur Morgan
Arthur Morgan
 
Splunk Security Update | Public Sector Summit Germany 2025
Splunk Security Update | Public Sector Summit Germany 2025Splunk Security Update | Public Sector Summit Germany 2025
Splunk Security Update | Public Sector Summit Germany 2025
Splunk
 
Mobile App Development Company in Saudi Arabia
Mobile App Development Company in Saudi ArabiaMobile App Development Company in Saudi Arabia
Mobile App Development Company in Saudi Arabia
Steve Jonas
 
Heap, Types of Heap, Insertion and Deletion
Heap, Types of Heap, Insertion and DeletionHeap, Types of Heap, Insertion and Deletion
Heap, Types of Heap, Insertion and Deletion
Jaydeep Kale
 
How analogue intelligence complements AI
How analogue intelligence complements AIHow analogue intelligence complements AI
How analogue intelligence complements AI
Paul Rowe
 
Andrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell
 
2025-05-Q4-2024-Investor-Presentation.pptx
2025-05-Q4-2024-Investor-Presentation.pptx2025-05-Q4-2024-Investor-Presentation.pptx
2025-05-Q4-2024-Investor-Presentation.pptx
Samuele Fogagnolo
 
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfThe Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdf
Abi john
 
Dev Dives: Automate and orchestrate your processes with UiPath Maestro
Dev Dives: Automate and orchestrate your processes with UiPath MaestroDev Dives: Automate and orchestrate your processes with UiPath Maestro
Dev Dives: Automate and orchestrate your processes with UiPath Maestro
UiPathCommunity
 
AI and Data Privacy in 2025: Global Trends
AI and Data Privacy in 2025: Global TrendsAI and Data Privacy in 2025: Global Trends
AI and Data Privacy in 2025: Global Trends
InData Labs
 
Greenhouse_Monitoring_Presentation.pptx.
Greenhouse_Monitoring_Presentation.pptx.Greenhouse_Monitoring_Presentation.pptx.
Greenhouse_Monitoring_Presentation.pptx.
hpbmnnxrvb
 
How Can I use the AI Hype in my Business Context?
How Can I use the AI Hype in my Business Context?How Can I use the AI Hype in my Business Context?
How Can I use the AI Hype in my Business Context?
Daniel Lehner
 
Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...
Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...
Transcript: #StandardsGoals for 2025: Standards & certification roundup - Tec...
BookNet Canada
 
Big Data Analytics Quick Research Guide by Arthur Morgan
Big Data Analytics Quick Research Guide by Arthur MorganBig Data Analytics Quick Research Guide by Arthur Morgan
Big Data Analytics Quick Research Guide by Arthur Morgan
Arthur Morgan
 
tecnologias de las primeras civilizaciones.pdf
tecnologias de las primeras civilizaciones.pdftecnologias de las primeras civilizaciones.pdf
tecnologias de las primeras civilizaciones.pdf
fjgm517
 
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...
TrustArc
 
TrsLabs - Fintech Product & Business Consulting
TrsLabs - Fintech Product & Business ConsultingTrsLabs - Fintech Product & Business Consulting
TrsLabs - Fintech Product & Business Consulting
Trs Labs
 
Generative Artificial Intelligence (GenAI) in Business
Generative Artificial Intelligence (GenAI) in BusinessGenerative Artificial Intelligence (GenAI) in Business
Generative Artificial Intelligence (GenAI) in Business
Dr. Tathagat Varma
 
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager API
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPath Community Berlin: Orchestrator API, Swagger, and Test Manager API
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager API
UiPathCommunity
 
Complete Guide to Advanced Logistics Management Software in Riyadh.pdf
Complete Guide to Advanced Logistics Management Software in Riyadh.pdfComplete Guide to Advanced Logistics Management Software in Riyadh.pdf
Complete Guide to Advanced Logistics Management Software in Riyadh.pdf
Software Company
 
Quantum Computing Quick Research Guide by Arthur Morgan
Quantum Computing Quick Research Guide by Arthur MorganQuantum Computing Quick Research Guide by Arthur Morgan
Quantum Computing Quick Research Guide by Arthur Morgan
Arthur Morgan
 
Splunk Security Update | Public Sector Summit Germany 2025
Splunk Security Update | Public Sector Summit Germany 2025Splunk Security Update | Public Sector Summit Germany 2025
Splunk Security Update | Public Sector Summit Germany 2025
Splunk
 
Mobile App Development Company in Saudi Arabia
Mobile App Development Company in Saudi ArabiaMobile App Development Company in Saudi Arabia
Mobile App Development Company in Saudi Arabia
Steve Jonas
 
Heap, Types of Heap, Insertion and Deletion
Heap, Types of Heap, Insertion and DeletionHeap, Types of Heap, Insertion and Deletion
Heap, Types of Heap, Insertion and Deletion
Jaydeep Kale
 
How analogue intelligence complements AI
How analogue intelligence complements AIHow analogue intelligence complements AI
How analogue intelligence complements AI
Paul Rowe
 
Andrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell: Transforming Business Strategy Through Data-Driven Insights
Andrew Marnell
 
Ad

1 query processing

  • 1. 1. Query Processing 2. Translating SQL queries into RA 3. Evaluation Plan 4. Query Execution 5. Query Optimization 6. Translation Rules 7. Cost Estimations
  • 2. 1. Query Processing 1. Query Processing ▪ Aim of query processing - to find information in one or more databases, - and deliver it to the user quickly and efficiently. - to choose the most cost effective. ▪ Translation of queries - into expressions that can be used at physical level of file system. - Includes query optimization and query evaluation.
  • 3. 1. Query Processing 1. Query Processing ▪ Typical steps when processing a high-level query (e.g. SQL query) Query tree internal representation of the query Execution strategy how to retrieve results of query
  • 4. 2. Translating SQL queries into RA 2. Translating SQL queries into RA ▪ Translate query into its internal form. - This is then translated into Relational Algebra(RA). - The parser checks syntax, verifies relations. ▪ A RA expression may have many equivalent expressions. ▪ Example Σbalance<2500(πbalance(account)) Is equivalent to Πbalance(σbalance<2500(account)) Each relational algebra operation can be evaluated using one of several different algorithms. Correspondingly, a relational-algebra expression can be evaluated in many ways.
  • 5. 3. Evaluation Plan 3. Evaluation Plan ▪ Annotated expression specifying detailed evaluation strategy. ▪ Example Use an index on balance to find accounts with balance < 2500, Or perform complete relation scan and discard accounts with balance ≥ 2500. Initial canonical query tree Book (access#, title) Member (ticket#, name) Loan(loanedbook,loanedto) Select member.name rom book, loan, member where book.title = "dracula" and member.ticket# = loan.loanedto and loan.loanedbook = book.access#
  • 6. 4. Query Execution 4. Query Execution For each operation (join, select, project, aggregation …) - Typical algorithms (e.g. Binary search for simple selection) - Specific or not to storage structure and access paths Book (access#, title) Member (ticket#, name) Loan(loanedbook,loanedto) Select member.name From book, loan, member where book.title = "dracula" and member.ticket# = loan.loanedto and loan.loanedbook = book.access#
  • 7. 4. Query Execution 4. Query Execution