SQL is a standard language for querying and manipulating data in relational databases, with standards like ANSI SQL and SQL99; it uses data definition language to create tables and data manipulation language to query, insert, delete, and modify data in tables; tables contain tuples (rows) made up of atomic data types and a primary key to uniquely identify each tuple.
Database Management System - SQL Advanced TrainingMoutasm Tamimi
Database Management System - SQL Advanced Training
Using SQL language
By Microsoft SQL Server program
version 2008-2010-2012-2014
Prepared by: Moutasm Tamimi
XAMPP
Client, Server, Apache server, MySQL server, Run at server and Run at client.
Skills: 1- Install "xampp" package. 2- Create Apache server and MySQL server.
Essential Questions: 1- How can you simulate the client computer as a server? 2- How can you install the "xampp" packetge in your computer and mention a function of each Apache server and MqSQL server?
https://www.youtube.com/watch?v=X3QfheIHt_8
What inner joins are all about and how to use them.
Inner Joins move data from two tables into their own columns.
Unions move data into the same columns and won't duplicate unless it is a "Union ALL".
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Database Management System - SQL Advanced TrainingMoutasm Tamimi
Database Management System - SQL Advanced Training
Using SQL language
By Microsoft SQL Server program
version 2008-2010-2012-2014
Prepared by: Moutasm Tamimi
XAMPP
Client, Server, Apache server, MySQL server, Run at server and Run at client.
Skills: 1- Install "xampp" package. 2- Create Apache server and MySQL server.
Essential Questions: 1- How can you simulate the client computer as a server? 2- How can you install the "xampp" packetge in your computer and mention a function of each Apache server and MqSQL server?
https://www.youtube.com/watch?v=X3QfheIHt_8
What inner joins are all about and how to use them.
Inner Joins move data from two tables into their own columns.
Unions move data into the same columns and won't duplicate unless it is a "Union ALL".
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
2. SQL Introduction
Standard language for querying and manipulating data
Structured Query Language
Many standards out there:
• ANSI SQL, SQL92 (a.k.a. SQL2), SQL99 (a.k.a. SQL3), ….
3. SQL
• Data Definition Language (DDL)
– Create/alter/delete tables and their attributes
– Following lectures...
• Data Manipulation Language (DML)
– Query one or more tables – discussed next !
– Insert/delete/modify tuples in tables
5. Tables Explained
• The schema of a table is the table name and
its attributes:
Product(PName, Price, Category, Manfacturer)
• A key is an attribute whose values are unique;
we underline a key
Product(PName, Price, Category, Manfacturer)
6. Data Types in SQL
• Atomic types:
– Characters: CHAR(20), VARCHAR(50)
– Numbers: INT, BIGINT, SMALLINT, FLOAT
– Others: MONEY, DATETIME, …
• Every attribute must have an atomic type
– Hence tables are flat
– Why ?
7. Tables Explained
• A tuple = a record
– Restriction: all attributes are of atomic type
• A table = a set of tuples
– Like a list…
– …but it is unorderd:
no first(), no next(), no last().
8. SQL Query
Basic form: (plus many many more bells and whistles)
SELECT <attributes>
FROM <one or more relations>
WHERE <conditions>
13. The LIKE operator
• s LIKE p: pattern matching on strings
• p may contain two special symbols:
– % = any sequence of characters
– _ = any single character
SELECT *
FROM Products
WHERE PName LIKE ‘%gizmo%’
14. Eliminating Duplicates
SELECT DISTINCT category
FROM Product
Compare to:
SELECT category
FROM Product
Category
Gadgets
Gadgets
Photography
Household
Category
Gadgets
Photography
Household
15. Ordering the Results
SELECT pname, price, manufacturer
FROM Product
WHERE category=‘gizmo’AND price > 50
ORDER BY price, pname
Ties are broken by the second attribute on the ORDER BY list, etc.
Ordering is ascending, unless you specify the DESC keyword.
16. SELECT Category
FROM Product
ORDER BY PName
PName Price Category Manufacturer
Gizmo $19.99 Gadgets GizmoWorks
Powergizmo $29.99 Gadgets GizmoWorks
SingleTouch $149.99 Photography Canon
MultiTouch $203.99 Household Hitachi
?
SELECT DISTINCT category
FROM Product
ORDER BY category
SELECT DISTINCT category
FROM Product
ORDER BY PName
?
?
17. Keys and Foreign Keys
PName Price Category Manufacturer
Gizmo $19.99 Gadgets GizmoWorks
Powergizmo $29.99 Gadgets GizmoWorks
SingleTouch $149.99 Photography Canon
MultiTouch $203.99 Household Hitachi
Product
Company
CName StockPrice Country
GizmoWorks 25 USA
Canon 65 Japan
Hitachi 15 Japan
Key
Foreign
key
18. Joins
Product (pname, price, category, manufacturer)
Company (cname, stockPrice, country)
Find all products under $200 manufactured in Japan;
return their names and prices.
SELECT PName, Price
FROM Product, Company
WHERE Manufacturer=CName AND Country=‘Japan’
AND Price <= 200
Join
between Product
and Company
19. Joins
PName Price Category Manufacturer
Gizmo $19.99 Gadgets GizmoWorks
Powergizmo $29.99 Gadgets GizmoWorks
SingleTouch $149.99 Photography Canon
MultiTouch $203.99 Household Hitachi
Product
Company
Cname StockPrice Country
GizmoWorks 25 USA
Canon 65 Japan
Hitachi 15 Japan
PName Price
SingleTouch $149.99
SELECT PName, Price
FROM Product, Company
WHERE Manufacturer=CName AND Country=‘Japan’
AND Price <= 200
20. More Joins
Product (pname, price, category, manufacturer)
Company (cname, stockPrice, country)
Find all Chinese companies that manufacture products
both in the ‘electronic’ and ‘toy’ categories
SELECT cname
FROM
WHERE
21. A Subtlety about Joins
Product (pname, price, category, manufacturer)
Company (cname, stockPrice, country)
Find all countries that manufacture some product in the
‘Gadgets’ category.
SELECT Country
FROM Product, Company
WHERE Manufacturer=CName AND Category=‘Gadgets’
Unexpected duplicates
22. A Subtlety about Joins
Name Price Category Manufacturer
Gizmo $19.99 Gadgets GizmoWorks
Powergizmo $29.99 Gadgets GizmoWorks
SingleTouch $149.99 Photography Canon
MultiTouch $203.99 Household Hitachi
Product
Company
Cname StockPrice Country
GizmoWorks 25 USA
Canon 65 Japan
Hitachi 15 Japan
Country
??
??
What is
the problem ?
What’s the
solution ?
SELECT Country
FROM Product, Company
WHERE Manufacturer=CName AND Category=‘Gadgets’
23. Tuple Variables
SELECT DISTINCT pname, address
FROM Person, Company
WHERE worksfor = cname
Which
address ?
Person(pname, address, worksfor)
Company(cname, address)
SELECT DISTINCT Person.pname, Company.address
FROM Person, Company
WHERE Person.worksfor = Company.cname
SELECT DISTINCT x.pname, y.address
FROM Person AS x, Company AS y
WHERE x.worksfor = y.cname
24. Meaning (Semantics) of SQL
Queries
SELECT a1, a2, …, ak
FROM R1 AS x1, R2 AS x2, …, Rn AS xn
WHERE Conditions
Answer = {}
for x1 in R1 do
for x2 in R2 do
…..
for xn in Rn do
if Conditions
then Answer = Answer {(a1,…,ak)}
return Answer
25. SELECT DISTINCT R.A
FROM R, S, T
WHERE R.A=S.A OR R.A=T.A
An Unintuitive Query
Computes R (S T) But what if S = f ?
What does it compute ?
26. Subqueries Returning Relations
SELECT Company.city
FROM Company
WHERE Company.name IN
(SELECT Product.maker
FROM Purchase , Product
WHERE Product.pname=Purchase.product
AND Purchase .buyer = ‘Joe Blow‘);
Return cities where one can find companies that manufacture
products bought by Joe Blow
Company(name, city)
Product(pname, maker)
Purchase(id, product, buyer)
27. Subqueries Returning Relations
SELECT Company.city
FROM Company, Product, Purchase
WHERE Company.name= Product.maker
AND Product.pname = Purchase.product
AND Purchase.buyer = ‘Joe Blow’
Is it equivalent to this ?
Beware of duplicates !
28. Removing Duplicates
Now
they are
equivalent
SELECT DISTINCT Company.city
FROM Company
WHERE Company.name IN
(SELECT Product.maker
FROM Purchase , Product
WHERE Product.pname=Purchase.product
AND Purchase .buyer = ‘Joe Blow‘);
SELECT DISTINCT Company.city
FROM Company, Product, Purchase
WHERE Company.name= Product.maker
AND Product.pname = Purchase.product
AND Purchase.buyer = ‘Joe Blow’
29. Subqueries Returning Relations
SELECT name
FROM Product
WHERE price > ALL (SELECT price
FROM Purchase
WHERE maker=‘Gizmo-Works’)
Product ( pname, price, category, maker)
Find products that are more expensive than all those produced
By “Gizmo-Works”
You can also use: s > ALL R
s > ANY R
EXISTS R
30. Question for Database Fans
and their Friends
• Can we express this query as a single
SELECT-FROM-WHERE query, without
subqueries ?
31. Question for Database Fans
and their Friends
• Answer: all SFW queries are
monotone (figure out what this means).
A query with ALL is not monotone
32. Correlated Queries
SELECT DISTINCT title
FROM Movie AS x
WHERE year <> ANY
(SELECT year
FROM Movie
WHERE title = x.title);
Movie (title, year, director, length)
Find movies whose title appears more than once.
Note (1) scope of variables (2) this can still be expressed as single SFW
correlation
33. Complex Correlated Query
Product ( pname, price, category, maker, year)
• Find products (and their manufacturers) that are more expensive
than all products made by the same manufacturer before 1972
Very powerful ! Also much harder to optimize.
SELECT DISTINCT pname, maker
FROM Product AS x
WHERE price > ALL (SELECT price
FROM Product AS y
WHERE x.maker = y.maker AND y.year < 1972);
34. Aggregation
SELECT count(*)
FROM Product
WHERE year > 1995
Except count, all aggregations apply to a single attribute
SELECT avg(price)
FROM Product
WHERE maker=“Toyota”
SQL supports several aggregation operations:
sum, count, min, max, avg
35. COUNT applies to duplicates, unless otherwise stated:
SELECT Count(category)
FROM Product
WHERE year > 1995
same as Count(*)
We probably want:
SELECT Count(DISTINCT category)
FROM Product
WHERE year > 1995
Aggregation: Count
36. Purchase(product, date, price, quantity)
More Examples
SELECT Sum(price * quantity)
FROM Purchase
SELECT Sum(price * quantity)
FROM Purchase
WHERE product = ‘bagel’
What do
they mean ?
38. Grouping and Aggregation
Purchase(product, date, price, quantity)
SELECT product, Sum(price*quantity) AS TotalSales
FROM Purchase
WHERE date > ‘10/1/2005’
GROUP BY product
Let’s see what this means…
Find total sales after 10/1/2005 per product.
39. Grouping and Aggregation
1. Compute the FROM and WHERE clauses.
2. Group by the attributes in the GROUPBY
3. Compute the SELECT clause: grouped attributes and aggregates.
41. 3. SELECT
SELECT product, Sum(price*quantity) AS TotalSales
FROM Purchase
WHERE date > ‘10/1/2005’
GROUP BY product
Product Date Price Quantity
Bagel 10/21 1 20
Bagel 10/25 1.50 20
Banana 10/3 0.5 10
Banana 10/10 1 10
Product TotalSales
Bagel 50
Banana 15
42. GROUP BY v.s. Nested Quereis
SELECT product, Sum(price*quantity) AS TotalSales
FROM Purchase
WHERE date > ‘10/1/2005’
GROUP BY product
SELECT DISTINCT x.product, (SELECT Sum(y.price*y.quantity)
FROM Purchase y
WHERE x.product = y.product
AND y.date > ‘10/1/2005’)
AS TotalSales
FROM Purchase x
WHERE x.date > ‘10/1/2005’
44. HAVING Clause
SELECT product, Sum(price * quantity)
FROM Purchase
WHERE date > ‘10/1/2005’
GROUP BY product
HAVING Sum(quantity) > 30
Same query, except that we consider only products that had
at least 100 buyers.
HAVING clause contains conditions on aggregates.
45. General form of Grouping and
Aggregation
SELECT S
FROM R1,…,Rn
WHERE C1
GROUP BY a1,…,ak
HAVING C2
S = may contain attributes a1,…,ak and/or any aggregates but NO OTHER
ATTRIBUTES
C1 = is any condition on the attributes in R1,…,Rn
C2 = is any condition on aggregate expressions
Why ?
46. General form of Grouping and
Aggregation
Evaluation steps:
1. Evaluate FROM-WHERE, apply condition C1
2. Group by the attributes a1,…,ak
3. Apply condition C2 to each group (may have aggregates)
4. Compute aggregates in S and return the result
SELECT S
FROM R1,…,Rn
WHERE C1
GROUP BY a1,…,ak
HAVING C2
48. 1. INTERSECT and EXCEPT:
(SELECT R.A, R.B
FROM R)
INTERSECT
(SELECT S.A, S.B
FROM S)
SELECT R.A, R.B
FROM R
WHERE
EXISTS(SELECT *
FROM S
WHERE R.A=S.A and R.B=S.B)
(SELECT R.A, R.B
FROM R)
EXCEPT
(SELECT S.A, S.B
FROM S)
SELECT R.A, R.B
FROM R
WHERE
NOT EXISTS(SELECT *
FROM S
WHERE R.A=S.A and R.B=S.B)
If R, S have no
duplicates, then can
write without
subqueries
(HOW ?)
INTERSECT and EXCEPT: not in SQL Server
49. 2. Quantifiers
Product ( pname, price, company)
Company( cname, city)
Find all companies that make some products with price < 100
SELECT DISTINCT Company.cname
FROM Company, Product
WHERE Company.cname = Product.company and Product.price < 100
Existential: easy !
50. 2. Quantifiers
Product ( pname, price, company)
Company( cname, city)
Find all companies s.t. all of their products have price < 100
Universal: hard !
Find all companies that make only products with price < 100
same as:
51. 2. Quantifiers
2. Find all companies s.t. all their products have price < 100
1. Find the other companies: i.e. s.t. some product 100
SELECT DISTINCT Company.cname
FROM Company
WHERE Company.cname IN (SELECT Product.company
FROM Product
WHERE Produc.price >= 100
SELECT DISTINCT Company.cname
FROM Company
WHERE Company.cname NOT IN (SELECT Product.company
FROM Product
WHERE Produc.price >= 100
52. 3. Group-by v.s. Nested Query
• Find authors who wrote 10 documents:
• Attempt 1: with nested queries
SELECT DISTINCT Author.name
FROM Author
WHERE count(SELECT Wrote.url
FROM Wrote
WHERE Author.login=Wrote.login)
> 10
This is
SQL by
a novice
Author(login,name)
Wrote(login,url)
53. 3. Group-by v.s. Nested Query
• Find all authors who wrote at least 10
documents:
• Attempt 2: SQL style (with GROUP BY)
SELECT Author.name
FROM Author, Wrote
WHERE Author.login=Wrote.login
GROUP BY Author.name
HAVING count(wrote.url) > 10
This is
SQL by
an expert
No need for DISTINCT: automatically from GROUP BY
54. 3. Group-by v.s. Nested Query
Find authors with vocabulary 10000 words:
SELECT Author.name
FROM Author, Wrote, Mentions
WHERE Author.login=Wrote.login AND Wrote.url=Mentions.url
GROUP BY Author.name
HAVING count(distinct Mentions.word) > 10000
Author(login,name)
Wrote(login,url)
Mentions(url,word)
55. Two Examples
Store(sid, sname)
Product(pid, pname, price, sid)
Find all stores that sell only products with price > 100
same as:
Find all stores s.t. all their products have price > 100)
56. SELECT Store.name
FROM Store, Product
WHERE Store.sid = Product.sid
GROUP BY Store.sid, Store.name
HAVING 100 < min(Product.price)
SELECT Store.name
FROM Store
WHERE Store.sid NOT IN
(SELECT Product.sid
FROM Product
WHERE Product.price <= 100)
SELECT Store.name
FROM Store
WHERE
100 < ALL (SELECT Product.price
FROM product
WHERE Store.sid = Product.sid)
Almost equivalent…
Why both ?
58. Two Examples
SELECT Store.sname, max(Product.price)
FROM Store, Product
WHERE Store.sid = Product.sid
GROUP BY Store.sid, Store.sname
SELECT Store.sname, x.pname
FROM Store, Product x
WHERE Store.sid = x.sid and
x.price >=
ALL (SELECT y.price
FROM Product y
WHERE Store.sid = y.sid)
This is easy but doesn’t do what we want:
Better:
But may
return
multiple
product names
per store
59. Two Examples
SELECT Store.sname, max(x.pname)
FROM Store, Product x
WHERE Store.sid = x.sid and
x.price >=
ALL (SELECT y.price
FROM Product y
WHERE Store.sid = y.sid)
GROUP BY Store.sname
Finally, choose some pid arbitrarily, if there are many
with highest price:
60. NULLS in SQL
• Whenever we don’t have a value, we can put a NULL
• Can mean many things:
– Value does not exists
– Value exists but is unknown
– Value not applicable
– Etc.
• The schema specifies for each attribute if can be null
(nullable attribute) or not
• How does SQL cope with tables that have NULLs ?
61. Null Values
• If x= NULL then 4*(3-x)/7 is still NULL
• If x= NULL then x=“Joe” is UNKNOWN
• In SQL there are three boolean values:
FALSE = 0
UNKNOWN = 0.5
TRUE = 1
62. Null Values
• C1 AND C2 = min(C1, C2)
• C1 OR C2 = max(C1, C2)
• NOT C1 = 1 – C1
Rule in SQL: include only tuples that yield TRUE
SELECT *
FROM Person
WHERE (age < 25) AND
(height > 6 OR weight > 190)
E.g.
age=20
heigth=NULL
weight=200
64. Null Values
Can test for NULL explicitly:
– x IS NULL
– x IS NOT NULL
Now it includes all Persons
SELECT *
FROM Person
WHERE age < 25 OR age >= 25 OR age IS NULL
65. Outerjoins
Explicit joins in SQL = “inner joins”:
Product(name, category)
Purchase(prodName, store)
SELECT Product.name, Purchase.store
FROM Product JOIN Purchase ON
Product.name = Purchase.prodName
SELECT Product.name, Purchase.store
FROM Product, Purchase
WHERE Product.name = Purchase.prodName
Same as:
But Products that never sold will be lost !
66. Outerjoins
Left outer joins in SQL:
Product(name, category)
Purchase(prodName, store)
SELECT Product.name, Purchase.store
FROM Product LEFT OUTER JOIN Purchase ON
Product.name = Purchase.prodName
67. Name Category
Gizmo gadget
Camera Photo
OneClick Photo
ProdName Store
Gizmo Wiz
Camera Ritz
Camera Wiz
Name Store
Gizmo Wiz
Camera Ritz
Camera Wiz
OneClick NULL
Product Purchase
68. Application
Compute, for each product, the total number of sales in ‘September’
Product(name, category)
Purchase(prodName, month, store)
SELECT Product.name, count(*)
FROM Product, Purchase
WHERE Product.name = Purchase.prodName
and Purchase.month = ‘September’
GROUP BY Product.name
What’s wrong ?
69. Application
Compute, for each product, the total number of sales in ‘September’
Product(name, category)
Purchase(prodName, month, store)
SELECT Product.name, count(*)
FROM Product LEFT OUTER JOIN Purchase ON
Product.name = Purchase.prodName
and Purchase.month = ‘September’
GROUP BY Product.name
Now we also get the products who sold in 0 quantity
70. Outer Joins
• Left outer join:
– Include the left tuple even if there’s no match
• Right outer join:
– Include the right tuple even if there’s no match
• Full outer join:
– Include the both left and right tuples even if there’s no
match
71. Modifying the Database
Three kinds of modifications
• Insertions
• Deletions
• Updates
Sometimes they are all called “updates”
72. Insertions
General form:
Missing attribute NULL.
May drop attribute names if give them in order.
INSERT INTO R(A1,…., An) VALUES (v1,…., vn)
INSERT INTO Purchase(buyer, seller, product, store)
VALUES (‘Joe’, ‘Fred’, ‘wakeup-clock-espresso-machine’,
‘The Sharper Image’)
Example: Insert a new purchase to the database:
73. Insertions
INSERT INTO PRODUCT(name)
SELECT DISTINCT Purchase.product
FROM Purchase
WHERE Purchase.date > “10/26/01”
The query replaces the VALUES keyword.
Here we insert many tuples into PRODUCT
74. Insertion: an Example
prodName is foreign key in Product.name
Suppose database got corrupted and we need to fix it:
name listPrice category
gizmo 100 gadgets
prodName buyerName price
camera John 200
gizmo Smith 80
camera Smith 225
Task: insert in Product all prodNames from Purchase
Product
Product(name, listPrice, category)
Purchase(prodName, buyerName, price)
Purchase
75. Insertion: an Example
INSERT INTO Product(name)
SELECT DISTINCT prodName
FROM Purchase
WHERE prodName NOT IN (SELECT name FROM Product)
name listPrice category
gizmo 100 Gadgets
camera - -
76. Insertion: an Example
INSERT INTO Product(name, listPrice)
SELECT DISTINCT prodName, price
FROM Purchase
WHERE prodName NOT IN (SELECT name FROM Product)
name listPrice category
gizmo 100 Gadgets
camera 200 -
camera ?? 225 ?? - Depends on the implementation
77. Deletions
DELETE FROM PURCHASE
WHERE seller = ‘Joe’ AND
product = ‘Brooklyn Bridge’
Factoid about SQL: there is no way to delete only a single
occurrence of a tuple that appears twice
in a relation.
Example:
78. Updates
UPDATE PRODUCT
SET price = price/2
WHERE Product.name IN
(SELECT product
FROM Purchase
WHERE Date =‘Oct, 25, 1999’);
Example: