![Wildcards
● 'a%' - Finds any values that starts with "a"
● '%a' - Finds any values that ends with "a"
● '%or%’ - Finds any values that have "or" in any position
● '_r%' - Finds any values that have "r" in the second position
● 'a_%_%' - Finds any values that starts with "a" and are at least 3 characters in length
● 'a%o' - Finds any values that starts with "a" and ends with "o"
● [charlist] - Defines sets and ranges of characters to match
○ [abs]
○ [a-d]
● [^charlist] or [!charlist] - Defines sets and ranges of characters NOT to match
○ [!bef]
○ [!g-r]](https://image.slidesharecdn.com/sql-gettingstarted-190207223847/85/SQL-with-PostgreSQL-Getting-Started-21-320.jpg)
![Joining information
select t1.column1, t1.column2, t2.column1, t2.column2, t2.column3...
from t1 [A] (first table)
Join t2 [B] (second table) on t1.columnX = t2.columnX
● (Inner) join - Returns records that have matching values in both tables
● Left join - Return all records from the left table, and the matched records from
the right table
● Right join - Return all records from the right table, and the matched records
from the left table
● Full outer join - Return all records when there is a match in either left or right
table](https://image.slidesharecdn.com/sql-gettingstarted-190207223847/85/SQL-with-PostgreSQL-Getting-Started-25-320.jpg)
![Functions
Select [columns…], function(columnX), [columns…] from
tableName
● Count() - counts the number of rows that returned from the query.
Doesn’t count nulls
● Max() - gives the maximal value in a column
● Min() - gives the minimum value in a column
● Avg() - gives the average value of all values in a column
● Sum() - sums up all values in a column
● More...](https://image.slidesharecdn.com/sql-gettingstarted-190207223847/85/SQL-with-PostgreSQL-Getting-Started-32-320.jpg)
SQL with PostgreSQL - Getting Started
- 3. Overview ● History ● Concept ● Existing technologies
- 4. Basic entities in relational databases ID Column1 Column2 Column3 1 datum1. 1 datum2. 1 datum3. 1 2 datum1. 2 datum2. 2 datum3. 2 3 datum1. 3 datum2. 3 datum3. 3 4 datum1. 4 datum2. 4 datum3. 4 Tables ● Int ● Varchar(size) ● Date ● Double ● Datetime ● And many more Data Types ● One → One ● One → Many ● Many → Many ● Self Referencing Connections
- 6. Steps to install the DB ● Step 1: enter this site postgres ● Step 2: choose the Os you are working on ● Step 3: click on download the installer under Interactive installer by EnterpriseDB ● Step 4: download the dmg file (mac) exe file (windows) of version 10 ● Step 5: follow the installer when it asks you for password choose something you can remember. IF YOU FORGET THIS PASSWORD YOU’LL NEED TO REMOVE ALL THE COMPONENTS FROM YOUR COMPUTER AND IT IS A MESS ● Step 6: open pgadmin (it is already installed during the postgres installation)
- 7. pgAdmin - Connecting to a server 21 3
- 8. pgAdmin - Creating new DB 1 2 3
- 9. pgAdmin - Creating a new table 1 2
- 10. Creating a new table - Live example
- 11. pgAdmin - Import data from csv 1 2 3
- 12. Import data from csv - Live example
- 13. SQL (Structured Query Language)
- 14. Basic query select column1, column2, … from tableName ● The * - selects all columns in a table ● The keyword as - used for giving aliases to columns or tables ● The keyword distinct - returns all distinct values of a table ● The keyword top x|percent - returns x or x percent top results ● The keyword limit x - limits the number of results returned from a query to x
- 15. Example select id, fName as first_name, lName, age, from person id fName lName age Country City Phone_Number 1 Sammy Blumberg 43 Israel Jerusalem +972528534467 2 Diana Smith 60 Italy Rome +390611532846 3 Rachel Wilson 24 France Paris +33523449285
- 16. Result id first_name lName age 1 Sammy Blumberg 43 2 Diana Smith 60 3 Rachel Wilson 24 select id, fName as first_name, lName, age, from person
- 17. Order Results select column1, column2, … from tableName order by column1, column2, … ● Numbers instead of column names ● The keywords asc (default) and desc
- 18. Example select id,fName, lName, age, from person order by Age id fName lName age 1 Sammy Blumberg 43 2 Diana Smith 60 3 Rachel Wilson 24 id fName lName age 3 Rachel Wilson 24 1 Sammy Blumberg 43 2 Diana Smith 60
- 19. Conditions select column1, column2, … from tableName where (not) condition1 (andor + (not)) condition2 ... ● Conditions with operators - =, >, <, >=, <=, <> ○ Name = ‘Rachel’ ○ Age >= 23 ● Conditions with like keyword - coulmn(x) like pattern ○ lName like ‘%berg’ - any name that ends with berg ● The in keyword - columnX in (dataset) ○ Age in (23,43,67,80,92,13,15,6) ● The between keyword - columnX between a and b ○ Age between 12 and 30
- 20. Operators ● = - equals ● <> (!=) - not equals ● > - greater thane ● < - less than ● >= - greater than equals ● <= less than equals
- 21. Wildcards ● 'a%' - Finds any values that starts with "a" ● '%a' - Finds any values that ends with "a" ● '%or%’ - Finds any values that have "or" in any position ● '_r%' - Finds any values that have "r" in the second position ● 'a_%_%' - Finds any values that starts with "a" and are at least 3 characters in length ● 'a%o' - Finds any values that starts with "a" and ends with "o" ● [charlist] - Defines sets and ranges of characters to match ○ [abs] ○ [a-d] ● [^charlist] or [!charlist] - Defines sets and ranges of characters NOT to match ○ [!bef] ○ [!g-r]
- 22. Example select fName from person where lName = ‘Wilson’ and age > 30 id fName lName age 1 Sammy Blumberg 43 2 Diana Smith 60 3 Rachel Wilson 24 4 Tomy Wilson 32 fName Tomy
- 23. Group by + Conditions select column1, column2, … from tableName group by coulmn1, column2 having (not) condition1 (andor + (not)) condition2 … Conditions in having sentence affect only groups and not the entire dataset. To add condition on the entire dataset use the where clause.
- 24. Example select fName, lName from person where age > 24 group by country having lName like ‘B%’ order by Age desc id fName lName age country 1 Sammy Blumberg 43 USA 2 Diana Smith 60 UK 3 Rachel Wilson 24 USA 4 Jacque Brel 30 France 5 Mike Brant 50 USA 6 Claire Bakingham 37 UK fName lName Mike Brant Sammy Blumberg Claire Bakingham Jacque Brel
- 25. Joining information select t1.column1, t1.column2, t2.column1, t2.column2, t2.column3... from t1 [A] (first table) Join t2 [B] (second table) on t1.columnX = t2.columnX ● (Inner) join - Returns records that have matching values in both tables ● Left join - Return all records from the left table, and the matched records from the right table ● Right join - Return all records from the right table, and the matched records from the left table ● Full outer join - Return all records when there is a match in either left or right table
- 26. Join Types Full Outer JoinRight joinLeft joinInner join TableA TableA TableATableBTableB TableBTableA TableB
- 27. Example select p.fName, p.lName, cd.email from person p join contact_details cd p.id = cd.person_id where fname = ‘Rachel’ id fName lName 1 Sammy Blumberg 2 Diana Smith 3 Rachel Wilson 4 Rachel Rosenberg id person_id email phone 1 3 [email protected] 0542221307 2 2 [email protected] 0521342555 3 1 [email protected] 0503078242 4 4 [email protected] 0545557731
- 28. Result select p.fName, p.lName, cd.email from person p join contact_details cd p.id = cd.person_id where fname = ‘Rachel’ fName lName email Rachel Wilson [email protected] Rachel Rosenberg [email protected]
- 29. Subqueries ● Each query returns a table ● Each query manipulates the data in one or more tables ● Hence we can run queries on results of other queries ● These “other queries” are called subqueries
- 30. Example select p.fName as first_name, p.eyesColor as eyes_color from person p where p.eye_color in (select color from colors where colorTag = ‘eyes’) id fName eyesColor 1 Sammy blue 2 Diana green 3 Rachel blue 4 Danielle brown id color colorTag code 1 blue eyes #13c3ff 2 green eyes #32c512 3 brown hair #673a07 4 black skin #000000
- 31. Result id first_name eyesColor 1 Sammy blue 2 Diana green 3 Rachel blue select p.fName as first_name, p.eyesColor as eyes_color from person p where p.eye_color in (select color from colors where colorTag = ‘eyes’)
- 32. Functions Select [columns…], function(columnX), [columns…] from tableName ● Count() - counts the number of rows that returned from the query. Doesn’t count nulls ● Max() - gives the maximal value in a column ● Min() - gives the minimum value in a column ● Avg() - gives the average value of all values in a column ● Sum() - sums up all values in a column ● More...
- 33. Example select Count(*) as num_of_people, Avg(age) as average_age from person where country = ‘USA’ id fName lName age country 1 Sammy Blumberg 43 USA 2 Diana Smith 60 UK 3 Rachel Wilson 24 USA 4 Jacque Brel 30 France 5 Mike Brant 50 USA 6 Claire Bakingham 37 UK num_of_people average_age 3 51
- 34. Demo