Lab # 4 Hands-On. DDL and DML Advance SQL Statements Institute of Computer Science, University of Tartu, Estonia

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Lab # 4 Hands-On DDL and DML Advance SQL Statements Institute of Computer Science, University of Tartu, Estonia Advance Part A: Demo by Instructor in Lab a.

1 Lab # 4 Hands-On DDL and DML Advance SQL Statements Institute of Computer Science, University of Tartu, Estonia Advance Part A: Demo by Instructor in Lab a. AND/OR - Operators are used to filter records based on more than one condition. b. Order By To sort a result c. Group By is used in a SELECT statement to collect data across multiple records and group the results by one or more columns. d. Having Clause is used in the SELECT statement to specify filter conditions for a group of rows or aggregates. Part B: Hands-on by Students in Lab Page 1 of 7

2 Part A: Demo by Instructor in Lab a. AND/OR: In the previous lab, we have seen that the WHERE keyword can be used to conditionally select data from a table. This condition can be a simple condition (like the one presented in the previous lab), or it can be a compound condition. Compound conditions are made up of multiple simple conditions connected by AND or OR. There is no limit to the number of simple conditions that can be present in a single SQL statement. The syntax for a compound condition is as follows: SELECT "column_name" FROM "table_name" WHERE "simple condition" { [AND OR] "simple condition"}+; The { }+ means that the expression inside the bracket will occur one or more times. [AND OR] means that either AND or OR can be used. In addition, we may use the parenthesis sign ( ) to indicate the order of the condition. SELECT * FROM countrylanguage; select * from countrylanguage where (Language = 'English') AND (Percentage >=70); select * from countrylanguage where (Language = 'English') OR (Percentage >=70); b. Order by: The ORDER BY keyword is used to sort the result-set by one or more columns. The ORDER BY keyword sorts the records in ascending order by default. To sort the records in a descending order, you can use the DESC keyword. SELECT column_name, column_name FROM table_name ORDER BY column_name ASC DESC, column_name ASC DESC; select * from countrylanguage ORDER BY Language limit 10; select * from countrylanguage ORDER BY Language DESC limit 10; select * from countrylanguage ORDER BY Percentage DESC; select * from countrylanguage where language='english' ORDER BY CountryCode, Percentage DESC; Page 2 of 7

3 c. Group by: The GROUP BY clause, which is an optional part of the SELECT statement, groups a set of rows into a set of summary rows by values of columns or expressions. The GROUP BY clause returns one row for each group. In other words, it reduces the number of rows in the result set. The Group by clause often use with aggregate functions such as SUM, AVG, MAX, MIN, and COUNT. The aggregate function that appears in the SELECT clause provides the information about each group: SELECT expression1, expression2,... expression_n, aggregate_function (expression) FROM tables [WHERE conditions] GROUP BY expression1, expression2,... expression_n; select name, Continent, min(population) from country GROUP BY continent; select region from country GROUP BY region; Having Clause: The HAVING clause was added to SQL because the WHERE keyword could not be used with aggregate functions. The HAVING clause is often used with the GROUP BY clause. When using with the GROUP BY clause, we can apply a filter condition to the columns that appear in the GROUP BY clause. If the GROUP BY clause is omitted, the HAVING clause behaves like the WHERE clause. Notice that the HAVING clause applies the filter condition to each group of rows, while the WHEREvclause applies the filter condition to each individual row. SELECT column_name, aggregate_function(column_name) FROM table_name WHERE column_name operator value GROUP BY column_name HAVING aggregate_function(column_name) operator value; select * from country having Population >= (select max(population) from country); select * from country having LifeExpectancy >= (select max(lifeexpectancy) from country); Page 3 of 7

The table had been created with following structure a) and load

4 Part B: Hands-on by Students in Lab Use the script from additional material to create EmployeeTable in UT_Database. The table had been created with following structure a) and load records in the table b). a) Meta data of EmployeeTable b) Entered records in EmployeeTable Page 4 of 7

Those work in DeptNo 40 or having PostalAddress of Tallinn. Records display like below: c.

5 a. Retrieve only those Employee records. Those work in DeptNo 20 and PostalAddress is Tartu. Records display like below: b. Retrieve only those Employee records. Those work in DeptNo 40 or having PostalAddress of Tallinn. Records display like below: c. Sort out the records of employee by DeptNo and in each Department descending order sort of EmpName. Records display like below: Page 5 of 7

Group the job column in EmployeeTable. Records display like below: f.

6 d. Sort out the records of employee by YearOfEnrollment and display only 5 top records. Records display like below: e. Group the job column in EmployeeTable. Records display like below: f. Use having clause to display those record who recently hired by company. Records display like below: Page 6 of 7

7 Additional Material: Scripts to create EmployeeTable create table EmployeeTable ( EmpNo INT NOT NULL auto_increment, EmpName VARCHAR(40) NOT NULL, Job CHAR(10) NOT NULL, DeptNo INT NOT NULL, Phone_No INT, YearOfEnrollment YEAR, Percentage float(2, 2), Address VARCHAR(20) NOT NULL, PostalAddress VARCHAR(100), PRIMARY KEY (EmpNo) ); Script to enter records in EmployeeTable insert into employeetable (EmpName, Job, DeptNo, Phone_No, YearOfEnrollment, Address, PostalAddress) Values ('Marko', 'Manager', 20, 3434, 2009, 'marko@gmail.com', 'Tartu'), ('Sander', 'Director', 10, , 2013, 'sander@gmail.com', 'Tallinn'), ('Paul', 'Programmer', 20, , 2010, 'paul@gmail.com', 'Parnu'), ('Toomas', 'Director', 40, , 2000, 'toomas@gmail.com', 'Tallinn'), ('Riina', 'Admin', 30, , 2009, 'riina@gmail.com', 'Tartu'), ('Jak', 'Head', 30, 97878, 2005, 'jak@gmail.com', 'Parnu'), ('Villo', 'Director', 10, , 2015, 'villo@gmail.com', 'Tartu'), ('Magi', 'Researcher', 20, , 2008, 'magi@gmail.com', 'Tallinn'), ('Jana', 'Researcher', 40, , 2012, 'jana@gmail.com', 'Tartu'), ('Rauno', 'Researcher', 10, , 2013, 'rauno@gmail.com', 'Tallinn') ; Page 7 of 7

Lab # 3 Hands-On. DML Basic SQL Statements Institute of Computer Science, University of Tartu, Estonia

Lab # 3 Hands-On. DML Basic SQL Statements Institute of Computer Science, University of Tartu, Estonia Lab # 3 Hands-On DML Basic SQL Statements Institute of Computer Science, University of Tartu, Estonia DML: Data manipulation language statements access and manipulate data in existing schema objects. These