Group By, Having Clause and Order By clause
•Download as PPTX, PDF•
0 likes•741 views
This presentation contains: Definition of the group by, having and order by clauses Examples with tables of the group by, having and order by clauses SQL queries for the group by, having and order by clauses
Report
Share
Report
Share
Recommended
SQL subquery
The document discusses subqueries in SQL. It defines a subquery as a SELECT statement embedded within another SELECT statement. Subqueries allow queries to be built from simpler statements by executing an inner query and using its results to inform the conditions of the outer query. The key aspects covered are: subqueries can be used in the WHERE, HAVING, FROM and other clauses; single-row subqueries use single-value operators while multiple-row subqueries use operators like ANY and ALL; and subqueries execute before the outer query to provide their results.
Aggregate function
Aggregate functions are functions that take a collection of values as input and return a single value.The ISO standard defines five (5) aggregate functions namely :-
1) COUNT
2) SUM
3) AVG
4) MIN
5) MAX
1.COUNT Function
The COUNT function returns the total number of values in the specified field. It works on both numeric and non-numeric data types. All aggregate functions by default exclude nulls values before working on the data.
MIN function
The MIN function returns the smallest value in the specified table field.
2.MAX function
Just as the name suggests, the MAX function is the opposite of the MIN function. It returns the largest value from the specified table field.
3.SUM function
Suppose we want a report that gives total amount of payments made so far. We can use the MySQL SUM function which returns the sum of all the values in the specified column. SUM works on numeric fields only. Null values are excluded from the result returned.
4.AVG function
MySQL AVG function returns the average of the values in a specified column. Just like the SUM function, it works only on numeric data types.
5.MIN function
The MIN function returns the smallest value in the specified table field.
SQL Commands
Consists of the explanations of the basics of SQL and commands of SQL.Helpful for II PU NCERT students and also degree studeents to understand some basic things.
SQL Joins.pptx
This presentation gives a clear and concise description of joins in sql and several types of sql joins.
These slides also contains the pictorial representation as well as syntax for each type of joins.
introdution to SQL and SQL functions
This document provides an introduction to SQL (Structured Query Language). It defines SQL as a standard language for accessing and manipulating databases. The key points covered include:
- SQL lets you perform queries against a database to retrieve, insert, update, and delete data. It can also be used to create and modify database structures.
- Common SQL commands covered are SELECT, INSERT, UPDATE, DELETE, CREATE TABLE, ALTER TABLE, DROP TABLE.
- Additional SQL concepts explained are data types, WHERE clauses, ORDER BY clauses, GROUP BY clauses, and JOIN operations.
- RDBMS systems like MySQL, SQL Server, Oracle, etc. use SQL to communicate with the databases they manage.
Create table
The document discusses the concept of tables in databases and how to create tables in SQL. It defines what a table is, explains that tables can represent entities, relationships between entities, or lists. It then covers the syntax and rules for creating tables, including specifying the table name, columns, data types, constraints like primary keys, unique keys, foreign keys, default values and check constraints. Examples are provided for creating tables with different constraints. The roles of constraints in enforcing data integrity are also discussed.
Constraints In Sql
The document discusses various types of constraints in SQL including column level constraints like NOT NULL, UNIQUE, DEFAULT, and CHECK constraints as well as table level constraints like PRIMARY KEY and FOREIGN KEY. It provides examples of how to define these constraints when creating or altering tables and explains how each constraint enforces integrity rules and data validation. Constraints are used to impose rules on data values and relationships between columns and tables.
SQL Functions
This document discusses different types of SQL functions including string, numeric, conversion, group, date/time, and user-defined functions. It provides examples of common string functions like UPPER, LENGTH, SUBSTR. Numeric functions covered include ABS, ROUND, POWER. Group functions include AVG, COUNT, MAX, MIN, SUM. Date functions allow conversion and calculation involving dates. The document demonstrates how to create scalar and table-valued user-defined functions in SQL.
Recommended
SQL subquery
The document discusses subqueries in SQL. It defines a subquery as a SELECT statement embedded within another SELECT statement. Subqueries allow queries to be built from simpler statements by executing an inner query and using its results to inform the conditions of the outer query. The key aspects covered are: subqueries can be used in the WHERE, HAVING, FROM and other clauses; single-row subqueries use single-value operators while multiple-row subqueries use operators like ANY and ALL; and subqueries execute before the outer query to provide their results.
Aggregate function
Aggregate functions are functions that take a collection of values as input and return a single value.The ISO standard defines five (5) aggregate functions namely :-
1) COUNT
2) SUM
3) AVG
4) MIN
5) MAX
1.COUNT Function
The COUNT function returns the total number of values in the specified field. It works on both numeric and non-numeric data types. All aggregate functions by default exclude nulls values before working on the data.
MIN function
The MIN function returns the smallest value in the specified table field.
2.MAX function
Just as the name suggests, the MAX function is the opposite of the MIN function. It returns the largest value from the specified table field.
3.SUM function
Suppose we want a report that gives total amount of payments made so far. We can use the MySQL SUM function which returns the sum of all the values in the specified column. SUM works on numeric fields only. Null values are excluded from the result returned.
4.AVG function
MySQL AVG function returns the average of the values in a specified column. Just like the SUM function, it works only on numeric data types.
5.MIN function
The MIN function returns the smallest value in the specified table field.
SQL Commands
Consists of the explanations of the basics of SQL and commands of SQL.Helpful for II PU NCERT students and also degree studeents to understand some basic things.
SQL Joins.pptx
This presentation gives a clear and concise description of joins in sql and several types of sql joins.
These slides also contains the pictorial representation as well as syntax for each type of joins.
introdution to SQL and SQL functions
This document provides an introduction to SQL (Structured Query Language). It defines SQL as a standard language for accessing and manipulating databases. The key points covered include:
- SQL lets you perform queries against a database to retrieve, insert, update, and delete data. It can also be used to create and modify database structures.
- Common SQL commands covered are SELECT, INSERT, UPDATE, DELETE, CREATE TABLE, ALTER TABLE, DROP TABLE.
- Additional SQL concepts explained are data types, WHERE clauses, ORDER BY clauses, GROUP BY clauses, and JOIN operations.
- RDBMS systems like MySQL, SQL Server, Oracle, etc. use SQL to communicate with the databases they manage.
Create table
The document discusses the concept of tables in databases and how to create tables in SQL. It defines what a table is, explains that tables can represent entities, relationships between entities, or lists. It then covers the syntax and rules for creating tables, including specifying the table name, columns, data types, constraints like primary keys, unique keys, foreign keys, default values and check constraints. Examples are provided for creating tables with different constraints. The roles of constraints in enforcing data integrity are also discussed.
Constraints In Sql
The document discusses various types of constraints in SQL including column level constraints like NOT NULL, UNIQUE, DEFAULT, and CHECK constraints as well as table level constraints like PRIMARY KEY and FOREIGN KEY. It provides examples of how to define these constraints when creating or altering tables and explains how each constraint enforces integrity rules and data validation. Constraints are used to impose rules on data values and relationships between columns and tables.
SQL Functions
This document discusses different types of SQL functions including string, numeric, conversion, group, date/time, and user-defined functions. It provides examples of common string functions like UPPER, LENGTH, SUBSTR. Numeric functions covered include ABS, ROUND, POWER. Group functions include AVG, COUNT, MAX, MIN, SUM. Date functions allow conversion and calculation involving dates. The document demonstrates how to create scalar and table-valued user-defined functions in SQL.
SQL Queries
This document provides an introduction to SQL and database systems. It begins with example tables to demonstrate SQL concepts. It then covers the objectives of SQL, including allowing users to create database structures, manipulate data, and perform queries. Various SQL concepts are introduced such as data types, comparison operators, logical operators, and arithmetic operators. The document also discusses SQL statements for schema and catalog definitions, data definition, data manipulation, and other operators. Example SQL queries are provided to illustrate concepts around selecting columns, rows, sorting, aggregation, grouping, and more.
joins in database
The document discusses different types of joins in database systems. It defines natural join, inner join, equi join, theta join, semi join, anti join, cross join, outer join including left, right and full outer joins, and self join. Examples are provided for each type of join to illustrate how they work.
SQL - DML and DDL Commands
SQL is a standard language for querying and manipulating data in relational databases. It contains five categories of statements: data definition language (DDL) for defining data structure, data manipulation language (DML) for managing data, data control language (DCL) for privileges, transaction control statements for transactions, and session control statements for sessions. Common DDL commands include CREATE, ALTER, and DROP for databases and tables. Common DML commands include SELECT, INSERT, UPDATE, and DELETE for querying and modifying data. Joins are used to combine data from two or more tables.
DDL And DML
This document discusses DML and DDL in SQL. DML is used to manipulate data in databases through statements like SELECT, UPDATE, DELETE, and INSERT. It allows users to specify and modify data. DDL is used to define and modify database structures through statements like CREATE, ALTER, DROP, TRUNCATE, and RENAME. DDL manages database schemas and DML manages the data. Both have advantages like shared data, integrity, security and efficiency.
oracle Sql constraint
This document discusses SQL constraints. It defines constraints as limitations on the type of data that can go into a table. The main types of constraints covered are:
1. Not null constraints, which enforce that a column cannot be null
2. Unique constraints, which uniquely identify each record in a table
3. Primary key constraints, which uniquely identify each record and cannot be null
4. Foreign key constraints, which link to primary keys in other tables to define relationships
5. Check constraints, which define valid value ranges for a column
6. Default constraints, which provide a default value for a column if no other value is specified.
Examples are provided for each constraint type to illustrate their syntax and usage
Group By, Order By, and Aliases in SQL
The document discusses SQL Group By, Order By, and Aliases. It explains that the Group By clause groups identical data, follows the WHERE clause, and precedes ORDER BY. ORDER BY sorts data in ascending or descending order specified by ASC or DESC. Aliases can temporarily rename tables or columns for brevity in a SELECT statement.
Sql queries presentation
Structured Query Language (SQL) is a query language that allows users to specify conditions to retrieve data from a database. SQL queries select rows from database tables that satisfy specified conditions. The results are output in a table format. Common SQL clauses include SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY, and INTO to output results to a table, cursor, file or printer. SQL can perform queries on single or multiple related tables through joins.
Sql commands
Data Definition Language (DDL), Data Definition Language (DDL), Data Manipulation Language (DML) , Transaction Control Language (TCL) , Data Control Language (DCL) - , SQL Constraints
Aggregate functions
This document discusses aggregate functions in SQL. It defines aggregate functions as functions that summarize expression results over multiple rows into a single value. Commonly used aggregate functions include SUM, COUNT, AVG, MIN, and MAX. Examples are provided calculating sums, averages, minimums, and maximums of salaries in an employee table to illustrate the use of these functions. It also discusses issues like ignoring null values and the need to use the GROUP BY clause with aggregate functions.
Sql joins inner join self join outer joins
This document discusses different types of SQL joins, including inner joins, left joins, right joins, full joins, and self joins. It provides examples of the syntax for each type of join, along with sample queries and resulting tables to illustrate how each join works. Inner joins return rows where there is a match in both tables. Left and right joins return all rows from the left or right table respectively, along with matched or null rows from the other table. Full joins return all rows and fill in nulls for missing matches. Self joins allow a table to join with itself.
Relational algebra in dbms
Introduction to Relational algebra in DBMS - The relational algebra is explained with all the operations. Some of the examples from the textbook is also solved and explained.
DML, DDL, DCL ,DRL/DQL and TCL Statements in SQL with Examples
DML, DDL, DCL ,DRL/DQL and TCL Statements in SQL with ExamplesLGS, GBHS&IC, University Of South-Asia, TARA-Technologies
SQL language includes four primary statement types: DML, DDL, DCL, and TCL. DML statements manipulate data within tables using operations like SELECT, INSERT, UPDATE, and DELETE. DDL statements define and modify database schema using commands like CREATE, ALTER, and DROP. DCL statements control user access privileges with GRANT and REVOKE. TCL statements manage transactions with COMMIT, ROLLBACK, and SAVEPOINT to maintain data integrity.11. transaction sql
This document discusses transactions in SQL and database management systems. It explains that DBMSs use transactions to ensure atomicity, consistency, isolation, and durability when multiple users access and modify data simultaneously. SQL supports transactions through statements like COMMIT, ROLLBACK, and by setting the transaction isolation level. The isolation level determines how transactions interact with each other and see concurrent changes to the database.
Joins in SQL
Joins in SQL are used to combine data from two or more tables based on common columns between them. There are several types of joins, including inner joins, outer joins, and cross joins. Inner joins return rows that match between tables, outer joins return all rows including non-matching rows, and cross joins return the cartesian product between tables.
Aggregate Function - Database
Shahadat Hossain presented on aggregate functions in SQL. Aggregate functions take a collection of values as input and return a single value. Common aggregate functions include MAX(), MIN(), AVG(), SUM(), and COUNT(). Each function operates on a single column and returns a single value. SUM() and AVG() operate on numeric data, while MIN(), MAX(), and COUNT() can operate on numeric or non-numeric data. Examples demonstrated how to use each function to return values like the total salary, average salary, minimum salary, and number of records that meet a condition.
Data Manipulation Language
The DBMS provides a set of operations or a language called the data manipulation language (DML) for modification of the data.
Data manipulation can be performed either by typing SQL statements or by using a graphical interface, typically called Query-By-Example (QBE).
Subqueries
This document discusses subqueries, which are SELECT statements nested inside other SELECT statements. Subqueries can be used in the SELECT, FROM, WHERE, or HAVING clauses. They can return scalar values, lists, or correlated results depending on how they are used. Examples are provided to illustrate scalar, list, and correlated subqueries as well as common uses of subqueries to retrieve related data from different tables.
Oracle SQL Basics
This document provides an overview and introduction to Oracle SQL basics. It covers topics such as installing Oracle software like the database, Java SDK, and SQL Developer tool. It then discusses database concepts like what a database and table are. It also covers database fundamentals including SQL queries, functions, joins, constraints, views and other database objects. The document provides examples and explanations of SQL statements and database components.
SQL
SQL is a standard language for accessing and manipulating databases. The document provides an introduction to SQL basics including SQL statements to select, insert, update and delete data from database tables. It explains key SQL components like the WHERE clause for filtering records and the ORDER BY clause for sorting query results. Examples are given for each SQL statement and concept discussed.
Set operators
The document describes eight relational operators: SELECT, PROJECT, JOIN, INTERSECT, UNION, DIFFERENCE, PRODUCT, and DIVIDE. It provides examples of how each operator manipulates data from one or more tables by selecting, combining, or relating their contents.
Group by clause mod
The document discusses the GROUP BY clause in SQL, which groups or categorizes data in a table into smaller groups based on specified column(s). Group functions like SUM, COUNT, MAX, MIN can then return summary information for each group. The GROUP BY clause is used with SELECT statements to group data and apply aggregate functions to each group. It explains how to group data by single or multiple columns, and restrict groups using the HAVING clause.
12. Basic SQL Queries (2).pptx
The document outlines SQL commands for creating and manipulating databases and tables, including creating and deleting databases and tables, inserting, updating, deleting and reading records from tables, and using clauses like WHERE, ORDER BY, GROUP BY and aggregate functions like COUNT, SUM, AVG, MIN, MAX. It also discusses set operations like UNION, INTERSECT, EXCEPT and using nested queries.
More Related Content
What's hot
SQL Queries
This document provides an introduction to SQL and database systems. It begins with example tables to demonstrate SQL concepts. It then covers the objectives of SQL, including allowing users to create database structures, manipulate data, and perform queries. Various SQL concepts are introduced such as data types, comparison operators, logical operators, and arithmetic operators. The document also discusses SQL statements for schema and catalog definitions, data definition, data manipulation, and other operators. Example SQL queries are provided to illustrate concepts around selecting columns, rows, sorting, aggregation, grouping, and more.
joins in database
The document discusses different types of joins in database systems. It defines natural join, inner join, equi join, theta join, semi join, anti join, cross join, outer join including left, right and full outer joins, and self join. Examples are provided for each type of join to illustrate how they work.
SQL - DML and DDL Commands
SQL is a standard language for querying and manipulating data in relational databases. It contains five categories of statements: data definition language (DDL) for defining data structure, data manipulation language (DML) for managing data, data control language (DCL) for privileges, transaction control statements for transactions, and session control statements for sessions. Common DDL commands include CREATE, ALTER, and DROP for databases and tables. Common DML commands include SELECT, INSERT, UPDATE, and DELETE for querying and modifying data. Joins are used to combine data from two or more tables.
DDL And DML
This document discusses DML and DDL in SQL. DML is used to manipulate data in databases through statements like SELECT, UPDATE, DELETE, and INSERT. It allows users to specify and modify data. DDL is used to define and modify database structures through statements like CREATE, ALTER, DROP, TRUNCATE, and RENAME. DDL manages database schemas and DML manages the data. Both have advantages like shared data, integrity, security and efficiency.
oracle Sql constraint
This document discusses SQL constraints. It defines constraints as limitations on the type of data that can go into a table. The main types of constraints covered are:
1. Not null constraints, which enforce that a column cannot be null
2. Unique constraints, which uniquely identify each record in a table
3. Primary key constraints, which uniquely identify each record and cannot be null
4. Foreign key constraints, which link to primary keys in other tables to define relationships
5. Check constraints, which define valid value ranges for a column
6. Default constraints, which provide a default value for a column if no other value is specified.
Examples are provided for each constraint type to illustrate their syntax and usage
Group By, Order By, and Aliases in SQL
The document discusses SQL Group By, Order By, and Aliases. It explains that the Group By clause groups identical data, follows the WHERE clause, and precedes ORDER BY. ORDER BY sorts data in ascending or descending order specified by ASC or DESC. Aliases can temporarily rename tables or columns for brevity in a SELECT statement.
Sql queries presentation
Structured Query Language (SQL) is a query language that allows users to specify conditions to retrieve data from a database. SQL queries select rows from database tables that satisfy specified conditions. The results are output in a table format. Common SQL clauses include SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY, and INTO to output results to a table, cursor, file or printer. SQL can perform queries on single or multiple related tables through joins.
Sql commands
Data Definition Language (DDL), Data Definition Language (DDL), Data Manipulation Language (DML) , Transaction Control Language (TCL) , Data Control Language (DCL) - , SQL Constraints
Aggregate functions
This document discusses aggregate functions in SQL. It defines aggregate functions as functions that summarize expression results over multiple rows into a single value. Commonly used aggregate functions include SUM, COUNT, AVG, MIN, and MAX. Examples are provided calculating sums, averages, minimums, and maximums of salaries in an employee table to illustrate the use of these functions. It also discusses issues like ignoring null values and the need to use the GROUP BY clause with aggregate functions.
Sql joins inner join self join outer joins
This document discusses different types of SQL joins, including inner joins, left joins, right joins, full joins, and self joins. It provides examples of the syntax for each type of join, along with sample queries and resulting tables to illustrate how each join works. Inner joins return rows where there is a match in both tables. Left and right joins return all rows from the left or right table respectively, along with matched or null rows from the other table. Full joins return all rows and fill in nulls for missing matches. Self joins allow a table to join with itself.
Relational algebra in dbms
Introduction to Relational algebra in DBMS - The relational algebra is explained with all the operations. Some of the examples from the textbook is also solved and explained.
DML, DDL, DCL ,DRL/DQL and TCL Statements in SQL with Examples
DML, DDL, DCL ,DRL/DQL and TCL Statements in SQL with ExamplesLGS, GBHS&IC, University Of South-Asia, TARA-Technologies
SQL language includes four primary statement types: DML, DDL, DCL, and TCL. DML statements manipulate data within tables using operations like SELECT, INSERT, UPDATE, and DELETE. DDL statements define and modify database schema using commands like CREATE, ALTER, and DROP. DCL statements control user access privileges with GRANT and REVOKE. TCL statements manage transactions with COMMIT, ROLLBACK, and SAVEPOINT to maintain data integrity.11. transaction sql
This document discusses transactions in SQL and database management systems. It explains that DBMSs use transactions to ensure atomicity, consistency, isolation, and durability when multiple users access and modify data simultaneously. SQL supports transactions through statements like COMMIT, ROLLBACK, and by setting the transaction isolation level. The isolation level determines how transactions interact with each other and see concurrent changes to the database.
Joins in SQL
Joins in SQL are used to combine data from two or more tables based on common columns between them. There are several types of joins, including inner joins, outer joins, and cross joins. Inner joins return rows that match between tables, outer joins return all rows including non-matching rows, and cross joins return the cartesian product between tables.
Aggregate Function - Database
Shahadat Hossain presented on aggregate functions in SQL. Aggregate functions take a collection of values as input and return a single value. Common aggregate functions include MAX(), MIN(), AVG(), SUM(), and COUNT(). Each function operates on a single column and returns a single value. SUM() and AVG() operate on numeric data, while MIN(), MAX(), and COUNT() can operate on numeric or non-numeric data. Examples demonstrated how to use each function to return values like the total salary, average salary, minimum salary, and number of records that meet a condition.
Data Manipulation Language
The DBMS provides a set of operations or a language called the data manipulation language (DML) for modification of the data.
Data manipulation can be performed either by typing SQL statements or by using a graphical interface, typically called Query-By-Example (QBE).
Subqueries
This document discusses subqueries, which are SELECT statements nested inside other SELECT statements. Subqueries can be used in the SELECT, FROM, WHERE, or HAVING clauses. They can return scalar values, lists, or correlated results depending on how they are used. Examples are provided to illustrate scalar, list, and correlated subqueries as well as common uses of subqueries to retrieve related data from different tables.
Oracle SQL Basics
This document provides an overview and introduction to Oracle SQL basics. It covers topics such as installing Oracle software like the database, Java SDK, and SQL Developer tool. It then discusses database concepts like what a database and table are. It also covers database fundamentals including SQL queries, functions, joins, constraints, views and other database objects. The document provides examples and explanations of SQL statements and database components.
SQL
SQL is a standard language for accessing and manipulating databases. The document provides an introduction to SQL basics including SQL statements to select, insert, update and delete data from database tables. It explains key SQL components like the WHERE clause for filtering records and the ORDER BY clause for sorting query results. Examples are given for each SQL statement and concept discussed.
Set operators
The document describes eight relational operators: SELECT, PROJECT, JOIN, INTERSECT, UNION, DIFFERENCE, PRODUCT, and DIVIDE. It provides examples of how each operator manipulates data from one or more tables by selecting, combining, or relating their contents.
What's hot (20)
DML, DDL, DCL ,DRL/DQL and TCL Statements in SQL with Examples
DML, DDL, DCL ,DRL/DQL and TCL Statements in SQL with Examples
Similar to Group By, Having Clause and Order By clause
Group by clause mod
The document discusses the GROUP BY clause in SQL, which groups or categorizes data in a table into smaller groups based on specified column(s). Group functions like SUM, COUNT, MAX, MIN can then return summary information for each group. The GROUP BY clause is used with SELECT statements to group data and apply aggregate functions to each group. It explains how to group data by single or multiple columns, and restrict groups using the HAVING clause.
12. Basic SQL Queries (2).pptx
The document outlines SQL commands for creating and manipulating databases and tables, including creating and deleting databases and tables, inserting, updating, deleting and reading records from tables, and using clauses like WHERE, ORDER BY, GROUP BY and aggregate functions like COUNT, SUM, AVG, MIN, MAX. It also discusses set operations like UNION, INTERSECT, EXCEPT and using nested queries.
Les05
This document discusses how to aggregate and group data using SQL functions. It covers various group functions like COUNT, MAX, MIN, AVG, and SUM. It explains how to use the GROUP BY clause to group rows by one or more columns and produce an aggregate result per group. It also explains how to use the HAVING clause to filter groups based on aggregate conditions.
SQL-AGG-FUN.pdfiiiijuyyttfffgyyuyyyyyhhh
Aggregate functions operate on a collection of values from a column and return a single value. The main aggregate functions are SUM, AVG, MIN, MAX, and COUNT. COUNT returns the number of rows, SUM adds values, AVG calculates the average, MIN returns the minimum value, and MAX returns the maximum value. The GROUP BY clause groups data by one or more columns and the HAVING clause allows filtering groups based on aggregate functions.
Les04
This document discusses SQL group functions and how to summarize aggregated data from tables. It covers:
1) The main group functions - AVG, COUNT, MAX, MIN, SUM - and how to use them to aggregate data from columns.
2) Using the GROUP BY clause to divide rows into groups and apply aggregate functions per group.
3) Using the HAVING clause to restrict groups based on aggregate conditions, since aggregates cannot be used in the WHERE clause.
SQL.pptx
The document discusses aggregate functions in SQL such as SUM, AVG, COUNT, MAX, MIN. It provides examples of using these functions to calculate totals, averages, counts and find maximum and minimum values from columns in tables. It also covers the use of the GROUP BY clause to perform aggregate calculations on grouped data and the HAVING clause to filter groups.
Les04
This document discusses SQL group functions and how to summarize aggregated data from tables. It covers:
1) The main group functions - AVG, COUNT, MAX, MIN, SUM - and how to use them to aggregate numeric, character and date fields.
2) Using the GROUP BY clause to divide rows into groups and return aggregate results per group. Columns in the SELECT must be in the GROUP BY or be aggregate functions.
3) Applying the HAVING clause to restrict groups based on aggregate results, after rows are grouped and aggregate functions applied. HAVING cannot be used in the WHERE clause.
Les04
This document discusses how to use group functions in SQL to aggregate data and summarize it. It covers the available group functions like COUNT, MAX, MIN, AVG, and SUM. It explains how to use the GROUP BY clause to group data and the HAVING clause to restrict groups. It provides examples of queries that use group functions with GROUP BY and HAVING to summarize data at the group level.
Dynamic websites lec2
This document discusses various SQL concepts including the LIKE operator, TOP clause, UNION vs UNION ALL, IN operator, aggregation functions, GROUP BY clause, HAVING clause, and the difference between HAVING and WHERE. It provides examples of queries using these concepts on sample tables and explains the purpose and syntax of each concept. Quizzes with sample queries and answers are also included.
Aggregate Functions,Final
The document discusses various aggregate functions used in SQL such as SUM, COUNT, AVG, MIN, and MAX. It provides examples of how to use these functions to retrieve aggregated data from tables, including the use of GROUP BY and HAVING clauses. Aggregate functions summarize data over multiple rows, returning a single value. COUNT(*) counts all rows while other functions like COUNT ignore NULL values.
Les06 (using subqueries to solve queries)
This document discusses using subqueries to solve database queries. It defines subqueries and describes how they allow querying values based on unknown criteria from another table. The document outlines single-row and multiple-row subqueries, and how to write them using operators like >, <, =, IN, ALL, and ANY. It provides examples of using subqueries with aggregation functions and the HAVING clause.
PHP mysql Aggregate functions
Aggregate functions summarize data from multiple rows into a single value. They operate on a single column and return a single value. Common aggregate functions include SUM, AVG, MIN, MAX, and COUNT. SUM returns the sum of numeric column values. AVG returns the average of numeric column values. MIN and MAX return the minimum and maximum values in a column. COUNT returns the number of rows.
Introduction to Oracle Functions--(SQL)--Abhishek Sharma
Functions make query results easier to understand and manipulate data values. There are two categories of functions: single row/scalar functions that return one value per row, and group/aggregate functions that operate on sets of values to return a single result. The GROUP BY clause groups rows based on columns and is used with aggregate functions to return summary results for each group.
Les06
This document discusses subqueries, which are inner queries that are nested within outer queries. It describes two types of subqueries: single-row subqueries that return one row and can be used with single-row operators like =, >, etc, and multiple-row subqueries that return multiple rows and use operators like IN, ANY, ALL. It provides examples of how to write different types of subqueries and the proper syntax to use, and common issues to avoid like using single-row operators with multiple-row subqueries.
Les06
This document discusses using subqueries to solve database queries. It defines subqueries and describes how they allow querying values based on unknown criteria from another table. The document outlines single-row and multiple-row subqueries and how to write them. It provides examples of using operators like >, <, =, IN, ALL, and ANY with subqueries to return rows that meet conditions compared to results from the subquery.
James Colby Maddox Business Intellignece and Computer Science Portfolio
This portfolio covers the business intelligence course work I have completed at Set Focus, and some of the course work I have completed at Kennesaw State University
Sql5
Group functions operate on sets of rows to give one result per group. Common group functions include COUNT, SUM, AVG, MIN, and MAX. The GROUP BY clause is used to divide rows into groups and the HAVING clause excludes groups based on a condition. Nesting group functions allows analyzing groups of groups, like finding the maximum of several averages.
Database Management System - SQL Advanced Training
Database Management System - SQL Advanced Training
Using SQL language
By Microsoft SQL Server program
version 2008-2010-2012-2014
Prepared by: Moutasm Tamimi
Introduction to oracle functions
Functions in Oracle can be used to manipulate data values and are categorized as single-row/scalar functions and group/aggregate functions. Single-row functions operate on each row and return one value per row, while group functions operate on sets of values to return one result. The GROUP BY clause is used to group or categorize data and can be used with aggregate functions to return summary results for each group.
Similar to Group By, Having Clause and Order By clause (20)
Introduction to Oracle Functions--(SQL)--Abhishek Sharma
Introduction to Oracle Functions--(SQL)--Abhishek Sharma
James Colby Maddox Business Intellignece and Computer Science Portfolio
James Colby Maddox Business Intellignece and Computer Science Portfolio
Database Management System - SQL Advanced Training
Database Management System - SQL Advanced Training
More from Deepam Aggarwal
Frames and its components
What is a frame in HTML?
Drawbacks of frame
Explanation with examples
frame, frameset, noframe
Attributes of frame tag
Interesting examples
Bank managment system
This document provides an overview of a bank management system called BANDICO. It includes a table of contents, lists of tables and figures, and 5 chapters. Chapter 1 defines the problem and objectives of the system. It describes issues currently faced by banks and customers. Chapter 2 covers the system analysis and design, including block diagrams, use cases, entity-relationship diagrams, and data flow diagrams. Chapter 3 provides a summary and discusses the future scope of the system. The document presents information on requirements gathering and system modeling for developing a software system to help manage bank operations and customer services more efficiently.
Monolithic and Procedural Programming
This presentation contains:
About Monolithic and Procedural Programming and their features
Difference between Monolithic and Procedural Programming
Examples of Monolithic and Procedural Programming
Combine example of Monolithic and Procedural Programming
Inventory Management
This document defines inventory and its components, which include finished goods, work in progress, and raw materials. It describes the costs included in inventory valuation, such as purchase costs, conversion costs, and other costs to bring inventory to its present condition. It also outlines costs excluded from inventory valuation, like abnormal waste and administrative overheads. Common inventory costing methods are identified as specific identification, FIFO, LIFO, and weighted average. The objectives of inventory management are given as achieving satisfactory customer service while keeping inventory costs reasonable. Examples of specific identification, FIFO, LIFO, and weighted average inventory costing methods are also provided.
Dynamic memory allocation and linked lists
This presentation contains:
About dynamic memory allocations
Methods or functions used for dynamic memory allocation
Examples of dynamic memory allocation with code
Difference between array and linked lists
Merits and demerits of linked lists
What we can achieve with linked lists?
Cyber Criminal and Cyber Security
This presentation includes :
What is cybercrime?
What is cybersecurity?
Types of cybercrime
How to be safe from cybercrime?
Different cyber laws
Mdi vb.net
Presentation on the topic "MDI"
Includes:
What is MDI?
How to create MDI forms?
Step by step guide
Example code of MDI form with output
Stress Management
Presentation on the topic "Stress Management"
Includes:
What is stress?
What is stress management?
Types of stress and their relaxation methods
How to handle stress at the time of Interview
How to handle stress at the workplace
IT INCLUDES TWO VIDEOS, IF YOU WILL DOWNLOAD YOU CAN PLAY THEM
Impressionism
Impressionism was an art movement developed in the late 1800s by a group of Paris-based artists who began publicly exhibiting their paintings in the 1860s. The name comes from Claude Monet's painting Impression, Sunrise. Impressionist artists felt photography was ruining painting, so they created a new style focusing on capturing sensations rather than accurately rendering subjects. They used short, thick brushstrokes; painted outdoors capturing changing light; and did not blend or smoothly shade colors. Though initially disliked, Impressionism came to be seen as capturing a fresh vision and was influential to later art movements. Major Impressionist artists included Monet, Renoir, Degas, Pissarro, and Sis
Powersharinginindia 150527161221-lva1-app6892
About power-sharing in the constitution of India
About different Institutions in the constitution
Government and its governance
Politics
Triangle and its properties
This presentation discusses properties of triangles, including:
- Classifying triangles by side lengths as scalene, isosceles, or equilateral.
- Classifying triangles by angle measures as acute, obtuse, or right.
- Defining medians and altitudes of triangles.
- Proving properties such as the angle sum theorem, the exterior angle theorem, and Pythagorean theorem.
probability-game of chances
Probability
Game of chance
Binomial distribution
Throwing of a dice
Cell phone transmission
Earthquakes
Metro
Political and public awareness through media (B.st)
B.st
Public awareness created through media
Political awareness
Social media
Publicity
Media
Broadcast
Advantages of media
Disadvantages of media
More from Deepam Aggarwal (13)
Political and public awareness through media (B.st)
Political and public awareness through media (B.st)
Recently uploaded
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Building RAG with self-deployed Milvus vector database and Snowpark Container...
This talk will give hands-on advice on building RAG applications with an open-source Milvus database deployed as a docker container. We will also introduce the integration of Milvus with Snowpark Container Services.
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentationsみなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
How to Get CNIC Information System with Paksim Ga.pptx
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Communications Mining Series - Zero to Hero - Session 1
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
“I’m still / I’m still / Chaining from the Block”
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Recently uploaded (20)
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Large Language Model (LLM) and it’s Geospatial Applications
Large Language Model (LLM) and it’s Geospatial Applications
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Building RAG with self-deployed Milvus vector database and Snowpark Container...
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
Group By, Having Clause and Order By clause
- 1. GROUP BY,HAVING and ORDER BY clause DEEPAM AGGARWAL 1
- 2. org payroll X 1500 Y 3500 Z 3000 GROUP BY Clause SELECT Statement – Grouping Rows Find the payrollof each organization. SELECT org, sum(salary) payroll FROM salary_statistics GROUP BY org Result: salary_statistics emp org salary A X 500 B X 1000 C Y 1000 D Y 2500 E Z 3000 2
- 3. org payroll X 1500 Z 3000 HAVING Clause Find the organizations with payroll less than $3200. SELECT org, sum(salary) payroll FROM salary_statistics GROUP BY org HAVING payroll < 3200 Result: salary_statistics emp org salary A X 500 B X 1000 C Y 1000 D Y 2500 E Z 3000 3
- 4. The Difference Between WHERE and HAVING Clauses WHERE gets processed before any GROUP BY, and so it doesn't have access to aggregated values (that is, the results of min(), max(), etc. functions). HAVING gets processed after GROUP BY and so can be used to constrain the result set to only those with aggregated values that match a certain predicate. Find the organizations with payroll less than $3200. SELECT org, sum(salary) payroll FROM salary_statistics }✗Incorrect WHERE payroll < 3200 GROUP BY org SELECT org, sum(salary) payroll FROM salary_statistics }✓ Correct GROUP BY org HAVING payroll < 3200 4
- 5. SELECT Statement – ORDER BY Clause Find students ordered by merit position. SELECT * FROM result ORDER BY marks DESC result student marks A 25 B 56 C 82 D 25 E 39 5