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    SQL Order of Operations

    Is the order in which SQL operations are executed important? Improve your SQL skills by learning the order of operations execution in SQL.

    8th Oct 2019 7 minutes read

    SQL Order of Operations

    Ignacio L. Bisso SQL Learn Sql SQL Basics

    SQL is not a traditional programming language in which you write a sequence of instructions in a given order of execution. Instead, SQL is a "declarative" language, which means that by writing a SQL query, you declare what data you expect as a result of the query, but you don't indicate how to obtain it.

    Six Operations to Order: SELECT, FROM, WHERE, GROUP BY, HAVING, and ORDER BY

    By using examples, we will explain the execution order of the six most common operations or pieces in an SQL query. Because the database executes query components in a specific order, it's helpful for the developer to know this order. It's similar to following a recipe: you need to know the ingredients and what to do with ingredients, but you also need to know in which order do the tasks. If the database follows a different order of operations, the performance of the query can decrease dramatically.

    The best way to learn SQL order of operations is through practice. I recommend LearnSQL.com's SQL Practice track. It contains over 600 hands-on exercises to practice your SQL skills. Or select the best course for you from over 30 interactive SQL courses we offer at various levels of proficiency.

    LearnSQL.com provides a one-stop-shop for all things SQL, covering basic to advanced concepts in one single platform. LearnSQL.com is specifically geared towards SQL. It offers 30 interactive SQL courses that range in difficulty from beginner to advanced and monthly SQL challenges to practice your SQL skills.

    The Employee Database

    In this article, we will work with a database for a typical company that has employees distributed in different departments. Each employee has an ID, a name, and a salary and belongs to a department, as we can see in the following tables.

    Sample of the EMPLOYEE table:

    EMPLOYEE_ID FIRST_NAME LAST_NAME SALARY DEPARTMENT

    100 James Smith 78,000 ACCOUNTING

    101 Mary Sexton 82,000 IT

    102 Chun Yen 80,500 ACCOUNTING

    103 Agnes Miller 95,000 IT

    104 Dmitry Komer 120,000 SALES

    Sample of the DEPARTMENT table:

    DEPT_NAME MANAGER BUDGET

    ACCOUNTING 100 300,000

    IT 101 250,000 SALES 104 700,000

    In this article, we will also use frequent SQL queries used in a company: "Obtain the names of employees working for the IT department" or "Obtain the number of employees in each department with a salary higher than 80.000." For each of these queries, we will analyze the order of execution of its components.

    Let's start with a simple query to obtain the names of the employees in the IT department:

    SELECT LAST_NAME, FIRST_NAME

    FROM EMPLOYEE

    WHERE DEPARTMENT = 'IT'

    First, we execute FROM EMPLOYEE, which retrieves this data:

    EMPLOYEE_ID FIRST_NAME LAST_NAME SALARY DEPARTMENT

    100 James Smith 78,000 ACCOUNTING

    101 Mary Sexton 82,000 IT

    102 Chun Yen 80,500 ACCOUNTING

    103 Agnes Miller 95,000 IT

    104 Dmitry Komer 120,000 SALES

    Second, we execute WHERE DEPARTMENT = 'IT', which narrows it down to this:

    EMPLOYEE_ID FIRST_NAME LAST_NAME SALARY DEPARTMENT

    101 Mary Sexton 82,000 IT

    103 Agnes Miller 95,000 IT

    Finally, we apply SELECT FIRST_NAME, LAST_NAME, producing the final result of the query:

    FIRST_NAME LAST_NAME

    Mary Sexton Agnes Miller

    Great! After completing our first query dissection, we can conclude that the order of execution for simple queries with SELECT, FROM, and WHERE is:

    The best way to practice SQL is with our SQL Practice track. It has 600+ interactive exercises, and we keep adding more!

    Changes in the Order of Operations If We Add ORDER BY

    Suppose your boss receives a report based on the query in the previous example and rejects it, because the employee names are not in alphabetical order. To fix it, you need to add an ORDER BY clause to the previous query:

    SELECT LAST_NAME, FIRST_NAME

    FROM EMPLOYEE

    WHERE DEPARTMENT = 'IT'

    ORDER BY FIRST_NAME

    The execution process of this query is almost the same as in the previous example. The only change is at the end, when the ORDER BY clause is processed. The final result of this query orders the entries by FIRST_NAME, as shown below:

    FIRST_NAME LAST_NAME

    Agnes Miller Mary Sexton

    So, if we have SELECT with FROM, WHERE, and ORDER BY, the order of execution is:

    Adding GROUP BY and HAVING Clauses to the Query

    In this example, we will use a query with GROUP BY. Suppose we want to obtain how many employees in each department have a salary higher than 80,000, and we want the result in descending order by the number of people in each department. The query for this situation is:

    SELECT DEPARTMENT, COUNT(*)

    FROM EMPLOYEES

    WHERE SALARY > 80000

    GROUP BY DEPARTMENT

    ORDER BY COUNT(*) DESC

    Again, we first execute FROM EMPLOYEE, which retrieves this data:

    EMPLOYEE_ID FIRST_NAME LAST_NAME SALARY DEPARTMENT

    100 James Smith 78,000 ACCOUNTING

    101 Mary Sexton 82,000 IT

    102 Chun Yen 80,500 ACCOUNTING

    103 Agnes Miller 95,000 IT

    104 Dmitry Komer 120,000 SALES

    Second, we execute WHERE SALARY > 80000, which narrows it down to this:

    स्रोत : learnsql.com

    [Solved] The Correct order of SQL expression is

    The correct answer is Select, where, group by, having. Additional Information Six Operations to Order: SELECT, FROM, WHERE, GROUP BY, HAVING, and&nb

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    The Correct order of SQL expression is

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    Select, group by, where, having

    Select, having, group by, where

    Select, having, where, group by

    Select, where, group by, having

    Answer (Detailed Solution Below)

    Option 4 : Select, where, group by, having

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    The correct answer is Select, where, group by, having.

    Additional Information

    Six Operations to Order: SELECT, FROM, WHERE, GROUP BY, HAVING, and ORDER BY. Because the database executes query components in a specific order,

    SELECT select_list [ INTO new_table ]  [ FROM table_source ]

    [ WHERE search_condition ]

    [ GROUP BY group_by_expression ]

    [ HAVING search_condition ]

    [ ORDER BY order_expression [ ASC | DESC ] ]

    Hence Option 4 is correct

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    Q1. Which of the following word is associated with database?Q2. ______ is an advanced discipline that teaches students how to analyse and find patterns in large amounts of data.Q3. The _______ is a simple query language used for accessing, handling and managing data in a relational database.Q4. A collection of interrelated files and a set of programs that allow users to access and modify these files is known as ______________.Q5. Which of the following is NOT an example of DBMS?Q6. In MS-DOS, which command displays all the files having the same name but different extensions?Q7. In a Database Management System (DBMS) which of the following is True of an Index?Q8. In MS-DOS, only filenames and extensions are to be displayed in wide format, which command you'll use?Q9. Developing database and maintaining standards and controls for an organization’s databases is calledQ10. Data bases that support the major business process of an organization are

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    SQL Order of Operations

    A quick review of an SQL query's order of operations, to learn more about the different parts of an SQL query, their order of execution and their dependencies.

    SQL Order of Operations – In Which Order MySQL Executes Queries?

    September 21, 2018

    Tomer Shay @ EverSQL

    This post's content [hide]

    FROM and JOINs WHERE clause GROUP BY clause HAVING clause Window functions SELECT clause DISTINCT keyword UNION keyword ORDER BY clause LIMIT and OFFSET

    Knowing the bits and bytes of an SQL query's order of operations can be very valuable, as it can ease the process of writing new queries, while also being very beneficial when trying to optimize an SQL query.

    If you're looking for the short version, this is the logical order of operations, also known as the order of execution, for an SQL query:

    FROM, including JOINs

    WHERE GROUP BY HAVING WINDOW functions SELECT DISTINCT UNION ORDER BY LIMIT and OFFSET

    But the reality isn't that easy nor straight forward. As we said, the SQL standard defines the order of execution for the different SQL query clauses. Said that, modern databases are already challanaging that default order by applying some optimization tricks which might change the actual order of execution, though they must end up returning the same result as if they were running the query at the default execution order.

    Why would they do that? Well, it can be silly if the database would first fetch all data mentioned in the FROM clause (including the JOINs), before looking into the WHERE clause and its indexes. Those tables can hold lots of data, so you can imagine what will happen if the database's optimizer would stick to the traditional order of operations of an SQL query.

    Let's look into each of the SQL query parts according to their execution order.

    FROM and JOINs

    The tables specified in the FROM clause (including JOINs), will be evaluated first, to determine the entire working set which is relevant for the query. The database will merge the data from all tables, according to the JOINs ON clauses, while also fetching data from the subqueries, and might even create some temporary tables to hold the data returned from the subqueries in this clause.

    In many cases though, the database's optimizer will choose to evaluate the WHERE part first, to see which part of the working set can be left out (preferably using indexes), so it won't inflate the data set too much if it doesn't really have to.

    WHERE clause

    The WHERE clause will be the second to be evaluated, after the FROM clause. We have the working data set in place, and now we can filter the data according to the conditions in the WHERE clause.

    These conditions can include references to the data and tables from the FROM clause, but cannot include any references to aliases defined in the SELECT clause, as that data and those aliases may not yet 'exist' in that context, as that clause wasn't yet evaluated by the database.

    Also, a common pitfall for the WHERE clause would be to try and filter out aggregated values in the WHERE clause, for example with this clause: "WHERE sum(available_stock) > 0". This statement will fail the query execution, because aggregations will be evaluated later in the process (see the GROUP BY section below). To apply filtering condition on aggregated data, you should use the HAVING clause and not the WHERE clause.

    GROUP BY clause

    Now that we filtered the data set using the WHERE clause, we can aggregate the data according to one or more columns appearing in the GROUP BY clause. Grouping the data is actually splitting it to different chunks or buckets, where each bucket has one key and a list of rows that match that key. Not having a GROUP BY clause is like putting all rows in a one huge bucket.

    Once you aggregate the data, you can now use aggregation functions to return a per-group value for each of the buckets. Such aggregation functions include COUNT, MIN, MAX, SUM and others.

    HAVING clause

    Now that we have grouped the data using the GROUP BY clause, we can use the HAVING clause to filter out some buckets. The conditions in the HAVING clause can refer to the aggregation functions, so the example which didn't work in the WHERE clause above, will work just fine in the HAVING clause: "HAVING sum(available_stock) > 0".

    As we've already grouped the data, we can no longer access the original rows at this point, so we can only apply conditions to filter entire buckets, and not single rows in a bucket.

    Also, as we mentioned in previous sections, aliases defined in the SELECT clause cannot be accessed in the section either, as they weren't yet evaluated by the database (this is true in most databases).

    Window functions

    If you are using Window functions, this is the point where they'll be executed. Just like the grouping mechanism, Window functions are also performing a calculation on a set of rows. The main difference is that when using Window functions, each row will keep its own identity and won't be grouped into a bucket of other similar rows.

    Window functions can only be used in either the SELECT or the ORDER BY clause. You can use aggregation functions inside the Window functions, for example:

    SUM(COUNT(*)) OVER ()

    SELECT clause

    Now that we are done with discarding rows from the data set and grouping the data, we can select the data we want to be fetched from the query to the client side. You can use column names, aggregations and subqueries inside the SELECT clause. Keep in mind that if you're using a reference to an aggregation function, such as COUNT(*) in the SELECT clause, it's merely a reference to an aggregation which already occurred when the grouping took place, so the aggregation itself doesn't happen in the SELECT clause, but this is only a reference to its result set.

    स्रोत : www.eversql.com

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