SELECT Queries Deep Dive — WHERE, Operators, ORDER BY, LIMIT & More

SQL ki sabse powerful command — SELECT ko andar bahar se samjho. Real-world queries, har operator ka use, aur interview mein pooche jaane wale saare questions — sab kuch ek jagah Data Insights par.

📑 Is Part 2 Mein Aap Kya Sikhenge:

SELECT command ke saare operators aur clauses — ek ek karke real examples ke saath:

• Topic 1: Basic SELECT — *, Columns, Aliases, Expressions
• Topic 2: WHERE Clause — Row Filtering
• Topic 3: AND, OR, NOT — Logical Operators
• Topic 4: BETWEEN — Range Filtering
• Topic 5: IN — List Matching
• Topic 6: LIKE — Pattern Matching
• Topic 7: IS NULL / IS NOT NULL
• Topic 8: ORDER BY — Sorting Results
• Topic 9: LIMIT & OFFSET — Pagination
• Topic 10: DISTINCT — Unique Values

📋 Note: Is poore Part 2 mein hum ek hi employees table use karenge jo Part 1 mein banai thi. Saare queries usi table pe run honge taaki concept clearly samajh aaye.

Pehle yeh data insert karo — baaki saare topics isi data pe run honge:

CREATE TABLE employees (
emp_id      INT PRIMARY KEY AUTO_INCREMENT,
name        VARCHAR(50) NOT NULL,
dept        VARCHAR(30),
salary      DECIMAL(10,2),
city        VARCHAR(30),
hire_date   DATE,
age         INT,
manager_id  INT
);

INSERT INTO employees (name, dept, salary, city, hire_date, age, manager_id)

VALUES
('Rahul Sharma', 'IT', 75000, 'Delhi', '2021-03-15', 28, NULL),
('Priya Singh', 'HR', 62000, 'Mumbai', '2020-07-01', 32, 1),
('Amit Kumar', 'Sales', 48000, 'Delhi', '2022-01-10', 25, 1),
('Sneha Patel', 'IT', 88000, 'Bangalore','2019-11-20', 35, 1),
('Ravi Verma', 'HR', 53000, 'Chennai', '2021-09-05', 29, 2),
('Kavita Joshi', 'Sales', 45000, 'Mumbai', '2023-02-14', 24, 2),
('Deepak Rao', 'Finance', 68000, 'Delhi', '2020-05-30', 31, 1),
('Anjali Mehta', 'IT', 92000, 'Bangalore','2018-08-12', 38, NULL),
('Suresh Nair', 'Sales', 51000, 'Chennai', '2022-06-20', 27, 2),
('Neha Gupta', 'Finance', 71000, 'Mumbai', '2019-04-18', 36, 1),
('Vikram Bose', 'IT', 83000, 'Delhi', '2020-12-01', 33, 8),
('Pooja Reddy', 'HR', NULL, 'Bangalore','2023-07-01', 23, 2),
('Arjun Das', 'Sales', 39000, 'Delhi', '2023-09-15', 22, 2),
('Meena Iyer', 'Finance', 65000, 'Chennai', '2021-11-08', 30, 1),
('Rohit Sharma', 'IT', 55000, 'Mumbai', '2022-03-22', 26, 8);

📊 Table Preview:

15 rows in set

🔍 Definition: The SELECT statement retrieves data from a table. You can select all columns using *, specific columns by name, create aliases for display, and perform arithmetic expressions directly in the query.

🎯 Samjho Simple Bhasha Mein: SELECT ek waiter ki tarah hai jo tumhara order leta hai. Tum keh sakte ho "sab kuch lao" (SELECT *), ya "sirf naam aur salary lao" (SELECT name, salary), ya "salary ko 12 se multiply karke annual salary bhi dikha do" (expression). Alias matlab — column ka display naam change karna sirf dikhane ke liye, actual column name nahi badalta.

💡 SELECT Query ka Basic Structure:

SELECT column1, column2 FROM table_name;

Execution Order yaad rakho: FROM pehle → phir SELECT. Matlab pehle table identify hoti hai, phir columns choose hote hain.

💻 Real-World Code Examples:

Example 1: Saare columns aur saari rows fetch karo.

-- Sabse basic query
SELECT *
FROM employees;

Example 2: Sirf specific columns select karo.

-- Sirf naam, department aur salary
SELECT name, dept, salary

FROM employees;

Example 3: Alias use karo aur expressions calculate karo.

-- Column aliases + calculations
SELECT
name AS 'Employee Name',
dept AS 'Department',
salary AS 'Monthly Salary',
salary * 12 AS 'Annual Salary',
salary * 0.10 AS 'Bonus (10%)'

FROM employees;

📊 Expected Output (Example 3):

(15 rows total...)

⚠️ Common Mistakes:

• Mistake: Production mein SELECT * use karna → Unnecessary data fetch, slow performance.
  Fix: Hamesha specific column names likho.
• Mistake: Alias mein space dena bina quotes ke → AS Annual Salary ❌
  Fix: AS 'Annual Salary' ya backticks use karo ✅
• Mistake: Alias ko WHERE clause mein use karna → Error aayega.
  Fix: WHERE mein original column name use karo — alias sirf display ke liye hai.

💬 Interview Questions:

🔍 Definition: The WHERE clause filters rows from a table based on a specified condition. Only rows that satisfy the condition are included in the result. WHERE works with comparison operators: = (equal), != or <> (not equal), > (greater than), < (less than), >= (greater than or equal), <= (less than or equal).

🎯 Samjho Simple Bhasha Mein: Socho tumhare paas 15 employees hain. Tum sirf IT department ke employees dekhna chahte ho — WHERE lagao aur filter ho jayega. WHERE ek security guard ki tarah hai jo sirf specific criteria wale logon ko andar aane deta hai.

💡 Comparison Operators:
= Equal to | != or <> Not equal to
> Greater than | < Less than
>= Greater or equal | <= Less or equal

💻 Real-World Code Examples:

Example 1: Sirf IT department ke employees dikhao.

-- String comparison (quotes zaroori hain)
SELECT name, dept, salary

FROM employees

WHERE dept = 'IT';

Example 2: 60000 se zyada salary wale employees.

-- Numeric comparison (quotes nahi lagte numbers mein)
SELECT name, dept, salary

FROM employees

WHERE salary > 60000;

Example 3: Sales department ke employees ko exclude karo.

-- Not equal operator
SELECT name, dept, salary

FROM employees

WHERE dept != 'Sales';

-- Ya yeh bhi same kaam karta hai:

WHERE dept <> 'Sales';

📊 Expected Output (Example 1 — IT Employees):

5 rows in set

⚠️ Common Mistakes:

• Mistake: String values mein quotes bhool jaana → WHERE dept = IT ❌ — MySQL "IT" ko column name samjhega.
  Fix: WHERE dept = 'IT' ✅
• Mistake: Numbers mein quotes lagana → WHERE salary > '60000' — kaam toh karega but implicit type conversion hogi, slow performance.
  Fix: WHERE salary > 60000 ✅
• Mistake: NULL check ke liye = use karna → WHERE salary = NULL ❌ — hamesha FALSE return karega.
  Fix: WHERE salary IS NULL ✅ (Topic 7 mein detail mein)

💬 Interview Questions:

🔍 Definition: Logical operators combine multiple conditions in a WHERE clause. AND requires ALL conditions to be true. OR requires ANY ONE condition to be true. NOT reverses/negates a condition.

🎯 Samjho Simple Bhasha Mein: AND matlab "yeh bhi aur woh bhi" — dono conditions true honi chahiye. OR matlab "yeh ya woh" — koi ek bhi true ho toh chalega. NOT matlab "ulta karo" — jo true tha woh false, jo false tha woh true. Real life mein: "IT department AND salary > 70000" — dono conditions zaroor honi chahiye tab row select hogi.

💡 Operator Precedence (Priority Order):
MySQL mein pehle NOT, phir AND, phir OR evaluate hota hai.
WHERE A OR B AND C → Actually: WHERE A OR (B AND C)
Best Practice: Hamesha parentheses use karo confusion avoid karne ke liye!

💻 Real-World Code Examples:

Example 1 (AND): IT department mein 80000 se zyada salary wale.

-- AND: Dono conditions true honi chahiye
SELECT name, dept, salary, city

FROM employees

WHERE dept = 'IT' AND salary > 80000;

Example 2 (OR): IT ya Finance department ke employees.

-- OR: Koi ek condition true ho toh chalega
SELECT name, dept, salary

FROM employees

WHERE dept = 'IT' OR dept = 'Finance';

Example 3 (NOT): Delhi mein nahi rehne wale employees.

-- NOT: Condition ko negate karo
SELECT name, city, dept

FROM employees

WHERE NOT city = 'Delhi';

Example 4 (Combined): IT ya HR department mein ho AND salary 60000 se zyada ho AND Delhi mein na ho.

-- Complex condition with parentheses (best practice)
SELECT name, dept, salary, city

FROM employees

WHERE (dept = 'IT' OR dept = 'HR')
AND salary > 60000
AND NOT city = 'Delhi';

📊 Expected Output (Example 1 — AND):

3 rows in set

📊 Expected Output (Example 4 — Combined):

3 rows in set

⚠️ Common Mistakes:

• Mistake: Parentheses na lagana complex queries mein → Wrong results milenge silently.
  Fix: Hamesha OR ke groups ko parentheses mein wrap karo.
• Mistake: WHERE dept = 'IT' OR 'HR' ❌ — 'HR' ko boolean treat karega.
  Fix: WHERE dept = 'IT' OR dept = 'HR' ✅ — Har condition mein column name repeat karo.
• Mistake: AND aur OR ki priority bhool jaana → AND pehle evaluate hota hai OR se.
  Fix: Parentheses se explicit order define karo.

💬 Interview Questions:

🔍 Definition: BETWEEN operator filters rows where a column value falls within a specified range — inclusive of both boundary values. It works with numbers, dates and strings. Syntax: column BETWEEN value1 AND value2.

🎯 Samjho Simple Bhasha Mein: BETWEEN ek range define karta hai. Jaise "50000 se 80000 ke beech salary" — toh 50000 aur 80000 dono included hain. Yeh salary >= 50000 AND salary <= 80000 likhne ka shortcut hai. Dates ke saath bhi kaam karta hai — "January 2021 se December 2022 ke beech join hue employees."

💡 Important: BETWEEN inclusive hota hai — matlab dono boundary values (value1 aur value2) bhi result mein aayenge. BETWEEN 50000 AND 80000 mein exactly 50000 aur exactly 80000 dono included hain.

💻 Real-World Code Examples:

Example 1: 50000 se 80000 ke beech salary wale employees.

-- Numeric range
SELECT name, dept, salary

FROM employees

WHERE salary BETWEEN 50000 AND 80000;

-- Equivalent to:
-- WHERE salary >= 50000 AND salary

Example 2: 2021 se 2022 ke beech hire hue employees.

-- Date range
SELECT name, hire_date, dept

FROM employees

WHERE hire_date BETWEEN '2021-01-01' AND '2022-12-31';

Example 3: NOT BETWEEN — 50000-80000 range ke bahar salary wale.

-- NOT BETWEEN: Range ke bahar
SELECT name, salary

FROM employees

WHERE salary NOT BETWEEN 50000 AND 80000;

📊 Expected Output (Example 1):

9 rows in set

⚠️ Common Mistakes:

• Mistake: BETWEEN mein bada value pehle dena → BETWEEN 80000 AND 50000 ❌ — Koi result nahi aayega.
  Fix: Hamesha chota value pehle: BETWEEN 50000 AND 80000 ✅
• Mistake: Date BETWEEN mein time ignore karna → BETWEEN '2022-01-01' AND '2022-12-31' mein December 31 ka time 00:00:00 maana jayega, baad ke records miss honge.
  Fix: BETWEEN '2022-01-01' AND '2022-12-31 23:59:59' ✅
• Mistake: BETWEEN ko exclusive samajhna → Yeh inclusive hai, dono boundary values included hain.

💬 Interview Questions:

🔍 Definition: The IN operator checks if a column value matches any value from a specified list. It is a cleaner alternative to writing multiple OR conditions. Syntax: column IN (value1, value2, value3, ...).

🎯 Samjho Simple Bhasha Mein: IN ek guest list ki tarah hai. Tum keh rahe ho "andar wohi aayega jo is list mein hai." WHERE city IN ('Delhi', 'Mumbai', 'Bangalore') matlab sirf in teeno cities ke employees aayenge. Yeh multiple OR likhne ka shortcut hai aur query zyada readable hoti hai.

💡 IN vs OR — Kab kya use karein:
2-3 values → OR theek hai.
4+ values → IN zyada readable aur maintainable hai.
IN can also take a subquery as its list — very powerful! (Part 5 mein cover hoga)

💻 Real-World Code Examples:

Example 1: Delhi, Mumbai ya Bangalore ke employees.

-- IN with string list
SELECT name, city, dept

FROM employees

WHERE city IN ('Delhi', 'Mumbai', 'Bangalore');

-- Equivalent to (but less readable):
-- WHERE city = 'Delhi' OR city = 'Mumbai' OR city = 'Bangalore'

Example 2: IT, HR aur Finance department ke employees.

SELECT name, dept, salary

FROM employees

WHERE dept IN ('IT', 'HR', 'Finance');

Example 3: NOT IN — Sales department ke employees exclude karo.

-- NOT IN: List ke bahar wale
SELECT name, dept, salary

FROM employees

WHERE dept NOT IN ('Sales');

📊 Expected Output (Example 2):

11 rows in set

⚠️ Common Mistakes:

• Mistake: NOT IN list mein NULL include karna → WHERE dept NOT IN ('IT', NULL) — Koi result nahi aayega!
  Fix: NULL ko NOT IN list mein kabhi mat daalo. NULL ke liye IS NOT NULL separately use karo.
• Mistake: Bahut badi IN list → Performance slow ho sakti hai.
  Fix: Large lists ke liye subquery ya temporary table use karo.
• Mistake: IN mein values ke beech space bhool jaana → Syntax error nahi aayega but wrong matching ho sakti hai.

💬 Interview Questions:

🔍 Definition: LIKE operator performs pattern matching on string columns using two wildcards: % (percent — matches any sequence of characters including none) and _ (underscore — matches exactly one character). It is used for partial string searches.

🎯 Samjho Simple Bhasha Mein: LIKE ek search tool hai jab exact value pata na ho. % matlab "kuch bhi, kitna bhi." _ matlab "exactly ek character." Socho Gmail search — tum "Rah" likhte ho aur "Rahul", "Rahman", "Raheja" sab show ho jaate hain — yeh LIKE 'Rah%' jaisa kaam hai.

💡 Wildcard Patterns — Quick Reference:
'R%' → R se shuru hone wale (Rahul, Ravi, Rohit)
'%a' → a pe khatam hone wale (Priya, Sneha, Neha)
'%ar%' → beech mein "ar" aane wale (Rahul Sharma, Arjun)
'R_vi' → R + exactly 1 char + vi (Ravi) — not Rahul
'____' → Exactly 4 characters

💻 Real-World Code Examples:

Example 1: "R" se shuru hone wale employees.

-- R se shuru hone wale naam
SELECT name, dept

FROM employees

WHERE name LIKE 'R%';

Example 2: Naam mein "Sharma" aane wale employees.

-- Beech mein 'Sharma' aane wale
SELECT name, city

FROM employees

WHERE name LIKE '%Sharma%';

Example 3: "a" pe khatam hone wale naam.

-- 'a' pe khatam hone wale
SELECT name

FROM employees

WHERE name LIKE '%a';

Example 4: NOT LIKE — "Sharma" naam wale exclude karo.

-- NOT LIKE
SELECT name

FROM employees

WHERE name NOT LIKE '%Sharma%';

📊 Expected Output (Example 1 — R% names):

3 rows in set

⚠️ Common Mistakes:

• Mistake: LIKE '%value%' leading wildcard use karna large tables par → Full table scan hoga, index use nahi hoga — very slow!
  Fix: Agar possible ho toh LIKE 'value%' (leading wildcard nahi) use karo — index ka fayda milega.
• Mistake: Case sensitivity bhool jaana → MySQL mein LIKE by default case-insensitive hai (utf8 collation). 'sharma' aur 'Sharma' dono match honge.
  Fix: Case-sensitive search ke liye LIKE BINARY 'Sharma%' use karo.
• Mistake: % aur _ ka role confuse karna → % = any length, _ = exactly 1 character.

💬 Interview Questions:

🔍 Definition: NULL represents the absence of a value — it is not zero, not empty string, not false. It means "unknown" or "not applicable." IS NULL checks for missing values and IS NOT NULL checks for present values. Standard comparison operators (=, !=) do NOT work with NULL.

🎯 Samjho Simple Bhasha Mein: NULL matlab "pata nahi" ya "available nahi." Jaise Pooja Reddy ki salary table mein NULL hai — matlab uski salary abhi set nahi hui. Rahul Sharma ka manager_id NULL hai — matlab woh khud manager hai. NULL ko normal = se check nahi kar sakte — sirf IS NULL ya IS NOT NULL se check hota hai. Yeh SQL ka sabse confusing concept hai!

💡 NULL ke baare mein 3 Important Rules:
1. NULL = NULL → FALSE (NULL khud se bhi equal nahi hota!)
2. NULL != NULL → FALSE
3. Koi bhi comparison NULL ke saath → UNKNOWN return karta hai

Isliye hamesha: IS NULL ya IS NOT NULL use karo — koi aur operator nahi.

💻 Real-World Code Examples:

Example 1: Jinki salary NULL hai (abhi set nahi hui).

-- NULL salary wale employees
SELECT name, dept, salary

FROM employees

WHERE salary IS NULL;

-- ❌ Yeh WRONG hai — koi result nahi aayega:
-- WHERE salary = NULL

Example 2: Jinki salary set hai (NULL nahi hai).

-- Salary filled wale employees
SELECT name, dept, salary

FROM employees

WHERE salary IS NOT NULL;

Example 3: Manager ke NULL hone ka matlab — jo top-level managers hain (koi manager nahi hai inke upar).

-- Top level managers (koi manager nahi hai inke upar)
SELECT name, dept, manager_id

FROM employees

WHERE manager_id IS NULL;

-- NULL ko handle karna display mein — IFNULL / COALESCE
SELECT
name,
IFNULL(salary, 0) AS salary,
COALESCE(manager_id, 0) AS manager_id

FROM employees;

📊 Expected Output (Example 1 — NULL salary):

1 row in set -- Example 3 (Top managers with NULL manager_id): 2 rows in set

⚠️ Common Mistakes:

• Mistake: WHERE salary = NULL use karna → Hamesha 0 rows return karega.
  Fix: WHERE salary IS NULL ✅
• Mistake: NULL aur empty string ('') ko same samajhna → '' ek valid empty string hai, NULL bilkul alag hai.
  Fix: Dono alag alag handle karo: WHERE name = '' aur WHERE name IS NULL.
• Mistake: NULL values aggregate functions mein ignore hona bhool jaana → COUNT(*) saari rows count karta hai, COUNT(salary) NULL values ignore karta hai.

💬 Interview Questions:

🔍 Definition: ORDER BY clause sorts the result set based on one or more columns. ASC (ascending — default) sorts from lowest to highest or A to Z. DESC (descending) sorts from highest to lowest or Z to A. You can sort by multiple columns — first column sorts first, ties broken by second column.

🎯 Samjho Simple Bhasha Mein: ORDER BY results ko arrange karta hai. Jaise salary ke hisaab se top earners pehle dikhao (DESC), ya naam ke alphabetical order mein dikhao (ASC). Multiple columns — pehle department ke hisaab se sort karo, phir same department mein salary ke hisaab se — yeh bhi possible hai.

💡 NULL values in ORDER BY:
ASC order mein NULL values pehle aate hain (sabse chhote maane jaate hain).
DESC order mein NULL values baad mein aate hain.
ORDER BY column position number se bhi ho sakta hai: ORDER BY 3 DESC = 3rd column descending.

💻 Real-World Code Examples:

Example 1: Salary ke hisaab se descending order (highest first).

-- Highest salary first
SELECT name, dept, salary

FROM employees

ORDER BY salary DESC;

Example 2: Naam ke alphabetical order mein (ASC — default).

-- Alphabetical A to Z (ASC is default, can skip writing it)
SELECT name, dept

FROM employees

ORDER BY name ASC;

Example 3: Pehle department alphabetically, phir same department mein salary descending.

-- Multi-column sort
SELECT name, dept, salary

FROM employees

ORDER BY dept ASC, salary DESC;

📊 Expected Output (Example 3 — Multi Column Sort):

15 rows in set

⚠️ Common Mistakes:

• Mistake: ORDER BY ke baad LIMIT lagana bhool jaana → Large tables par saara sorted data memory mein load hoga.
  Fix: Top N results ke liye hamesha ORDER BY ... LIMIT n use karo.
• Mistake: ORDER BY column position number use karna production mein → ORDER BY 3 — Agar table structure change ho toh wrong column sort hoga.
  Fix: Hamesha explicit column name use karo.
• Mistake: ORDER BY aur GROUP BY dono hone par ORDER BY pehle likhna → Syntax error aayega.
  Fix: Sequence: WHERE → GROUP BY → HAVING → ORDER BY → LIMIT.

💬 Interview Questions:

🔍 Definition: LIMIT restricts the number of rows returned by a query. OFFSET skips a specified number of rows before starting to return results. Together they enable pagination — showing data in pages like websites do (Page 1, Page 2, Page 3...).

🎯 Samjho Simple Bhasha Mein: LIMIT matlab "sirf itne results do." OFFSET matlab "pehle itne skip karo, phir dena shuru karo." Jaise Flipkart par 100 products hain par page par sirf 10 dikhate hain — pehla page: LIMIT 10 OFFSET 0, doosra page: LIMIT 10 OFFSET 10, teesra page: LIMIT 10 OFFSET 20. Yahi pagination hai!

💡 Pagination Formula:
LIMIT page_size OFFSET (page_number - 1) * page_size

Page 1: LIMIT 5 OFFSET 0
Page 2: LIMIT 5 OFFSET 5
Page 3: LIMIT 5 OFFSET 10

Shorthand: LIMIT offset, count → LIMIT 10, 5 = skip 10, show 5

💻 Real-World Code Examples:

Example 1: Top 5 highest salary wale employees.

-- Top 5 earners
SELECT name, dept, salary

FROM employees

ORDER BY salary DESC

LIMIT 5;

Example 2: Page 2 of results (5 per page — skip first 5, show next 5).

-- Page 2 (records 6 to 10)
SELECT name, dept, salary

FROM employees

ORDER BY emp_id ASC

LIMIT 5
OFFSET 5;

-- Shorthand (same result):

LIMIT 5, 5;
-- LIMIT offset, count

Example 3: Salary mein 3rd highest earner kaun hai.

-- 3rd highest salary (skip top 2, show 1)
SELECT name, salary

FROM employees

WHERE salary IS NOT NULL

ORDER BY salary DESC

LIMIT 1
OFFSET 2;

📊 Expected Output (Example 1 — Top 5):

5 rows in set

-- Example 3 (3rd highest):

1 row in set

⚠️ Common Mistakes:

• Mistake: LIMIT bina ORDER BY use karna → Random rows milenge — pagination consistent nahi hogi.
  Fix: Hamesha LIMIT ke saath ORDER BY use karo.
• Mistake: LIMIT 0, 5 ko confuse karna → LIMIT 0, 5 matlab OFFSET 0, COUNT 5 (pehle 5 records).
  Fix: Clarity ke liye explicit syntax use karo: LIMIT 5 OFFSET 0.
• Mistake: Bahut bade OFFSET ke saath slow query → LIMIT 5 OFFSET 100000 — MySQL 100000 rows skip karne ke liye scan karega.
  Fix: Cursor-based pagination use karo large datasets ke liye: WHERE id > last_seen_id LIMIT 5.

💬 Interview Questions:

🔍 Definition: DISTINCT eliminates duplicate rows from the result set, returning only unique combinations of the selected columns. It is placed immediately after SELECT keyword and applies to all selected columns together.

🎯 Samjho Simple Bhasha Mein: 15 employees hain aur 4 departments hain. Agar tum sirf departments ki list chahte ho (repetitions ke bina), toh DISTINCT use karo. Bina DISTINCT: IT, HR, Sales, IT, HR, Sales, Finance... DISTINCT ke saath: IT, HR, Sales, Finance — bas ek baar. Yeh "unique values" nikalne ka tool hai.

💡 Important: DISTINCT multiple columns ke saath — combination unique hoti hai, individual column nahi. SELECT DISTINCT dept, city mein (IT, Delhi) aur (IT, Mumbai) dono aayenge — kyunki combination alag hai, even though dept same hai.

💻 Real-World Code Examples:

Example 1: Unique departments ki list.

-- Unique departments
SELECT DISTINCT dept

FROM employees;

Example 2: Unique department + city combinations.

-- Unique dept + city combinations
SELECT DISTINCT dept, city

FROM employees

ORDER BY dept, city;

Example 3: Kitne unique cities hain — COUNT with DISTINCT.

-- Count of unique cities
SELECT COUNT(DISTINCT city) AS unique_cities

FROM employees;

-- Count of unique departments
SELECT COUNT(DISTINCT dept) AS total_departments

FROM employees;

📊 Expected Output:

-- Example 1 (Unique departments):

4 rows in set

-- Example 2 (Unique dept+city combos):

12 rows in set

-- Example 3 (Count):

⚠️ Common Mistakes:

• Mistake: DISTINCT ko sirf pehle column par apply samajhna → SELECT DISTINCT dept, city mein DISTINCT dono columns ki combination par apply hota hai.
  Fix: Clearly samjho — DISTINCT entire row combination check karta hai.
• Mistake: DISTINCT aur GROUP BY ko same samajhna → Dono unique values dete hain but GROUP BY aggregation bhi kar sakta hai.
  Fix: Sirf unique values chahiye → DISTINCT. Aggregate calculations bhi chahiye → GROUP BY.
• Mistake: Large tables par DISTINCT overuse karna → Performance issue hoga kyunki sorting/hashing lagti hai.
  Fix: Index use karo ya GROUP BY prefer karo jahan possible ho.

💬 Interview Questions:

Next: Data Insights MySQL Masterclass — Part 3

Part 3 mein hum cover karenge: Aggregate Functions + GROUP BY + HAVING — COUNT, SUM, AVG, MIN, MAX ke saath real-world analytics queries aur interview questions Data Insights par.

Happy Querying & Keep Learning SQL! 🚀