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10. MySQL Part 1: Install, Create, Insert and SELECT

10.8 Aggregate Functions, GROUP BY and HAVING

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Aggregate functions anek rows varun ek uttar kaadhtat. GROUP BY rows gat-gat karto, HAVING gatanvar filter lavto.

SELECT COUNT(*) AS total_students FROM students;
SELECT COUNT(email) FROM students;                     -- ignores NULLs → 9
SELECT SUM(fees_paid), AVG(fees_paid), MIN(age), MAX(age) FROM students;

SELECT city, COUNT(*) AS students FROM students GROUP BY city;
SELECT city, SUM(fees_paid) AS total_fees FROM students
  GROUP BY city ORDER BY total_fees DESC;

SELECT city, COUNT(*) AS students FROM students
  GROUP BY city HAVING COUNT(*) >= 2;                  -- only cities with 2+ students

SELECT city, AVG(age) AS avg_age FROM students
  WHERE fees_paid > 0                                  -- filter rows first
  GROUP BY city
  HAVING AVG(age) > 23;                                -- then filter groups
Clause Filters Can use aggregates?
WHERE Individual rows, before grouping No
HAVING Groups, after grouping Yes

Order of execution: FROM → WHERE → GROUP BY → HAVING → SELECT → ORDER BY → LIMIT.

Ravindra Bagale's Tip

Many students who write WHERE COUNT(*) > 1 see an error. WHERE runs before grouping, when COUNT doesn't exist yet – a filter on an aggregate means HAVING. Write down the execution order once, and you'll never be confused again.

Practice task

Show the number of students and total fees per city; only cities whose total fees exceed 20000; and the average score per course from enrollments.

Extended teaching notes

Why this lesson matters

Use this lesson to strengthen systems you own: understand the risk, practise safely in a lab, then write and apply the fix.

Apply the fix across stacks

Same class of bug, same idea in every language.

Java / Spring Boot

Parameterise queries, encode output, CSRF tokens, limited Actuator, dependency scanning.

ASP.NET Core

EF Core / parameterised SQL, Razor encoding, HTTPS, Data Protection.

Node.js / Express

helmet, parameterised SQL, npm audit, avoid eval and shell concat.

Python / Django / Flask / FastAPI

ORM, autoescape, pip-audit, Bandit; never shell=True with user input.

PHP / Laravel

PDO/Eloquent, Blade escaping, composer audit.

Go / Ruby

database/sql placeholders / ActiveRecord; html/template / ERB escaping; govulncheck / Brakeman.

nginx / Apache / Tomcat

Hide versions, TLS, security headers, least-open ports.

MySQL / PostgreSQL / MongoDB / Redis

Private networks, auth on, least-privilege users, no 0.0.0.0/0.

AWS / Azure / GCP

Roles not long-lived keys, private data stores, cloud audit logs on.

Mini case study

Suppose we are on a purple-team exercise for an Indian mid-size company (sample data). Red notes a technique from this lesson against a lab clone. Blue must show the control that stops it, the log that would have fired, and the ticket that hardens production. That is the standard this course trains you for.

Defender's worksheet (do this today)

  1. Write the lesson title, date and the exact lab target you are allowed to use.
  2. List three owned systems (VMs, apps, or cloud accounts) where this lesson applies.
  3. Run one safe check from the lesson on a lab system only. Paste the command and output.
  4. Write a two-sentence fix you would give a teammate.
  5. Name one related public advisory (CERT-In, CISA, NVD, or a vendor bulletin) with its date.

Indian workplace (sample data)

Suppose we are a junior analyst at Infosys, TCS, Wipro or a fintech SOC in Bengaluru/Pune. Turn this lesson into one checklist item with an owner, a due date and a place to store evidence (ticket + screenshot).

Global practice

Compare your notes with OWASP, CIS Benchmarks, NIST CSF/IR guidance or a cloud Well-Architected security question. Write five lines on what overlaps.

Everyday analogy

Explain the risk and the fix to a family member without jargon. If they can repeat the warning, you understand it well enough to teach juniors.

Key terms

  • Control: a safeguard (patch, config, process, detection).
  • Finding: a weakness backed by evidence.
  • Remediation: the fix plus how you verified it.
  • Scope: systems you have written permission to touch.
  • Least privilege: only the access the task needs.
  • Defence in depth: several layers so one failure does not end the story.

Common mistakes

  • Skipping written permission "just for a quick scan".
  • Practising on hostel, office or public targets without authorisation.
  • Collecting tool output without writing the fix.
  • Copying attack steps onto production to "verify". Defenders verify with versions, configs and patches.
  • Publishing screenshots that contain secrets, cookies or internal hostnames.

Recap

  • Evidence, fix, owner, date.
  • Own lab only.
  • Fix > spectacle.