📖
Notes
  • 🙌Welcome!
  • CyberSecurity
    • Penetration Testing
      • ELearnSecurity
        • eJPT
          • Footprinting & Scanning
            • Port Scanning
            • Mapping Networks
          • Information Gathering
            • Subdomain Enumeration
          • Network Attacks
            • Arp Poisoning
            • Null Sessions
            • Windows Shares
            • Authentication Cracking
          • Networking
            • Python Server to Receive Exfiltrated Data
            • CLI Tool to interact with HTTP/HTTPS
          • Programming
            • C++ Keylogger
            • C++ Information Stealer
          • System Attacks
            • Pivoting
            • Backdoor
          • Vulnerability Assessment
          • Web Attacks
            • SQL Injection
            • HTTP Verbs
            • Web Server Fingerprinting
      • PortSwigger
        • Cross-origin resource sharing (CORS)
          • Access-Control-Allow-Origin response header
          • Vulnerabilities arising from Misconfigurations
            • Server-generated ACAO header from client-specified Origin header
            • Errors parsing Origin headers
            • Whitelisted null origin value
            • Exploiting XSS via CORS trust relationships
            • Breaking TLS with poorly configured CORS
            • Intranets and CORS without credentials
            • Mitigations
        • Sql Injection
          • Examining the database
          • Retrieving data from other database tables
          • Blind SQL injection
          • Mitigation
      • TryHackMe
        • Main Methodology
          • 1. Reconnaissance
            • Google Dorking
            • Metadata Reader/Writer
            • Steghide - Stegnography
            • OSINT Framework
          • 2. Enumeration/Scanning
            • NFS Enumeration Tools
            • NMAP - Port Scanning
            • Web Enumeration Tools
            • SMB Enumeration Tools
            • SMTP Enumeration Tools
            • Shodan - IOT Search Engine
            • FTP Enumeration Tools
            • Wordpress Enumeration Tools
            • OWASP ZAP - WebApp Testing
            • BurpSuite - WebApp Testing
            • MySQL Enumeration Tools
            • Wordlists
          • 3. Gaining Access / Exploitation
            • Buffer Overflow
              • 1. Immunity Debugger
              • 2. Mona Setup
              • 3. Spiking
              • 4. Fuzzing
              • 5. Crash Replication & Controlling EIP
              • 6. Finding Bad Characters
              • 7. Find a Jump Point
              • 8. Generate Payload
              • 9. Prepend NOPs
              • 10. Final Buffer
            • Cryptography
              • Hash Crack Tools
              • Online Password Cracking Tools
              • Encryption
              • John the Ripper
            • Evasion Techniques
            • Shells
              • Powershell
              • Msfvenom
              • Meterpreter
              • Metasploit -- multi/handler
              • Netcat
              • Socat
            • Web Applications
              • OWASP Top 10
              • File Upload Vulnerabilities
              • Authentication Vulnerability
              • XML External Entity (XXE)
              • Cross-Site Scripting (XSS)
              • ZTH: Obscure Web Vulns
              • Server Side Request Forgery (SSRF)
              • Insecure Direct Object Reference (IDOR)
              • ZTH : Continued
              • File Inclusion Vulnerability
                • Local File Inclusion (LFI)
                • Log Poisoning Attack (LFI to RCE via Log files)
            • Windows Applications
              • Jenkins
              • Windows Active Directory
                • Impacket's secretsdump.py
                • Kerberos
                  • Enumerating Users with Kerbrute
                  • Enumerating SPN Accounts with Powershell
                  • Get SPN Account Ticket with Invoke-Kerberoast
                  • Kerberoasting with Rubeus & Impacket
                  • AS-REP Roasting with Rubeus/GetNPUsers.py
                  • Pass the Ticket with mimikatz
                  • Golden/Silver Ticket Attacks with mimikatz
                  • Kerberos Backdoors with mimikatz
                  • Harvesting and Brute-Forcing with Rubeus
                  • Conclusion and Resources
          • 4. Post Exploitation
            • Privilege Escalation
              • Linux
                • 1. Introduction
                • 2. Scripts
                • 3. Kernel Exploits
                • 4. Service Exploits
                • 5. Weak File Permissions
                • 6. Sudo
                • 7. Cron jobs
                • 8. SUID/SGID Executable
                • 9. CAP_SETUID Capabilities Executable
                • 10. Passwords & Keys
                • 11. NFS
                • PrivEsc CTF Checklists
              • Windows
                • Token Impersonation
                • PrivEsc CTF Checklists
                • Permission
                • Scripts
                • Unquoted Service Path
            • Tools
              • Meterpreter Modules
              • Impacket's Psexec
              • Impacket's mssqlclient.py
              • Firefox Decryptor
              • Socat - Reverse TCP Tunnel
            • Windows Active Directory
              • Enumeration with Powerview
              • Enumeration with Bloodhound (GUI)
              • Dumping Hashes with mimikatz
              • Golden Ticket Attacks with mimikatz
              • Enumeration with Server Manager
              • Maintaining Access
              • Additional Resources
          • 5. Covering Tracks
          • 6. Reporting
        • Networking Concepts
          • SSH Reverse Tunnels
        • Scripting
          • Curl
          • Powershell
            • Basic Powershell Commands
            • Enumeration
        • Web Extensions
          • Shodan
          • Wappalyzer
      • Miscellaneous
        • SMTP Enumeration
        • Nmap Advanced Scanning
        • Persistence via Meterpreter
        • DNS Enumeration
        • NetBIOS & SMB
        • DHCP Starvation
        • Packet Manipulation
        • Hash Cracking
        • MITM
        • Msfvenom Payload in APK (Manual Embedding)
    • Blue Teaming
      • Digital Forensics & Incidence Response
        • Memory Acquisition with LIME
        • Disk Analysis with Autopsy
        • Data and Memory Collection with FireEye Redline
        • Memory Forensice with Volatility
      • Intrusion Detection
        • Intrusion Detection Systems (IDS)
        • Threat Monitoring with Security Information & Event Management (SIEM)
        • Security Event Monitoring
        • Host Based Intrusion Detection System (HIDS) - OSSEC
      • Miscellaneous
        • Docker Image Security Analysis with Trivy
  • DevOps
    • Infrastructure as a Code (IaC)
      • Ansible
        • 1. Playbooks
        • 2. Modules
        • 3. Inventory
        • 4. Roles
        • 5. Ansible Tower
      • Terraform
        • 1. Overview
        • 2. Modify Resources
        • 3. Delete Resources
        • 4. Reference Resources
        • 5. Terraform Files
        • 6. Terraform State Commands
        • 7. Terraform Output
        • 8. Target Resources
        • 9. Terraform Variables
        • 10. Expressions + Functions
        • 11. Meta-Arguments
        • 12. Modules
        • 13. Managing Multiple Environments
        • 14. Testing Terraform Code
        • 15. Final Thoughts
    • Orchestration
      • Kubernetes
        • 1. Main K8s Components
        • 2. K8s Architecture
        • 3. Minikube & Kubectl
        • 4. YAML Configuration File
        • 5. K8s Namespaces
        • 6. K8s Ingress
        • 7. Helm - Package Manager of K8s
        • 8. K8 Volumes
        • 9. K8 StatefulSet
        • 10. K8 Services
  • Development
    • Blockchain
      • FreeCodeCamp Course
        • 1. Introduction
        • 2. Solidity Basics
        • 3. Storage Factory
        • 4. Fund Me
        • 5. Ethers.js
        • 6. Hardhat
        • 7. Hardhat | Fund Me
        • 8. Contract Lottery | Raffle
        • 9. IPFS
        • 10. ERC20s
        • 11. DeFi & Aave
        • 12. NFTs | Encoding
        • 13. Reentrancy Attack
    • Backend
      • NodeJs
        • Introduction
        • Additional Concepts
        • ExpressJs
    • Database
      • SQL
        • Basics
          • 1. Querying Data
          • 2. Filtering Data
          • 3. Joining Multiple Tables
          • 4. Grouping Data
          • 5. Set Operations
          • 6. Grouping Sets, Cube, and Rollup
          • 7. Subquery
          • 8. Common Table Expressions
          • 9. Modifying Data
          • 10. Transactions
          • 11. Import & Export Data
          • 12. Managing Tables
    • Testing
      • Test Driven Development (TDD)
      • Jest js
      • Cypress js
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On this page
  • Subquery
  • ANY
  • ALL
  • EXISTS
  1. Development
  2. Database
  3. SQL
  4. Basics

7. Subquery

Subquery

(write a query nested inside another query)

  • a subquery is a query nested inside another query such as SELECT, INSERT, DELETE & UPDATE

Example 1 (get films whose rental rate is higher than average rental rate)

SELECT
	film_id,
	title,
	rental_rate
FROM
	film
WHERE
	rental_rate > (
		SELECT
			AVG (rental_rate)
		FROM
			film
	);

Example 2 (get films that have returned rate between two dates)

SELECT
	film_id,
	title
FROM
	film
WHERE
	film_id IN (
		SELECT
			inventory.film_id
		FROM
			rental
		INNER JOIN inventory USING (inventory_id)
		WHERE
			return_date BETWEEN '2005-05-29' AND '2005-05-30'
	);

Example 3 (get customers who have paid)

SELECT
	first_name,
	last_name
FROM
	customer
WHERE
	EXISTS (
		SELECT
			1
		FROM
			payment
		WHERE
			payment.customer_id = customer.customer_id;
	);

ANY

(retrieve data by comparing a value with a set of values returned by a subquery.)

  • The subquery must return exactly one column.

  • The ANY operator must be preceded by one of the following comparison operator =, <=, >, <, > and <>

  • The ANY operator returns true if any value of the subquery meets the condition, otherwise, it returns false.

  • The = ANY is equivalent to IN operator.

Example 1 (get films whose category is either Action or Drama)

SELECT
	title,
	category_id
FROM
	film
INNER JOIN film_category
	USING(film_id)
WHERE
	category_id = ANY(
		SELECT
			category_id
		FROM
			category
		WHERE
			NAME = 'Action'
			OR
			NAME = 'Drama'
	);

ALL

(query data by comparing a value with a list of values returned by a subquery.)

With the assumption that the subquery returns some rows, the ALL operator works as follows:

  1. column_name > ALL (subquery) the expression evaluates to true if a value is greater than the biggest value returned by the subquery.

  2. column_name >= ALL (subquery) the expression evaluates to true if a value is greater than or equal to the biggest value returned by the subquery.

  3. column_name < ALL (subquery) the expression evaluates to true if a value is less than the smallest value returned by the subquery.

  4. column_name <= ALL (subquery) the expression evaluates to true if a value is less than or equal to the smallest value returned by the subquery.

  5. column_name = ALL (subquery) the expression evaluates to true if a value is equal to any value returned by the subquery.

  6. column_name != ALL (subquery) the expression evaluates to true if a value is not equal to any value returned by the subquery.

Example 1 (find all films whose lengths are greater than the list of the average lengths)

SELECT
	film_id,
	title,
	length
FROM
	film
WHERE
	length > ALL (
		SELECT
			ROUND(AVG(length), 2) avg_length
		FROM
			film
		GROUP BY
			rating
	)
ORDER BY
	length;

EXISTS

(check for the existence of rows returned by a subquery.)

  • If the subquery returns at least one row, the result of EXISTS is true. In case the subquery returns no row, the result is of EXISTS is false

    • If the subquery returns NULL, EXISTS returns true

  • The result of EXISTS operator depends on whether any row returned by the subquery, and not on the row contents. Therefore, columns that appear on the SELECT clause of the subquery are not important.

Example 1 (Find customers who have at least one payment whose amount is greater than 11)

SELECT
	customer_id,
	first_name,
	last_name
FROM
	customer c
WHERE
	EXISTS (
		SELECT
			1
		FROM
			payment p
		WHERE
			c.customer_id = p.customer_id
			AND
			amount > 11
	)
ORDER BY
	first_name,
	last_name;
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Last updated 1 year ago