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๐ง SQL Interview Question (ModerateโTricky & Duplicate Transaction Detection)
๐
transactions(transaction_id, user_id, transaction_date, amount)
โ Ques :
๐ Find users who made multiple transactions with the same amount consecutively.
๐งฉ How Interviewers Expect You to Think
โข Sort transactions chronologically for each user
โข Compare the current transaction amount with the previous one
โข Use a window function to detect consecutive duplicates
๐ก SQL Solution
SELECT
user_id,
transaction_date,
amount
FROM (
SELECT
user_id,
transaction_date,
amount,
LAG(amount) OVER (
PARTITION BY user_id
ORDER BY transaction_date
) AS prev_amount
FROM transactions
) t
WHERE amount = prev_amount;
๐ฅ Why This Question Is Powerful
โข Tests understanding of LAG() for row comparison
โข Evaluates ability to identify patterns in sequential data
โข Reflects real-world use cases like detecting suspicious or duplicate transactions
โค๏ธ React if you want more tricky real interview-level SQL questions ๐
๐
transactions(transaction_id, user_id, transaction_date, amount)
โ Ques :
๐ Find users who made multiple transactions with the same amount consecutively.
๐งฉ How Interviewers Expect You to Think
โข Sort transactions chronologically for each user
โข Compare the current transaction amount with the previous one
โข Use a window function to detect consecutive duplicates
๐ก SQL Solution
SELECT
user_id,
transaction_date,
amount
FROM (
SELECT
user_id,
transaction_date,
amount,
LAG(amount) OVER (
PARTITION BY user_id
ORDER BY transaction_date
) AS prev_amount
FROM transactions
) t
WHERE amount = prev_amount;
๐ฅ Why This Question Is Powerful
โข Tests understanding of LAG() for row comparison
โข Evaluates ability to identify patterns in sequential data
โข Reflects real-world use cases like detecting suspicious or duplicate transactions
โค๏ธ React if you want more tricky real interview-level SQL questions ๐
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Coding Interview Prep Guide ๐ป๐ฅ
1๏ธโฃ Core Programming Fundamentals
โข Variables, data types, operators
โข Control flow (loops, conditions)
โข Functions recursion
โข Time space complexity basics
โข Debugging mindset
2๏ธโฃ Data Structures (High Priority)
โข Arrays Strings
โข Linked Lists
โข Stacks Queues
โข HashMaps / Dictionaries
โข Trees Binary Trees
โข Heaps Priority Queues
โข Graphs (BFS, DFS)
3๏ธโฃ Algorithms You MUST Know
โข Searching (Binary Search)
โข Sorting (Quick, Merge, Heap)
โข Recursion Backtracking
โข Greedy algorithms
โข Dynamic Programming
โข Sliding Window
โข Two Pointers
โข Prefix Sum
4๏ธโฃ Problem-Solving Patterns
โข Brute force โ optimized approach
โข Hashing for lookups
โข Divide and conquer
โข Recursion โ DP conversion
โข Spaceโtime tradeoffs
5๏ธโฃ Language-Specific Prep
โข Python / Java / C++ fundamentals
โข Built-in data structures
โข Edge cases constraints
โข Writing clean, readable code
โข Input/output handling
6๏ธโฃ Coding Interview Expectations
โข Explain approach before coding
โข Write code step-by-step
โข Handle edge cases
โข Analyze time space complexity
โข Optimize if asked
7๏ธโฃ Common Interview Questions
โข Reverse a string / array
โข Find duplicates
โข Two Sum / Subarray problems
โข Palindrome checks
โข Tree traversal
โข LRU Cache
โข Longest substring problems
8๏ธโฃ Where to Practice
โข LeetCode (Top priority)
โข HackerRank
โข Codeforces
โข CodeChef
โข GeeksforGeeks
9๏ธโฃ Mock Interview Focus
โข Think out loud
โข Donโt panic on hard questions
โข Ask clarifying questions
โข Partial solutions still matter
โข Correct approach > perfect code
๐ Pro Tips
โ๏ธ Master patterns, not random problems
โ๏ธ Revise mistakes weekly
โ๏ธ Practice writing code without IDE help
โ๏ธ Speed improves with consistency
โ๏ธ Interviews test thinking, not memory
Double Tap โฅ๏ธ For More
1๏ธโฃ Core Programming Fundamentals
โข Variables, data types, operators
โข Control flow (loops, conditions)
โข Functions recursion
โข Time space complexity basics
โข Debugging mindset
2๏ธโฃ Data Structures (High Priority)
โข Arrays Strings
โข Linked Lists
โข Stacks Queues
โข HashMaps / Dictionaries
โข Trees Binary Trees
โข Heaps Priority Queues
โข Graphs (BFS, DFS)
3๏ธโฃ Algorithms You MUST Know
โข Searching (Binary Search)
โข Sorting (Quick, Merge, Heap)
โข Recursion Backtracking
โข Greedy algorithms
โข Dynamic Programming
โข Sliding Window
โข Two Pointers
โข Prefix Sum
4๏ธโฃ Problem-Solving Patterns
โข Brute force โ optimized approach
โข Hashing for lookups
โข Divide and conquer
โข Recursion โ DP conversion
โข Spaceโtime tradeoffs
5๏ธโฃ Language-Specific Prep
โข Python / Java / C++ fundamentals
โข Built-in data structures
โข Edge cases constraints
โข Writing clean, readable code
โข Input/output handling
6๏ธโฃ Coding Interview Expectations
โข Explain approach before coding
โข Write code step-by-step
โข Handle edge cases
โข Analyze time space complexity
โข Optimize if asked
7๏ธโฃ Common Interview Questions
โข Reverse a string / array
โข Find duplicates
โข Two Sum / Subarray problems
โข Palindrome checks
โข Tree traversal
โข LRU Cache
โข Longest substring problems
8๏ธโฃ Where to Practice
โข LeetCode (Top priority)
โข HackerRank
โข Codeforces
โข CodeChef
โข GeeksforGeeks
9๏ธโฃ Mock Interview Focus
โข Think out loud
โข Donโt panic on hard questions
โข Ask clarifying questions
โข Partial solutions still matter
โข Correct approach > perfect code
๐ Pro Tips
โ๏ธ Master patterns, not random problems
โ๏ธ Revise mistakes weekly
โ๏ธ Practice writing code without IDE help
โ๏ธ Speed improves with consistency
โ๏ธ Interviews test thinking, not memory
Double Tap โฅ๏ธ For More