TodayILearned
365 days of learning in public
One fullstack engineering concept every day — taught deeply, then compressed into a public post. Day 1 was June 23, 2026.
Why does an index speed up a query?
And the part nobody mentions: when it actually makes things worse.
What is caching?
And when does it bite you?
Reading EXPLAIN output
How to see what the database is actually doing — and whether your index is being used.
Contains Duplicate — the hash set pattern
When 'have I seen this before?' is the question, a hash set is the answer.
Valid Anagram — the frequency count pattern
When the question is 'how many times?', a hash map is the answer.
Composite indexes — the leftmost prefix rule
When you index multiple columns, order matters. Here's why — with a real benchmark.
Load balancing — distributing traffic
One server can't handle it all. Here's how you spread the load — and the tradeoffs of each strategy.
Connection pooling — sharing database connections
Every database connection is expensive. A pool keeps a few warm and reuses them — the load balancer's cousin, one layer deeper.
Rate limiting — protecting your API
A load balancer distributes traffic. A rate limiter caps it. Here are the four algorithms and the tradeoff each one makes.
Transactions and ACID — when all or nothing is the point
A connection pool gives you a connection. A transaction is what you do inside it — a unit of work that either fully succeeds or fully fails.
Two Sum — hash map complement lookup
The #1 most-asked LeetCode problem. One pass, one hash map, one key insight: for each number, check if you've already seen its complement.
Group anagrams — sort key vs count key
Two ways to build a canonical key: sort each string (O(n × k log k)) or count characters (O(n × k)). The benchmark reveals a surprising crossover.
Database normalization — 1NF, 2NF, 3NF
Three normal forms, three problems they solve. Normalization prevents anomalies; denormalization trades safety for speed.
Message queues — when the request can't wait for the work
A load balancer distributes requests synchronously. A message queue decouples them asynchronously — the producer fires and forgets, the consumer processes at its own pace.
JOINs — when two tables become one
Normalization split your data into honest tables. JOINs stitch it back together — at a cost. The planner picks the algorithm, but you control the indexes that make it fast.
API Gateway — The Front Door
Load balancing distributes traffic. Rate limiting caps it. Caching skips work entirely. An API gateway does all three — plus authentication, routing, and protocol translation — at a single entry point. It's the composition layer where every previous lesson converges.
Keyset Pagination — Why OFFSET Breaks at Scale
Your API returns page 500 in 50ms. Page 5000 takes half a second. Page 10000 takes two seconds. The user is just clicking 'next page' — so why does each page get slower? The answer is OFFSET, and the fix is a cursor.
Top K Frequent Elements — Heap vs Bucket Sort
Day 5 counted frequencies. Day 12 grouped by frequency. Today: find the top K. Three approaches, three Big O complexities — and a benchmark that shows the textbook O(n) answer isn't always the fastest in practice.
Product of array except self — prefix × suffix
The no-division constraint forces a reframe: the answer for each position is the product of everything before it × everything after it. Two passes, O(n) time, O(1) space.
Covering indexes — when the index is enough
An index finds rows fast. A covering index returns the data too — PostgreSQL skips the table entirely. Heap Fetches: 0 is the magic line in EXPLAIN.