Topic 11.5
Final Readiness Checklist and Study Plan
In one line
The final self-check before an interview and a four-week plan that covers the whole course, with the common mistakes to avoid.
Think of it like this
A pilot's pre-flight checklist. Experienced pilots still run it every time, because forgetting one item is how accidents happen.
Key ideas
- 01
You're ready when you can: explain false positives vs negatives; derive and use the FPR formula; compute m and k; explain saturation; explain why deletes fail; implement a thread-safe filter with serialisation; compare counting, scalable, blocked, partitioned, cuckoo, quotient and xor filters; use RedisBloom; design cache penetration protection with Redis and a database; keep filters updated from Kafka or CDC; rebuild, version and monitor filters; design crawlers, blocklists and billion-scale checks; and say when not to use a Bloom filter.
- 02
Week 1: Phases 0–2 (foundations, maths, hashing). Do the sizing drills by hand.
- 03
Week 2: Phases 3–4 (implementation, variants). Build the Java filter with tests and a benchmark.
- 04
Week 3: Phases 5–8 (storage engines, Redis, lifecycle, distribution). Run the Spring Boot + RedisBloom + Kafka project.
- 05
Week 4: Phases 9–11 (operations, system design, revision). Practise designs out loud, timed.
- 06
Common mistakes: treating "maybe" as "yes", using the filter as the source of truth, ignoring capacity, no rebuild plan, weak hashes, deleting bits, stale filters, unreliable updates, choosing FPR without costs, and exposing sensitive membership.
Code & diagrams
Explain it without notes
What are the three most common production mistakes with Bloom filters?
Practice
Run the readiness checklist and mark each item green, amber or red; schedule the red items first.
Trade-offs
- ↔
Breadth vs depth: nail the core maths and one full design before memorising every variant.
Done when you can
I have gone through the readiness checklist and every item is green.