Day 84 — REVIEW — Revisit hardest

Coding problem

ProblemREVIEW — Revisit hardest
LeetCode ID(s)
DifficultyMixed
PatternReview
Company tags
Suggested time30m

Solution outline (coding)

  • Open your “hardest” list from prior weeks; pick top 2 by dread.
  • Solve one completely, skim solution for the other.
  • Add a one-page cheat sheet for those patterns only.

Time complexity: Varies.

Space complexity: Varies.

Show Python solution
class ReviewDay:
  """Practice / review: REVIEW — Revisit hardest."""

  def practice_plan(self):
    return [
      "Pick 2–3 problems from this phase; re-solve timed without notes.",
      "For each: pattern name, time/space complexity, one alternative approach.",
    ]


# Input:  (your choice of problems from this week or phase)
# Output: a short list of gaps to drill before the next session

SQL interview practice

1. Interview question

Companies / track: Review / mixed (see weekly theme)

This is a review / mixed day. Expect SQL that blends data quality, funnels, and metric definitions—the same mix you see across consumer tech and ads analytics.

What you are asked to write (SQL prompt):

Review / mixed week — use the same tables and deliverables as in a standard onsite SQL round.
Collect hardest unsolved SQL questions in a table and design meta-queries that classify them by pattern and typical failure mode.

Tables implied by the prompt:

  • Infer schemas from the prompt and state them before coding.

2. Solution outline

  • Clarify out loud: result grain (one row per what?), join keys, time zone, and any ORDER BY / LIMIT / tie-breakers.
  • Map Review to SQL: say the relational equivalent (e.g. hash map → GROUP BY + key; two pointers → ordered window + filter).
  • Structure: CTEs (WITH) — one step per CTE; validate on a tiny slice (counts, nulls, duplicates).
Show SQL solution (BigQuery)

Main query

SELECT difficulty, COUNT(*) FROM unsolved_sql_bank GROUP BY difficulty;