Day 70: Review + Phase 3 Assessment

Day 70 — Review + Phase 3 Assessment

Coding problem

Solution outline (coding)

• Simulate a full round: hard medium + design from weeks 7–9.
• Strict timing: 25 min code + 10 min dry-run tests.
• Debrief: where you lost time (reading, debugging, complexity).

Time complexity: Varies — mock interview.

Space complexity: Varies.

class ReviewDay:
  """Practice / review: Review + Phase 3 Assessment."""

  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.
For all hard-style metrics tables above, create a BigQuery job that snapshots KPIs daily and supports A/B tests on algorithm variants via side-by-side metrics.

Tables implied by the prompt:

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

Engine: BigQuery — use its date, array, and approximate functions as documented.

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).
• Filter time first: predicate on DATE(ts) / partition column before heavy joins; state the window in plain English.
• Structure: CTEs (WITH) — one step per CTE; validate on a tiny slice (counts, nulls, duplicates).

SELECT run_date, variant, AVG(metric) AS kpi FROM ab_algo_runs GROUP BY run_date, variant;