Day 42: Review – Week 6

Day 42 — Review – Week 6

Coding problem

Solution outline (coding)

• Review heap/intervals/greedy from the week — one problem fully blind.
• Practice stating why sort order (by end, by start) before coding.
• List one counterexample if you sort wrong (overlapping chain).

Time complexity: Varies.

Space complexity: Varies.

class ReviewDay:
  """Practice / review: Review – Week 6."""

  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.
Summarize an interval-analysis pattern in BigQuery: given events with start_ts/end_ts, produce utilization %, overlaps, and max concurrency per dimension.

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).

WITH intervals AS (
  SELECT start_ts, end_ts FROM events
),
pts AS (
  SELECT start_ts AS t, 1 AS d FROM intervals UNION ALL SELECT end_ts, -1 FROM intervals
),
conc AS (
  SELECT t, SUM(d) OVER (ORDER BY t) AS running FROM pts
)
SELECT MAX(running) AS max_concurrency FROM conc;