Day 77: REVIEW — Meta Mock

Day 77 — REVIEW — Meta Mock

Coding problem

Solution outline (coding)

• Revisit problems you missed from the Meta mock; re-solve without notes.
• Record patterns: intervals, graphs, system bits specific to that session.
• One timed redo of the hardest problem.

Time complexity: Varies.

Space complexity: Varies.

class ReviewDay:
  """Practice / review: REVIEW — Meta Mock."""

  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: Meta

Meta: expect event logging, ads / integrity, and social product analytics—deduping, sessionization, and window functions are frequent themes.

What you are asked to write (SQL prompt):

Frame this as metrics work for **Meta**-scale surfaces (ads, product, or engagement — as the tables suggest).
Store mock results (timing, bytes processed, correctness flags) in a BigQuery table and write queries to analyze where you lost performance or made mistakes.

Tables implied by the prompt:

• results(timing, bytes processed, correctness flags)

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).
• Windows: align PARTITION BY / ORDER BY with the business rule; use QUALIFY in BigQuery when you need top-N per group.
• Cost: selective columns, partition pruning, avoid SELECT * when tables are huge.
• Structure: CTEs (WITH) — one step per CTE; validate on a tiny slice (counts, nulls, duplicates).

SELECT problem_id, AVG(duration_sec) AS avg_time, AVG(bytes_billed) AS avg_bytes
FROM mock_results
GROUP BY problem_id;