WEEK 06 · 2026-09-03 · THU

Ad Click Aggregator:at-least-once aggregation、late events、dedupe state 与 reconciliation

不幻想 exactly-once;用 signed impression ID、dedupe cache、raw lake replay 和 batch true-up 把错误变成可修复。

今日固定时间表

只有三个学习窗口:08:50-10:55、14:30-16:15、20:30-21:15。section links 只放在本日页面。

08:50-10:55System design
读 Ad Click Aggregator Potential Deep Dives:10k clicks/sec, no click loss, abuse/dedupe, low-latency metrics;做 hot shard split 方案。
14:30-16:15NeetCode Linked List
三道连续题位,每题 30m solve + 5m pattern/invariant/bug/complexity evidence。
20:30-21:15Recall / Staff Q&A / Mock
Frontier radar gate:无一手 AI source 改变本周 contract,记录 intentional omission;不加泛 RAG/agent 阅读。

算法模块

连续 NeetCode Linked List tag;每天恰好 3 个 slot。

#Problem / modePatternInvariantBug riskTimeSpace
10Merge K Sorted Linked Lists
NEW · 30m solve + 5m evidence
heap by node valueheap contains next smallest candidate per listpushing null or losing node.nextO(N log k)O(k)
11Reverse Nodes In K Group
NEW · 30m solve + 5m evidence
bounded in-place reversalonly complete groups of k are reversedreversing short tailO(n)O(1)
12Swap Nodes in Pairs
NEW · 30m solve + 5m evidence
local two-node rewiringdummy.next points to processed prefixcycle from pointer assignment orderO(n)O(1)

Hello Interview 精确目录

保留 live original titles;每行都有 canonical anchor 和 disposition。

项目精确 canonical sectionDisposition今天怎么用
Ad Click AggregatorPotential Deep Divesdeep divescale, no loss, dedupe, low-latency queries
Ad Click Aggregator1) How can we scale to support 10k clicks per second?deep diveservice, stream, processor, OLAP bottlenecks
Ad Click AggregatorHot Shardsdeep dive subheadingsplit hot AdId with suffix and merge at sink/query
Ad Click Aggregator2) How can we ensure that we don't lose any click data?deep diveretention, replay, raw lake archive, reconciliation
Ad Click AggregatorReconciliationdeep dive subheadingbatch truth corrects low-latency speed layer
Ad Click Aggregator3) How can we prevent abuse from users clicking on ads multiple times?deep divesigned impression ID as idempotency key
Ad Click AggregatorBut how do we dedup?deep dive subheadingpre-stream dedupe across window boundaries
Ad Click Aggregator4) How can we ensure that advertisers can query metrics at low latency?deep diverollups, pre-aggregation, OLAP trade-offs
Ad Click AggregatorFinal Designsynthesisspeed layer + batch layer + dedupe + OLAP
Ad Click AggregatorWhat is Expected at Each Level?level expectationcalibrate Senior+/Staff depth
Ad Click AggregatorMid-levellevel expectationpre-aggregation basics
Ad Click AggregatorSeniorlevel expectationreal-time processing and fault tolerance
Ad Click AggregatorStaff+level expectationteach trade-offs across batch/stream/storage

DDIA 精确决策卡

只读 Ch8、Ch12、Ch13 中能改变今天设计选择的小节。

项目问题精确 DDIA subsection改变的系统决定
Duplicate click across minute boundary must not count twiceCh12 · 幂等性signed impression ID is deduped before the stream and reconciled later
Flink state or consumer dies during aggregationCh12 · 失败后重建状态replay retained raw events and restore dedupe/aggregate state
Late events and bad deploy corrupt real-time viewsCh12 · 处理滞留事件admit lateness policy plus batch true-up; do not call the speed layer final
Batch layer must repair speed-layer mistakesCh13 · 应用演化后重新处理数据raw event lake enables reprocessing after schema/code fixes

本日项目 artifacts

今日产出、修复与英语 recall

必须交付Ad Click deep-dive sheet:event-time window, watermark/late policy, dedupe TTL, hot shard suffix, reconciliation correction protocol。
修复规则如果回答只说组件名,重写为 decision -> mechanism -> invariant -> failure window -> recovery -> metric。
English recall
Correctness is the durable source of truth; low-latency status, aggregates, dashboards, and alerts are views with freshness and repair semantics.
Local study materials
Detailed lecture notes, audio, recall scripts, PDFs, Staff Q&A, and mock packs are archived locally and are intentionally not published on this site.