30: LinkedIn Mutual Connection Search | Systems Design Interview Questions With Ex-Google SWE
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- เผยแพร่เมื่อ 19 ก.ค. 2024
- Forget searching mutual connections, when will there be a database for me to find my eskimo brothers?
• Taco Corp's EBDBBnB - ... - วิทยาศาสตร์และเทคโนโลยี
isn't count 500 X 500 = 250K ? which is 10 time more. Or are we assuming only 10% of friends will be mutual or something like that?
Oof yeah good catch. Point is, fan-out probably won't work here.
Keep doing its help us out so much
You are great bro
Awesome , great video🎉
Hi Jordan, loving this video. A couple of quick questions: 1. For the adding a connection workflow, is it supposed to be real-time processing or batch? 2. Let's say B accepted A's invite to connect and A wants to view the change right after it, how can we ensure that? 3. Does it make sense if we put the mutual connection data in memory cache servers and have a graph db to store the raw connections so that we can rebuild the cache if any node fails? Any idea or discussion is appreciated. Thanks!
1) Realtime
2) You could first write to a table before using CDC to sink to Kafka and then see the first degree connection there
Does profile update mean updating the latest job or education? If yes, why do we need to update the mutual connection DB for that?
Yes - because the data is denormalized in our mutual connections database
When adding mutual connections from the Flink nodes. How is it known that the new mutual connections are not already direct connections?
e.g. For 10: 3, 4, 15 you are creating 3,15 and 4,15. What if 3,15 and/or 4,15 are direct connections? These connections could also be on a different Flink node/partition.
Fair point - you can always just hit the database first here. We will have a connections table sharded by user Id so we know where to look.
Same doubt
Thank you :)!
Thanks for making this video Jordan. I have two questions: a) You mention "Mutual Cache table", but it appears you are using SQL db for that. Does not cache mean keeping in memory? b) It is mentioned that we need very fast reads ("fast as humanly possible"), should it not engender use of mongodb or something liek that instead of SQL db?
Cache doesn't inherently mean memory, it just means having the result of a computation easily accessible. Why are mongoreads faster thansql?
hey, i have some questions if anyone can please help me :)
1) when jordan says shard the database by userID, it means shard it by the hash of the userID (for consistent hashing)?
2) sometimes i see the term partitioned by instead of sharded by, are those the same?
1) yes
2) I think so, others seem to disagree
@@jordanhasnolife5163 thank you so much for taking the time to answer :) also, can't thank you enough for all the knowledge i gained since finding your channel
I have a question on brokers and message queue.
Do i setup the broker on a server and then set the consumers on other servers?
Lets say i have a mail server and i need to classify the emails and send them after classification to there right system.
Where do i host the broker and the Ai classification model?
I mean you can technically set them up wherever, but ideally different containers yeah
W as always
How mutually awesome
Watched. --