88 lines
1.9 KiB
Markdown
88 lines
1.9 KiB
Markdown
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layout: page
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title: System Design - link shortener
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---
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[educative.io](https://www.educative.io/courses/grokking-the-system-design-interview/m2ygV4E81AR)
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7. data partitioning and replication
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-----------------------
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- range based partitioning:
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- all URL's starting with 'A' goes into this bucket
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- can store less frequently used letters in one bucket/node
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- could become unblanced
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- hash-based partitioning
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- use a key hash to map to one of 1-256 servers
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- could still lead to overloaded partitions? can be solved by consistent hashing?
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8. caching
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------------
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- app level cache
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- CDN
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- cache invalidation
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- cache evictin polices
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- to reduce DB load, can check cache before hitting the DB
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- can precompute frequently used data and store in cache
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- consider cache eviction policies like LRU
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- what happens in a cache miss?
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-> fetch from backend DB
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-> update all cache replicas
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- memcache
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- stores in memory to avoid giong to external disks
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- large distributed hashtable
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- reduces DB load
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- client server app over tcp/udp
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- NOT persistent
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- redit
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- get/set operations
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- supports richer data types including string, hash, list
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9. load balancers
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----------------
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- add LB at 3 layers
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- between users and app servers
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- between app servers and DB
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- between servers and cache servers
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- round robin approach to distribute incoming requests
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- algorithms
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- round robin
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- ip hash
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- least connections/response time/bandwidth
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10. purging or DB cleanup (expired urls)
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----------------------
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Approaches
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- active search for exipred links could put pressure on DB
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- lazy cleanup could delete links as user requests them and delete if expired
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- cleanup service to be schduled to run at low usage hours
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11 and 12. analytics and security
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--------------------
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otehr requirements that needs to be considered
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-
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