Distributed Computing

Distributed Systems

Scale computation across machines.

Concepts

Partitioning: split data. Replication: copies for fault tolerance. Consistency: data agreement.

MapReduce

Map: transform data. Reduce: aggregate results. Sorting happens automatically.

Challenges

Network latency. Partial failures. Distributed transactions.

Key Takeaways

1. Partition and replicate for scale
2. MapReduce: map + reduce
3. Distributed challenges: latency, failures