38 lines
1.7 KiB
Markdown
38 lines
1.7 KiB
Markdown
# notes
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## [profiling a warehouse-scale computer](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44271.pdf)
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## [cassandra](https://www.cs.cornell.edu/projects/ladis2009/papers/lakshman-ladis2009.pdf)
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## [bigtable](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf)
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## [gfs](https://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
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- System Design as development for use case
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- Optimized for record append and random reads
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- Master-Slave
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- Limitations: faul tolerance despite replicas, throughput
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- Bottlenecks & network optimization
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- Data & Control flow separation
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- State restoration & logging (lots of things I don't get here)
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- Related: OS journaling
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- Weak consistency - "tolerable errors" (i.e. clients reading different states)
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- Garbage Collection
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- Amortized cost w/ FS scans
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- Parallels w/ language design
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- Terms to learn:
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1. Network Bandwidth and _per-machine_ limit
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2. Racks & data centers - how are these managed (i.e. "cross-{rack,DC} replication")?
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- Use the latest {soft,hard}ware or deal with slowdowns (older kernel `fsync()` requiring reading entirety of file on append)
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- Getting to know the real numbers: 440 MB/s throughput on double chunkserver kill & google network
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- Network as the ultimate bottleneck & inefficiency
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## [mapreduce](https://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
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## [spark](https://www.usenix.org/system/files/conference/nsdi12/nsdi12-final138.pdf)
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## [rpc](https://www.h3c.com/en/Support/Resource_Center/EN/Home/Switches/00-Public/Trending/Technology_White_Papers/gRPC_Technology_White_Paper-6W100/)
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