1. Paper Notes
  2. 1. benchmarks
    1. 1.1. ssb
  3. 2. bigdata
    1. 2.1. mapreduce
    2. 2.2. nephele
    3. 2.3. dataflow model
    4. 2.4. flink
    5. 2.5. flink state management
  4. 3. databases
    1. 3.1. columnstores vs rowstores
    2. 3.2. kv
      1. 3.2.1. rocksdb cidr17
    3. 3.3. mmdb
      1. 3.3.1. mmdb overview
    4. 3.4. olap
      1. 3.4.1. lakehouse
      2. 3.4.2. delta lake
    5. 3.5. cdc
      1. 3.5.1. dblog
    6. 3.6. rum conjecture
  5. 4. datalayout
    1. 4.1. cstore
    2. 4.2. dremel
    3. 4.3. rcfile
    4. 4.4. orc
  6. 5. data structures
    1. 5.1. skip list
    2. 5.2. bloom filter
  7. 6. distributed system
    1. 6.1. consensus
      1. 6.1.1. flp
      2. 6.1.2. paxos made simple
      3. 6.1.3. paxos made live
      4. 6.1.4. viewstamped replication
      5. 6.1.5. zab
      6. 6.1.6. paxos vs. vr vs. zab
      7. 6.1.7. raft
      8. 6.1.8. paxos vs raft
    2. 6.2. scheduler
      1. 6.2.1. borg
    3. 6.3. primary backup
    4. 6.4. chain replication
    5. 6.5. bolosky
    6. 6.6. holy grail
    7. 6.7. chandy lamport
    8. 6.8. asynchronous barrier snapshotting
    9. 6.9. zookeeper
  8. 7. filesystem
    1. 7.1. gfs
    2. 7.2. polarfs
  9. 8. storage
    1. 8.1. kv store
      1. 8.1.1. dynamo
    2. 8.2. kudu
    3. 8.3. bluestore

论文阅读笔记

bigdata

  • MapReduce: Simplified Data Processing on Large Clusters
  • Nephele: Efficient Parallel Data Processing in the Cloud
  • The Dataflow Model
  • Apache Flink: Stream and Batch Processing in a Single Engine
  • State Management in Apache Flink