Paper Notes
1.
benchmarks
1.1.
ssb
2.
bigdata
2.1.
mapreduce
2.2.
nephele
2.3.
dataflow model
2.4.
flink
2.5.
flink state management
3.
databases
3.1.
columnstores vs rowstores
3.2.
kv
3.2.1.
rocksdb cidr17
3.3.
mmdb
3.3.1.
mmdb overview
3.4.
oltp
3.4.1.
through the looking glass
3.4.2.
staring into the abyss
3.5.
olap
3.5.1.
lakehouse
3.5.2.
delta lake
3.5.3.
vertica
3.6.
htap
3.6.1.
greenplum
3.7.
concurrency control
3.7.1.
evaluation of in-memory mvcc
3.8.
cdc
3.8.1.
dblog
3.9.
rum conjecture
4.
datalayout
4.1.
cstore
4.2.
cstore compression
4.3.
dremel
4.4.
rcfile
4.5.
orc
4.6.
table placement methods
5.
data structures
5.1.
btree family
5.1.1.
bw-tree
5.2.
trie family
5.2.1.
art
5.3.
skip list
5.4.
bloom filter
6.
distributed system
6.1.
consensus
6.1.1.
flp
6.1.2.
paxos made simple
6.1.3.
paxos made live
6.1.4.
viewstamped replication
6.1.5.
zab
6.1.6.
paxos vs. vr vs. zab
6.1.7.
raft
6.1.8.
paxos vs raft
6.2.
scheduler
6.2.1.
borg
6.3.
primary backup
6.4.
chain replication
6.5.
bolosky
6.6.
holy grail
6.7.
chandy lamport
6.8.
asynchronous barrier snapshotting
6.9.
zookeeper
7.
filesystem
7.1.
gfs
7.2.
polarfs
8.
storage
8.1.
kv store
8.1.1.
dynamo
8.2.
kudu
8.3.
bluestore
Light (default)
Rust
Coal
Navy
Ayu
论文阅读笔记
storage
KV store
Dynamo: Amazon’s Highly Available Key-value Store
Kudu: Storage for Fast Analytics on Fast Data
File Systems Unfit as Distributed Storage Backends: Lessons from 10 Years of Ceph Evolution