- Starting Points in Distributed Systems, Pt. I: Background
- Distributed computing
- A Thorough Introduction to Distributed Systems
- Distributed systems for fun and profit
- Fallacies of distributed computing
- Notes on Distributed Systems for Young Bloods
- An introduction to distributed systems
- awesome-distributed-systems
- 分布式系统(Distributed System)资料
- The System Design Primer
- BigData Notes
- Designing Data-Intensive Applications
- 设计数据密集型应用
- Distributed systems theory for the distributed systems engineer
- Readings in distributed systems
- 分布式系统前沿技术
- Distributed Algorithms
- Principles of Distributed Computing
- DISTRIBUTED ALGORITHMS
- 分布式系统原理
- CSE5306: Distributed Systems
- Distributed Computing: Principles, Algorithms, and Systems
- CS5620: Distributed Systems and Algorithms
- W4995-1: Distributed Systems
- G22.3033-001: Distributed Systems
- 15-440: Distributed Systems
- COS-418: Distributed Systems
- COS-418: Distributed Systems
- arxiv
- 系统
- 数据库
- LESLIE LAMPORT'S HOME PAGE
- Martin Kleppmann
- The Paper Trail
- the morning paper
- Metadata
- Read, Write, Execute
- Marc's Blog
- Peter Bailis :: Highly Available, Seldom Consistent
- db ranking
- 阿里中间件
- 美团技术
- 数据库内核月报
- 阿里云服务产品目录
- NoSQL Distilled
- 数据中台之结构化大数据存储设计
- 百万节点数据库扩展之道
- lamport clock
- vector clock
- matrix clock
- dotted version vectors
- interval tree clock
- concensus clock
- hlc
- hvc
- shared
- shared nothing
- shared disk
- shared memory
- shared everything
- message
- 1
- udp/tcp
- queue/channel
- message broker
- 2
- block/nonblock
- sync/async
- 1
- log
- application log
- database
- log structured kv database
- wal log
- replication log
- log-based message broker
- consensus/atomic broadcast
- cdc/etl
- state
- stateless
- stateful
- stream
- immutable
- mutable
- process
- batch
- stream
- 数据库
- KV存储/对象存储
- 文件存储/块存储
- 日志
- 计算的一致性
- 存储的一致性
- distributed file system
- gfs
- hdfs
- curve
- ceph
- cache
- redis
- memcached
- kv cluster
- dynamo
- voldemort
- riak
- gobeansdb
- document database
- mongodb
- rethinkdb
- couchdb
- couchbase/membase
- hbase
- cassandra
- boltdb
- badger
- leveldb
- rocksdb
- agatedb
- terarkdb
- pebble
- bitcask
- sqlite
- oracle
- mysql
- myrocks
- postgres
- gluesql
- peloton
- noisepage
- duckdb
- velox
- chiselstore
- rqlite
- toydb
- vitess
- tdsql
- kunlun
- aurora
- cockroachdb
- yugabytedb
- baikaldb
- polardb
- oceanbase
- pingcap
- matrixorigin
- map reduce
- pig
- hive
- dremel
- bigquery
- arrow-datafusion
- arrow-ballista
- drill
- kylin
- impala
- presto
- kudu
- starrocks
- doris
- snowflake
- clickhouse
- datafuse
- hologres
- greenplum
- exact once message passing
- atomic commit
- idempotent
- message order
- fault tolerance
- drop message
- apply backpressure
- buffer message
- ring buffer
tcp | message broker | |
---|---|---|
exact once message passing | sequence number | log-based |
message order | sequence number | log-based |
falut tolerance | slide window, traffic control | log-based |
- expressive: sql
- expressive: fork-join, dag
- expressive: language, framework
- throughoutput: partition, parallel
- fault tolerance
spark / flink | tensorflow / pytorch | pregel | |
---|---|---|---|
parallel | dag + cluster parallel | dag + standalone parallel |
- data integration
- distributed transaction vs log-based system
- kappa architecture vs lambda architecture vs lambda plus architecture
- batch process vs stream process
- aiming for correctness
- the end-to-end argument
- inner vs outer
- correctness and fault-tolerance
- timeliness and integrity
- the end-to-end argument