cockroach

README

Cockroach

A Scalable, Geo-Replicated, Transactional Datastore

Status

ALPHA

• Gossip network
• Cluster initialization and joining
• Basic Key-Value REST API
• NO: Raft consensus, range splitting, transactions (!)

Simple Setup

• node1> ./cockroach init hdd=<path>

• node1> ./cockroach start -gossip=:8081 -rpc_addr=:8081 -http_adr=:8080 -stores=hdd=<path>

• node2> ./cockroach start -gossip=node1:8081 -http_adr=:8080 -stores=hdd=<path>

Next Steps

See TODO

Get in touch

• cockroach-db@googlegroups.com
• #cockroachdb on freenode

Contributing

See CONTRIBUTING.md

Design

For full design details, see the original design doc.

Cockroach is a distributed key/value datastore which supports ACID transactional semantics and versioned values as first-class features. The primary design goal is global consistency and survivability, hence the name. Cockroach aims to tolerate disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention. Cockroach nodes are symmetric; a design goal is one binary with minimal configuration and no required auxiliary services.

Cockroach implements a single, monolithic sorted map from key to value where both keys and values are byte strings (not unicode). Cockroach scales linearly (theoretically up to 4 exabytes (4E) of logical data). The map is composed of one or more ranges and each range is backed by data stored in RocksDB (a variant of LevelDB), and is replicated to a total of three or more cockroach servers. Ranges are defined by start and end keys. Ranges are merged and split to maintain total byte size within a globally configurable min/max size interval. Range sizes default to target 64M in order to facilitate quick splits and merges and to distribute load at hotspots within a key range. Range replicas are intended to be located in disparate datacenters for survivability (e.g. { US-East, US-West, Japan }, { Ireland, US-East, US-West}, { Ireland, US-East, US-West, Japan, Australia }).

Single mutations to ranges are mediated via an instance of a distributed consensus algorithm to ensure consistency. We’ve chosen to use the Raft consensus algorithm. All consensus state is stored in RocksDB.

A single logical mutation may affect multiple key/value pairs. Logical mutations have ACID transactional semantics. If all keys affected by a logical mutation fall within the same range, atomicity and consistency are guaranteed by Raft; this is the fast commit path. Otherwise, a non-locking distributed commit protocol is employed between affected ranges.

Cockroach provides snapshot isolation (SI) and serializable snapshot isolation (SSI) semantics, allowing externally consistent, lock-free reads and writes--both from an historical snapshot timestamp and from the current wall clock time. SI provides lock-free reads and writes but still allows write skew. SSI eliminates write skew, but introduces a performance hit in the case of a contentious system. SSI is the default isolation; clients must consciously decide to trade correctness for performance. Cockroach implements a limited form of linearalizability, providing ordering for any observer or chain of observers.

Similar to Spanner directories, Cockroach allows configuration of arbitrary zones of data. This allows replication factor, storage device type, and/or datacenter location to be chosen to optimize performance and/or availability. Unlike Spanner, zones are monolithic and don’t allow movement of fine grained data on the level of entity groups.

A Megastore-like message queue mechanism is also provided to 1) efficiently sideline updates which can tolerate asynchronous execution and 2) provide an integrated message queuing system for asynchronous communication between distributed system components.

SQL - NoSQL - NewSQL Capabilities

Architecture

Cockroach implements a layered architecture, with various subdirectories implementing layers as appropriate. The highest level of abstraction is the SQL layer (currently not implemented). It depends directly on the structured data API (structured/). The structured data API provides familiar relational concepts such as schemas, tables, columns, and indexes. The structured data API in turn depends on the distributed key value store (kv/). The distributed key value store handles the details of range addressing to provide the abstraction of a single, monolithic key value store. It communicates with any number of cockroach nodes (server/), storing the actual data. Each node contains one or more stores (storage/), one per physical device.

Each store contains potentially many ranges, the lowest-level unit of key-value data. Ranges are replicated using the Raft consensus protocol. The diagram below is a blown up version of stores from four of the five nodes in the previous diagram. Each range is replicated three ways using raft. The color coding shows associated range replicas.