Ra is a Raft implementation by Team RabbitMQ. It is not tied to RabbitMQ and can be used in any Erlang or Elixir project. It is, however, heavily inspired by and geared towards RabbitMQ needs.
Ra (by virtue of being a Raft implementation) is a library that allows users to implement persistent, fault-tolerant and replicated state machines.
This library is maturing and is currently in a pre-1.0 phase. This means that
the primary APIs (ra
, ra_machine
modules) and on disk formats are unlikely
to change significantly until 1.0 is tagged but may need to be if deemed
necessary.
The following Raft features are implemented:
- Leader election
- Log replication
- Cluster membership changes: one server (member) at a time
- Log compaction (with limitations and RabbitMQ-specific extensions)
- Snapshot installation
Ra requires Erlang/OTP 21.x.
%% All servers in a Ra cluster are named processes.
%% Create some Server Ids to pass to the configuration
ErlangNodes = [ra@node1, ra@node2, ra@node3]
ServerIds = [{quick_start, N} || N <- ErlangNodes]
%% start a simple distributed addition state machine with an initial state of 0
{ok, ServersStarted, ServersNotStarted} = ra:start_cluster(quick_start, {simple, fun erlang:'+'/2, 0}, ServerIds),
%% Add a number to the state machine
%% Simple state machines always return the full state after each operation
{ok, StateMachineResult, LeaderId} = ra:process_command(hd(ServersStarted), 5),
%% use the leader id from the last command result for the next
{ok, 12, LeaderId1} = ra:process_command(LeaderId, 7),
"Simple" state machines like the above can only take you so far. See Ra state machine tutorial
for how to write a state machine by implementing the ra_machine
behaviour.
- Low footprint: use as few resources as possible, avoid process tree explosion
- Able to run thousands of
ra
clusters within an Erlang node - Provide adequate performance for use as a basis for a distributed data service
This library is primarily developed as the foundation for replication layer for replicated queues in a future version of RabbitMQ. The design it aims to replace uses a variant of Chain Based Replication which has two major shortcomings:
- Replication algorithm is linear
- Failure recovery procedure requires expensive topology changes
- API docs: https://rabbitmq.github.io/ra/
- How to write a Ra state machine: Ra state machine tutorial
- Design and implementation details: Ra internals guide
A number of examples can be found in a separate repository.
data_dir
:
A directory name where ra
will store it's data.
wal_max_size_bytes
:
The maximum size of the WAL (Write Ahead Log). Default: 128Mb.
wal_compute_checksums
:
Indicate whether the wal should compute and validate checksums. Default: true
-
wal_write_strategy
:default
:
The default. Actual
write(2)
system calls are delayed until a buffer is due to be flushed. Then it writes all the data in a single call then fsyncs. Fastest but incurs some additional memory use.do_sync
:
Like
default
but will try to open the file withO_SYNC
and thus wont need the additionalfsync(2)
system call. If it fails to open the file with this flag this mode falls back todefault
Example:
[{data_dir, "/tmp/ra-data"},
{wal_max_size_bytes, 134217728},
{wal_compute_checksums, true},
{wal_write_strategy, default},
]
(c) 2017-2018, Pivotal Software Inc.
Double licensed under the ASL2 and MPL1.1. See LICENSE for details.