machi/doc
2015-08-04 16:25:20 +09:00
..
cluster-of-clusters Clarify name-game-sketch.org's use of K (placement key) 2015-08-04 16:25:20 +09:00
src.high-level ROTFL, time is hard. The current year is *2015*. 2015-06-17 12:30:48 +09:00
chain-self-management-sketch.Diagram1.dia Initial documentation import 2015-03-02 13:32:56 +09:00
chain-self-management-sketch.Diagram1.pdf Initial documentation import 2015-03-02 13:32:56 +09:00
chain-self-management-sketch.org Bring chain-self-management-sketch.org into sync with high-level-chain-mgr.tex 2015-04-23 12:56:14 +09:00
high-level-chain-mgr.pdf ROTFL, time is hard. The current year is *2015*. 2015-06-17 12:30:48 +09:00
high-level-machi.pdf ROTFL, time is hard. The current year is *2015*. 2015-06-17 12:30:48 +09:00
overview.edoc Add first basic round of EDoc documentation, 'make edoc' target 2015-04-08 17:32:01 +09:00
README.md cluster-of-clusters WIP 2015-06-17 10:44:35 +09:00
Using-Basho-Bench.md Fix handling of {error, partial_read} 2015-05-21 15:12:46 +09:00

Machi Documentation Overview

For a Web-browsable version of a snapshot of the source doc "EDoc" Erlang documentation, please use this link: Machi EDoc snapshot.

Documents in this directory

chain-self-management-sketch.org

chain-self-management-sketch.org is a mostly-deprecated draft of an introduction to the self-management algorithm proposed for Machi. Most material has been moved to the high-level-chain-mgr.pdf document.

cluster-of-clusters (directory)

This directory contains the sketch of the "cluster of clusters" design strawman for partitioning/distributing/sharding files across a large number of independent Machi clusters.

high-level-machi.pdf

high-level-machi.pdf is an overview of the high level design for Machi. Its abstract:

Our goal is a robust & reliable, distributed, highly available large file store based upon write-once registers, append-only files, Chain Replication, and client-server style architecture. All members of the cluster store all of the files. Distributed load balancing/sharding of files is outside of the scope of this system. However, it is a high priority that this system be able to integrate easily into systems that do provide distributed load balancing, e.g., Riak Core. Although strong consistency is a major feature of Chain Replication, this document will focus mainly on eventual consistency features --- strong consistency design will be discussed in a separate document.

high-level-chain-mgr.pdf

high-level-chain-mgr.pdf is an overview of the techniques used by Machi to manage Chain Replication metadata state. It also provides an introduction to the Humming Consensus algorithm. Its abstract:

Machi is an immutable file store, now in active development by Basho Japan KK. Machi uses Chain Replication to maintain strong consistency of file updates to all replica servers in a Machi cluster. Chain Replication is a variation of primary/backup replication where the order of updates between the primary server and each of the backup servers is strictly ordered into a single chain''. Management of Chain Replication's metadata, e.g., What is the current order of servers in the chain?'', remains an open research problem. The current state of the art for Chain Replication metadata management relies on an external oracle (e.g., ZooKeeper) or the Elastic Replication algorithm.

This document describes the Machi chain manager, the component responsible for managing Chain Replication metadata state. The chain manager uses a new technique, based on a variation of CORFU, called ``humming consensus''. Humming consensus does not require active participation by all or even a majority of participants to make decisions. Machi's chain manager bases its logic on humming consensus to make decisions about how to react to changes in its environment, e.g. server crashes, network partitions, and changes by Machi cluster admnistrators. Once a decision is made during a virtual time epoch, humming consensus will eventually discover if other participants have made a different decision during that epoch. When a differing decision is discovered, new time epochs are proposed in which a new consensus is reached and disseminated to all available participants.