kappa-core

> kappa-core is a minimal peer-to-peer database, based on append-only logs and materialized views.

New to kappa architecture? There is a short introduction.

Example

This example sets up an on-disk log store and an in-memory view store. The view
tallies the sum of all of the numbers in the logs, and provides an API for
getting that sum.

``js
var kappa = require('kappa-core')
var view = require('kappa-view')
var memdb = require('memdb')

// Store logs in a directory called "log". Store views in memory.
var core = kappa('./log', { valueEncoding: 'json' })
var store = memdb()

// View definition
var sumview = view(store, function (db) {
return {
// Called with a batch of log entries to be processed by the view.
// No further entries are processed by this view until 'next()' is called.
map: function (entries, next) {
db.get('sum', function (err, value) {
var sum
if (err && err.notFound) sum = 0
else if (err) return next(err)
else sum = value
})
entries.forEach(function (entry) {
if (typeof entry.value === 'number') sum += entry.value
})
db.put('sum', sum, next)
},

// Whatever is defined in the "api" object is publicly accessible
api: {
get: function (core, cb) {
this.ready(function () { // wait for all views to catch up
cb(null, sum)
})
}
}
}
})

// the api will be mounted at core.api.sum
core.use('sum', 1, sumview) // name the view 'sum' and consider the 'sumview' logic as version 1

core.writer('default', function (err, writer) {
writer.append(1, function (err) {
core.api.sum.get(function (err, value) {
console.log(value) // 1
})
})
})
`

API

`js
var kappa = require('kappa-core')
`

$3

Create a new kappa-core database.

- storage is a random-access-storage function, or a string. If a string is given, random-access-file is used with that string as the filename.
- Valid opts include:
- valueEncoding: a string describing how the data will be encoded.
- multifeed: A preconfigured instance of multifeed

$3

Get or create a local writable log called name. If it already exists, it is
returned, otherwise it is created. A writer is an instance of
hypercore.

$3

Fetch a log / feed by its public key (a Buffer or hex string).

$3

An array of all hypercores in the kappa-core. Check a feed's key to find the
one you want, or check its writable / readable properties.

Only populated once core.ready(fn) is fired.

$3

Install a view called name to the kappa-core instance. A view is an object of
the form

`js
// All are optional except "map"
{

// Process each batch of entries
map: function (entries, next) {
entries.forEach(function (entry) {
// ...
})
next()
},

// Your useful functions for users of this view to call
api: {
someSyncFunction: function (core) { return ... },
someAsyncFunction: function (core, cb) { process.nextTick(cb, ...) }
},

// Save progress state so processing can resume on later runs of the program.
// Not required if you're using the "kappa-view" module, which handles this for you.
fetchState: function (cb) { ... },
storeState: function (state, cb) { ... },
clearState: function (cb) { ... }

// Runs after each batch of entries is done processing and progress is persisted
indexed: function (entries) { ... },

// Number of entries to process in a batch
maxBatch: 100,
}
`

NOTE: The kappa-core instance core is always passed as the first parameter
in all of the api functions you define.

version is an integer that represents what version you want to consider the
view logic as. Whenever you change it (generally by incrementing it by 1), the
underlying data generated by the view will be wiped, and the view will be
regenerated again from scratch. This provides a means to change the logic or
data structure of a view over time in a way that is future-compatible.

The fetchState, storeState, and clearState functions are optional: they
tell the view where to store its state information about what log entries have
been indexed thus far. If not passed in, they will be stored in memory (i.e.
reprocessed on each fresh run of the program). You can use any backend you want
(like leveldb) to store the Buffer object state. If you use a module like
kappa-view, it will handle state
management on your behalf.

indexed is an optional function to run whenever a new batch of entries have
been indexed and written to storage. Receives an array of entries.

$3

Wait until all views named by viewNames are caught up. E.g.

`
// one
core.ready('sum', function () { ... })

// or several
core.ready(['kv', 'refs', 'spatial'], function () { ... })
`

If viewNames is [] or not included, all views will be waited on.

$3

Pause some or all of the views' indexing process. If no viewNames are given,
they will all be paused. cb is called once the views finish up any entries
they're in the middle of processing and are fully stopped.

$3

Resume some or all paused views. If no viewNames is given, all views are
resumed.

$3

Create a duplex replication stream. opts are passed in to
multifeed's API of the same name.

Ensure that isInitiator to true to one side, and false on the other. This is necessary for setting up the encryption mechanism.

$3

Event emitted when an error within kappa-core has occurred. This is very
important to listen on, lest things suddenly seem to break and it's not
immediately clear why.

Install

With npm installed, run

`
$ npm install kappa-core
``

Useful helper modules

Here are some useful modules that play well with kappa-core for building
materialized views:

- unordered-materialized-bkd: spatial index
- unordered-materialized-kv: key/value store
- unordered-materialized-backrefs: back-references

Why?

kappa-core is built atop two major building blocks:

1. [hypercore][hypercore], which is used for (append-only) log storage
2. materialized views, which are built by traversing logs in potentially out-of-order sequence

hypercore provides some very useful superpowers:

1. all data is cryptographically associated with a writer's public key
2. partial replication: parts of logs can be selectively sync'd between peers,
instead of all-or-nothing, without loss of cryptographic integrity

Building views in arbitrary sequence is more challenging than when order is
known to be topographic or sorted in some way, but confers some benefits:

1. most programs are only interested in the latest values of data; the long tail
of history can be traversed asynchronously at leisure after the tips of the
logs are processed
2. the views are tolerant of partially available data. Many of the modules
listed in the section below depend on topographic completeness: all entries
referenced by an entry must be present for indexes to function. This makes
things like the equivalent to a shallow clone (think [git][git-shallow]),
where a small subset of the full dataset can be used and built on without
breaking anything.

Acknowledgments

kappa-core is built atop ideas from a huge body of others' work:

- [flumedb][flumedb]
- secure scuttlebutt
- [hypercore][hypercore]
- hyperdb
- forkdb
- hyperlog
- a harmonious meshing of ideas with @substack in the south of spain

Further Reading

- kappa architecture

License

ISC

[hypercore]: https://github.com/mafintosh/hypercore
[flumedb]: https://github.com/flumedb/flumedb
[git-shallow]: https://www.git-scm.com/docs/gitconsole.log(one#gitconsole.log(one---depthltdepthgt)
[kappa]: http://kappa-architecture.com