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https://github.com/kappa-db/kappa-core

Minimal peer-to-peer database, based on kappa architecture.
https://github.com/kappa-db/kappa-core

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Minimal peer-to-peer database, based on kappa architecture.

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# 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](./intro.md).



## 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')

```



### var core = kappa(storage, opts)



Create a new kappa-core database.



- `storage` is a [random-access-storage](https://github.com/random-access-storage) function, or a string. If a string is given, [random-access-file](https://github.com/random-access-storage/random-access-storage) 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](https://github.com/kappa-db/multifeed)



### core.writer(name, cb)



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](https://github.com/mafintosh/hypercore).



### var feed = core.feed(key)



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



### var feeds = core.feeds()



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.



### core.use(name[, version], view)



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](https://github.com/kappa-db/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.



### core.ready(viewNames, cb)



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.



### core.pause([viewNames], [cb])



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.



### core.resume([viewNames])



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

resumed.



### core.replicate(isInitiator, [opts])



Create a duplex replication stream. `opts` are passed in to

[multifeed](https://github.com/kappa-db/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.



### core.on('error', function (err) {})



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](https://npmjs.org/) 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](https://github.com/digidem/unordered-materialized-bkd): spatial index

- [unordered-materialized-kv](https://github.com/digidem/unordered-materialized-kv): key/value store

- [unordered-materialized-backrefs](https://github.com/digidem/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](http://scuttlebutt.nz)

- [hypercore][hypercore]

- [hyperdb](https://github.com/mafintosh/hyperdb)

- [forkdb](https://github.com/substack/forkdb)

- [hyperlog](https://github.com/mafintosh/hyperlog)

- a harmonious meshing of ideas with @[substack](https://github.com/substack) in the south of spain



## Further Reading



- [kappa architecture](http://kappa-architecture.com)



## 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