#Lunr

A RESTful full-text indexer, searcher, and recommendation engine.

##Install

npm install lunr -g

##Start

npm explore lunr
cp config-default.json config.json
lunrd start

##Configuration

All configuration is stored in config.json. This is the default configuration:

{
  "port": 6969,    // accept REST requests on this port
  "cache": false,  // enable Redis caching of GET requests?
  "ttl": null,     // cache TTL in milliseconds [default 60000]
  "cluster": true, // spawn up a server worker for each CPU?
  "queue": false,  // use Redis as a FIFO queue for PUT commands?
  "mongo": {
    "host": "localhost",
    "port": 27017,
    "database": "test"
  },
  "redis": {
    "host": "localhost",
    "post": 6379
  }
}

##How it works

When a PUT command is issued against lunrd, it is put into a FIFO queue (stored in Redis). This allows Lunr nodes to be load balanced. Each will process keys as it is able to, responding to other commands first (GETs and DELETEs take precedence over PUTs).

Every piece of content PUT into Lunr will be stemmed and subsequestly indexed. Lunr will store all documents in Mongo with the following schema:

{
  "_id": "myID",
  "t": "My Title",
  "c": "blah blah blah",
  "ts": [ "title" ],
  "cs": [ "blah", "blah", "blah" ]
}

It will then index the terms in a separate collection:

{
  "_id": "blah",
  "e": [
    {
      "_id": "myID",
      "count": 3
    }
  ]
}

If the cache config variable is set to true, GET requests will be cached to Redis - either for ttl milliseconds or 5 minutes.

##API

####GET /:id

Grab the full document from the index.

curl http://localhost:6969/myID

####PUT /

Insert a document into the index.

curl -i -X PUT \
-d '{"_id": "myID", "title": "my title", "content": "blah blah blah"}' \
http://localhost:6969/

####DELETE /:id

Unindex a document.

curl -i -X DELETE http://localhost:6969/myID

####GET /search/:query

Run a lexical similarity query against the index. :query must be URL encoded.

curl http://localhost:6969/search/hello%20world

####GET /similar/:id

Run a similarity query against the index by ID.

curl http://localhost:6969/similary/myID

##Node convenience wrapper client

npm install lunr

var lunr = require('lunr');

var client = new lunr({
  host: 'localhost',
  port: 6969
});

client.get('myID', console.log);
client.put(doc, console.log);
client.del('myID', console.log);
client.search('blah blah', console.log);
client.similar('myID', console.log);

##License

MIT