The Simplest ElasticSearch Node.js Module
Q: There is already an "official" ElasticSearch module, why create a new one...?
A: Have you tried using the official client...? Did you enjoy the experience?
We needed an easy way to create, read, update and search our ElasticSearch records from node.js. All the available modules were way too complicated to use for beginners. So we decided to invest the time to create something much simpler!
Creating a record in ElasticSearch from your node.js app using esta is this simple:
var es = require('esta'); // the simplest way to use ElasticSearch in node.js!
es.create({'message':'ElasticSearch is awesome!'}, function(response){
console.log('record created '+ response.created); // record created true
})
As you are about to discover, there is a much easier way to use ElasticSearch!
##Guide to esta Documentation
Usage:
- Installation
- CONNECT to ElasticSearch Cluster
- CRUD
- SEARCH for Record(s)
- STATS
- Error handling
- Local/Dev Machine
- (Travis) CI
- (Optional) Use Vagrant to Run ElasticSearch
Philosophy / Background / Detail:
## Usage ### Install from [NPM](https://www.npmjs.com/package/esta)npm install esta --save
If you need to check the connection status to the ElasticSearch Instance/Cluster
we expose the handy ES.CONNECT
method:
var ES = require('esta');
ES.CONNECT(index, function (response) {
console.log(response);
// for more detailed stats see: STATS method below
});
Pass in the index name as the first argument if you have not set an ES_INDEX environment variable.
example ES.CONNECT
response:
{ status: 200,
name: 'Ultragirl',
cluster_name: 'elasticsearch',
version:
{ number: '1.4.2',
build_hash: '927caff6f05403e936c20bf4529f144f0c89fd8c',
build_timestamp: '2014-12-16T14:11:12Z',
build_snapshot: false,
lucene_version: '4.10.2' },
tagline: 'You Know, for Search' }
###[CRUD](http://en.wikipedia.org/wiki/Create,_read,_update_and_delete) Methods #### CREATE (Save) a (new) record using `ES.CREATE(record, callback(response))`
Creating a new record is easy:
// define the record you want to store:
var record = {
date: new Date().toISOString(),
message: 'Your amazing message goes here'
};
ES.CREATE(record, function(response) {
// do what ever you like with the response
});
A typical successful ES.CREATE
response:
{ _index: 'index',
_type: 'type',
_id: '112669114721',
_version: 1,
created: true }
index
can be compared to a Database in SQL see: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/glossary.html#glossary-indextype
is like the table in SQL-world or a collection in other NoSQL systems. see: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/glossary.html#glossary-typeid
is the unique key for your record. equivalent to the primary-key in a SQL-world
While its optional to set these on your record before asking esta to create it,
we highly recommend using index
, type
and id
to organise your records.
#### READ a record using `ES.READ(record, callback(response))`
READing your record:
// define the record you want to retrieve:
var record = {
index: 'twitter',
type: 'tweet',
id: 1234, // or what ever GUID you want to lookup
};
ES.READ(record, function(response) {
// do what ever you like with the response
});
A typical successful ES.READ
response:
{ _index: 'twitter',
_type: 'tweet',
_id: '735981868114',
_version: 1,
found: true,
_source: { message: 'My Awesome Message' }
}
Here _source is the original data you inserted as the record.
When a record does not exist response.found
is false
. e.g:
{ _index: 'twitter',
_type: 'tweet',
_id: '804164689732',
found: false }
index
we need to know which "database" our record is intype
"table"id
the unique key for the record you are looking up.
#### UPDATE an (existing) record using `ES.UPDATE(record, callback(response))`
UPDATE an existing record:
// define the record you want to store:
var record = {
index: 'twitter',
type: 'tweet',
id: 1234, // or what ever GUID you want
message: 'Revised message'
};
ES.UPDATE(record, function(response) {
// do what ever you like with the response
});
A typical successful ES.UPDATE
response:
{ _index: 'twitter',
_type: 'tweet',
_id: '639403095701',
_version: 2,
created: false }
Notice how the _version gets incremented to 2
index
we need to know which "database" our record is intype
"table"id
the unique key for the record you are updating.
Note: UPDATE actually performs an UPSERT
UPdate record if already exists or inSERT (create) if its new.
#### DELETE a record using `ES.DELETE(record, callback(response))`
// define the record you want to store:
var record = {
type: 'tweet',
index: 'twitter',
id: 1234, // or what ever GUID you want
message: 'Revised message'
};
ES.DELETE(record, function(response) {
// do what ever you like with the response
});
A typical successful ES.DELETE
response:
{ found: true,
_index: 'twitter',
_type: 'tweet',
_id: '137167415115',
_version: 2,
deleted: true }
Notice how the deleted is true
index
we need to know which "database" our record is intype
"table"id
the unique key for the record you are updating.
Obviously if the record is NOT Found, there is nothing to delete. In that case, the response look like this: (found is false)
{ found: false,
_index: 'twitter',
_type: 'tweet',
_id: '951078315032',
_version: 1 }
ElasticSearch does not store revisions of your documents by default, we made a "BACKUP" method which stores previous versions of records, when ever they are updated or deleted.
The old versions are stored as different type
to avoid polluting
the main "table" with copies this type is named: {typename}_bak
For example, if a document has an id abc
and its current version
is 2 we can find the previous version (v1) of the document by issuing the following read
query:
var backup = { index: 'twitter', type: 'tweets_bak', id: 'abc_1'}
### SEARCH for Record(s) using `ES.SEARCH(query, callback(response))`
Searching is super easy:
// setup query:
var query = {
index: 'twitter',
type: 'tweet',
field: 'text', // the field we want to search in
text: 'amazing' // string we are searching for
};
SEARCH(query, function(response) {
// console.log(res);
t.equal(res.hits.total > 0, true,
chalk.green("โ Search results found: "+ res.hits.total));
t.end();
});
A typical successful ES.SEARCH
response:
{ took: 8,
timed_out: false,
_shards: { total: 5, successful: 5, failed: 0 },
hits:
{ total: 924,
max_score: 0.6355637,
hits:
[ [Object],
[Object],
etc...
}
}
The response.hits.total is 924 (the number of records that matched our SEARCH query)
index
we need to know which "database" our record is intype
"table"field
the field in the record you want to search in.text
the text you are searching for.
When NO RECORDS are FOUND the response will look this:
{ took: 2,
timed_out: false,
_shards: { total: 5, successful: 5, failed: 0 },
hits: { total: 0, max_score: null, hits: [] } }
We check for if(response.hits.total > 0) { /* use/display results */ } else { /* show sad face */}
Here's the image we use:
### Get Cluster STATS using `ES.STATS(callback(response))`
The ES.STATS method exposes the ElasticSearch Instance/Cluster _stats
see: http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/indices-stats.html
STATS(function (response) {
// do something awesome response
});
ElasticSearch returns rich information on cluster health, document count etc. see: #31 for complete STATS output
To help you get started as fast as possible, esta defaults to using your local machine for ElasticSearch.
### Local/Dev Machine [![Beginner Friendly](https://img.shields.io/badge/shoshin-yes-brightgreen.svg?style=flat)](http://en.wikipedia.org/wiki/Shoshin "Beginner Friendly")Provided you already have ElasticSearch installed (we recommend using Vagrant, see below), there is nothing to setup or configure to use esta on your local machine!
If you are deploying your App to Heroku there are two ElasticSearch-as-a-Service providers that offer Free entry level service:
- Bonsai: https://addons.heroku.com/bonsai
- SearchBox: https://addons.heroku.com/searchbox
esta supports both of these providers out-of-the-box! as soon as you add the "addon" to your heroku app it "just works!"
Our Travis Build Process includes checks for both Bonsai and SearchBox: See: https://travis-ci.org/dwyl/esta/jobs/58582216#L270
### (Travis) CISpeaking of Travis-CI, if you are using their fine build tool, here's a sample .travis.yml file:
language: node_js
node_js:
- 6
services:
- elasticsearch
if you are new to Travis-CI see: https://github.com/docdis/learn-travis
## (*Optional*) Use *Vagrant* to Run ElasticSearch [![vagrant up](https://img.shields.io/badge/vagrant-up-brightgreen.svg?style=flat)](https://github.com/nelsonic/learn-vagrant)If, like me you prefer not to have Java running on your dev machine (because its chronically insecure) I highly recommend using Vagrant to run a light-weight virtual machine to isolate ElasticSearch and only install Java in the VM.
The other obvious benefit of using Vagrant is that all your fellow developers will have exactly the same (latest) build so there's no risk of version incompatibility. Learn more at: https://github.com/nelsonic/learn-vagrant
I've included a Vagrantfile in this repo which will get you up-and-running with Ubuntu, Node.js & ElasticSearch with a single command: vagrant up
all you need to do is run the following commands in your terminal:
vagrant up
vagrant ssh
sudo service elasticsearch start
If you have any questions, just ask!
We wanted something simpler and thus much easier to extend if you need to!
esta is easy to understand. The entire module is 129 lines of clear/clean/commented/DRY code;
you can read & understand it all before breakfast!
Dive in at /lib. Each method has a corresponding file in /test
We wanted a way of "soft-deleting" records (i.e. avoiding data loss.) If you like the idea of being able to * recover accidentally deleted data*, you will love our DELETE method see: lib/delete.js
## *Only* Core Modules [![Dependency Status](https://david-dm.org/dwyl/esta.svg)](https://david-dm.org/dwyl/esta)Zero external dependencies (3rd party modules).
There are quite a few modules in the node ecosystem for use with ElasticSearch. However, when I saw how many dependencies the "Official" ElasticSearch Node.js Module https://github.com/elasticsearch/elasticsearch-js had and especially the number of DevDependencies, it made it hard to contribute to the project...
Our aim is to build something that only uses core modules with
Stable APIs,
so we never have to think about upgrading - it also makes it a
lot easier for others to learn how the module works, which
invites contribution from the community.
Given that ElasticSearch has a REST API we are only using Node's http (core) module.
and this is kept DRY (only in one file)
see: lib/http_request.js
We carefully select and only use well-maintained "pure" JavaScript modules in our development toolchain:
- Tape for testing: https://github.com/substack/tape
- Istanbul for Code Coverage: https://github.com/nelsonic/learn-istanbul
- Chalk for colors in test output (readability)
- Pre-commit for ensuring all commits pass strict quality checks before being pushed to GitHub. see: https://github.com/nelsonic/learn-pre-commit
- jshint checks code style is consistent: https://github.com/nelsonic/learn-jshint
- CodeClimate for tracking code quality and test coverage: https://github.com/nelsonic/learn-codeclimate
If you are looking for a module you can trust, these are the "badges" you are looking for.
## Contributing [![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/dwyl/esta/issues)All contributions are welcome.
If anything is unclear please create an issue:
https://github.com/dwyl/esta/issues
Most of the Node.js developers I've worked with, don't handle errors well.
A typical (bad) example:
if(error) {
console.log(error); // this is worse than useless!
}
So instead of having of having code full of if(err) ...
we have deliberately cut out errors
from callback functions completely.
Thus, all the methods in this module have the simplified signature:
ES.METHOD(record, function(response){
// do something with response
});
Instead, we propose using a central error catcher. e.g:
process.on('uncaughtException', function(err) {
console.log('ERROR: ' + err); // preferably handle errors appropriately
});
or, if you are using Hapi.js we recommend using https://github.com/hapijs/poop
For more on Errors, please read: https://www.joyent.com/developers/node/design/errors
We prefer to have the METHOD names UPPERCASE because it makes them easy to spot and differentiate from your code. If you feel they are a bit "shouty" all methods are available in lowercase too; take your pick! see: http://git.io/pZ6t
## Module NameThe choice of module name was the answer to the question:
Q: Which ElasticSearch Node Module should I use...?
A: https://translate.google.com/#auto/en/esta