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Namshi's indexer: a central place to work with storage engines and syncing data here and there.

Zindex is a very simple library that, at its core, simply fetches some data from a source and indexes them in backends.


Clone this repository and install the required dependencies:

npm install zindex --save

zindex cannot be globally installed at this time

Zindex 101:

Zindex can be called directly as a runnable command with:

~/projects/myIndexer$ ./node_modules/zindex/bin/zindex.js

or as a normal library by

var zindex = require('zindex');


You can create your very own command by putting this in yuor own javascript file:

// example run.js
#!/usr/bin/env node
var zindex = require('zindex');

and than chmod a+x run.js


Zindex by default will look for scripts inside a indexers and a watchers in your project's directory.

Hoever you can configure these path as you best wish since we're including nm-config. The Avvailable options are:

  base: './src'

Will tell to zindex to look for both indexers and watchers under your projects src/ directory

  indexers: './foo/index'
  watchers: './bar/watch'

Will cause zindex to search for indexers inside the foo/index directory and for watchers inside bar/watch


If you wish to have these configs in your package.json you can add a zindex section:

   "name": "myDataApp",
   "version": "0.0.1",
   "description": "I move data!",
   "zindex": {
     "dirs": {
       "base": "./src"


~/projects/myIndexer$ ./node_modules/zindex/bin/zindex.js index --help

  Usage: index [options]


    -h, --help           output usage information
    -S --since [value]   index entities in the specified timeframe (ie. "3h")
    -M --mode [value]    partial or full
    -E --entity [value]  which entity to index

Zindex' primary role is to be able to sync data between one data source to N backends.


With bootstrapping we indicate the act of building a backend from scratch. This commands works only on backends that expose a "bootstrap" function. If the backend does not have one, it just does nothing.

~/projects/myIndexer$ ./node_modules/zindex/bin/zindex.js bootstrap --help

  Usage: bootstrap [options]

  Bootstrap one or more backends


    -h, --help            output usage information
    -E --entity [value]   which entity to index, you can specify a comma-separated list of entities


With Sourcing we indicate the base indexing action: fetching data from a Source, ie: a mysql table

Zindex will look by default look for indexers in you local indexers folder.

In order to do so, you simply need to create a directory in your indexers folder with the entity you want to sync, ie. products:

Zindex will read a source.js file that is inside that directory to source the data that needs to be synced; an example source.js would look like:

# lib/indexer/products/source.js
var shops = include('storages/mysql');
var path  = require('path');
module.exports = function(options) {
  var products = mysql.query('severId', 'SELECT * FROM db.products');
  return {
    data: products,
    options: {myProperty: 'value'}

the return value will be further explained below in the Data format section


Use the included mysql helper (storages/mysql), it will manage connections etc for you. severId will be the key for the configure connections in the config files.

   database: 'zindex_{{ env }}'
   host: 'db_1'
   user: 'user'
   password: 'password'
   connectTimeout: 10000
   acquireTimeout: 10000

As for the above config your serverId will be myDatabaseName


With Transforming we indicate the actual process of manipulating your data objects.

At this point, once the data has been extracted from the source, you might want to apply some transformations, like renaming a boolean field to TRUE or FALSE and so on: to do so zindex will look for a transformer.js script inside indexer/ENTITY/.

An example transformer.js would look like:

# indexer/products/transformer.js
function transform(product, options) {
  product['in_stock'] = !!(product.quantity > 0);
  return product;
module.exports = function(products, options) {
  return products.map(function(product) {
    return transform(product, options);


As you see we define a transform() function out of the exported lamba: this is to allow a better optimization from V8 since in this place we're likely touching lots of objects and deopt code might badly impact both memory usage and performances.

To ease your life, zindex will transform the data it got from the source to an "Highland Stream" object.

Having an Highland Stream means you can do stuff like this:

return products.filter(function(product){
  return product.price > 100;

As you see an observable is a simple collection which you can chunk, filter, etc.

In the example above we are simply filtering our collection to pick the first ten products which have a price higher than 100.


Persisting is the last and final step of our indexing process: here we save the data were they need to be saved!

The data is then fed to what we call "backends": Zindex looks for them scripts under indexer/ENTITY/backends and will send the data to each one of them so they can be be stored in each backend; think of your backends as different storage systems: for example you might want to sync products in a mysql table and in redis, which means you will create two backends, one called products_table.js and the other one called redis.js.

If we create a file called redis.js under indexer/products/backends and write something like:

# indexer/products/backends/redis.js
var redis = require('redis')('...', '...', '...');
module.exports = function(data) {
  data.each(funciton(product) {
    redis.execute('HSET', 'namshi:products', product);

We will effectively have setup a sync of the products from a MySQL table to a redis hash.


As you'll more likely deal with quite a bit of data, you might want to collect a number of them before actually saving them inside your backend facility. To achieve this you can leverage on Highland Stream's batches (batch()):

data.batch(20000).each(function(products) {
   redis.execute('HSET', 'namshi:products', products);

Zindex Advanced:

Under the hood

Here are a few things you might want to know to better understand how zindex internally works.

Data format

A source should return a result object with a data property, containing the actual data, and an (optional ;P) options property containing all those other useful bits of information you'd like to carry on in your indexing process. Data will be transformed into the Highland Stream, and options will be added to the usual options fed into every each step.

For example, the Bob source could return something like:

var result = {
  data: [{id: 'row_1'}, {id: 'row_2'}, ...],
  options: {shop: 'ae'}

For backends that have multiple data sources, they can simply return arrays of the above structure; for example, a more extensive implementation of the Bob source would return something like:

var results = [{
  data: [{id: 'row_1'}, {id: 'row_2'}, ...],
  options: { shop: 'ae'}
  data: [{id: 'row_1'}, {id: 'row_2'}, ...],
  options: {shop: 'sa'}
  data: [{id: 'row_1'}, {id: 'row_2'}, ...],
  options: {shop: 'me'}


Your source, as data, can return a stream! And everything can be wrapped into a promise (or more). Actually Zindex its self internally uses promisses and streams as we'll see later on

Even though sources might return either an array of objects or a stream, transformers and backends will always receive the data as a first argument in the form of a Highland Stream object, and all other informations as options:

var backend = function(data, options) {
  console.log('Got shop?', options.shop);
    return product.gender === 'male';
    return product.sku;
    redis.save('male_skus', skus);

Async loading: behind the scenes

As you porbably noticed we always and up having an Highland Stream in our hands, and this happens asyncronusly even if we're returning an object. Under the hood Zindex uses streams and promises to avoid blocking the main thread, and since it likes them so much it will always try to mangle what you give to it in one fo the 2 things (or a combination of them).

In depth for maniacs; Anatomy of processing a source:

Since your data can come either from a single simple table, or from many different palces, what Zindex would really like to have are either promises or streams, or lists of them as data property for the returned object.

Depending on your data, what Zindex provides might not be enough to save you from the deadly threat of blocking. Let's say your final data need to be enriched by another source (the ERP for example). In that case we strongly suggest you to leverage on promises(through bluebird) that can be conveniently fed back into Highland Stream and everything goes back to normal :)


Indexing can take some options like --since 3h and be used within sources / backends to optimize queries: for example, you could use an option like since to optimize sourcing of your data, to speed up sync times.


To ease your life you might consider using templates for you queries. For your teplating needs we provide an included template compiler

Realtime indexing

In order to do realtime indexing (a record gets changed and it gets immediately indexed) we simply rely on RabbitMQ and process messages that come through:

~/projects/myIndexer$ ./node_modules/zindex/bin/zindex.js index-realtime --entity products --priority 0

info: Waiting to receive updates for products
info: Connected to the AMQP server...
info: Received a message to index the products with id "2567"
Starting to index...
info: Loading data for entity "products"
info: Loaded template:
FROM myDb.products

  WHERE product_id = 2567

info: Found 1 backends
info: Indexing products in backend "sample"
indexing: [ { product_id: 2567, name: 'shoes' } ]

Demons will need an entity and a priority, so that they will be able to receive specific updates: the queues will take the name indexer.ENTITY.PRIORITY, for example indexer.products.1.

What the demon does is to simply call the indexer, passing it the entity and the ID of the update. Then the indexer runs with the given options; for example, you can customize your queries using something like:

FROM myDb.products
{% if id %}
  WHERE product_id = {{ id }}
{% endif %}


The basics

~/projects/myIndexer$ ./node_modules/zindex/bin/zindex.js watch --help

  Usage: watch [options]


    -h, --help                       output usage information
    -E --entity <entity,entity,...>  One or more entities to watch, comma separated
    -I --interval [value]            interval between checks (ie. "3m")

Watchers are what keeps an eye on data changes and broadcast messages based on the obtained data: as we saw, realtime indexing will consume messages that come through RabbitMQ and the watchers are the ones responsible for keeping an eye on the DB and, as soon as a record gets updated, send a message to Rabbit.

A watcher provides the watch() method including the actual logic to watch a source. A notify function will be provided to the watch() logic in order to broadcast messages.

You can specify an entity name for the watcher if the "watcher file" (ie. items.js) has a different name from your entity ("items").

Long story short: when the watcher finds that a record gets updated it calls notify(entity, id [, priority]) which will send a message to Rabbit

watcher example:

module.exports = {
  entity: 'products',
  watch: function (options, notify) {
      products = db.query('SELECT * FROM products WHERE updated_at < 5000');
        // notify(key, value, [priority])
        notify('product', product.id, 0);
    }, 5000);

Depending on the source of your data it might need to poll, in that case you can use on javascript's setInterval() but bare in mind is not guaranteed to be accurate So you might need to detect and adjust the time-shift error. We do provide some support objects capable to deal with this as we'll see later.

Once you create a new watcher simply include it in the watchers/ directory and it will be usable via the -E option on the command line.

~/projects/myIndexer$ ./node_modules/zindex/bin/zindex.js watch -E your_new_watcher_name

All the watchers will run automatically if no -E is provided.


Running multiple watchers at once isn't a great idea and it is allowed mainly for debugging purposes. If one watcher goes down it takes all the other ones with him -- so yeah be careful :)

Watchers' Sources: keeping an eye on multiple things

The root of a watcher is a Source object

Here is an example watcher using a custom source extending the base one:

module.exports = {
  init: function(templates, options) {
    this.entity = options.name || null;
    this.templates = templates || null;
    this.globOptions = options.globOptions || null;
  watch: function (options, notify) {
    var self = this;
    notifier.options.priority = 0;
    var source = new mySource(options, self.templates, self.globOptions);
    function getNewData() {
      source.get().then(function(results) {
        _.forEach(results, function(value, key) {
          notifier.notify(key, value);
    setInterval(function() {
      logger.debug('Poller:: run (' + self.entity + ')');
    }, source.interval);

For you convenience we build a mysql abstract source that will ease your life :)

Zindex toolkit:

Sindex exports a special include() function giving access to a series of provided goodies to ease your indexing needs:


var config = include('config'); this will return a reconfig object gnerated by the underlying nm-config

Mysql Helper

var mysql = include('storages/mysql');

This is an helper build on top of node's mysql library, it's aim is to conceal most of the cerramony you'd need ot do to connect and query a mysql database in a single convenient method:

mysql.query(targetPool, sql, options);

The possible params are the following:

targetPool: the name of the database server we want to connect to as listed inside the config file sql: your sql or sql template options: formatted data in case of a sql template.

It will also take care of making your communication towards the database simpler and more efficient, spawning N connecitons (as set in the config file), queueing your queries, and taking everything up or down upon need.


Use bulk queries and templates to insert lots of data in a single shot.

AMPQ Helper

var amqp = include('storages/amqp');

As by its name, this library will help you connectiong to an amqp queue (rabbit, for instance) To listen on a queue and get a message you smply need to do:

amqp.listen(options).then(function() {
  amqp.queue.each(function(message) {

Zindex will figure out the correct queue for you based on the command's option received in consolle.

If you need to send a message you can use the notifier library build on top of this helper.


var notifier = include('notifier');

It's the one automatically injected in all teh watchers, and it provides and handy way to push messages on the rabbit queues without all the cerramony.

to queue a message simply do:

notifier(options).notify(key, message, priority);

The options can have 2 keys:

  • entity: as the entty sending the message
  • priority: the queue's default priority

The notify() method's message parameter can be whatever value transformable in a valid json, and it mostly depends on what the receving indexer is expecting to have. The priority param for the notification will effect only the current message.


var utils = include('utils');

This little lib wraps and increments node's util module with some comodity functions.

Among all you might watn to take a look to:

  • stringToMoment(): dealing with date and times between humans and computers can be quite anoying so we choose to use momentjs to provide and easy way to teh use to specify times and intervals, and a ceveniente way for us to use it.

  • prepareForBulkQuery(): you'll fine this littel function expeciallly usefull in your mysql backends. Give it a list of objects and it will transform them in an handy object easy to use with a sql template query to feed to our helper

  • wrapInPromise(): wrap your data structure in a promise for you to carry around convenintly in async contexts.


var logger = include('logger');

Our logger exposes a classic winston logging interface with some added config values as well as a graylog transport handy in the production enviroment.


By default Zindex will log in console.

Access the web interface with the admin:zindex account and configure a UDP endpoint.

Enjoy graylogging!

Template Compiler

var tpl = include('tpl');

The tpl module provides a way to parse template files and transform them into queries:

FROM myDb.products
{% if since %}
  WHERE UPDATED_AT > "{{ since.format('YYYY-DD-MM HH:mm:s') }}"
{% endif %}

It will also cache the compiled query for you so your logic will not need to access the filesystem every time :)


Tests are run through mocha, you can simply run npm test.

The build is continuosly run on travis as well.


npm i zindex

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