Mongolike

Mongolike is an experimental MongoDB clone being built on top of PLV8 and Postgres.

Implemented (so far)

• create_collection()
• drop_collection()
• save()
• find()
• runCommand() (Map/Reduce)
• ensureIndex()
• removeIndex()
• getIndexes()

Installing

Install PLV8

Visit http://code.google.com/p/plv8js/wiki/PLV8 and follow the build instructions.

Install Mongolike

The Easy Way

The easy way to install is to use node.js.

$ npm install -g mongolike
$ mongolike-install -d yourdb

The Slight Less Easy Way

$ psql yourdb <sql/*.sql

Running Tests

Mongolike includes a test suite and a test runner.

$ test/test_runner.js -d yourdb

Additional tests can be added to test/tests.sql.

Using

All commands must be prefixed by SELECT, and are modified slightly to work in the Postgres environment.

create_collection(collection)

Create a collection.

Example:

SELECT create_collection('test');

drop_collection(collection)

Drop a collection.

Example:

SELECT drop_collection('test');

save(collection, object)

Save an object into a collection.

Example:

SELECT save('test', '{ "foo": "bar" }');

find(collection /*, terms, limit, skip */)

Find an object, with optional terms, limit, and skip.

Example:

SELECT find('test', '{ "type": { "$in": [ "food", "snacks" ] } }');

runCommand(command)

Run a command on the Database. Currently only mapReduce is supported.

NOTE The JSON object cannot have carriage returns, the example below does for readability.

Example:

SELECT runCommand('{
  "map": "function MapCode() {
    emit(this.Country, {
      \"data\": [
        {
          \"city\": this.City, 
          \"lat\":  this.Latitude, 
          \"lon\":  this.Longitude
        }
      ]
    });
  }",
  "reduce": "function ReduceCode(key, values) {
    var reduced = {
      \"data\": [ ]
    };
    for (var i in values) {
      var inter = values[i];
      for (var j in inter.data) {
        reduced.data.push(inter.data[j]);
      }
    }
    return reduced;
  }",
  "mapreduce": "cities",
  "finalize": "function Finalize(key, reduced) {
    if (reduced.data.length == 1) {
      return {
        \"message\" : \"This Country contains only 1 City\"
      };
    }

    var min_dist = 999999999999;
    var city1 = { \"name\": \"\" };
    var city2 = { \"name\": \"\" };
    var c1;
    var c2;
    var d;

    for (var i in reduced.data) {
      for (var j in reduced.data) {
        if (i >= j) continue;
        c1 = reduced.data[i];
        c2 = reduced.data[j];
        d = Math.sqrt((c1.lat-c2.lat)*(c1.lat-c2.lat)+(c1.lon-c2.lon)*(c1.lon-c2.lon));

        if (d < min_dist && d > 0) {
          min_dist = d;
          city1 = c1;
          city2 = c2;
        }
      }
    }
    return {
      \"city1\": city1.city,
      \"city2\": city2.city,
      \"dist\": min_dist
    };
  }" }');

ensureIndex(collection, terms /*, type */)

Creates a new index on a collection.

Example:

SELECT ensureIndex('test', '{ "foo", "bar" }', '{ "unique": true }');

removeIndex(collection, name)

Removes an index from a collection by name.

Example:

SELECT removeIndex('test', 'idx_col_woo_foo');

removeIndex(collection, terms)

Removes an index from a collection by terms.

NOTE in order to remove an index with terms you MUST cast the query due to how Postgres handles JSON.

Example:

SELECT removeIndex('test', '{ "foo", "bar" }'::json);

getIndexes(collection)

Retrieves all indexes for a given collection.

Example:

SELECT getIndexes('test');

Importing the Data

I have included a modest amount of data for testing and benchmarking, both for Postgres and for MongoDB (1,706,873 rows).

Importing into Postgres:

$ psql yourdb < data/cities.sql

This will create the collection and save() all of the data.

Importing into MongoDB

$ mongoimport --collection cities --type csv --headerline --file data/cities.csv --db yourdb

Follow along at http://legitimatesounding.com/blog/