🚀 Big News: Socket Acquires Coana to Bring Reachability Analysis to Every Appsec Team.Learn more
Socket
DemoInstallSign in
Socket

mongodb-schema

Package Overview
Dependencies
Maintainers
3
Versions
77
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

mongodb-schema

Infer the probabilistic schema for a MongoDB collection.

4.0.0
Source
npm
Version published
Weekly downloads
20K
89.4%
Maintainers
3
Weekly downloads
 
Created
Source

mongodb-schema

Infer a probabilistic schema for a MongoDB collection.

A high-level view of the class interactions is as follows:

Example

mongodb-schema doesn't do anything directly with mongodb so to try the examples we'll install the node.js driver.
As well, we'll need some data in a collection to derive the schema of.

Make sure you have a mongod running on localhost on port 27017 (or change the example accordingly). Then, do:

  • npm install mongodb mongodb-schema
  • mongo --eval "db.test.insert([{_id: 1, a: true}, {_id: 2, a: 'true'}, {_id: 3, a: 1}, {_id: 4}])" localhost:27017/test
  • Create a new file parse-schema.js and paste in the following code:
var parseSchema = require('mongodb-schema');
var connect = require('mongodb');

connect('mongodb://localhost:27017/test', function(err, db){
  if(err) return console.error(err);

  parseSchema('test.test', db.collection('test').find(), function(err, schema){
    if(err) return console.error(err);

    console.log(JSON.stringify(schema, null, 2));
    db.close();
  });
});
  • When we run the above with node parse-schema.js, we'll see something like the following (some fields not present here for clarity):
{
  "count": 4,                   // parsed 4 documents
  "ns": "test.test",            // namespace
  "fields": [                   // an array of Field objects, @see `./lib/field.js`
    {
      "name": "_id",
      "count": 4,               // 4 documents counted with _id
      "type": "Number",         // the type of _id is `Number`
      "probability": 1,         // all documents had an _id field
      "unique": 4,              // 4 unique values found
      "has_duplicates": false,  // therefore no duplicates
      "types": [                // an array of Type objects, @see `./lib/types/`
        {
          "name": "Number",     // name of the type
          "count": 4,           // 4 numbers counted
          "probability": 1,
          "unique": 4,
          "values": [           // array of encountered values
            1,
            2,
            3,
            4
          ]
        }
      ]
    },
    {
      "name": "a",
      "count": 3,               // only 3 documents with field `a` counted
      "probability": 0.75,      // hence probability 0.75
      "type": [                 // found these types
        "Boolean",
        "String",
        "Number",
        "Undefined"             // for convenience, we treat Undefined as its own type
      ],
      "unique": 3,
      "has_duplicates": false,   // there were no duplicate values
      "types": [
        {
          "name": "Boolean",
          "count": 1,
          "probability": 0.25,  // probabilities for types are calculated factoring in Undefined
          "unique": 1,
          "values": [
            true
          ]
        },
        {
          "name": "String",
          "count": 1,
          "probability": 0.25,
          "unique": 1,
          "values": [
            "true"
          ]
        },
        {
          "name": "Number",
          "count": 1,
          "probability": 0.25,
          "unique": 1,
          "values": [
            1
          ]
        },
        {
          "name": "Undefined",
          "count": 1,
          "probability": 0.25,
          "unique": 0
        }
      ]
    }
  ]
}

More Examples

mongodb-schema supports all BSON types. Checkout the tests for more usage examples.

Schema Statistics

To compare schemas quantitatively we introduce the following measurable metrics on a schema:

Schema Depth

The schema depth is defined as the maximum number of nested levels of keys in the schema. It does not matter if the subdocuments are nested directly or as elements of an array. An empty document has a depth of 0, whereas a document with some top-level keys but no nested subdocuments has a depth of 1.

Schema Width

The schema width is defined as the number of individual keys, added up over all nesting levels of the schema. Array values do not count towards the schema width.

Examples

{}
StatisticValue
Schema Depth0
Schema Width0
{
  one: 1
}
StatisticValue
Schema Depth1
Schema Width1
{
  one: [
    "foo",
    "bar",
    {
      two: {
        three: 3
      }
    },
    "baz"
  ],
  foo: "bar"
}
StatisticValue
Schema Depth3
Schema Width4
{
  a: 1,
  b: false,
  one: {
    c: null,
    two: {
      three: {
        four: 4,
        e: "deepest nesting level"
      }
    }
  },
  f: {
    g: "not the deepest level"
  }
}
StatisticValue
Schema Depth4
Schema Width10
// first document
{
  foo: [
    {
      bar: [1, 2, 3]
    }
  ]
},
// second document
{
  foo: 0
}
StatisticValue
Schema Depth2
Schema Width2

Installation

npm install --save mongodb-schema

Testing

npm test

Dependencies

Under the hood, mongodb-schema uses ampersand-state and ampersand-collection for modeling Schema, Field's, and Type's.

Note: Currently we are pinning ampersand-state to version 4.8.2 due to a backwards-breaking change introduced in version 4.9.x. For more details, see ampersand-state issue #226.

License

Apache 2.0

Keywords

mongodb

FAQs

Package last updated on 04 Mar 2016

Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts