In Node.js using JSON.stringify results in 'process out of memory' error

Question

With Node I am trying to collect user data from an LDAP server and then write that data to a JSON file. I am using the following code to do this:

fs.writeFile('data.json', JSON.stringify(data, null, 4));

The problem is the JSON.stringify method is causing the following error:

FATAL ERROR: JS Allocation failed - process out of memory

I know the problem is with JSON.stringify because if I use console.log rather than fs.writeFile I get the same error.

I am trying to write a lot of data (over 500 entries in the LDAP database). Does anyone know how I can get this to work? Here is the code in full:

var ldap = require('ldapjs');
var util = require('util');
var fs = require('fs');
var client = ldap.createClient({
  url: '************'
});

client.bind('CN=**********,OU=Users,OU=LBi UK,OU=UK,DC=********,DC=local', '*********', function(err) {
  if (err) {
    console.log(err.name);
  }
});


// taken from http://ldapjs.org/client.html
client.search('OU=Users,OU=******,OU=UK,DC=******,DC=local', {
  scope: 'sub',
  filter: 'objectClass=organizationalPerson',
  attributes: ['givenName', 'dn', 'sn', 'title', 'department', 'thumbnailPhoto', 'manager']
  // filter by organizational person
}, function(err, res) {
  if (err) {
    console.log(err.name);
  }

  var limit = 1;
  var data = {"directory": []};

  res.on('searchEntry', function(entry) {

    var obj = {};
    entry.attributes.forEach(function (attribute) {
      var value;
      if (attribute.type === 'thumbnailPhoto') {
        value = attribute.buffers[0];

      } else {
        value = attribute.vals[0];
      }
      obj[attribute.type] = value;
    });
    data.directory.push(obj);
  });
  res.on('error', function(err) {
    console.log('error: ' + err.message);
  });
  res.on('end', function(result) {
    fs.writeFile('data.json', JSON.stringify(data, null, 4));
  });

});

Answer 1

As @freakish mentioned the problem was my data was too big.

The reason the data was so big was due to a large number of images that were being returned as objects. In the end all I needed to do was encode the object as base64 using Buffers and then the size of the data became much more manageable.