Abed01-lab/mongodb-assignment

What is sharding in mongoDB?

Sharding is a mechanism for horizontally partitioning large datasets across multiple servers in MongoDB. It allows MongoDB to scale horizontally by distributing data across multiple machines.

What are the different components required to implement sharding?

The different components required to implement sharding are:

Shard: Each shard is a separate MongoDB instance that stores a subset of the data.
Config servers: These servers keep track of the metadata and configuration for the sharded cluster.
Query router: Also known as the mongos process, it acts as an interface between the application and the sharded cluster. It routes queries to the appropriate shards and aggregates the results.

Explain architecture of sharding in mongoDB?

The architecture of sharding in MongoDB consists of three main components:

Shards: Each shard contains a subset of the data, and can be either a replica set or a standalone MongoDB instance.
Config servers: Config servers store the metadata and configuration for the sharded cluster.
Query router: Query router (mongos) routes the queries from the application to the appropriate shards, and returns the results.

Provide implementation of map and reduce function

db.myCollection.mapReduce(
   function() {
      // map function
      emit(this.field1, this.field2);
   },
   function(key, values) {
      // reduce function
      return Array.sum(values);
   },
   {
      // options
      out: { sort: -1 }
   }
)

Provide execution command for running MapReduce or the aggregate way of doing the same

db.collection.aggregate([
  { $match: { text: /#[^\s]+/ } }, // filter only tweets with hashtags

  { $unwind: "$entities.hashtags" }, // unwind the array of hashtags

  { $group: { _id: "$entities.hashtags.text", count: { $sum: 1 } } }, // group by hashtag text and count occurrences

  { $sort: { count: -1 } }, // sort by count descending

  { $limit: 10 } // limit to the top 10 hashtags
]);

Provide top 10 recorded out of the sorted result. (hint: use sort on the result returned by MapReduce or the aggregate way of doing the same)

The top 10 hastags are:

 "top10Agg": [
    {
      "_id": "FCBLive",
      "count": 27
    },
    {
      "_id": "AngularJS",
      "count": 21
    },
    {
      "_id": "nodejs",
      "count": 20
    },
    {
      "_id": "LFC",
      "count": 19
    },
    {
      "_id": "EspanyolFCB",
      "count": 18
    },
    {
      "_id": "webinar",
      "count": 16
    },
    {
      "_id": "IWCI",
      "count": 15
    },
    {
      "_id": "javascript",
      "count": 14
    },
    {
      "_id": "RedBizUK",
      "count": 12
    },
    {
      "_id": "GlobalMoms",
      "count": 12
    }
  ]

Abed01-lab / mongodb-assignment