MongoDB : Creating a Large Document

In order to try various queries or to check the performance of the database, we need to have large enough documents; here we will create a couple of large documents and try to query those with different operators and functions available in MongoDB

In the below examples we will create two collections techno_col and tech_large with 2000 and 15000 documents in it. Insertion might take some time depending on number of documents

> for (i = 0; i < 2000; i++) { db.techno_col.save({num: i}); }

WriteResult({ "nInserted" : 1 })

> 

> db.techno_col.count();

2000

> 

> for(i = 0;  i < 15000;  i++) {db.tech_large.save({emp_id : i});};

WriteResult({ "nInserted" : 1 })

> 

> db.tech_large.count();

15000

> 

Now try to query documents from techno_col collections, 

> db.techno_col.find()

{ "_id" : ObjectId("5c5d66a310f3108c3c83d574"), "num" : 0 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d575"), "num" : 1 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d576"), "num" : 2 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d577"), "num" : 3 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d578"), "num" : 4 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d579"), "num" : 5 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d57a"), "num" : 6 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d57b"), "num" : 7 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d57c"), "num" : 8 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d57d"), "num" : 9 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d57e"), "num" : 10 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d57f"), "num" : 11 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d580"), "num" : 12 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d581"), "num" : 13 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d582"), "num" : 14 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d583"), "num" : 15 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d584"), "num" : 16 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d585"), "num" : 17 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d586"), "num" : 18 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d587"), "num" : 19 }

Type "it" for more

> 

Here we can see only 20 documents, it will depend upon the platform, next documents can be seen using "it" as suggested at the end of the result

> it

{ "_id" : ObjectId("5c5d66a310f3108c3c83d588"), "num" : 20 }

{ "_id" : ObjectId("5c5d66a310f3108c3c83d589"), "num" : 21 }

.....

{ "_id" : ObjectId("5c5d66a310f3108c3c83d59b"), "num" : 39 }

Type "it" for more

> 

Now try finding details for employees with emp_id 2000 from collection tech_large

> db.tech_large.find({emp_id: 2000});

{ "_id" : ObjectId("5c5d69e110f3108c3c83e514"), "emp_id" : 2000 }

> 

Find details of num value greater than 1991 

> db.techno_col.find({num: {"$gt" :1991}});

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd3c"), "num" : 1992 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd3d"), "num" : 1993 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd3e"), "num" : 1994 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd3f"), "num" : 1995 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd40"), "num" : 1996 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd41"), "num" : 1997 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd42"), "num" : 1998 }

{ "_id" : ObjectId("5c5d66a510f3108c3c83dd43"), "num" : 1999 }

> 

Now try finding the employees between emp_id 5000 and 5009. 

> db.tech_large.find({emp_id : {"$gt" : 5000, "$lt" : 5009}});

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0cd"), "emp_id" : 5001 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0ce"), "emp_id" : 5002 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0cf"), "emp_id" : 5003 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0d0"), "emp_id" : 5004 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0d1"), "emp_id" : 5005 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0d2"), "emp_id" : 5006 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0d3"), "emp_id" : 5007 }

{ "_id" : ObjectId("5c5d69e410f3108c3c83f0d4"), "emp_id" : 5008 }

> 

Use of $and and $or operators :

As I have only typical documents in the collection, results may not differ, but these operators will be a handful

> db.techno_col.find({$and: [{_id : ObjectId("5c5d66a410f3108c3c83d8ea")}, {num : 886}]})

{ "_id" : ObjectId("5c5d66a410f3108c3c83d8ea"), "num" : 886 }

> 

> db.techno_col.find({$or: [{_id : ObjectId("5c5d66a410f3108c3c83d8ea")}, {num : 887}]})

{ "_id" : ObjectId("5c5d66a410f3108c3c83d8ea"), "num" : 886 }

{ "_id" : ObjectId("5c5d66a410f3108c3c83d8eb"), "num" : 887 }

>

In next article of MongoDB will be learn Indexing and explain plan.