> For the complete documentation index, see [llms.txt](https://gchandra.gitbook.io/big-data-and-tools-with-nosql/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gchandra.gitbook.io/big-data-and-tools-with-nosql/nosql/mongodb/insert-document.md).

# Insert Document

```
db.friendsCollection.insertOne(
{
    "firstname": "Monica",
    "lastname":"Geller",
    "age": 30,
    "location":"NYC",
    "profession":"chef"
}
)
```

1. **Command Purpose**:  `db.friendsCollection.insertOne({...})` it is used to insert a single document into the `friendsCollection`. If `friendsCollection` doesn't exist, MongoDB will create it automatically when you insert the first document.
2. **Document Structure**: The document being inserted is enclosed in curly braces `{...}`. It represents a single record or entry in the `friendsCollection`. This document is similar to a row in a relational database table but can have a complex, nested structure.
3. **Field-Value Pairs**: Inside the document, data is stored as field-value pairs. For example, `"firstname": "Monica"` means there's a field named `firstname` with the value `"Monica"`. Fields are similar to column names in a relational database, and values can be various data types (e.g., string, number, array, object).
4. **Data Types**:  MongoDB supports various data types. In this command, `firstname`, `lastname`, `location`, and `profession` are strings and `age` is a number.
5. **Collection**: A collection is similar to a table in a relational database. It's a grouping of documents, usually with related information. In this case, `friendsCollection` might hold documents for each friend, including their name, age, location, and profession.
6. **Database**: The `db` part refers to the database you're working with. Databases contain collections, and a MongoDB server can host multiple databases.
7. **Read and Write Operations**: After inserting data, you can retrieve, update, or delete it using MongoDB's CRUD (Create, Read, Update, Delete) operations. For example, you could use `db.friendsCollection.findOne({firstname: "Monica"})` to find Monica's document.
8. **Flexibility**:  MongoDB's schema-less nature means documents in the same collection don't need the same fields.

```
db.friendsCollection.find()
```

```
// "_id"

Autogenerated ObjectID consists of 12 bytes. It's of type BSON

4 bytes - Unix Epoch
3 bytes - machine identifier
2 bytes - process id
3 bytes - random value
```

**Globally Unique:** The first 9 bytes (timestamp, machine identifier, and process ID) indeed contribute to the global uniqueness of the ObjectId.

**Automatic Indexing:** By default, MongoDB automatically creates a unique index on the `_id` field for every collection, which helps in efficiently querying documents by their `_id`.

**Hexadecimal Representation** The ObjectId is displayed as 24 hexadecimal characters when represented as a string. This is because each byte (8 bits) of the ObjectId is represented as two hexadecimal characters (each hex digit represents 4 bits). The conversion to hexadecimal doubles the apparent length of the ObjectId when viewed as a string.\
\
**BSON**

**Binary encoded JSON**

Widely used to transmit and store data across web apps. JSON is human-readable.

BSON is encoded, making it easier for machines to read.

MongoDB stores data in BSON format both internally and over the network.

**Advantages of BSON**

* Efficient
* Rich Data Types
* Field Indexing

<figure><img src="/files/cbCJblngL0CAzTcJIfvo" alt=""><figcaption></figcaption></figure>

### How BSON is stored in the MongoDB Database

<figure><img src="/files/ahqVPorfYB0RzftxX6rh" alt=""><figcaption><p>src:mongodb.com/basics/</p></figcaption></figure>

insertMany() is used to insert more than one document.

```
db.friendsCollection.insertMany([
{
    "firstname": "Phoebe",
    "lastname":"Buffay",
    "age": 31,
    "profession":"Therapist"
},
{
    "firstname": "Ross", 
    "lastname":"Geller",
    "age": 31,
    "location": "NY",
    "profession":"Palentologist",
    "spouses":["Carol","Emily","Rachel"]
},
{
    "firstname": "Chandler",
    "lastname":"Bing",
    "age": 31,
    "location": "NY"
},
{
    "firstname": "Joey",
    "lastname":" Tribianni",
    "age": 32,
    "location": "NYC",
    "profession":"actor"
}
])
```

```
db.friendsCollection.insertMany([
{
    "firstname": "rachel",
    "lastname" : "green",
    "age" : 30,
    "location": "NYC",
    "profession":"Fashion Designer"
},
{
    "name":{"firstname":"Ben",
            "lastname" : "Geller"}, 
    "age" : 6,
    "location": "NYC"
},
{
    "name":{"firstname":"Emma",
            "lastname" : "Geller"},
    "age" : 1,
    "location": "NYC"
}
])
```

**Index**

MongoDB cannot create a unique index on the specified index field(s) if the collection already contains data that would violate the unique constraint for the index.

```
db.friendsCollection.createIndex({"firstname" : 1} , {unique : true})
```