https://github.com/dev-sathya17/-day35-guvi
https://github.com/dev-sathya17/-day35-guvi
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/dev-sathya17/-day35-guvi
- Owner: dev-sathya17
- Created: 2024-06-14T10:38:59.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-06-14T14:36:09.000Z (11 months ago)
- Last Synced: 2025-01-18T13:40:05.515Z (4 months ago)
- Size: 1.42 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.MD
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README
# GUVI - DAY 35
## MongoDB Day 1 Exercises
1. About MongoDB.
> - MongoDB is a No-SQL database.
> - It is a document oriented database that utilizes JSON like documents.
> - Unlike MySQL, where data is split as tables, here data is classified into collections and documents.
> - To infer directly from MySQL, we can say that _Collections_ are equivalent to _MySQL Tables_ and Documents are equivalent to _MySQL Rows_.
> - Unlike MySQL, MongoDB documents are unstructured, which makes it more scalable.
2. About the Task.
> - In this task, we are given a data file URL.
> - The data from that URL is downloaded and uploaded to our mongodb database. [Source](./product.json)
> - This data is to be queried as per the given 10 questions and their solutions are to be attached.
> - The complete solution is compiled into a single document. [Source](./Document.pdf)
3. Setup
> - First, we download the data from the task document specified URL.
> - we create a database, using the MongoDB Compass UI.
> - We create a database named `zenTask35` and a collection named `products`.
> - We click on `add data` option, and upload our `product.json` file.
> - On refreshing the collection, the data get populated.
4. Solution
> - In this section, the query solutions for our given 10 questions are discussed. The solution snippets, with the data output are attached in the solution document. [Document URL](./Document.pdf)
1. Find all the information about each products.
```
db.products.find()
```
2. Find the product price which are between 400 to 800.
```
db.products.find({product_price:{$gte:400,$lte:800}})
```
3. Find the product price which are not between 400 to 600.
```
db.products.find({product_price:{$not:{$gte:400, $lte:600}}})
```
4. List the four product which are greater than 500 in price.
```
db.products.find({product_price:{$gt:500}},{}).limit(4)
```
5. Find the product name and product material of each products.
```
db.products.find({},{product_name:1, product_material:1})
```
6. Find the product with a row id of 10.
```
db.products.find({id:"10"},{})
```
7. Find only the product name and product material.
```
db.products.find({},{product_name:1, product_material:1})
```
8. Find all products which contain the value of soft in product material.
```
db.products.find({product_material:"Soft"})
```
9. Find products which contain product color indigo and product price 492.00.
```
db.products.find({product_color:"indigo",product_price:492.00})
```
10. Delete the products which product price value are 28.
```
db.products.deleteOne({product_price:28})
```