Monday, 31 December 2018

MongoDB with Python - Basics III - Find/Select Operation


Hoping you guys are enjoying the NoSql journey so far (previous posts links), till now we have seen basic CRUD operation. From this post onward, I am diving in details of these operations and starting with FIND or SELECT operation in MongoDB. We will learn what are the ways and options provided by MongoDB to select or project the data.

When you start working with complex queries you might {as I have said "Might"} face difficulties with tracking of braces {([ as I've experienced the same with me/my team/students and colleagues. But no worries, Jupyter Notebook provides a  couple highlighter for braces when selected or you can use notepad++ also (which I think is not so useful as you are not gonna copy/paste the syntax so frequently).

I advise everyone to avoid the writing queries directly on mongo shell prompt as it doesn't provide any intelligence and not so good in fixing queries if made mistake.

I am sure you will love this post as well and if have any question feel free to ask in comment section below.

For on Mongo DB -> Link


There are many more Find/Read Operators supported by MongoDB, Full list can be found HERE

CRUD Operation - (Read) : Link




Next Post on this Series and more on MongoDB can be find here -> LINK




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Saturday, 29 December 2018

MongoDB with Python - Basics II - CRUD Operations


In this post, we will learn about the Advance Find and Create Operations with Sort, Skip and Limit functionality. Pymongo driver support almost same kind of syntax for python which mongo shell used.
The benefit of python (or any programming language) + mongo is to use both langauge/db functionality to work with mongo. Though, to perform the same operation is faster then performing by python but it depends on the activity you are performing.



CRUD Operation - (Create, Read, Update & Delete) : Link




Next Post on this Series and more on MongoDB can be find here -> LINK




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Friday, 28 December 2018

MongoDB with Python - Basics I - CRUD Operations


In Previous few posts (Link), We have learnt about MongoDB Cloud Setup, Installation and Basic commands to do CRUD operation with MongoDB. It can be accessed by programming language such as python, java, and node.js by using respective native drivers. We will start with PyMongo (python driver) to access mongo from python.



CRUD Operation - (Create, Read, Update & Delete) : Link




Next Post on this Series and more on MongoDB can be find here -> LINK





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Tuesday, 25 December 2018

MongoDB Atlas - Off Premise Way (DBaaS)


MongoDb also provide cloud services (Database as a Service - DaaS), called MongoDB Atlas, to host your mongo database on cloud. Let's see how we can setup an cloud account and access the MDB from local machine.

Cluster Step :
1. Create an account on https://cloud.mongodb.com
2. Once you are in, the very first thing which it asked to choose your cluster configuration.
2a. It gives you to choose one of cloud service which are - AWS, Google, Azure, Choose whatever you like
2b. But always choose "FREE TIER CLUSTER" (M0 Instance) else there will be usage charge.
3. Once you have selected appropriate config, it will start building your mongoDB Cluster, it will take few mins to complete the setup.
4. When done, it will be like this, usually use Cluster0 as name, you can modify it though -




How to access from local system :

You need to install Mongo Shell to access cloud db which comes with Mongo DB pkg. You can download and install on your OS (Windows/Linux) from here - https://www.mongodb.com/download-center/enterprise

1. Login on https://cloud.mongodb.com and click on Clusters in left hand side list.
2. Click on Connect and follow below steps -
3a. Whitelist your id so that you can connect with your system or any ip address. Click on "Add a different IP Address" and to allow to connect from any system, Use 0.0.0.0 as IP address
3b. Create your cluster credential


4. Once done, you will see the below screen
5a. Now, Click on Choose connection method and click on "Connect with Mongo Shell" -


5b. Now, click on standard connection string


6. Copy the string and replace the <PASSWORD> with the password which you created in Cluster Setup Step #4.
7. Now, As I have installed the MongoDB Shell in Step #1, we need to add MongoDB Bin directory path into system path. You can add this path into windows env variable or Linux user profile so that you can access mongo command from any location.
8. Once path has been added, open cmd or terminal and paste the connection string which you copied and modified in step #5


9. When connected successfully, you can try to run commands as below -


10. For more commands, you can visit this link - https://www.datagenx.net/2018/12/learn-mongo-db-basics.html

11. Mongo Atlas Cloud Step has been completed and verified successfully. You can connect with the same connection string from any system (if firewall allows and have mongo shell installed)

Let me know in comments if you face any issue while doing Atlas setup.
Next Post on this Series and more on MongoDB can be find here -> LINK




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MongoDB - Embedding v/s Referencing


MongoDb, a NoSQL document DB, doesn't support the JOIN as RDBMS do which is a very useful feature in DB domain. So what's new or addition in MongoDb which can overcome the JOIN feature. Let's understand this.

First of all, MongoDb is NOT a replacement of standard RDBMS system. It is misconception in DB world that NoSQL DB system will/can replace RDBMS or vice versa. No, It isn't or going to be. Both Database systems have own pros and cons which we will see later.



Embedding:
As the name itself reveals, Embed the data into the document means put all the data together in one document. This will provide a better read performance when you want to get all the related data in one read call as MongoDb stores one document at one place on the disk so minimum seek time is required when reading the data from disk drive.

Let's suppose. we want to create a data model for below ask -
==

So, Embedding document will look like -
==


Referencing:
Embedding will cause performance slowness when there are frequent CRUD operations on embedded document. In embedding, data duplication is highly probable. In these cases, we create a document reference rather than document. This is similar to parent-child relationship as we have in RDBMS.

Let's see now how our collection Books will look like -
==

Next Post on this Series and more on MongoDB can be find here -> LINK





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Friday, 21 December 2018

Learn Mongo DB - Basics #1


While going through old pages, saw these mongoDB posts, so thought of continuing, We have already completed Installation of MongoDB, Now starting off with few basic commands which will help you to play around MongoDB :-)
==
Next Post on this Series and more on MongoDB can be find here -> LINK




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