MongoDB with Python - Basics IV - Update & Delete Operation

Welcome to one more quick session on MongoDB CRUD Basics with Update and Delete Operations. MDB Provides below methods under these operations -

** Update
      * update_one
      * update_many
      * replace_one

** Delete
      * delete_one
      * delete_many

For on Mongo DB -> Link

As it is quite clear from the name itself (_one and _many) that these methods perform the operation on single or multiple records based on the passed condition.
There are so many operator supported by update statement, few are as below -

$set - Add new or update field value
$unset  - Remove field
$inc - increment the current value
$push - push element into array field
$push with $each - push multiple elements into array field
$pop - pull out last value from array field

There are many more Update operators support by MongoDB, Full list can be found HERE


CRUD Operation - (Update & Delete) : Link

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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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Purging SQL Table without impacting the users

This happens very rarely but sometime I have been asked to conditional purge the SQL table without impacting the Users (So we can not use the truncate which is quick and harsh  :) ), These kind of request is pain when client says this table is business critical and used by different application 24/7 so can not take offline and delete the data. So I came up with SQL script or Stored Procedure which will purge the data without impacting the users, though this Proc can run slow or fast based on the Batch Size you have selected, Smaller (not Smallest) the batch size lower the deadlock risk. You can select the Batch and Total deleted row count based on your need. 

Hope, This proc will be useful for you and let me know if required any improvement. I have written this for SQL Server, you can rewrite for any other DB as well after small tweaking

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