MongoDB Official Documentation

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MongoDB Official Documentation

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MongoDB World 2019: Raiders of the Anti-patterns: A Journey Towards Fixing Schema Mistakes in MongoDB

As a software adventurer, Charles "Indy" Sarrazin, has brought numerous customers through the MongoDB world, using his extensive knowledge to make sure they always got the most out of their databases. Let us embark on a journey inside the Document Model, where we will identify, analyze and fix anti-patterns.

https://www.slideshare.net/mongodb/mongodb-world-2019-raiders-of-the-antipatterns-a-journey-towards-fixing-schema-mistakes-in-mongodb

MongoDB World 2019: Raiders of the Anti-patterns: A Journey Towards Fixing Schema Mistakes in MongoDB

Anti-patterns commonly found with MongoDB

Practical MongoDB Aggregations Book

Learn how to develop effective and optimal data manipulation and analytics pipelines with this book, using the MongoDB Aggregation Framework

https://www.practical-mongodb-aggregations.com/

MongoDB Aggregation Pipeline Cookbook

This is a set of tools to view/process the MongoDB logs for debugging and perf tuning

How To SELECT ... FOR UPDATE inside MongoDB Transactions | MongoDB Blog

The most common question that I receive as a MongoDB Consultant since we introduced Multi-document ACID transactions in MongoDB 4.0 is: "How can I be sure that the documents that I am reading inside a transaction are not modified by another operation before the commit?"

https://www.mongodb.com/blog/post/how-to-select--for-update-inside-mongodb-transactions

How To SELECT ... FOR UPDATE inside MongoDB Transactions | MongoDB Blog

Record level locks

Improve MongoDB Performance Using Projection

This article documents all my findings and analysis on how much performance was improved using projection in MongoDB. At the end of this article, we will be able to know whether MongoDB query performance will be improved by leveraging projection. Without further ado, let's start.

Improve MongoDB Performance Using Projection

https://betterprogramming.pub/improve-mongodb-performance-using-projection-c08c38334269

Improve MongoDB Performance Using Projection

MongoDB Pagination, Fast & Consistent

When it comes to pagination, the simplest method that comes to mind is the , but it is not always the best solution! Although the skip-limit is suitable for some applications, it suffers from 2 major problems As mentioned in MongoDB docs, it requires scanning all the previous docs before reaching the desired one, so it becomes slower as the offset increases.

MongoDB Pagination, Fast & Consistent

https://medium.com/swlh/mongodb-pagination-fast-consistent-ece2a97070f3

MongoDB Pagination, Fast & Consistent

This is actually a great idea for pagination everywhere in the portal

Building with Patterns: The Bucket Pattern

One frequently asked question when it comes to MongoDB is "How do I structure my schema in MongoDB for my application?" The honest answer is, it depends. Does your application do more reads than writes? What data needs to be together when read from the database? What performance considerations are there?

https://www.mongodb.com/developer/how-to/polymorphic-pattern/

Building with Patterns: The Bucket Pattern

Pre-paginated records grouped into buckets (with a continuation token)

Repeatable Performance Tests: CPU Options Are Best Disabled | MongoDB Blog

In an effort to improve repeatability, the MongoDB Performance team set out to reduce noise on several performance test suites run on EC2 instances. At the beginning of the project, it was unclear whether our goal of running repeatable performance tests in a public cloud was achievable.

https://www.mongodb.com/blog/post/repeatable-performance-tests-cpu-options-best-disabled

Repeatable Performance Tests: CPU Options Are Best Disabled | MongoDB Blog

When optimizing IOPS, optimizing CPU utilization will increase performance and consistency significantly

blog.insiderattack.net

https://blog.insiderattack.net/implementing-event-sourcing-and-cqrs-pattern-with-mongodb-66991e7b72be

5 successful tips you need to optimise MongoDB

Increase performance four times and reduce the size of your MongoDB by 83 % with these five suggestions. Go through our optimization experiments and see how we've reached these results. Relational databases have been around for a long time and they have been the primary way to store data in a consistent way.

5 successful tips you need to optimise MongoDB

https://medium.com/tech-hunters/optimising-size-performance-mongodb-ad7ea5f30dc5

5 successful tips you need to optimise MongoDB

MongoDB: Storage Optimization Just by Using Shorter Filed-Names/Enum-Values.

This is an easy small straightforward change not used much, We might not want to shorten the field-name/enum values present for the existing collection, but keeping this in mind when creating a new collection will help, will see how. Filed name size/length contributes to the document size as MongoDB stores all field names in every document.

MongoDB: Storage Optimization Just by Using Shorter Filed-Names/Enum-Values.

https://medium.com/swlh/mongodb-use-shorter-filed-names-enum-values-optimize-disk-memory-f73f64db324e

MongoDB: Storage Optimization Just by Using Shorter Filed-Names/Enum-Values.

Short name optimization Frank previously mentioned

Generate fake data to use in performance testing with MongoDB

Configuration File Options

The following page describes the configuration options available in MongoDB 5.0. For configuration file options for other versions of MongoDB, see the appropriate version of the MongoDB Manual. You can configure and instances at startup using a configuration file. The configuration file contains settings that are equivalent to the and command-line options.

https://docs.mongodb.com/manual/reference/configuration-options/#mongodb-setting-storage.journal.commitIntervalMs

Configuration File Options

Lower values increase the durability of the journal, at the expense of disk performance.

Advanced Options for MongoDB Deployments - MongoDB Ops Manager upcoming

The following mongod and mongos configuration options are available through the Ops Manager Advanced Configuration Options field when you deploy MongoDB. You select advanced options when deploying: The Ops Manager Advanced Configuration Options map to the MongoDB configuration options and parameters described as follows.

https://docs.opsmanager.mongodb.com/current/reference/deployment-advanced-options/

Advanced Options for MongoDB Deployments - MongoDB Ops Manager upcoming

All options for MongoDB instances

Reducing Queue Times by Using Speculative Execution | MongoDB Blog

When solving concurrency problems in software, the simplest solution is often to make the trickiest part of the problem serial. Here at MongoDB, this is exactly the approach we took to implement a commit queue, where engineers submit code changes to be tested and then merged into a repository.

https://www.mongodb.com/blog/post/reducing-queue-times-using-speculative-execution

Reducing Queue Times by Using Speculative Execution | MongoDB Blog

Honestly not sure I understand this one, but it looks like it could allow parallel processing with bull queues needed to scale horizontally.

notion image

notion image

Available block sizes

Any document that is larger than the block size, will double the IOPS consumption when performing actions on that document

64 KB
128 KB
256 KB
512 KB
1 MB
2 MB
4 MB
8 MB
15 MB

notion image

Considerations for Shard-Key

Cardinality

Key distribution across cardinal values

Hot spot consideration

Hashed strategy — Optimal write scalability but read scalability is limited

Range strategy (with and without Tags) — Optimal read scalability

MongoDB: Sharding

Sharding is Mongo's answer for scaling. It is a way of distributing both work and data. More work over more data. And it is required for big-data problems - really really big data. So it is important to understand It achieves the scaling requirements by scaling out, i.e.

https://sarada-sastri.medium.com/mongodb-sharding-95871e5dea1c

MongoDB: Sharding