Want to experience preparing scalable and efficient databases for your applications? Then this is the right course for you. MongoDB is the most popular NoSQL database in the market today. With support for real-time analytics, it is being used by many big enterprises for efficient and fast processing of data.
This Video Learning Path will show you how you can get the most out of MongoDB’s advanced features with ease. After getting a quick overview of the basics of MongoDB, you will directly jump to covering the concepts related to advanced data modelling, complex querying, indexing, and database operations.
This Video Learning Path will also cover important aspects such as cloud deployment which is important when it comes to web applications and integration with Hadoop for fast and efficient Big Data processing.
MongoDB provides excellent set of tools and services to maximize your application’s performance. You will explore real-world examples that you can watch and use directly for your application.
We will then explore the profiling and performance tools for MongoDB. We will make it even more accessible by moving to MongoDB cloud services, including analytics, automation, and even Database-as-a-Service.
By the end of this Video Learning Path, you will have mastered all the concepts of MongoDB along with learning to boost your application’s performance.
About the Author
Rick Copeland is the Principal Consultant of Arborian Consulting, which provides MongoDB and Python-focused consulting, training, and custom development services. Rick has been using MongoDB since 2009 and Python since 2005, and has spoken at various user groups and conferences on both topics. He is a member of the Python Software Foundation and the Masters of MongoDB.
Replication is the core method to achieve durability in MongoDB. Developers need to understand why replication is important and the basics of how it works.
MongoDB clusters scale best by sharding partitioning data across many servers. Developers need to know the basics of how this works and how it affects their application design.
How can you query the database using the shell?
The student should be able to use the shell to create and drop various index types.
To start using MongoDB, the student must be able to connect to a database server using the pymongo driver.
The student needs to know how to manage cursors through large data sets in pymongo.
The student should be able to write performant bulk load/update scripts using pymongo.
Understand how MongoDB documents give more flexibility to schema design.
Understand the trade-off between linking and embedding.
Understand how to design your schema to allow for scaling via sharding.
Understand how and when to use MongoDB's covered queries, geospatial indexes, and full-text indexes.
You should be able to examine a running system to see its performance characteristics.
You should be able to use the profiler to identify and correct slow queries in a running system.
How can I configure my database without going through the trouble of getting my own EC2 account?
How can I scale the read bandwidth using MongoDB replica sets?
What impacts the single-node performance of a MongoDB system, and when does vertical scaling beat horizontal?
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