Chodorow - Scaling MongoDB
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- Book:Scaling MongoDB
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Abstract: Create a MongoDB cluster that will to grow to meet the needs of your application. With this short and concise ebook, youll get guidelines for setting up and using clusters to store a large volume of data, and learn how to access the data efficiently. Read more...
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This text is for MongoDB users who are interested in sharding. It is a comprehensive look at how to set up and use a cluster.
This is not an introduction to MongoDB; I assume that you understand what a document, collection, and database are, how to read and write data, what an index is, and how and why to set up a replica set.
If you are not familiar with MongoDB, its easy to learn. There are a number of books on MongoDB, including MongoDB: The Definitive Guide from this author. You can also check out the online documentation.
The following typographical conventions are used in this book:
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In the Terminator movies, an artificial intelligence called Skynet wages war on humans, chugging along for decades creating robots and killing off humanity. This is the dream of most ops peoplenot to destroy humanity, but to build a distributed system that will work long-term without relying on people carrying pagers. Skynet is still a pipe dream, unfortunately, because distributed systems are very difficult, both to design well and to keep running.
A single database server has a couple of basic states: its either up or down. If you add another machine and divide your data between the two, you now have some sort of dependency between the servers. How does it affect one machine if the other goes down? Can your application handle either (or both) machines going down? What if the two machines are up, but cant communicate? What if they can communicate, but only very, very, slowly?
As you add more nodes, these problems just become more numerous and complex: what happens if entire parts of your cluster cant communicate with other parts? What happens if one subset of machines crashes? What happens if you lose an entire data center? Suddenly, even taking a backup becomes difficult: how do you take a consistent snapshot of many terabytes of data across dozens of machines without freezing out the application trying to use the data?
If you can get away with a single server, it is much simpler. However, if you want to store a large volume of data or access it at a rate higher than a single server can handle, youll need to set up a cluster. On the plus side, MongoDB tries to take care of a lot of the issues listed above. Keep in mind that this isnt as simple as setting up a single mongod (then again, what is?). This book shows you how to set up a robust cluster and what to expect every step of the way.
Sharding is the method MongoDB uses to split a large collection across several servers (called a cluster). While sharding has roots in relational database partitioning, it is (like most aspects of MongoDB) very different.
The biggest difference between any partitioning schemes youve probably used and MongoDB is that MongoDB does almost everything automatically. Once you tell MongoDB to distribute data, it will take care of keeping your data balanced between servers. You have to tell MongoDB to add new servers to the cluster, but once you do, MongoDB takes care of making sure that they get an even amount of the data, too.
Sharding is designed to fulfill three simple goals:
We want an application to have no idea that what its talking to is anything other than a single, vanilla mongod.
To accomplish this, MongoDB comes with a special routing process called
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