Download 50 Tips and Tricks for MongoDB Developers by Kristina Chodorow PDF

By Kristina Chodorow

Getting begun with MongoDB is simple, yet when you start construction purposes with it, you'll face a few complicated concerns. What are the tradeoffs among normalized and denormalized info? How do you deal with reproduction set failure and failover? This number of MongoDB suggestions, methods, and hacks is helping you get to the bottom of concerns with every little thing from software layout and implementation to facts defense and monitoring.

You get particular assistance in 5 subject parts at once from engineers at 10gen, the corporate that develops and helps this open resource database:
Application layout Tips: What to bear in mind whilst designing your schema
Implementation Tips: Programming purposes opposed to MongoDB
Optimization Tips: dashing up your functions
Data defense Tips: utilizing replication and journaling to maintain facts safe—without sacrificing an excessive amount of functionality
Administration Tips: the way to configure MongoDB and hold it operating easily

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You must set up replica sets and sharding programmatically, but you could write out the setup functions in a JavaScript file which you could execute to set up the set. It’s close to being able to use a configuration file. Tip #50: Use a single connection to read your own writes When you create a connection to a MongoDB server, this connection behaves like a queue for requests. So, for example, if you send messages A, B, and then C to the database through this connection, MongoDB will process message A, then message B, then message C.

If you have 200GB of data, your disk must have at least 200GB of free space to run repair). One problem a lot of people have is that they have too much data to run repair: they might have a 500GB database on a server with 700GB of disk. If you’re in this situation, you can do a “manual” repair by doing a mongodump and then a mongorestore. For example, suppose we have a server that’s filling up with mostly empty space at ny1. The database is 300GB and the server it’s on only has a 400GB disk. However, we also have ny2, which is an identical 400GB machine with nothing on it yet.

This means that the ratio of disk time to RAM time is 1 millisecond to 1 nanosecond. One millisecond is equal to one million nanoseconds, so accessing disk takes (roughly) a million times longer than accessing RAM. Thus, reading off of disk takes a really long time in computing terms. On Linux, you can measure sequential disk access on your machine by running sudo hdparm -t /dev/hdwhatever. This doesn’t give you an exact measure, as MongoDB will be doing non-sequential reads and writes, but it’s interesting to see what your machine can do.

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