MongoDB with Async Python Transcripts
Chapter: Performance Tuning
Lecture: Levers and Knobs of MongoDB Performance
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So you've heard that MongoDB is fast, and yet you go and run a query, and here you can see it's taking 0.7 seconds.
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Now, I don't know where you're coming from or your perspective, that may seem actually somewhat fast, but to me, that's slow, slow, slow.
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We should be able to do so much better than going and getting our data back in a second or so. So in this chapter, like I said,
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we're gonna make it fast, we're gonna get that same answer back, but this time, it's going to fly.
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You can see now we got that 700 millisecond request down to be 700 times faster to being just one millisecond. There we go.
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So what knobs and levers do we have to turn to make MongoDB fast? What is available to us to actually affect and control how it runs?
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We have indexes, indexes, indexes, indexes, never forget indexes. They're easy to add, although they are a limited resource for you per collection.
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But they're really easy to add and they are like magic database fairy dust.
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You sprinkle a little bit of index on and wham, your database is so, so much faster. That thing you just saw where it went 706 times faster.
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because we added an index. Incredible. Another one we've touched on this, but not so much
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from a perspective of performance is document design or just how we model our data. We did
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talk about to embed or not to embed and all that. But reiterating that is a huge knob
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that you can control on how you design your documents. Query style. Previously, when we
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built that API a couple of chapters ago, what we did is we said, first, let's check and And make sure the package is there.
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And then we're going to do a request to get the package back, make some changes in memory and push all those things back into the database.
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That's one query style and extremely ODM object oriented style programming. And I do like that style and it has its place.
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But not always, especially not when you're worried about performance.
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So as we saw, there's atomic in place updates and those types of things we can do.
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So we can change our query style for pushing more of the work straight into MongoDB instead of inside our Python app.
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We can also do what are called projections. You may have heard that select stars a bad idea because it takes all the data and you
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should select only what you need. Well when we just pull back documents by themselves, we are effectively saying give us all of the document.
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But not just that also the embedded documents and possibly their embedded documents as well. So that can be a ton of data.
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If you don't need it, don't ask for it. And two larger deployment topology, distributed database types of things you can do with MongoDB
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that we are not going to cover in this course, 'cause it's not really about Python and async, you can look into this if you want,
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is we can create what's called a replica set. Oftentimes this is done for uptime and durability. So there's sometimes three MongoDB servers
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working in a cluster and you connect to all of them, if one goes down, then another one picks up and they're replicating within themselves,
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in that scenario, you can set it up so that you can read from the other replicas. So for example, let's say you have five MongoDB servers
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in a replica set, you could sort of 5X the performance or the capacity of your database by saying, I'm willing to read from any of the replicas.
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You start to get into consistency And it's it's can be tricky, but under extreme needs for performance, it's an option.
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Another one is sharding, which is to say, I'm going to take part of the data and put
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it in one MongoDB server, have another one kind of like replica, but instead of making
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a copy, we're going to put a slice of the data for each one, like, maybe if we're tracking
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people by where they lived in US states, each state could have its own server assigned to it so that we spread out the work across many other servers.
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That'll make reading and writing faster. Cool, but again, not something we're covering.
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You can look into those two things over at, it's a pure MongoDB server side type of thing that you want to control there.
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So interesting, knobs you can turn, not knobs that we will be turning in this course.