Advanced Schema Design Patterns

Editor's Notes

• #2: Welcome May not have time for questions, however come see me at the end [Remember] Beware of transitions, keep them smooth [TODOs] Add the page numbers Drawing of a working set Consider removing ":" in the slide titles Consider changing "revenues" => revenue, in few slides More on the value and use cases for each pattern
• #3: Previous Jobs => Gang of Four I like Food, Beers and Movies … and MongoDB. My inspiration for this talk comes from the "Gang of Four". How many of you are familiar with the "Gang of Four"?
• #4: Building blocks, Some patterns, => Same for MongoDB Basically the ones who wrote this book on "Design Patterns" GOF are Erich Gamma, Richard Helm, Ralph Johnson and John Vlissides https://en.wikipedia.org/wiki/Design_Patterns Key words are "Elements of Reusable Software" Assemble their experience on designing and implementing software over the years They found that a lot of the solutions were sharing some "patterns" Examples of patterns from "Design Patterns" Types: Creational (5), Structural (7), Behavioral (11) Singleton (restrict the creation to a single object for a given class) Observer (number of objects to see an event) Command (user operation) Decorator (embellishing a UI element) Memento (ability to restore an object to a previous state) … So, they went and made a catalog of those "patterns". The idea is enable people who write software to share a common language and have building blocks for solutions.
• #5: 10 Years, Vocabulary, Building Blocks, "Art", => Why create models? We use that contents in our internal trainings, however is it the first time we are presenting it at a conference, well… including the "data modeling" workshop we ran yesterday. The goal is not to teach you about doing schema design. I am expecting you to either have done some with MongoDB or with a Relational Database My goal is to help you formalize the process of creating schemas for MongoDB, help you work in team by sharing visuals, vocabulary
• #6: Performance & scalability, "air" Before we get going, let's just answer why we create models. In a perfect world, you don't really have to model. I mean if everything is super fast and resources are abundant, you really don't care where and how data is stored Every day I get up I don't make plans on how I will breathe air. However if you go to space or under water, you will need a "design" that will let you get the amount of air you need.
• #7: Design is optional, cost of developer, 5 or 10 shards If performance is not an issue, meaning you have resources to spare, then you are likely to model for simplicity. The reason is that software engineers are very expensive. You may not think so, but your manager does. If you need to shard the database, it is likely that performance is very important Why using 10 shards, if you can reduce the number of operations (reads and writes) by 2 and be able to do the same with 5 shards?
• #8: Fictional site, Entities In order to illustrate this talk, let's assume there is a fictional site called the "World Movie Database". This site is so popular that everyone goes there on Thursdays before the release of new movies and it crashes the site. Then some people tried to migrate the site to a NoSQL database, MongoDB obviously.
• #9: Collections, grouping not optimal => accept challenge This is the first try of trying to move the schema from Relational to MongoDB. There are 3 collections: movies, moviegoers and screenings. Simply grouping entities into collections is not optimal. The solution using this design did not perform much better than the previous one. This is still normalized. When you remove this restriction, duplication is fine, 1-1 relationships are fine. You open the door to some important transformations. Those will be our patterns. [NOTE] Use "Sync Visibility" once you activate the color layer to also see it in the PNG file.
• #10: Perform & Scale, without training Our goal, no need to say, is to fix this website before it gets the same fate as this tape recorder.
• #11: Some heroes need a lot of gadgets to achieve their mission. We will do our with a very powerfull one, patterns.
• #12: Categories, top 5 most frequent patterns We will use patterns, like the Gang of Four. Most patterns can be grouped in 3 categories. We will cover those patterns identified with check marks in this presentation. Also, I will cover the patterns in order of importance, or so. For the other ones, I will refer you to the slides of this presentation and subsequent content we will have on the subject.
• #13: Documents are too big How do I search on movies being released on a given date in the USA? The same would apply to products you could see on E-commerce site. For example, clothes may have a size that is expressed as S, M, L, while for some other products like a laptop, size would be something like 13", 15"
• #14: Transitions Don't mention that you used this pattern in your personal info, as it is now a Quiz
• #15: Inventory of things to insure Polymorphic entities Vehicles: submarine, car
• #16: "Adding a qualifier on the attribute" may be "currency"
• #17: Definition of Working set With everyone pounding on the WMDB site, it was observed that the working set does not fit in memory. What can you do? Looking at the design we see that we are putting all the actors and all reviews for a given movie in the main document [TODO] Add a drawing showing what the working set is
• #18: Remember this collection in the middle?
• #19: The collection "castandcrew" contains all the actors, but also the producers, costume makers, stunts, etc. For this pattern to be worth it, it has to have a fair amount of information left aside.
• #20: Top level information for a first page If this is slow, you may not keep your users on the site You want them to validate that this is what they want, then dig for more if needed
• #22: Please come see us at the Education booth, we have prizes for people who will get the answers right
• #24: As you may guess, people pay attention to the popularity of the movies. So, metrics like "revenues" and "viewers" are really important. In the current design, those numbers are calculated every time the page of a movie is displayed. Let’s calculate those numbers once in a while and stick the results on the page instead.
• #25: Also refer to "Rolled up" as CQRS - Command Query Responsibility Segregation According to Bryan, that sounds good at a Party.
• #29: Another thing that was observed with the current design is that trying to keep track of all page views of the site resulted in very poor performance. That was seen for both MMAPv1 and WT. In MMAPv1, you get a lot of threads looking for the write lock. While with WT, you get a lot of write conflicts that need to be retried. One solution is to record "good enough" numbers. Well no one cares that the count is 100 millions or 100 millions and few. What is the tolerance level here? Let’s assume 1000. In this case, we will let the application update the page views by 1000, however only 1/1000th of the time. Statistically, we should get a result very close to the exact count, however doing only 1/1000th of the writes. If you make the parallel to a movie, we never see a movie as a continuous image, the movie is made by displaying 24 static images per second, however this is enough to our eyes to not see the discontinuties. How do you do that? Let’s have the application run a (X mod 1000) operation, where X is a random number. If the result is 0, let’s update the counter by 1000.
• #30: Another thing that was observed with the current design is that trying to keep track of all page views of the site resulted in very poor performance. That was seen for both MMAPv1 and WT. In MMAPv1, you get a lot of threads looking for the write lock. While with WT, you get a lot of write conflicts that need to be retried. One solution is to record "good enough" numbers. Well no one cares that the count is 100 millions or 100 millions and few. What is the tolerance level here? Let’s assume 1000. In this case, we will let the application update the page views by 1000, however only 1/1000th of the time. Statistically, we should get a result very close to the exact count, however doing only 1/1000th of the writes. If you make the parallel to a movie, we never see a movie as a continuous image, the movie is made by displaying 24 static images per second, however this is enough to our eyes to not see the discontinuities. How do you do that? Let’s have the application run a (X mod 1000) operation, where X is a random number. If the result is 0, let’s update the counter by 1000.
• #31: You can have a counter. Once you reach the count, you do the write. Or you can use a random generator and when you get a specific value, you do the write. As you guess, this simple pattern is also applicable to Relational databases. … it is just that NoSQL people have more tricks to handle performance bottlenecks.
• #35: Let's face it configuration management and database usually don't work well together. Database tend to keep the "latest" state of your data, while "CM" systems remember everything. Those of us who checked in stupid mistakes in Git, ClearCase, etc know CM systems have a very long memory. For this pattern, we are keeping track of the shape of the document. We are not addressing keeping track of the different contents of the document it self. This other case is solved by the Document Versioning pattern.
• #36: Instead of using a "version" field, we could discover the version number based on fields
• #37: - Few million references would not even fit into an embedded array. And if it did, you would not want to construct a query by passing a million values to the $in operator.
• #39: MongoDB has been around for many years. We wish we could have gone in the future few years ago and see how people use our database. That did not happen. However, now we know better how people are designing with MongoDB. We are able to identify patterns because we have seen a lot of models. Those are "plug-and-play" elements that let you go faster in your designs. Will we are on the subject of the future, I do believe MongoDB has a bright future. Most data that could be put in a Relational Database is already there. We are left with: Data this is "not square", meaning it does not fit well in square tables. Large datasets We believe the document model and the scalability of MongoDB are prime to store those data sets. Ensure you are ready for the future by becoming an expert on MongoDB and how to model for it We did use a fictional site, however all the patterns we used would also apply to "Internet of Things", "Single View", "E-commerce" solutions.
• #40: Let’s pause from our pattern list, and let’s examine a characteristic or aspect of some patterns.
• #42: We touch a little bit the bucket pattern when we looked at the outlier one. The bucket pattern let you group X sub-documents into one document. When the bucket is full, you create another one. Pre-allocation will be the case where you pre-create an array of cells to have the reads and writes easily access the elements. This is a very important pattern if you are using MMAPv1, as continuously growing an array can have a negative effect. With Wired Tiger it is not as crucial, however may make the code in the application simpler. As for Trees are commonly represented by either having one node per document, where you can list the parent, the children, the ancestors, or a combination of those
• #43: 10 years of experience, building schema with the document model You may not know about all the solutions, however we collected those over our 10 years of working with customers. If you follow these advices, good things will happen. Armed with those patterns, you may fell like a SuperHero, more powerful
• #44: My goal was to introduce you to patterns, however if you want more complete solutions to common problems, there are few good books out there. Let me point you to those 2: The Little Mongo DB Schema Design Book Paperback, by Christian Kvalheim MongoDB Applied Design Patterns, by Rick Copeland
• #45: I am leaving you with where you can find more information about schema design M320/Data Modeling is likely to be available around April 2018