I am working on a group project and we are having a discussion about whether to calculate data that we want from an existing database and store it in a new database to query later, or calculate the data from the existing database every time we need to use it. I was wondering what the pros and cons may be for either implementation. Is there any advice you could give?
Edit: Here is more elaborate explanation. We have a large database that has a lot of information being submitted to it daily. We are building a system to track certain points of data. For example, we are getting the count of how many times a user does something that is entered in the database. Using this example (are actual idea is a bit more complex), we are discussing to methods of getting the count of actions per users. The first method is to create a database that stores the users and their action count, and query this database every time we need the action count. The second method would be to query the large database and count the actions per user every time we need to use it. I hope this explanation helps explain. Thoughts?
Edit 2: Two more things that may be useful to point out is 1: I only have read access to the large database and 2: My ultimate goal is to display this information on a web page for end users.
This is a generic question about optimization by caching. The following was my answer to essentially the same question. Even though that question provided a bunch of different details, none of them were specific enough to merit a non-generic answer either:
The more you want to calculate at query time, the more you want views,
calculated columns and stored or user routines. The more you want to
calculate at normalized base update time, the more you want cascades
and triggers. The more you want to calculate at some other (scheduled
or ad hoc) time, the more you use snapshots aka materialized views and
updated denormalized bases. You can combine these. Any time the
database is accessed it can be enabled by and restricted by stored
routines or other api.
Until you can show that they are in adequate, views and calculated
columns are the simplest.
The whole idea of a DBMS is to store a representation of your
application state as the database (which normalization reduces the
redundancy of) and then you query and let the DBMS implement and
optimize calculation of the answer. You haven't presented a reason for
not doing that in the most straightforward way possible.
[sic]
Always make sure an application is reading its own personal ("external") database that is a view of "the" ("conceptual") database so that when you change the implemention of the former (plus the rest of some combined interfact) by the latter (plus the rest of some compbined mechanisms) your applications do not have to change ("logical independence"). Here the applications are your users' and your trackers'.
Ultimately you must instrument and guestimate. When it is worth it you start caching. Preferably as much as possible in terms of high-level notions like views and snapshots and as little as possible in non-DBMS code. One of he benefits of the relational model is that it is easy to describe a strightforward relational interface in terms of another straightforward relational interface. You protect your applications from change by offering an interface that hides secrets of implementation or which of a family of interfaces is the current one.
Related
I'm trying to design a database schema for Djabgo rest framework web application.
At some point, I have two choces:
1- Choose a schema in which in one or several apies, I have to get a queryset from database and iterate and order it with python. (For example, I can store some datas in an array-data-typed column, get them from database and sort them with python.)
2- store the data in another table and insert a kind of big number of rows with each insert. This way, I can get the data in my favorite format in much less lines with orm codes.
I tried some basic tests and benchmarking to see which way is faster, and letting database handle more of the job (second way) didn't let me down. But I don't have the means of setting a more real situatuin and here's the question:
Is it still a good idea to let database handle the job when it also has to handle hundreds of requests from other apies and clients each second?
Is database (and orm) usually faster and more reliable than backend?
As a general rule, you want to let the database do work when the work is appropriate for the database. Sorting result sets would be in that category.
Keep in mind:
The database is running on a server, often on a distributed system and so it has access to more resources.
Databases are designed to handle large data, so they are not limited by the memory in a single thread.
When this question comes up, often more data needs to be passed back to the application than is strictly needed. Consider a problem such as getting the top 10 of something.
Mixing processing in the application and the database often requires multiple queries and passing data back and forth, which is expensive.
(And there are no doubt other considerations.)
There are some situations where it might be more efficient or convenient to do work in the application. A common example is formatting result sets for the application -- say turning 1234.56 into $1,234.56. Other examples would be when the application language has capabilities that are not directly in SQL or are hard to implement in SQL.
I know this is a topic that's been addressed ad nauseam but I also know there are people who enjoy opining about databases so I figured I'd just go ahead and ask the question again.
I'm building out a web application that on a very basic level displays a list of objects that meet a user-defined search criteria. The primary function of the application will be to provide an interface by which a user can perform realtime faceted searches on a large number of object properties, including ranges of data, location data, and probably related data.
Of course there will be ancillary information too: user accounts, lookup tables etc.
My background is entirely in relational database development, primarily SQL Server with a little bit of MySQL. However, I'm intrigued by the possible applicability of an object-relational approach or even a full-on document database. Without the experience of working in those paradigms I'm not sure what I might be getting myself into.
Here are some further considerations that may affect the decision:
The schema will likely evolve considerably over time as more properties and search options are added, creating the typical versioning/deployment challenges. This is the primary reason why I would consider a document database.
The application itself will likely be written in Node/Express with an Angular or React front-end using Typescript and so the code will be interacting with data in json format. In other words, regardless of what comes back from the db server, we want json on the code level. (Another case for a doc database.)
There is the potential for a large amount of search parameters and a large amount of data, so indexing will be key and performance will be a huge potential gotcha. This would seem to me to be a strong case against a document db.
A potential use case would involve a user adjusting a slider control (let's say it controls high and low price parameters or a distance range). The selected parameters would then be packaged as a json object and sent to a search controller, which would then pass these parameters to the db server on change and expect a list of objects in return. In other words, the user would generally not be pushing a button to refine search criteria. The search update would happen each time they change a parameter.
I don't know the extent to which this a thing or not, but it would also be great if there were some way to leverage technology that could cache search results and then search within those results if the search were narrowed, thus performing a second search only on the smaller subset of the first search rather than the entire universe of available objects.
I guess while I'm at it I should ask about ORMs. Also something I'm generally not some experienced with (I've used Entity Framework a bit) but wondering if I should expand my horizons.
Thanks and I look forward to your opinions!
I think that your requirement of "There is the potential for a large amount of search parameters and a large amount of data, so indexing will be key and performance will be a huge potential gotcha" makes a strong case for using a relational database to store the data.
Leveraging an ORM that can support data in JSON format would seem to be ideal in your use case. Schema evolution for a system in production would sure be a challenge (not unsurmountable though) but it would be nice to use an ORM product that can at least easily support schema evolution during the development stage when things are more likely to change and evolve rapidly.
Given the kind of queries you would typically be issuing (e.g., adjusting a slider control), an ORM that supports prepared statements that can have range criteria would be more efficient.
Also, given your need to "perform realtime faceted searches on a large number of object properties, including ranges of data, location data, and probably related data", an ORM product that can easily support one-to-one, one-to-many, and many-to-many relationships and path-expressions in search criteria should simplify your development process.
I am building a system that allows front-end users to define their own business objects. Defining a business object involves creating data fields for that business object and then relating it to other business objects in the system - fairly straight forward stuff. My question is, what is the most efficient storage strategy?
The requirements are:
Must support business objects with potentially 100+ fields (of all common data types)
The system will eventually support hundreds of thousands of business object instances
Business objects sometimes display data and aggregates from their relationships with other business objects
Users must be able to search for business objects by their data fields (and fields from related business objects)
The two possible solutions I can envisage are:
Have a dynamic schema such that when a new business object type is created a new table is created for storing instances of that object. The object's fields become columns in the storage table.
Have a fixed schema where instance data fields are stored as rows in basically a big long table.
I can see pros and cons to both approaches:
the dynamic schema allows me to index search columns
the dynamic tables are potentially limited in width by the max column size
dynamic schemas rule out / cause issues with replication
the static schema means less or even no dynamic sql generation
my guess is the static schema may perform like a dog when it comes to searching across 100,000+ objects
So what is the best soution? Is there another approach I haven't thought of?
Edit: The requirement I have been given is to build a generic system capable of supporting front-end user defined business objects. There will of course be restrictions on how these objects can be constructed and related, but the requirement itself is not up for negotiation.
My client is a service provider and requires a degree of flexibility in servicing their own clients, hence the need to create business objects.
I think your problem matches very well to a graph database like Neo4j, as it's built for the requested kind of flexibility from the beginning. It stores data as nodes and relationships/edges, and both nodes and relationships can hold arbitrary properties (in a key/value fashion). One important difference to a RDBMS is that a graph database won't need to lookup the relationships in a big long table (like in your fixed schema solution), so there should be a significant performance gain there. You can find out about language bindings for Neo4j in the wiki and read what others say about it in this stackoverflow thread. Disclaimer: I'm part of the Neo4j team.
Without much understanding of your situation...
Instead of writing a general purpose one-size-fits-all business objects system (which is the holy grail for Oracle, Microsoft, SAS, etc.), why not do it the typical way, where the requirements are gathered, and a developer designs and implements the users' business objects in an effective manner?
If your users are typical, they will create a monster, which will end up running slow, and they will hate it. Most users will view the data as an Excel sheet, and not understand relationships like: parent/child. As a result there will be some crazy objects built, and impossible-to-solve reports. You'll be forced to create scripts to manually convert many old objects to better and properly defined ones, etc...
Your requirements sound a little bit like an associative database with a front end to compose and edit entities.
I agree with KM above, unless you have a very compelling reason not to, you would be better off using a traditional approach. There are a lot of development tools and practices that allow you to build a robust and scalable system. Otherwise you will have to implement much of this yourself.
I don't know the best way to do this, because it sounds like something that has already been implemented by others. If I were asked to implement this feature, I would recommend buying a wheel instead of reinventing it.
Perhaps there are reasons you have to invent your own? If so, then you should add those reasons to the requirements you listed.
If you absolutely must be this generic, I still recommend buying a system that has been architected for this requirement. Not just the storage requirements, which are the least of the problems your customer will have; but also: how do you keep the customer from screwing up totally when given this much freedom. Some of the commercial systems already meet this challenge without going out of business because of customers messing up.
If you still need to do this on your own, then I suggest that your requirements (or perhaps those of another vendor?) must include: allow the customer to get it right, and help keep the customer from getting it wrong. You'll need some sort of UI to allow the customer to define these business objects, and the UI should validate the model that the customer builds.
I recommend a UI that works at a conceptual level. As an example, see NORMA, a Visual Studio add-in for Object-Role Modeling (the "other" ORM). Consider it as a example only, if your end users cannot afford a Visual Studio Standard license. Otherwise, you'll find that it is extensible, already produces many types of artifact (from SQL in various dialects to code), and will validate the model to see that it makes sense. End users would also be able to enter sample data that they believe should be valid, and the system will validate the data against the model.
If your customers are producing sensible (if dynamic) business objects, then the question of storage will be much simpler.
Have you thought about an XML based solution? The requirements suggested to me "Build a system that allows users to dynamically generate an XML Schema and work with XML documents based on that schema." I don't know enough about storing and querying XML documents to comment on your original question.
Another possibility might be to leverage NHibernate's ability to generate database schemas. If you can dynamically generate business objects, then you can generate XML mappings or Fluent mappings and use that to generate a normalized database schema.
Every user that I have ever talked to has always wanted "everything" in their project. Part of the job of gathering requirements is to guide the user, not just write down everything they say.
Your only hope is to build several template objects, that they can add properties to, you could code your application to handle each type of these objects, but allow the user to still slightly modify each as necessary.
You need to inform the user upfront of the major flaws this type of design has. This will help you in the end, when it runs slow, or if they screw up and need help fixing something. I'd put this in writing.
How many possible objects would they really need? Perhaps you could set these up using your system first. I have developed several very customizable systems over the years and when the user is sitting at an empty screen, it is like a deer in the headlights.
In any event, good luck.
I have a project involving a web voting system. The current values and related data is stored in several tables. Historical data will be an important aspect of this project so I've also created Audit Tables to which current data will be moved to on a regular basis.
I find this strategy highly inefficient. Even if I only archive data on a daily basis, the number of rows will become huge even if only 1 or 2 users make updates on a given day.
The next alternative I can think of is only storing entries that have changed. This will mean having to build logic to automatically create a view of a given day. This means less stored rows, but considerable complexity.
My final idea is a bit less conventional. Since the historical data will be for reporting purposes, there's no need for web users to have quick access. I'm thinking that my db could have no historical data in it. DB only represents current state. Then, daily, the entire db could be loaded into objects (number of users/data is relatively low) and then serialized to something like XML or JSON. These files could be diffed with the previous day and stored. In fact, SVN could do this for me. When I want the data for a given past day, the system has to retrieve the version for that day and deserialize into objects. This is obviously a costly operation but performance is not so much a concern here. I'm considering using LINQ for this which I think would simplify things. The serialization procedure would have to be pretty organized for the diff to work well.
Which approach would you take?
Thanks
If you're basically wondering how revisions of data are stored in relational databases, then I would look into how wikis do it.
Wikis are all about keeping detailed revision history. They use simple relational databases for storage.
Consider Wikipedia's database schema.
All you've told us about your system is that it involves votes. As long as you store timestamps for when votes were cast you should be able to generate a report describing the vote state tally at any point in time... no?
For example, say I have a system that tallies favorite features (eyes, smile, butt, ...). If I want to know how many votes there were for a particular feature as of a particular date, then I would simply tally all the votes for the feature with a timestamp smaller or equal to that date.
If you want to have a history of other things, then you would follow a similar approach.
I think this is the way it is done.
Have you considered using a real version control system rather than trying to shoehorn a database in its place? I myself am quite partial to git, but there are many options. They all have good support for differences between versions, and they tend to be well optimised for this kind of workload.
I am in the early stages of developing a database-driven system and the largest part of the system revolves around an inheritance type of relationship. There is a parent entity with about 10 columns and there will be about 10 child entities inheriting from the parent. Each child entity will have about 10 columns. I thought it made sense to give the parent entity its own table and give each of the children their own tables - a table-per-subclass structure.
Today, my users requested to see the structure of the system I created. They balked at the idea of the table-per-subclass structure. They would prefer one big ~100 column table because it would be easier for them to perform their own custom queries.
Should I consider denormalizing the database for the sake of the users?
Absolutely not. You can always create a view later to show them what they want to see.
They are effectively asking for a report.
You could give them access to a view containing all the fields they require... that way you don't mess up your data model.
No. Structure the data properly and if the users need the a denormalized view of the data create it as a VIEW in the database.
Alternatively, consider that perhaps an RDBMS is not the appropriate storage tool for this project.
They are the users and not the programmers of the system for a reason. Provide a separate interface for their queries. Power users like this can both be helpful and a pain to deal with. Just explain you need the database designed a certain way so you can do your job, period. Once that is accomplished you and provide other means to make querying easier.
What do they know!? You could argue that users shouldn't even be having direct access to a database in the first place.
Doing that leaves you open to massive performance issues, just because a couple of users are running ridiculous queries.
How about if you created a VIEW in the format your users wanted while still maintaining a properly normalized table?
Aside from a lot of the technical reasons for or against your users' proposition, you need to be on same page in communicating the consequences of various scenarious and (more importantly) the costs of those consequences. If the users are your clients and they are paying you to do a job, explain that their awful "proposed" ideas may cost them more money in development time, additional hardware resources, etc.
Hopefully you can explain it in such a way that shows your expertise and why your idea is a much better value to your users in the long run.
As everyone more or less mentioned, that way lies madness, and you can always build a view.
If you just can't get them to come around on this point, consider showing them this thread and the number of pros who weighed in saying that the users are meddling with things that they don't fully understand, and the impact will be an undermined foundation.
A big part of the developer's craft is the feel for what won't work out long term, and the rules of normalization are almost canonical in that respect. There are situations where you need to denormalize (data warehouses, etc) but this doesn't sound like one of them!
It also sounds as though you may have a particularly troubling brand of user on your hand -- the amatuer developer who thinks they could do your job better themselves if only they had the time. This may or may not help, but I've found that those types respond well to presentation -- a few times now I've found that if I dress sharp and show a little bit of force in my personality, it helps them feel like I'm an expert and prevents a bunch of problems before they start.
I would strongly recommend coming up with an answer that doesn't involve someone running direct reports against your database. The moment that happens, your DB structure is set in stone and you can basically consider it legacy.
A view is a good start, but later on you'll probably want to structure this as an export, to decouple further. Of course, then you'll encounter someone who wants "real time" data. Proper business analysis usually reveals this to be unnecessary. Actual real time requirements are not best handled through reporting systems.
Just to be clear: I'd personally favour the table per subclass approach, but I don't think it's actually as big an issue as the direct reporting off transaction tables is going to be.
I would opt for a view (as others have suggested) or an inline table-valued function (the benefits of this is you require parameters - like an date range or a customer account - which can help to stop users from querying without any limits on the problem space) first. An inline TVF is really a parametrized view and is far closer to a view in terms of how the engine treats them than it is to a multi-statement table valued function or a scalar function, which can perform incredibly poorly.
However, in some cases, this can impact production performance if the view is complex or intensive. With poorly written ad hoc user queries, it can also cause locks to persist longer or be escalated further than they would on a better built query. It is also possible for users to misinterpret an E-R data model and produce multiplied numbers in cases where there are many-to-one or many-to-many relationships. The next option might be to materialize these views with indexes or make tables and keep them updated, which gets us closer to my next option...
So, given those drawbacks of the view option and already thinking of mitigating it by starting to make copies of data, the next option I would consider is to have a separate read-only (for these users) version of the data which is structured differently. Typically, I would first look at a Kimball-style star schema. You do not need to have a full-fledged time-consistent data warehouse. Of course, that's an option, but you could simply keep a reporting model up to date with data. Star-schemas are a special form of denormalization and are particularly good for numerical reporting, and a given star should not be able to be abused by users accidentally. You can keep the star up to date in a number of ways, including triggers, scheduled jobs, etc. They can be very fast for reporting needs and run on the same production installation - perhaps on a separate instance if not just a separate database.
Although such a solution may require you to effectively more than double your storage requirements, when compared with other practices it might be a really good option if you understand your data well and don't mind having two models - one for transactions and one for analysis (note that you will already start to have this logical separation anyway with the use of a the simplest first option of view).
Some architects will often double their servers and use the SAME model with some kind of replication in order to provide a reporting server which is indexed more heavily or differently. Such a second server doesn't impact production transactions with reporting requirements and can be kept up to date fairly easily. There will only be one model, but of course, this has the same usability problems with allowing users ad hoc access to the underlying model only, without the performance affects, since they get their own playground.
There are a lot of ways to skin these cats. Good luck.
The customer is always right. However, the customer is likely to back down when you convert their requirement into dollars and cents. A 100 column table will require extra dev time to write the code that does what the database would do automatically with the proper implementation. Further, their support costs will be higher since more code means more problems and lower ease of debugging.
I'm going to play devil's advocate here and say that both solutions sound like poor approximations of the actual data. There's a reason that object-oriented programming languages don't tend to be implemented with either of these data models, and it's not because Codd's 1970 ideas about relations were the ideal system for storing and querying object-oriented data structures. :-)
Remember that SQL was originally designed as a user interface language (that's why it looks vaguely like English and not at all like other languages of that era: Algol, C, APL, Prolog). The only reasons I've heard for not exposing a SQL database to users today are security (they could take down the server!) and usability (who wants to write SQL when you can clicky clicky?), but if it's their server and they want to, then why not let them?
Given that "the largest part of the system revolves around an inheritance type of relationship", then I'd seriously consider a database that lets me represent that natively, either Postgres (if SQL is important) or a native object database (which are awesome to work with, if you don't need SQL compatibility).
Finally, remember that every engineering decision is a tradeoff. By "sticking to your guns" (as somebody else proposed), you're implicitly saying the value of your users' desires are zero. Don't ask SO for a correct answer to this, because we don't know what your users want to do with your data (or even what your data is, or who your users are). Go tell them why you want a many-tables solution, and then work out a solution with them that's acceptable to both of you.
You've implemented Class Table Inheritance and they're asking for Single Table Inheritance. Both designs are valid in certain situations.
You might want to get a copy of Martin Fowler's Patterns of Enterprise Application Architecture to read more about the advantages and disadvantages of each design. That book is a classic reference to have on your bookshelf, in any case.