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I've been reading the article The Vietnam of Computer Science by Ted Neward. Although there's much I don't understand, or have not fully grasped, I was struck by a thought while reading this paragraph.
The Partial-Object Problem and the Load-Time Paradox
It has long been known that network traversal, such as that done when making a traditional SQL request, takes a significant amount of time to process. ... This cost is clearly non-trivial, so as a result, developers look for ways to minimize this cost by optimizing the number of round trips and data retrieved.
In SQL, this optimization is achieved by carefully structuring the SQL request, making sure to retrieve only the columns and/or tables desired, rather than entire tables or sets of tables. For example, when constructing a traditional drill-down user interface, the developer presents a summary display of all the records from which the user can select one, and once selected, the developer then displays the complete set of data for that particular record. Given that we wish to do a drill-down of the Persons relational type described earlier, for example, the two queries to do so would be, in order (assuming the first one is selected):
SELECT id, first_name, last_name FROM person;
SELECT * FROM person WHERE id = 1;
In particular, take notice that only the data desired at each stage of the process is retrieved–in the first query, the necessary summary information and identifier (for the subsequent query, in case first and last name wouldn’t be sufficient to identify the person directly), and in the second, the remainder of the data to display. ... This notion of being able to return a part of a table (though still in relational form, which is important for reasons of closure, described above) is fundamental to the ability to optimize these queries this way–most queries will, in fact, only require a portion of the complete relation.
Skeleton Screens
Skeleton Screens are a relatively new UI design concept introduced in 2013 by Luke Wrobleski in this paper. It encourages avoiding spinners to indicate loading and to instead gradually build UI elements, during load time, which makes the user feel as if things are quickly progressing and progress is being made, even if it's, in fact, slower than than when using a traditional loading indicator.
Here is a Skeleton Screen in use in the Microsoft Teams chat app. It displays this while waiting for stored chat logs to arrive from the database.
Utilizing Skeleton Screen Style Data Loading as a Paradigm for Data Retrieval
While Neward's paper is focusing on Object Relational Mappers, I had this thought about structuring data retrieval.
The paragraph quoted above indicates a struggle with querying too much data at one time, increasing data retrieval times until all the indicated data is gathered. What if, similar to Neward's SQL example above, smaller chunks of data were retrieved, as necessary, and loaded piecemeal into the application?
This would necessitate a fundamental shift in database querying logic, I think. It would obviously be a ridiculous suggestion to have this implemented in application code. To have your everyday developer write a multi-layered retrieval scheme to retrieve a single object would be insane. Rather, there would need to be some sort of built-in method whereby the developer can indicate which properties are considered to be required (username, Id, permissions, roles, etc...) which must be retrieved fully before moving forward, and which properties are ancillary. After all, many app users navigate through an application faster than all the data can populate, if they are familiar with the application and just need to navigate to a certain page. All they need is enough data to be loaded, which is the point of this scheme.
On the database side, there would probably a series of smaller retrievals, rather than a large one. I know this is probably more expensive, although I'm not certain of the technicalities, and while database performance may suffer, application performance might improve, at least as perceived by the user.
Conclusion
Imagine pulling up your Instagram and having the first series of photos (the ones you can see) load, twice as quickly as before. Photos are likely your first priority. It wouldn't matter if your username, notification indicator, and profile picture takes a few extra seconds to populate, since you have already been fed your expected data and have begun consuming as a user. Contrast that with having structural data loaded first. Nobody cares about seeing their username or the company logo load. They want to see content.
I don't know if this is a terrible idea or something that has already been considered, but I'd love to get some feedback on it.
What do you think?
Is it possible, from a technical standpoint?
Whats the best practice to fetch details data in react app when you are dealing with multiple master details view?
For an example if you have
- /rest/departments api which returns list of departments
- /rest/departments/:departmentId/employees api to return all employees within department.
To fetch all departments i use:
componentDidMount() {
this.props.dispatch(fetchDepartments());
}
but then ill need a logic to fetch all employees per department. Would be a great idea to call employee action creator for each department in department reducer logic?
Dispatching employees actions in render method does not look like a good idea to me.
Surely it is a bad idea to call an employee action creator inside the department reducer, as reducers should be pure functions; you should do it in your fetchDepartments action creator.
Anyway, if you need to get all the employees for every department (not just the selected one), it is not ideal to make many API calls: if possible, I would ask to the backend developers to have an endpoint that returns the array of departments and, for each department, an embedded array of employees, if the numbers aren't too big of course...
Big old "It depends"
This is something that in the end, you will need to pick a way and see how it works out with your specific data and user needs. This somewhat deals with network issues as well, such as latency. In a very nicely networked environment, such as a top-3 insurance company I was a net admin for, you can achieve super low latency network calls. In such a case, multiple network requests would be significantly different than a homeowner internet based environment could be. Even then, you have to consider a wide range of possibilities. And you ALWAYS need to consider your end goals.
(Not to get too down in the technical aspects, but latency can fairly accurately be defined as "the time you are waiting for a network request to actually start sending data". A classic example of where this can be important is online first person shooter gaming. You click shoot, and the data is not transmitted as fast as you would like since the network is waiting to send the data, then you die. A classic example where bandwidth is more useful than latency is downloading or uploading large files. If you have to wait a second or two for the actual data to move, but when it moves you can download a GB in seconds, then oh well, I'll take it.)
Currently, I have our website making multiple calls to load dynamic menus and dynamic content. It is very small data. It is done in three separate calls. On the internet. It's "ok", but I would not say that it is "good". Since users are waiting for all of it to even start, I might as well throw it all in a single network call. Also, in case two calls go ok, then the third chokes a bit, the user may start to navigate, then more menus pop in and it is not ideal. This is why regardless, you have to think about your specific needs, and what range of possible use cases may likely apply. (I am currently re-writing the entire site anyways)
As a previous (in my opinion "good") answer stated, it probably makes sense to have the whole data set shot to you in one gulp. It appears to me this is an internal, or at least commercial app, with decent network and much more importantly, no risk of losing customers because your stuff did not load super fast.
That said, if things do not work out well with that, especially if you are talking large data sets, then consider a lazy loading architecture. For example, your user cannot get to an employee until they see the departments. So it may be ok, depending on your network and large data size, to load departments, and then after it returns initiate an asynchronous load of the employee data. The employee data is now being loaded while your user browses the department names.
A huge question you may want to clarify is whether or not any employee list data is rendered WITH the departments. In one of my cases, I have a work order system that I load after login, but lazy, and when it is loaded it throws a badge on the Work Order menu to show how many are outstanding. Since I do not have a lot of orders, it is basically a one second wait. No biggie. It is not like the user has to wait for it to load to begin work. If you wanted a badge per department, then it may get weird. You could, if you load by department, have multiple badges popping in randomly. In this case, it may cause user confusion, and it probably a good choice to load it in one large chunk. If the user has to wait anyways, it may produce one less call with a user asking "is it ok that it is doing this?". Especially with software for the workplace, it is more acceptable to have to wait for an initial load at the beginning of the work day.
To be clear, with all of these complications to consider, it is extremely important that you develop with as good of software coding practices as you are able. This way, you can code one solution, and if it does not meet your performance or user needs, it is not a nightmare to make a change. In a general case with small data, I would just load it in one big gulp to start, and if there are problems with load times complicate it from there. Complicating code from the beginning for no clearly needed reason is a good way to clutter your code up to the point of making it completely unwieldy to maintain.
On a third note, if you are dealing with enterprise size data sets, that is a whole different thing. Then you have to deal with pagination, and yes it gets a bit more complicated.
Regards,
DB
I'm not sure what fetchDepartments does exactly but I'd ensure the actual fetch request is executed from a Redux middleware. By doing it from middleware, you can fingerprint / cache / debounce all your requests and make a single one across the app no matter how many components request the thing.
In general, middleware is the best place to handle asynchronous side effects.
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At a new job, I've just been exposed to the concept of putting logic into SQL statements.
In MySQL, a dumb example would be like this:
SELECT
P.LastName, IF(P.LastName='Baldwin','Michael','Bruce') AS FirstName
FROM
University.PhilosophyProfessors P
// This is like a ternary operator; if the condition is true, it returns
// the first value; else the second value. So if a professor's last name
// is 'Baldwin', we will get their first name as "Michael"; otherwise, "Bruce"**
For a more realistic example, maybe you're deciding whether a salesperson qualifies for a bonus. You could grab various sales numbers and do some calculations in your SQL query, and return true / false as a column value called "qualifies."
Previously, I would have gotten all the sales data back from the query, then done the calculation in my application code.
To me, this seems better, because if necessary, I can walk through the application logic step-by-step with a debugger, but whatever the database is doing is a black box to me. But I'm a junior developer, so I don't know what's normal.
What are the pros and cons of having the database server do some of your calculations / logic?
**Code example based on Monty Python sketch.
This way SQL becomes part of your domain model. It's one more (and not necessarily obvious) place where domain knowledge is implemented. Such leaks result in tighter coupling between business logic / application code and database, what usually is a bad idea.
One exception is views, report queries etc. But these usually are so isolated that it's obvious what role they play.
One of the most persuasive reasons to push logic out to the database is to minimise traffic. In the example given, there is little gain, since you are fetching the same amount of data whether the logic is in the query or in your app.
If you want to fetch only users with a first name of Michael, then it makes more sense to implement the logic on the server. Actually, in this simple example, it doesn't make much difference, since you could specify users who's lastname is Baldwin. But consider a more interesting problem, whereby you give each user a "popularity" score based on how common their first and last names are, and you want to fetch the 10 most "popular" users. Calculating "popularity" in the app would mean that you have to fetch every single user before ranking, sorting and choosing them locally. Calculating it on the server means you can fetch just 10 rows across the wire.
There aren't a lot of absolute pros and cons to this argument, so the answer is 'it depends.' Some scenarios with different conditions that affect this decision might be:
Client-server app
One example of a place where it might be appropriate to do this is an older 4GL or rich client application where all database operations were done through stored procedure based update, insert, delete sprocs. In this case the gist of the architecture was to have the sprocs act as the main interface for the database and all business logic relating to particular entities lived in the one place.
This type of architecture is somewhat unfashionable these days but at one point it was considered to be the best way to do it. Many VB, Oracle Forms, Informix 4GL and other client-server apps of the era were done like this and it actually works fairly well.
It's not without its drawbacks, however - SQL is not particularly good at abstraction, so it's quite easy to wind up with fairly obtuse SQL code that presents a maintenance issue through being hard to understand and not as modular as one might like.
Is it still relevant today? Quite often a rich client is the right platform for an application and there's certainly plenty of new development going on with Winforms and Swing. We do have good open-source ORMs today where a 1995 vintage Oracle Forms app might not have had the option of using this type of technology. However, the decision to use an ORM is certainly not a black and white one - Fowler's Patterns of Enterprise Application Architecture does quite a good job of running through a range of data access strategies and discussing their relative merits.
Three tier app with rich object model
This type of app takes the opposite approach, and places all of the business logic in the middle tier model object layer with a relatively thin database layer (or perhaps an off-the-shelf mechanism like an ORM). In this case you are attempting to place all the application logic in the middle-tier. The data access layer has relatively little intelligence, except perhaps for a handful of stored procedured needed to get around limits of an ORM.
In this case, SQL based business logic is kept to a minimum as the main repository of application logic is the middle-tier.
Overhight batch processes
If you have to do a periodic run to pick out records that match some complex criteria and do something with them it may be appropriate to implement this as a stored procedure. For something that may have to go over a significant portion of a decent sized database a sproc based approch is probably going to be the only reasonably performant way to do this sort of thing.
In this case SQL may well be the appropriate way to do this, although traditional 3GLs (particularly COBOL) were designed specifically for this type of processing. In really high volume environments (particularly mainframes) doing this type of processing with flat or VSAM files outside a database may be the fastest way to do it. In addition, some jobs may be inherently record-oriented and procedural, or may be much more transparent and maintanable if implemented in this way.
To paraphrase Ed Post, 'you can write COBOL in any language' - although you might not want to. If you want to keep it in the database, use SQL, but it's certainly not the only game in town.
Reporting
The nature of reporting tools tends to dictate the means of encoding business logic. Most are designed to work with SQL based data sources so the nature of the tool forces the choice on you.
Other domains
Some applications like ETL processing may be a good fit for SQL. ETL tools start to get unwiedly if the transformation gets too complex, so you may want to go for a stored procedure based architecture. Mixing Queries and transformations across extraction, ETL processing and stored-proc based processing can lead to a transformation process that is hard to test and troubleshoot.
Where you have a significant portion of your logic in sprocs it may be better to put all of the logic in this as it gives you a relatively homogeneous and modular code base. In fact I have it on fairly good authority that around half of all data warehouse projects in the banking and insurance sectors are done this way as an explicit design decision - for precisely this reason.
Many times the answer to this type of question is going to depend a great deal on deployment approach. Where it makes the most sense to place your logic depends on what you'll need to be able to get access to when making changes.
In the case of web applications that aren't compiled, it can be easier to deal with changes to a page or file than it is to work with queries (depending on query complexity, programming backgrounds / expertise, etc). In these kinds of situations, logic in the scripting language is typically ok and make make it easier to revise later.
In the case of desktop applications that require more effort to modify, placing this kind of logic in the database where it can be adjusted without requiring a recompilation of the application may benefit you. If there was a decision made that people used to qualify for bonuses at 20k, but now must make 25k, it'd be much easier to adjust that on the SQL Server than to recompile your accounting application for all of your users, for example.
I'm a strong advocate of putting as much logic as possible directly into the database. That means incorporating it in views and stored procedures. I believe that most follows the DRY principle.
For example, consider a table with FirstName and LastName columns, and an application that frequently makes use of a FullName field. You have three choices:
Query first and last name and compute the full name in application code.
Query first, last, and (first || last) in your application's SQL whenever you query the table.
Define a view CustomerExt that includes the first and last columns, and a computed full name column and then query against that view, rather than the customer table.
I believe option 3 is clearly correct. Consider the addition of a MiddleInitial field to the table and the full name computation. Using option 3, you simply need to replace the view and every application across your company will instantly use the new format for FullName. The view still makes the base columns available for those instances in which you need to do some special formatting, but for the standard instance everything works "automatically".
That's a simple case, but the principle is the same for more complex situations. Perform application- or company-wide data logic directly in the database and you do not need to concern yourself with keeping different applications up to date.
The answer depends on your expertise and your familiarity with the technologies involved. Also, if you're a technical manager, it depends on your analysis of the skills of the people working on your team and whom you intend on hiring / keeping on staff to support, extend and maintain the application in future.
If you are not literate and proficient in the database , (as you are not) then stick with doing it in code. If otoh, you are literate and proficient in database coding (as you should be), then there is nothing wrong (and a lot right) abput doing it in the database.
Two other considerations that might influence your decision are whether the logic is of such a complex nature that doing it in database code would be inordinately more complex or more abstract than in code, and second, if the process involved requires data from outside the database (from some other source) In either of these scenarios I would consider moving the logic to a code module.
The fact that you can step through the code in your IDE more easily is really the only advantage to your post-processing solution. Doing the logic in the database server reduces the sizes of result sets, often drastically, which leads to less network traffic. It also allows the query optimizer to get a much better picture of what you really want done, again often allowing better performance.
Therefore I would nearly always recommend SQL logic. If you treat a database as a mere dumb store, it will return the favor by behaving dumb, and depending on the situation, that can absolutely kill your performance - if not today, possibly next year when things have taken off...
That particular first example is a bad idea. Per-row functions do not scale well as the table gets bigger. In fact, a (likely) better way to do it would be to index LastName and use something like:
SELECT P.LastName, 'Michael' AS FirstName
FROM University.PhilosophyProfessors P
WHERE P.LastName = 'Baldwin'
UNION ALL SELECT P.LastName, 'Bruce' AS FirstName
FROM University.PhilosophyProfessors P
WHERE P.LastName <> 'Baldwin'
On databases where data are read more often than written (and that's most of them), these sorts of calculations should be done at write time such as using an insert/update trigger to populate a real FirstName field.
Databases should be used for storing and retrieving data, not doing massive non-databasey calculations that will slow down everything.
One big pro: a query may be all you can work with. Reports have been mentioned: many reporting tools or reporting plugins to existing programs only allow users to make their own queries (the results of which they will display).
If you cannot alter the code (because it isn't yours), you may yet be able to alter a query. And in some cases (data migration), you'll be writing queries to do migration as well.
I like to distinguish data vs business rules, and push the data rules into the stored procs as much as possible. There is not always a hard and fast distinction between the two, but in your example of calculating sales bonuses, the formula itself might be a business rule but the work of gathering and aggregating the various figures used in the formula is a data rule.
Sometimes, though, it depends on the deployment model and change control procedures. If the sales formula changes frequently and deployment of the business layer code is cumbersome, then tweaking just one function/stored proc in the database would be a great solution.
I'm a big fan of elegant database queries because the code is closer to the data and SQL works very well. But such queries, whether they're text in you app, generated by an OR mapper or stored in the database are harder to test, especially in the cloud, because you need a database to run against.
Database is exactly what it's called. DATABASE.
You should not mix the business logic with data layer.
Keep it separate as any close coupling between data and business makes impossible to follow best standards in programming.
I was working recently on a project where all logic was in MS SQL. Horrible idea, that back-fired after few years (energy company), no easy way to scale-out, no easy way to follow up CI/CD, Agile or code repos. Very difficult to co-work, very slow and very inefficient.
Company basically was reaching hardware limits in order to make it work (they've spent £100k on SSD SAN), while you could reach the same performance with C# for business and keep the database for data, with perhaps 3-4 cheap servers, that could easily scale-out.
Horrible, horrible idea. Guess what ? Company went under, as one time SQL server has reached it's potential (sometimes some queries were running for hours (very well written, but SQL is not for business logic. End of story)) when one time failed to bill all DD customers and basically didn't took the monthly payment that they needed to survive till next month (millions of pounds).
I'd like to hear some opinions or discussion on a matter of database design. Me and my colleagues are developing a complex application in finance industry that is being installed in several countries.
Our contractors wanted us to keep a single application for all the countries so we naturally face the difficulties with different workflows in every one of them and try to make the application adjustable to satisfy various needs.
The issue I've encountered today was a request from the head of the IT department from the contractors side that we keep the database model in terms of tables and columns they consist of.
For examlpe, we got a table with different risks and we needed to add a flag column IsSomething (BIT NOT NULL ...). It fully qualifies to exists within the risk table according to the third normal form, no transitive dependency to the key, a non key value ...
BUT, the guy said that he wants to keep the tables as they are so we had to make a new table "riskinfo" and link the data 1:1 to the new column.
What is your opinion ?
We add columns to our tables that are referenced by a variety of apps all the time.
So long as the applications specifically reference the columns they want to use and you make sure the new fields are either nullable or have a sensible default defined so it doesn't interfere with inserts I don't see any real problem.
That said, if an app does a select * then proceeds to reference the columns by index rather than name you could produce issues in existing code. Personally I have confidence that nothing referencing our database does this because of our coding conventions (That and I suspect the code review process would lynch someone who tried it :P), but if you're not certain then there is at least some small risk to such a change.
In your actual scenario I'd go back to the contractor and give your reasons you don't think the change will cause any problems and ask the rationale behind their choice. Maybe they have some application-specific wisdom behind their suggestion, maybe just paranoia from dealing with other companies that change the database structure in ways that aren't backwards-compatible, or maybe it's just a policy at their company that got rubber-stamped long ago and nobody's challenged. Till you ask you never know.
This question is indeed subjective like what Binary Worrier commented. I do not have an answer nor any suggestion. Just sharing my 2 cents.
Do you know the rationale for those decisions? Sometimes good designs are compromised for the sake of not breaking currently working applications or simply for the fact that too much has been done based on the previous one. It could also be many other non-technical reasons.
Very often, the programming community is unreasonably concerned about the ripple effect that results from redefining tables. Usually, this is a result of failure to understand data independence, and failure to guard the data independence of their operations on the data. Occasionally, the original database designer is at fault.
Most object oriented programmers understand encapsulation better than I do. But these same experts typically don't understand squat about data independence. And anyone who has learned how to operate on an SQL database, but never learned the concept of data independence is dangerously ignorant. The superficial aspects of data independence can be learned in about five minutes. But to really learn it takes time and effort.
Other responders have mentioned queries that use "select *". A select with a wildcard is more data dependent than the same select that lists the names of all the columns in the table. This is just one example among dozens.
The thing is, both data independence and encapsulation pursue the same goal: containing the unintended consequences of a change in the model.
Here's how to keep your IT chief happy. Define a new table with a new name that contains all the columns from the old table, and also all the additional columns that are now necessary. Create a view, with the same name as the old table, that contains precisely the same columns, and in the same order, that the old table had. Typically, this view will show all the rows in the old table, and the old PK will still guarantee uniqueness.
Once in a while, this will fail to meet all of the IT chief's needs. And if the IT chief is really saying "I don't understand databases; so don't change anything" then you are up the creek until the IT chief changes or gets changed.
I am looking to design a database for a website where users will be able to gain points (reputation) for performing certain activities and am struggling with the database design.
I am planning to keep records of the things a user does so they may have 25 points for an item they have submitted, 1 point each for 30 comments they have made and another 10 bonus points for being awesome!
Clearly all the data will be there, but it seems like a lot or querying to get the total score for each user which I would like to display next to their username (in the form of a level). For example, a query to the submitted items table to get the scores for each item from that user, a query to the comments table etc. If all this needs to be done for every user mentioned on a page.... LOTS of queries!
I had considered keeping a score in the user table, which would seem a lot quicker to look up, but I've had it drummed into me that storing data that can be calculated from other data is BAD!
I've seen a lot of sites that do similar things (even stack overflow does similar) so I figure there must be a "best practice" to follow. Can anyone suggest what it may be?
Any suggestions or comments would be great. Thanks!
I think that this is definitely a great question. I've had to build systems that have similar behavior to this--especially when the table with the scores in it is accessed pretty often (like in your scenario). Here's my suggestion to you:
First, create some tables like the following (I'm using SQL Server best practices, but name them however you see fit):
UserAccount UserAchievement
-Guid (PK) -Guid (PK)
-FirstName -UserAccountGuid (FK)
-LastName -Name
-EmailAddress -Score
Once you've done this, go ahead and create a view that looks something like the following (no, I haven't verified this SQL, but it should be a good start):
SELECT [UserAccount].[FirstName] AS FirstName,
[UserAccount].[LastName] AS LastName,
SUM([UserAchievement].[Score]) AS TotalPoints
FROM [UserAccount]
INNER JOIN [UserAchievement]
ON [UserAccount].[Guid] = [UserAchievement].[UserAccountGuid]
GROUP BY [UserAccount].[FirstName],
[UserAccount].[LastName]
ORDER BY [UserAccount].[LastName] ASC
I know you've mentioned some concern about performance and a lot of queries, but if you build out a view like this, you won't ever need more than one. I recommend not making this a materialized view; instead, just index your tables so that the lookups that you need (essentially, UserAccountGuid) will enable fast summation across the table.
I will add one more point--if your UserAccount table gets huge, you may consider a slightly more intelligent query that would incorporate the names of the accounts you need to get roll-ups for. This will make it possible not to return huge data sets to your web site when you're only showing, you know, 3-10 users' information on the page. I'd have to think a bit more about how to do this elegantly, but I'd suggest staying away from "IN" statements since this will invoke a linear search of the table.
For very high read/write ratios, denormalizing is a very valid option. You can use an indexed view and the data will be kept in sync declaratively (so you never have to worry about there being bad score data). The downside is that it IS kept in sync.. so the updates to the store total are a synchronous aspect of committing the score action. This would normally be quite fast, but it is a design decision. If you denormalize yourself, you can choose if you want to have some kind of delayed update system.
Personally I would go with an indexed view for starting, and then later you can replace it fairly seamlessly with a concrete table if your needs dictate.
In the past we've always used some sort of nightly or perodic cron job to calculate the current score and save it in the database - sort of like a persistent view of the SUM on the activities table. Like most "best practices" they are simply guidelines and it's often better and more practical to deviate from a specific hard nosed practice on very specific areas.
Plus it's not really all that much of a deviation if you use the cron job as it's better viewed as a cache stored in the database.
If you have a separate scores table, you could update it each time an item is submitted or a comment is posted by a user. You could do this using a trigger or within the sites code.
The user scores would be updated continuously, and could be quickly queried for display.