You might as well timestamp it (2021)(changelog.com)
changelog.com
You might as well timestamp it (2021)
https://changelog.com/posts/you-might-as-well-timestamp-it
61 comments
I can't see how this is simpler or more effective than having 5 state fields, each with a timestamp. I guess it would make writing the query slightly easier, but you can put your clause for any given state into a builder function anyway.
What's the motivation for having an enum then holding in some other system a history of when that enum changed?
What's the motivation for having an enum then holding in some other system a history of when that enum changed?
If you're gonna use an enum for a true/false field, you might as well timestamp it. If you need enums, you changed the game.
The timestamp doesn't give you enough information to answer the questions it's typically going to be used for. It tells you "when", but not "who", and "what else at the same time".
A change history is a better solution, which would track:
* transaction requestor (user/job/etc)
* transaction timestamp
* diff encoding before/after state
Then if someone asks "why were these customer's disabled", we can answer "the XYZ cronjob went rabid and tore them down." and then hopefully use the diffs to reverse the transactions.
A change history is a better solution, which would track:
* transaction requestor (user/job/etc)
* transaction timestamp
* diff encoding before/after state
Then if someone asks "why were these customer's disabled", we can answer "the XYZ cronjob went rabid and tore them down." and then hopefully use the diffs to reverse the transactions.
Timestamps are a huge observability win relative to the amount of effort they take. "When" will give you hints to pull the other information out of logs etc. What you're proposing is better, but is a heavier lift; if you have capacity for that, awesome, if you don't, timestamps go a long way, take very little time to implement, and not having any information will really sting.
Sure - this is objectively better for tracking/auditing, but... now we're getting back into trade-off territory.
Where is that change history stored? How much data are the diffs generating? Are we deriving the final state from the log, or can the log the and record disagree?
Basically - this is now back in the "What is this history buying us?" realm, not in the "easy win" realm.
In some cases it can be absolutely worth it. But probably not all.
Where is that change history stored? How much data are the diffs generating? Are we deriving the final state from the log, or can the log the and record disagree?
Basically - this is now back in the "What is this history buying us?" realm, not in the "easy win" realm.
In some cases it can be absolutely worth it. But probably not all.
I think this may miss the point of the article, which is pointing out that you can get a lot of value for very little effort by using a timestamp instead of a boolean. I don't think it's intention is to replace a complete change history/audit log implementation, which would require a significant amount more time/effort to implement.
I recently converted some generation code to use a plan, so you can make a plan and then execute the plan. Architecting your code this way gives you things like dry runs and rollbacks for free; I feel like diff storage is in a similar realm of usefulness.
Sure, but now you REALLY changed the game.
If you're currently using a boolean, switch it to a timestamp. There are no real world downsides.
If you're currently using a boolean, switch it to a timestamp. There are no real world downsides.
Validity periods are superior to an is_active/is_expired boolean, as you can set an expiration ahead of time without any write transactions needed at expiration time to make the expiration happen.
For your example, however, I'd be tempted to have an enum as you suggest and associated history/audit table that has timestamps, mainly because there's no sense in setting timestamps into the future for the first two enum values. Still, I'd keep a timestamp for inactivation for the reason I gave above.
For your example, however, I'd be tempted to have an enum as you suggest and associated history/audit table that has timestamps, mainly because there's no sense in setting timestamps into the future for the first two enum values. Still, I'd keep a timestamp for inactivation for the reason I gave above.
Expiration times still need a status flag for cleanup.
What should the state be vs what is the current state vs when should the state change.
What should the state be vs what is the current state vs when should the state change.
Why repeat yourself? If you can have an expression-valued column, do that.
For expiration it's essential that it be able to happen at the scheduled time (when it is scheduled anyways) without having to execute a transaction at that time.
For expiration it's essential that it be able to happen at the scheduled time (when it is scheduled anyways) without having to execute a transaction at that time.
It’s fine for a DB be the source of truth as long as it’s the ultimate arbiter of what’s going on, but any kind of real world event has dependencies outside of the databases control.
A digital rental works as a pure time stamp in a DB, a car rental however can’t be rented out to the next person simply because the last persons rental period ended as you might not physically have the car etc.
A digital rental works as a pure time stamp in a DB, a car rental however can’t be rented out to the next person simply because the last persons rental period ended as you might not physically have the car etc.
The return of the car should have its own entry, separate from when the rental expires.
It doesn't mean you shouldn't have a an expiration field.
It doesn't mean you shouldn't have a an expiration field.
The point is the time stamp* has minimal value in the system.
It’s very tempting to tie various bits of business logic directly to that specific time stamp, but doing so is almost always a mistake instead you might want say a report for in_customers_hands and over 4 hours late or whatever.
The system directly doing stuff based on time stamps is a great way to get sued from regular data entry errors. One such case recently cost Hertz a $168 million payout and a lot of bad publicity.
*Of course it should also be calculated rather than being a numeric value in a table somewhere, but that’s another story.
It’s very tempting to tie various bits of business logic directly to that specific time stamp, but doing so is almost always a mistake instead you might want say a report for in_customers_hands and over 4 hours late or whatever.
The system directly doing stuff based on time stamps is a great way to get sued from regular data entry errors. One such case recently cost Hertz a $168 million payout and a lot of bad publicity.
*Of course it should also be calculated rather than being a numeric value in a table somewhere, but that’s another story.
This enum is a list of states.
Immediately should one think about a proper tool to handle it, which usually is a finite state machine. FSMs are somehow underappreciated outside of comm protocols and GUIs. They are an adequate tool for quite a few "backend" or "data representation" tasks though.
What the original post suggests is to timestamp the latest state transition. The approach is trivially obvious if you explicitly track state transitions as a part of the logic of your FSM.
Immediately should one think about a proper tool to handle it, which usually is a finite state machine. FSMs are somehow underappreciated outside of comm protocols and GUIs. They are an adequate tool for quite a few "backend" or "data representation" tasks though.
What the original post suggests is to timestamp the latest state transition. The approach is trivially obvious if you explicitly track state transitions as a part of the logic of your FSM.
That's a great way of phrasing it. A boolean can be a FSM in hiding.
Tracking FSM transitions is the change history/transaction log, isn't it?
It would be:
{timestamp, old_state, event, new_state}
If we convert booleans to timestamps for the FSM, I end up with:
timestamp not_configured;
timestamp being_provisioned;
timestamp active;
timestamp disabled;
timestamp deleted;
Which would cause confusion when there are multiple FSMs in the same database record.
We could isolate each FSM into its own column.
It still makes it kind-of hard to decide what's the current state. The set of timestamps needs to be considered and sorted, going from field to {field_name, timestamp} and then sorting by timestamp and extracting the max. It would make "select count(*) from customers where current_state = 'active'" brittle - the addition of a new state would require all existing queries to change.
Tracking FSM transitions is the change history/transaction log, isn't it?
It would be:
{timestamp, old_state, event, new_state}
If we convert booleans to timestamps for the FSM, I end up with:
timestamp not_configured;
timestamp being_provisioned;
timestamp active;
timestamp disabled;
timestamp deleted;
Which would cause confusion when there are multiple FSMs in the same database record.
We could isolate each FSM into its own column.
It still makes it kind-of hard to decide what's the current state. The set of timestamps needs to be considered and sorted, going from field to {field_name, timestamp} and then sorting by timestamp and extracting the max. It would make "select count(*) from customers where current_state = 'active'" brittle - the addition of a new state would require all existing queries to change.
If you need to hold timestamp, hold `deleted` and `deleted_at` together.
If you can't add a separate field, just add a log table.
Don't optimize for fictional requirements that haven't surfaced, and don't add shortcuts.
EDIT: Let me clarify my point here. A timestamp is just a timestamp. Giving a timestamp a role on signifying the state of an entity is a semantic shortcut, and semantic shortcuts lead to problems. I believe that DB structures should be as clear as possible. For example, it's impossible to know whether a timestamp is the authority on an entity's state by looking at a table structure. But a boolean field like "is_deleted" or "deleted" doesn't have that problem.
If you can't add a separate field, just add a log table.
Don't optimize for fictional requirements that haven't surfaced, and don't add shortcuts.
EDIT: Let me clarify my point here. A timestamp is just a timestamp. Giving a timestamp a role on signifying the state of an entity is a semantic shortcut, and semantic shortcuts lead to problems. I believe that DB structures should be as clear as possible. For example, it's impossible to know whether a timestamp is the authority on an entity's state by looking at a table structure. But a boolean field like "is_deleted" or "deleted" doesn't have that problem.
> For example, it's impossible to know whether a timestamp is the authority on an entity's state by looking at a table structure
This is just a matter of convention—if your codebase is consistent about it and there's no other option for "is this record deleted?", then yes it will be absolutely clear that "deleted_at" is the right column to use.
What's actually worse for making the database structure clear is to have "vestigial" columns that store old data, like you proposed for "deleted" and "deleted_at". Now, if they disagree, which one should you trust? Maybe some code is using one, while some code is using the other. Having a single source-of-truth column—no matter what the name is—is always going to be better then having two columns that could get out of sync or disagree.
This is just a matter of convention—if your codebase is consistent about it and there's no other option for "is this record deleted?", then yes it will be absolutely clear that "deleted_at" is the right column to use.
What's actually worse for making the database structure clear is to have "vestigial" columns that store old data, like you proposed for "deleted" and "deleted_at". Now, if they disagree, which one should you trust? Maybe some code is using one, while some code is using the other. Having a single source-of-truth column—no matter what the name is—is always going to be better then having two columns that could get out of sync or disagree.
I think you should have log table anyway because if you need that information storing it as column(s) next to the rest it’s not going to work well.
anyways i prefer to have nullable timeshamp columns instead of two like you suggested.
anyways i prefer to have nullable timeshamp columns instead of two like you suggested.
Make deleted_at nullable and put an index on it.
An audit log table isn't a bad idea, though. You can capture rich entity edit histories, attribution, etc.
An audit log table isn't a bad idea, though. You can capture rich entity edit histories, attribution, etc.
[deleted]
No need for both fields. A nullable timestamp column works fine: NULL until the record/row is deleted, at which point it holds the timestamp of when it happened.
You can derive a boolean "is it deleted" flag from that without adding another column to (mis)manage.
You can derive a boolean "is it deleted" flag from that without adding another column to (mis)manage.
Because they signify different things. For example, when you want to undo that delete operation, erasing timestamp would actually deprive you of the information that when it was deleted in the first place.
Sure, but that just kicks the can one iteration down the road, and now it's impossible to delete the record a SECOND time without "depriving" yourself of that information. If you need an audit table, use an audit table, but being able to say "deleted_at > 1.month.ago" to grab all records deleted in the past month is super useful.
What is a delete operation that can be "undone"? What is the timestamp supposed to mean in that scenario? What happens when it's deleted again then?
If you need a full record of state changes then just upgrade to an audit log, otherwise a nullable timestamp field is perfectly fine.
If you need a full record of state changes then just upgrade to an audit log, otherwise a nullable timestamp field is perfectly fine.
That's actually my main point. I edited my top comment to clarify that. A timestamp doesn't implicate "state." A bool, on the other hand, unquestionably does.
Again, the nullable nature of the column denotes both the state and when the state changed. You have more information in a single column, no need for both.
Nullability on timestamp only implies that the timestamp is optional that's all. It doesn't imply that the timestamp decides the state of the entity.
That's very strange. Database schema's don't need to be that literal, they're there to serve the business use-case for the underlying data.
A NULL `deleted_at` timestamp implies that it hasn't been deleted. That's far more simple and logical then 2 fields possibly conflicting or having an "optional" timestamp.
A NULL `deleted_at` timestamp implies that it hasn't been deleted. That's far more simple and logical then 2 fields possibly conflicting or having an "optional" timestamp.
time-series designs are generally better because they hold more information, and you can throw a view on top of them to present a nullable timestamp table if that's what's already been coded against. On the other hand once you go nullable it's difficult to figure out why the field was nulled after the fact.
It's a deleted timestamp. It's null until it's deleted. Why would there be confusion on it being null?
Nullable timestamp columns (64-bit integers) are what I prefer.
I don't know how much of a performance improvement I'd get if I had a separate indexed bool column for tracking just the truthiness, but I do know that it probably wouldn't be enough to matter, even if SQL was a meaningful bottleneck.
I really enjoy working with these as nullable DateTime in .NET as well:
I don't know how much of a performance improvement I'd get if I had a separate indexed bool column for tracking just the truthiness, but I do know that it probably wouldn't be enough to matter, even if SQL was a meaningful bottleneck.
I really enjoy working with these as nullable DateTime in .NET as well:
if (!record.CompletedUtc.HasValue) { /* completion logic */ }
Indexing a 64 bit versus a 1 bit column actually sounds like a potentially really good win to make the index much much smaller, which could help loads with keeping it in hot memory or cache.
On the other hand, on postgres & maybe others, one could perhaps index an expression deleted_at is not null, which would let one have the data shape they want while letting the index shape suit the typical access pattern.
On the other hand, on postgres & maybe others, one could perhaps index an expression deleted_at is not null, which would let one have the data shape they want while letting the index shape suit the typical access pattern.
Log tables are a super good idea in a lot of cases. And if your DB support it add a JSON column to that log table. Being able to dump either stricter data from our own logging or the reponcess from third part APIs in invaluable. You never know in advance what is going to be useful.
If you start generating too much data, add a cron job to purge older items or scale back the logging.
An example from our e-commerce platform, the "order/cart" tables have corresponding log table that log all changes, user interactions, and all requests/responses from Stripe during the checkout process.
It's super useful both for tracking down bugs, but also confirming what happed when customers contact support.
If you start generating too much data, add a cron job to purge older items or scale back the logging.
An example from our e-commerce platform, the "order/cart" tables have corresponding log table that log all changes, user interactions, and all requests/responses from Stripe during the checkout process.
It's super useful both for tracking down bugs, but also confirming what happed when customers contact support.
Yeah I much prefer keeping the deleted column as a boolean and then having a log table. I've done the timestamps instead of boolean thing before and it leads to two problems:
1. What happens when the record is "un-deleted?" Now the timestamp is null again and history has been lost. It's not the end of the world but if you're asked to create an account history report it's an awkward conversation. "I thought we tracked when records were deleted..."
2. Similar to the end of the last problem, it creates an expectation that the times that changes are made are tracked but it doesn't quite live up to that expectation. I've learned that business people love a feature that works well (like a log table), they can deal with a feature not existing at all (like a boolean and no logging), but a half-working feature causes a lot of suffering.
Just do logging right from the start if you are writing business software where the data and transaction volume are small compared to the value of the data.
1. What happens when the record is "un-deleted?" Now the timestamp is null again and history has been lost. It's not the end of the world but if you're asked to create an account history report it's an awkward conversation. "I thought we tracked when records were deleted..."
2. Similar to the end of the last problem, it creates an expectation that the times that changes are made are tracked but it doesn't quite live up to that expectation. I've learned that business people love a feature that works well (like a log table), they can deal with a feature not existing at all (like a boolean and no logging), but a half-working feature causes a lot of suffering.
Just do logging right from the start if you are writing business software where the data and transaction volume are small compared to the value of the data.
This was one of Luke Plant's YAGNI exceptions: https://lukeplant.me.uk/blog/posts/yagni-exceptions/
Discussed at the time:
You might as well timestamp it - https://news.ycombinator.com/item?id=26922759 - April 2021 (198 comments)
You might as well timestamp it - https://news.ycombinator.com/item?id=26922759 - April 2021 (198 comments)
I've frequently just done both, which I suppose is rather silly, but I like having a nicely named boolean field. I suppose I should probably just make those derived properties though.
Or, you know, use a time-aware database like XTDB or Datomic.
[deleted]
I kind of understand why the example was set up this way, but I died inside a little when he wrote to the console log without the timestamp in the message.
I always store a timestamp and have an "is_deleted" flag on the business object that checks if the "deleted_timestamp" is null or depending on the use case, whether the timestamp is in the future for records that are to be deleted.
I can also use the timestamp later if I want to move deleted records to a different table or database to improve performance depending on requirements.
I can also use the timestamp later if I want to move deleted records to a different table or database to improve performance depending on requirements.
Becareful from a privacy perspective. "User bob is active" is different than "User bob is active since <specific timesamp>". That said, in forensics, random things storing timestamps is a big treasure trove. The most innocent logs or entries can be correlated with something else about a user to figure out what they did.
> It’s like the exact opposite of YAGNI. You Ain’t Gonna Regret It?
Pagni's?
https://simonwillison.net/2021/Jul/1/pagnis/
Pagni's?
https://simonwillison.net/2021/Jul/1/pagnis/
This should definitely be implemented in projects where the use of the feature flag is common. When you go with boolean values, after a while you have a pile of data that you don't know what was done and when.
Never really felt the need but I suppose there has always been an updated_when field, so for something that is deleted the updated_when provides the time stamp.
Create an `updated_at` with an on update trigger to set it to NOW(). Your code will never have to explicitly remember to set it.
Go further and create an integer `version` vector clock that gets set to its value plus one. You can see the edit frequency of individual entities and construct a simple key for cache invalidation.
Go further and create an integer `version` vector clock that gets set to its value plus one. You can see the edit frequency of individual entities and construct a simple key for cache invalidation.
I'm going to steal YAGRI (You Ain't Gonna Regret It) for my own vocabulary.
But what timebase and precision? UTC in seconds? Unix time in nanoseconds? GPS time in 10us increments?
I'm going to have to respectfully disagree on this one, just because of unintended behavior and complexity.
Whether it's in a programming language or in a database... what is false? Is it false or null or 1970-01-01 00:00:00 UTC? What if different parts of the program/table use different versions of false? What happens when I combine two truthy values with a boolean operator -- for all combinations of values, what is the resulting type and is it the value even correct? (E.g. in SQL, NULL XOR 1672254005 is NULL, which is flat-out wrong if you're using NULL in place of FALSE, and it's easy to think of further examples.)
There's so much research I'd have to do to determine that this would always be bug-free for a particular language/platform, and then I'd need to remember which languages/platforms it is safe for and which ones aren't.
Whether it's in a programming language or in a database... what is false? Is it false or null or 1970-01-01 00:00:00 UTC? What if different parts of the program/table use different versions of false? What happens when I combine two truthy values with a boolean operator -- for all combinations of values, what is the resulting type and is it the value even correct? (E.g. in SQL, NULL XOR 1672254005 is NULL, which is flat-out wrong if you're using NULL in place of FALSE, and it's easy to think of further examples.)
There's so much research I'd have to do to determine that this would always be bug-free for a particular language/platform, and then I'd need to remember which languages/platforms it is safe for and which ones aren't.
For nullable timestamps, the timestamp itself is opaque. Having a value is indication that the thing happened. The time reading is orthogonal to that question.
If your language has a tough or flexible time with falsy, I found your problem. You shouldn't even be in that headspace, and languages that put you there introduce so much mental overhead that they're not worth it.
You shouldn't need to do research here. This should be a one and done solution from your toolbox that you can pull out at a moment's notice: "How do I handle record soft deletion and store some state around when it happened?" - zero effort, tried and true recipe borne of experience.
The database and data stores drive your product. They're the heart and soul.
If your language has a tough or flexible time with falsy, I found your problem. You shouldn't even be in that headspace, and languages that put you there introduce so much mental overhead that they're not worth it.
You shouldn't need to do research here. This should be a one and done solution from your toolbox that you can pull out at a moment's notice: "How do I handle record soft deletion and store some state around when it happened?" - zero effort, tried and true recipe borne of experience.
The database and data stores drive your product. They're the heart and soul.
So the problem is with SQL, because NULL doesn't act the same as false, and boolean operators may give incorrect results if you expect them to? I'm not sure how to respond if you think people shouldn't be in the headspace of SQL.
In SQL you won't typically coerce null to false, though there are mechanisms to accomplish this (which can be useful for analytics, ETLs, etc). Presence is first class and is probably what you want in your business logic queries.
If you let the SQL query predicates handle which records to select, I'm not sure I see the problem you originally outlined. Why do you care what value the timestamp has when the question is whether or not a record experienced an event.
If you let the SQL query predicates handle which records to select, I'm not sure I see the problem you originally outlined. Why do you care what value the timestamp has when the question is whether or not a record experienced an event.
No, you have to do this anyways. Assuming you're using a SQL database, a boolean field can be NULL too, unless you explicitly mark it non-nullable. If you are worried about obscure edge cases, use languages and tools with less of them. For example, it is VERY easy to reason about the date field being set or not if your language of choice represents it with an optional type you have to unwrap in some fashion.
But it's not really that bad in the worst case. Failing docs or the ability to read your db connector's source code enough to ascertain, you can always just test. Both in the sense of, try it and see what happens, and also, writing automated tests that ensure you're getting the expected behavior. If your line of logic is that hope is not a strategy, I agree. However, there are alternatives to hope that don't involve vacating best practices out of fear of hitting edge cases, and you probably want those automated tests anyways.
But it's not really that bad in the worst case. Failing docs or the ability to read your db connector's source code enough to ascertain, you can always just test. Both in the sense of, try it and see what happens, and also, writing automated tests that ensure you're getting the expected behavior. If your line of logic is that hope is not a strategy, I agree. However, there are alternatives to hope that don't involve vacating best practices out of fear of hitting edge cases, and you probably want those automated tests anyways.
That is precisely the point in any data oriented application (like a database) a boolean should actually have at least 3 possible value:
- True
- False
- Null/Nil/unset/error
Depending on how the application handle the third case it can be more than 3 return values.
timestamp require ad-hoc and potentially breakable workaround to emulate this behavior.
- True
- False
- Null/Nil/unset/error
Depending on how the application handle the third case it can be more than 3 return values.
timestamp require ad-hoc and potentially breakable workaround to emulate this behavior.
I'll have to disagree. I don't think I'd want that in most cases.
It's unclear what general problem it solves. If the database row is actually corrupted, I want the query to fail violently, and the database to fail all operations around it to avoid further corruption. If I really need to handle it, I'll handle it in my app layer.
If it's not, I don't want it to be set to some invalid state. I don't want every piece of code to need to deal with this invalid state that shouldn't be allowed to begin with. I'd rather gate it at the door and stop it from getting in there in the first place.
If you use a nullable timestamp as a boolean, this is fine; there's only two states w.r.t. set or not: NULL or not NULL, from the SQL perspective. How this is encoded in your language and tools of choice depends. If there's some database value not encodable to your language's native types, the db connector will probably decide what to do: truncate data, fail the whole query, use a type with additional entropy (like Go's NullString, for example.) In no way do I want there to be an error state for that field alone. If I did, though, for example because I need to handle partial data as an application concern, I'd want union typing. In that case you could have Error/Unset/Timestamp just fine. I don't believe SQL has this sort of union type natively, but it can be represented in many programming languages intuitively (like unsafely as a union in C, safely as an enum in Rust, safely as a discriminated union in TypeScript, and mostly safely in Go abusing interfaces.) However, that is only something I want to do if my application specifically needs it. Otherwise? Data that goes into the database must meet the constraints first.
It's unclear what general problem it solves. If the database row is actually corrupted, I want the query to fail violently, and the database to fail all operations around it to avoid further corruption. If I really need to handle it, I'll handle it in my app layer.
If it's not, I don't want it to be set to some invalid state. I don't want every piece of code to need to deal with this invalid state that shouldn't be allowed to begin with. I'd rather gate it at the door and stop it from getting in there in the first place.
If you use a nullable timestamp as a boolean, this is fine; there's only two states w.r.t. set or not: NULL or not NULL, from the SQL perspective. How this is encoded in your language and tools of choice depends. If there's some database value not encodable to your language's native types, the db connector will probably decide what to do: truncate data, fail the whole query, use a type with additional entropy (like Go's NullString, for example.) In no way do I want there to be an error state for that field alone. If I did, though, for example because I need to handle partial data as an application concern, I'd want union typing. In that case you could have Error/Unset/Timestamp just fine. I don't believe SQL has this sort of union type natively, but it can be represented in many programming languages intuitively (like unsafely as a union in C, safely as an enum in Rust, safely as a discriminated union in TypeScript, and mostly safely in Go abusing interfaces.) However, that is only something I want to do if my application specifically needs it. Otherwise? Data that goes into the database must meet the constraints first.
Still after all this explaining you agree there is only two state instead of three.
Usually it's used with the following logic for database oriented workflow.
True = true
False = false
Null = unknow (This which might be a real-world case that you can model using null)
Of course if there is an error the engine will thrown an exception Which is a whole other kind of signal.
Usually it's used with the following logic for database oriented workflow.
True = true
False = false
Null = unknow (This which might be a real-world case that you can model using null)
Of course if there is an error the engine will thrown an exception Which is a whole other kind of signal.
What I don't get is, why would I want there to be a third state in this boolean example? You're saying it could be useful. That's true, it could. However, we're talking about something that today is already just a boolean, such as "is_published." Even if you can envision a reason why you might want a third unknown state for "is_published", if you write a bunch of code that treats it as a boolean, without knowing what the null state might mean, you are not solving a problem. You're just modelling your data slightly less precisely. Saving a date is saving known, useful state, even if you don't need it yet. Using a nullable type for a field that can't yet be null is just adding an additional unknown state for no reason.
When using Go and sqlc, what would happen is I would use a NOT NULL field for the boolean, because I'm modelling a boolean, not a tri-state. If I was modelling something where I had three states I wanted to handle, I would use an enum instead. But even if I wanted to use NULL instead of an enum that explicitly specifies the meaning of the third state, I'd rather start as NOT NULL. Why? Because then, if I ever want to remove the constraint, I can. And when I do, sqlc will helpfully change the type of the field from a raw boolean to a nullable boolean wrapper. And doing this will break the existing code. This is good. Why? Because in every place where I assumed there were only two possible states, I can now check and see what I'd want to do in my new third case. This is better than starting with nullability, because if I don't know what NULL means or why I'd have it, it's really difficult to know what my code should do when it encounters it. You could always throw errors, but if you do that you have to ensure you clean all of that up before you start actually using NULL.
This is fundamentally about data modelling though. Talking in this abstract sense is not useful. What I feel you're failing to make an adequate case for is why a field like the one described in the linked article needs a state other than "set" or "unset". Just putting a nullable timestamp is a nearly free upgrade from putting a non nullable boolean, which is what I would've done anyways.
If I want to add more states, I want explicit data model changes, that result in explicit test and type checking errors, that highlight wherever I need to update my code's state management to account for new states.
Additional note: particular to SQL, removing not NULL constraints is basically free from the database end as far as I can tell. In addition, NULL has specific behaviors, especially w.r.t. JOINs, so I would NOT want to use NULL to model a tri-state.
When using Go and sqlc, what would happen is I would use a NOT NULL field for the boolean, because I'm modelling a boolean, not a tri-state. If I was modelling something where I had three states I wanted to handle, I would use an enum instead. But even if I wanted to use NULL instead of an enum that explicitly specifies the meaning of the third state, I'd rather start as NOT NULL. Why? Because then, if I ever want to remove the constraint, I can. And when I do, sqlc will helpfully change the type of the field from a raw boolean to a nullable boolean wrapper. And doing this will break the existing code. This is good. Why? Because in every place where I assumed there were only two possible states, I can now check and see what I'd want to do in my new third case. This is better than starting with nullability, because if I don't know what NULL means or why I'd have it, it's really difficult to know what my code should do when it encounters it. You could always throw errors, but if you do that you have to ensure you clean all of that up before you start actually using NULL.
This is fundamentally about data modelling though. Talking in this abstract sense is not useful. What I feel you're failing to make an adequate case for is why a field like the one described in the linked article needs a state other than "set" or "unset". Just putting a nullable timestamp is a nearly free upgrade from putting a non nullable boolean, which is what I would've done anyways.
If I want to add more states, I want explicit data model changes, that result in explicit test and type checking errors, that highlight wherever I need to update my code's state management to account for new states.
Additional note: particular to SQL, removing not NULL constraints is basically free from the database end as far as I can tell. In addition, NULL has specific behaviors, especially w.r.t. JOINs, so I would NOT want to use NULL to model a tri-state.
It always depend on the use case you are trying to model. My statement was primarily a counterpoint to OP "you might at well timestamp it".
I guess it is a valid take on the specific use case of publication date he mention. The problem is generalizing from that.
For user inputed data you might NOT want to coerce a default state when the user genuinely can't answer otherwise you might collect garbage because i can guarantee that the user will input random answer to unblock itself.
Of course you can define enum, but the NULL value already cover 80% of use case when used properly (as far as database are concerned).
NOT null might be a useful DB constraint (especially for ids participating columns). But you just have to read PostgreSQL release notes to notice that null handling is actually a hot topic which always call for more fine tuned settings to accommodate different workflow. People use theses features a lot. See : https://news.ycombinator.com/item?id=32053293
As far as JOIN are concerned bad NULL handling is almost always coming from a bad understanding of OUTER JOIN mechanics.
Anyhow it's an endless debate and I guess we won't be able to settle the NULL Schism tonight! See : https://news.ycombinator.com/item?id=18588239
So maybe let us end with this beautiful quote from last link top comment by @porpoisely
NULL exists to solve particular problems in computer science. It can also cause a lot of problems. You can argue it's the best solution and worst mistake depending on the situation.
I guess it is a valid take on the specific use case of publication date he mention. The problem is generalizing from that.
For user inputed data you might NOT want to coerce a default state when the user genuinely can't answer otherwise you might collect garbage because i can guarantee that the user will input random answer to unblock itself.
Of course you can define enum, but the NULL value already cover 80% of use case when used properly (as far as database are concerned).
NOT null might be a useful DB constraint (especially for ids participating columns). But you just have to read PostgreSQL release notes to notice that null handling is actually a hot topic which always call for more fine tuned settings to accommodate different workflow. People use theses features a lot. See : https://news.ycombinator.com/item?id=32053293
As far as JOIN are concerned bad NULL handling is almost always coming from a bad understanding of OUTER JOIN mechanics.
Anyhow it's an endless debate and I guess we won't be able to settle the NULL Schism tonight! See : https://news.ycombinator.com/item?id=18588239
So maybe let us end with this beautiful quote from last link top comment by @porpoisely
NULL exists to solve particular problems in computer science. It can also cause a lot of problems. You can argue it's the best solution and worst mistake depending on the situation.
> false or null
Not possible with a timestamp field.
> 00:00:00 UTC
I remember a bug around this in Python regarding times (only) a decade or two ago, it was fixed a long time ago. I assume this is not an issue for modern stacks, but I would double check under say PHP which has a known history. Not normally an issue I'd say.
> What happens when I combine two truthy values with a boolean operator
Type or Runtime error. Who is adding booleans and dates together? Such egregious mistakes don't take long to surface and are impossible if planned against beforehand.
I don't think these are things to be worried about (if you're paying attention even a tiny bit) to be honest.
Not possible with a timestamp field.
> 00:00:00 UTC
I remember a bug around this in Python regarding times (only) a decade or two ago, it was fixed a long time ago. I assume this is not an issue for modern stacks, but I would double check under say PHP which has a known history. Not normally an issue I'd say.
> What happens when I combine two truthy values with a boolean operator
Type or Runtime error. Who is adding booleans and dates together? Such egregious mistakes don't take long to surface and are impossible if planned against beforehand.
I don't think these are things to be worried about (if you're paying attention even a tiny bit) to be honest.
For example, let's start with an object, which has a boolean flag "active".
boolean is_active;
We will always want to get a bit more advanced, and get into sub-states as it is brought up. We can't do that with a boolean. So we go to an enum.
Enum current_state { not_configured; being_provisioned; active; disabled; deleted; }
current_state state;
We have an enum in hiding. Converting the boolean to a timestamp stops the conversion to an enum - we can't overload the presence of a timestamp into the multiple values in the enum.
The timestamp is "what happened, when", an audit log/change history function. That should be kept separate from the rest of the database.
Sometimes, there is a business reason to track a timestamp - charge the customer 30days after the item became "active". How to model that depends on your database and what is required - history table, convert the enum to struct, time_became_active, time_of_last_state_change, etc.