I want to know the exact difference between before_save and after_save. Now, I have read the documentation and I know the difference as per their name. But, I want to know the exact difference using real time entities. It would be great if you provide any example.
Before Save: The functionality written here will be called when you hit the save button and before the record is stored in the database.
Usage: Before save can be used normally. For a simple eg, lets say we can modify or add a field value just before the record goes into the database.
After Save: The functionality written here will be called when you hit the save button and after the record is stored in the database.
Usage: To help you understand the use of after_save, Lets take a scenario where we have Student record containing SL.No, Name, Course and Student No.
Lets say the SL.No is an auto incrementing field and Student no is the combination of the first letter of the Course and the SL.No.
Now here the auto incremented no wont exist untill the record is saved in the database, hence you wont get the required Student No unless the record is saved. So after_save here helps since the logic is executed after the record has been saved, to which an auto incremented no is already generated.
Related
As an amateur coder for some years I have generally used sub forms when dealing with linked tables to make the transfer of ID field from primary to sub nice and simple...
However in my latest project the main form is a continuous form with a list of delivery runs (Date, RunName, RunCompleted) etc... Linked to this primary table is a delivery list containing (SKU of product, Qty etc...). I use a simple Relationship between the two tables.
Now, On the main (RUNS) form at the end of each row is a button that opens the DELIVERIES form and displays all records with matching RUNID
This is fine for displaying pre-existing data but when I want to add new records I have been using the following code attached to the OnCurrent event:
Me.RunID = DLookup("[RunID]", "tbl_BCCRuns", "RunID = " & Forms![frm_BCC_Runs_list]![RunID])
I have also used:
Forms![frm_BCC_Deliveries].Controls![RunID] = Forms![tbl_BCCRuns].Controls![RunID]
(Note: above done from memory and exact code may be incorrect but that's not the problem at hand)
Now... Both these options give me what I need however...
I find that as I am working on the database, or if you open certain forms in the right order (a bug I need to identify and fix clearly) you can open the DELIVERIES form without the filter (to view all deliveries for arguments sake) and the top entry (usually the oldest record) suddenly adopts the RUNID of the selected record back in the main form.
Now, my question is this, and the answer may be a simple "no" and that's fine, I'll move on...
Is there a better way, a way I am not familiar with or just don't know about due to my inconsistent Access progress, to transfer ID's to a form without risking contamination from improper use? Or do I just have to bite the bullet and make sure that there is just no possible way for that to happen?
In effort to alleviate the issue, I have created a Display Only form for viewing the deliveries but there are still times when I need to access the live historical data to modify other fields without wanting to modify the RUNID.
Any pointers greatly appreciated...
Since you only want to pull the RunID if the form is on a new record row, do a check to verify this is a new record.
If Me.NewRecord Then
Me.RunID = DLookup("[RunID]", "tbl_BCCRuns", "RunID = " & Forms![frm_BCC_Runs_list]![RunID])
End If
Could also consider a technique to synchronize parent and child forms when both are subforms on a main form (the main form does not have to be bound) https://www.fmsinc.com/MicrosoftAccess/Forms/Synchronize/LinkedSubforms.asp
I have a task to create a database to track student results in a school. I came out with a set of relationships between the tables according to the 3 forms of normalisation(I hope I got it right. If not, please enlighten me).
One feature that I want to put in the Filemaker app is that when a teacher want to enter some assignment marks, he will just need to create a new submission record and all the student names in the class will appear.
I could not think how this feature can be done in Filemaker. I can only create a new submissions record and key in a student's score, then create another new record to do the same thing for a second student.
Can someone help? I am a teacher, not a Filemaker developer so please correct me if my database tables are done wrongly.
Update:
I will like the output to be like this
Spreadsheet is not suitable because it can't be used to search/sort easily.
I have a quick sample file here. It's an old sample and it uses a different (but similar) model. Basically the idea is that: You have a calculated field (I use a repeating field) to display the data. You also have a global repeating field that serves as an editing widget. Each time you go to a record you fill this field's reps with data from related records (using a OnRecordLoad trigger). This doesn't mean the field shows the same data for all records, because its conditional formatting rules are set to hide all data; so it only shows a piece of data when you actually enter one of its repetitions. This is the data that can be edited. And finally there's a trigger that fires each time you exit the field and posts your changes to the related table (adds, updates, or deletes).
The sample isn't quite complete because if there's fewer data columns than repetitions, you'd probably want to somehow lock the remaining repetitions; this part isn't done. Otherwise it works fairly well. In FM 12, however, it tends to freeze the app; I reported this to FMI, they acknowledged it, but I don't think it has been fixed already.
First of all I want to show how I made this in SQL:
Both the location and environment table will never contain more than those four rows. Each log can only be associated with 4 rows.
What I don't understand is how do I even start writing code that will take whatever the user has chosen, based on state switches etc in my UI and persist this?
Because when the user are done I want to store a "log-record", and the log-record may have location and environment rows associated with it. And what happen when the user let say, choose all the location rows, four times a row....does it add the location to the location "entity" every time? Would I end up with a lot of duplicated data? I would appreciate any help that can show me how to do this. Thank you!
Looks like you need three entities. You'll have Location and Environment entities that have whichever attributes they need, and a Log entity that has relationship with both Environment and Location. I think you're asking if instances of Location and Environment that happen to be the same will be duplicated in the core data store, or if multiple Log instances will relate to the same Location and Environment instances. Is that right? Answer: It's up to you. Say you want to save a Location instance that has a particular set of attributes. You could first search for one that has that exact set of attributes and associate it with your Log instance, or you could just create a new Location instance and not worry about the duplication. If you're storing zillions of these Log entries, the first plan might save a lot of space. If you're not saving them all that often, and particularly if the user can go back and change the data associated with a Log instance, you might want to use separate instances even if they happen to be the same.
We've got a set of forms in our web application that is managed by multiple staff members. The forms are common for all staff members. Right now, we've implemented a locking mechanism. But the issue is that there's no reliable way of knowing when a user has logged out of the system, so the form needs to be unlocked. I was wondering if there was a better way to manage concurrent users editing the same data.
You can use optimistic concurrency which is how the .Net data libraries are designed. Effectively you assume that usually no one will edit a row concurrently. When it occurs, you can either throw away the changes made, or try and create some nicer retry logic when you have two users edit the same row.
If you keep a copy of what was in the row when you started editing it and then write your update as:
Update Table set column = changedvalue
where column1 = column1prev
AND column2 = column2prev...
If this updates zero rows, then you know that the row changed during the edit and you can then deal with it, or simply throw an error and tell the user to try again.
You could also create some retry logic? Re-read the row from the database and check whether the change made by your user and the change made in the database are able to be safely combined, then do so automatically. Or you could present a choice to the user as to whether they still wish to make their change based on the values now in the database.
Do something similar to what is done in many version control systems. Allow anyone to edit the data. When the user submits the form, the database is checked for changes. If the record has not been changed prior to this submission, allow it as usual. If both changes are the same, ignore the incoming (now redundant) change.
If the second change is different from the first, the record is now in conflict. The user is presented with a new form, which indicates which fields were changed by the conflicting update. It is then the user's responsibility to resolve the conflict (by updating both sets of changes), or to allow the existing update to stand.
As Spence suggested, what you need is optimistic concurrency. A standard website that does no accounting for whether the data has changed uses what I call "last write wins". Simply put, whichever connection saves to the database last, that version of the data is the one that sticks. In optimistic concurrency, you use a "first write wins" logic such that if two connections try to save the same row at the same time, the first one that commits wins and the second is rejected.
There are two pieces to this mechanism:
The rules by which you fail the second commit
How the system or the user handles the rejected commit.
Determining whether to reject the commit
Two approaches:
Comparison column that changes each time a commit happens
Compare the data with its committed version in the database.
The first one entails using something like SQL Server's rowversion data type which is guaranteed to change each time the row changes. The upside is that it makes it simple to roll your own logic to determine if something has changed. When you get the data, you pull the rowversion column's value and when you commit, you compare that value with what is currently in the database. If they are different, the data has changed since you last retrieved it and you should reject the commit otherwise proceed to save the data.
The second one entails comparing the columns you pulled with their existing committed values in the database. As Spence suggested, if you attempt the update and no rows were updated, then clearly one of the criteria failed. This logic can get tricky when some of the values are null. Many object relational mappers and even .NET's DataTable and DataAdapter technology can help you handle this.
Handling the rejected commit
If you do not leave it up to the user, then the form would throw some message stating that the data has changed since they last edited and you would simply re-retrieve the data overwriting their changes. As you can imagine, users aren't particularly fond of this solution especially in a high volume system where it might happen frequently.
A more sophisticated (and also more complicated) approach is to show the user what has changed allow them to choose which items to try to re-commit, Behind the scenes you would retrieve the data again, overwrite the values picked by the user with their entries and try to commit again. In high volume system, this will still be problematic because by the time the user has tried to re-commit, the data may have changed yet again.
The checkout concept is effectively pessimistic concurrency where users "lock" rows. As you have discovered, it is difficult to implement in a stateless environment. Users are notorious for simply closing their browser while they have something checked out or using the Back button to return a set that was checked out and try to recommit it. IMO, it is more trouble than it is worth to try go this route in a web-based solution. Assuming you write the user name that last changed a given row, with optimistic concurrency, you can inform the user whose changes are rejected who saved the data before them.
I have seen this done two ways. The first is to have a "checked out" column in your database table associated with that data. Your service would have to look for this flag to see if it is being edited. You can have this expire after a time threshold is met (with a trigger) if the user doesn't commit changes. The second way is having a dedicated "checked out" table that stores id's and object names (probably the table name). It would work the same way and you would have less lookup time, theoretically. I see concurrency issues using the second method, however.
Why do you need to look for session timeout? Just synchronize access to your data (forms or whatever) and that's it.
UPDATE: If you mean you have "long transactions" where form is locked as soon as user opens editor (or whatever) and remains locked until user commits changes, then:
either use optimistic locking, implement it by versioning of forms data table
optimistic locking can cause loss of work, if user have been away for a long time, then tried to commit his changes and discovered that someone else already updated a form. In this case you may want to implement explicit "locking" of form, where user "locks" form as soon as he starts work on it. Other user will notice that form is "locked" and either communicate with lock owner to resolve issue, or he can "relock" form for himself, loosing all updates of first user in process.
We put in a very simple optimistic locking scheme that works like this:
every table has a last_update_date
field in it
when the form is created
the last_update_date for the record
is stored in a hidden input field
when the form is POSTED the server
checks the last_update_date in the
database against the date in the
hidden input field.
If they match,
then no one else has changed the
record since the form was created so
the system updates the data.
If they don't match, then someone else has
changed the record since the form was
created. The system sends the user back to the form edit page and tells the user that someone else edited the record and they must reapply their changes.
It is very simple and works well enough.
You can use "timestamp" column on your table. Refer: What is the mysterious 'timestamp' datatype in Sybase?
I understand that you want to avoid overwriting existing data with consecutively updates.
If so, when the user opens a screen you have to get last "timestamp" column to the client.
After changing data just before update, you should check the "timestamp" columns(yours and db) to make sure if anyone has changed tha data while he is editing.
If its changed you will alert an error and he has to startover. If it is not, update the data. Timestamp columns updated automatically.
The simplest method is to format your update statement to include the datetime when the record was last updated. For example:
UPDATE my_table SET my_column = new_val WHERE last_updated = <datetime when record was pulled from the db>
This way the update only succeeds if no one else has changed the record since the last read.
You can message to the user on conflict by checking if the update suceeded via a SELECT after the UPDATE.
I keep seeing questions floating through that make reference to a column in a database table named something like DateLastUpdated. I don't get it.
The only companion field I've ever seen is LastUpdateUserId or such. There's never an indicator about why the update took place; or even what the update was.
On top of that, this field is sometimes written from within a trigger, where even less context is available.
It certainly doesn't even come close to being an audit trail; so that can't be the justification. And if there is and audit trail somewhere in a log or whatever, this field would be redundant.
What am I missing? Why is this pattern so popular?
Such a field can be used to detect whether there are conflicting edits made by different processes. When you retrieve a record from the database, you get the previous DateLastUpdated field. After making changes to other fields, you submit the record back to the database layer. The database layer checks that the DateLastUpdated you submit matches the one still in the database. If it matches, then the update is performed (and DateLastUpdated is updated to the current time). However, if it does not match, then some other process has changed the record in the meantime and the current update can be aborted.
It depends on the exact circumstance, but a timestamp like that can be very useful for autogenerated data - you can figure out if something needs to be recalculated if a depedency has changed later on (this is how build systems calculate which files need to be recompiled).
Also, many websites will have data marking "Last changed" on a page, particularly news sites that may edit content. The exact reason isn't necessary (and there likely exist backups in case an audit trail is really necessary), but this data needs to be visible to the end user.
These sorts of things are typically used for business applications where user action is required to initiate the update. Typically, there will be some kind of business app (eg a CRM desktop application) and for most updates there tends to be only one way of making the update.
If you're looking at address data, that was done through the "Maintain Address" screen, etc.
Such database auditing is there to augment business-level auditing, not to replace it. Call centres will sometimes (or always in the case of financial services providers in Australia, as one example) record phone calls. That's part of the audit trail too but doesn't tend to be part of the IT solution as far as the desktop application (and related infrastructure) goes, although that is by no means a hard and fast rule.
Call centre staff will also typically have some sort of "Notes" or "Log" functionality where they can type freeform text as to why the customer called and what action was taken so the next operator can pick up where they left off when the customer rings back.
Triggers will often be used to record exactly what was changed (eg writing the old record to an audit table). The purpose of all this is that with all the information (the notes, recorded call, database audit trail and logs) the previous state of the data can be reconstructed as can the resulting action. This may be to find/resolve bugs in the system or simply as a conflict resolution process with the customer.
It is certainly popular - rails for example has a shorthand for it, as well as a creation timestamp (:timestamps).
At the application level it's very useful, as the same pattern is very common in views - look at the questions here for example (answered 56 secs ago, etc).
It can also be used retrospectively in reporting to generate stats (e.g. what is the growth curve of the number of records in the DB).
there are a couple of scenarios
Let's say you have an address table for your customers
you have your CRM app, the customer calls that his address has changed a month ago, with the LastUpdate column you can see that this row for this customer hasn't been touched in 4 months
usually you use triggers to populate a history table so that you can see all the other history, if you see that the creationdate and updated date are the same there is no point hitting the history table since you won't find anything
you calculate indexes (stock market), you can easily see that it was recalculated just by looking at this column
there are 2 DB servers, by comparing the date column you can find out if all the changes have been replicated or not etc etc ect
This is also very useful if you have to send feeds out to clients that are delta feeds, that is only the records that have been changed or inserted since the data of the last feed are sent.