How do I remove entire tables from Salesforce? - salesforce

I want to remove entire tables from Salesforce data that I am no longer using. I also want to prevent Salesforce from writing to these tables moving forward. Where do I start?

If it's your own custom tables you should be able to delete them. Hit delete action next to the table name in object manager and see what explodes?
The rule of thumb is "if you can create it straight in production without running a deployment process - you should be able to delete it". So if by "prevent Salesforce from writing to these" you mean flows, workflows, process builder... - they'll stop your delete, you'll have to get rid of them first before deleting the table itself - but should be relatively easy if repetitive.
It gets more interesting if you have code (triggers, classes, aura/lwc). You'll need to delete them using a special deployment command, changesets are useless. You can try to craft your own so-called destructiveChanges.xml (it'll be documented in metadata API guide) and try to deploy it even without any developer tools (for example with workbench.developerforce.com) but might be better idea to poke developer to do it. Identify dependencies and edit the code / delete classes as needed.
If it's custom tables but not your own (coming from managed package) - maybe packag has some config options, worst case uninstall it?

Related

Apex basics - quick question on code coverage

My company hired an agency to create an MQL salesforce object. Its constructed from an Apex class with various triggers.
We no longer have a need for it, and as the standing saleforce admin, there is none at the company who knows Apex. I'm taking classes to learn it, but wanted to check in and see how I can deprecate the object from salesforce by archiving/deleting (or even just commenting out the code) to push the update to production.
Does anyone have insight into how to go about doing this? All of the courses I've taken are basic understanding of Apex and how to write small triggers, classes and queries. The agency who built the class left 0 documentation on its code.
You can't write code in production so whatever you'll try to do - will have to be done in sandbox, tested and then deployed.
There's a way to do a "destructive deployment" and really delete it but you'll need programming tools (VSCode, Eclipse IDE or Ant + Migration Tool). It's bit advanced topic, I'd suggest you hire a dev ;) or try to just comment them out.
In sandbox you can comment out the body (bodies?) of triggers and classes. You shouldn't kill whole file, leave some empty skeletons like
public with sharing class MqlGenerator{
/* kill everything
*/
}
trigger MqlTrigger on MQL__c (after insert){
/* kill everything
*/
}
Of course if there's trigger on Account and it does 10 things, only 2 of them relate to MQL then don't comment everything out ;) It'll be bit of trial and error for you, depends how clean the code is.
You will have to touch triggers, normal classes and likely unit tests too because if they did decent job - there will be tests that verify these triggers do something and now these tests will start to fail.
Add the files to changeset as you go (you do changesets, right? Doesn't sound like you deploy with Git+SFDX for example). From time to time run Apex Classes -> Compile all classes and run unit tests. Some manual testing wouldn't hurt too. If you are unsure what's left you can click on MQL's fields, there's "Where is this used?" button. Or even try clicking delete & repeating until it succeeds ;)
After you deploy this changeset...
If the MQL__c has no triggers (for example it is created in Account updates but itself doesn't have triggers), you might actually be able to delete the object. If there are related triggers, workflows etc SF will stop you. The only way to really delete it would be to run this destructive deploy. It's possible without installing anything, use the link I included and for example workbench would let you make a deployment. But it's bit "pro", if you're unsure start with commenting stuff out and maybe leave the empty skeleton until you're more comfortable. You can always hide the object's Tab, remove right to Read the object and it'll disappear from listviews, reports... it'll be an eyesore only for sysadmins.
If object has to stay around but the data storage is significant you could try truncating the object. If it gives you trouble - Data Loader, export all records (just IDs), then delete. Maybe even with hard delete option so you skip recycle bin.

Is it possible to use Git as source control for code stored in a database?

I work on Labware LIMS, which has both configuration, and customization via its own programming language and internal code editor, and stores this customization code in database records. (Note, not the source code of the actual application itself, just the customization code a.k.a. LIMS Basic.) Almost everything in LIMS is stored in the database.
We want to investigate the possibility of using source control to protect this code but we don't know much more than the theory of using something like Git. (I have worked as a junior QA and used git but not as a dev and my knowledge is limited!)
Of particular use would be the merging tools, as currently we have to manually merge code in a text editor, if we even notice there is a conflict (checking content between dev and live is time consuming and involves using multiple tools, some of which are 3rd party tools we have developed ourselves, which are hit and miss. I personally find it easiest to cut and paste into a text file and then use Beyond Compare.
There is no notification that the code is different when moving it from dev to live (no deployment as such, you just import an xml file) so we often have things going live that someone was working on unbeknownst to each other. I.e. dev 1 is working on the code in object 1, dev 2 gets a ticket to make a change to object 1, does so and puts their change Live, whatever dev 1 was doing is now also Live in whatever state it was in. (Because we don't always have time to thoroughly check what state each object is in between up to 3 different databases.)
Is it possible to use source control just on the code within the database, but not necessarily the database itself? (We have backups and such for that but its easy for some aspects of the system to get overwritten by multiple devs working on overlapping areas at the same time.)
If anyone reading this has any specific knowledge of LW LIMS, we are referring to the Subroutines mostly, we have versioned Analyses which stands in for source control for the moment and is somewhat effective but no way to control who is doing what on the subroutines other than a comment log at the top. I have tried to find any information on how other teams source control their code in LIMS but to no avail.
The structure of one of these tables can range from as simple as the code just existing in one field as a straight text dump with a few other fields such as changed_on, changed_by and name (Subroutines), or more complex with code relating to one record being sprinkled around in multiple rows on another table entirely (Analyses) but even if it could just deal with the simple scenario to start with that would be great!
TL;DR: Could the contents of the Code field in a database record be treated like a regular code object in other dev environments somehow and source controlled using Git? (And is anyone willing to explain it simply for me to follow?)
As you need to version control table fields of subroutine, but LW LIMS doesn’t have the IDE for version control (such as git, svn etc). So the direct answer is no.
If you really want to do version control for the codes in database, you can create a git repository and only put the codes in git repository. when a file has updated, you can commit & push the changes. And it’s easy to compare the difference between versions.
More detail about git, you can refer git book.
LabWare LIMS has a number of options for version control. You COULD version the Subroutine table by adding a SUBROUTINE.VERSION field to the table, this works the same way as other versioned tables in LabWare where it asks you if you would like to create a new version of the object before saving. There are a few customers I work with that have done this.
Alternatively, (and possibly our more recommended method prior to LEM) there is the Snapshot capability where the system automatically takes a "snapshot" of objects as they are saved - when viewing these you have the ability to view them side by side in a comparison dialogue - it will show < or > for lines which are different.
Another approach is, if you have auditing turned on you are able to view the audit history for changes to specific objects - this includes subroutines.
One other approach is to use configuration packages - this has the ability to record version AND build numbers. Though individual subroutines is probably a bit too granular for it's intended design.
Lastly, since this question was originally posted we have developed a product called LabWare Environment Manager (LEM) which has some good change control functionality built-in.
For more information on the suggestions above, please have a look at the LabWare Technical manual for the version you are on. We also have a mailing list for questions like this to be posted. You might find an answer there. If you have access to our Support webpage you're able to search previous questions that have been asked. I'd also suggest that you get in touch with your Account Manager at LabWare who can help you answer some of your questions.
HTH

Database - Version Control - Managing dropped/deleted objects

We want to clean up our database schema and drop/delete objects which are no longer being used.
We suspect that sometime in the future we'll want to resurrect the removed functionality.
We've discussed the following options for dealing with dropped objects in version control:
Deleting the .sql files from source control once they are gone from the database and relying on the version history to store the definitions. Our concern with this approach is that sometime over the years source control will be moved and we will lose the history. It also seems difficult to know what to look for to recover if we can't see all the dropped objects.
Leaving the .sql files in source control but updating the definitions to "drop proc {someproc}". With this approach we our concerned about leaving the objects in version control which no longer exists and also the risk to losing the history if the vcs was moved
Creating a new repo for dropped objects and migrating .sql files to this repo once they have been dropped from SQL Server.
We're working in a windows environment and are fairly new to working with VCS for databases. Currently GIT + SSDT.
Currently option 3 is our preferred approach.
I see this a lot with database code, what happens is over time people end up with stuff in the database that is either not used or just does not work (think a proc that references a table and the table is modified but not the proc).
The thing to do is to get everything in source control (which it looks like you have) and then create a tag or branch of all the code before and after deleting it so you can get it back.
Two things normally transpire, either the code was genuinely never used or it was used at year end and when you find out, the world is about to fall on your head so better have a quick way to get it back.
Of course if you had a full suite of tests then even the year end process would be safe :)
I personally wouldn't use option 3, I would just keep the history in the main branch so you keep the history with it.
ed
There are a lot of good tools for versioning database changes: you have a big chance to get this question closed with "Too broad" reason, but I'll try to suggest to
Read about, understand and try to add Liquibase to your Development-Toolbox
Adopt your workflow for using this additional layer - technically it will be one more file (changelog in terms of Liquibase) in changesets, where you changing DD and|or data.
These changelogs provide good and smooth way of moving back and forth in linear history of changes in databases, not so good (or I don't know The Right Way) for direct jumping between nodes of diverged history, but it seems not your case
From your options-list it will be more p.1, than others (but it's storing changes in database in version-contol, not states)
Just to note another option, in SSDT you can mark the file property as Build Action = None. The file won't be included in the dacpac when this build option is selected. But I tend to agree with the idea that you should rely on your VCS to handle history.

Creating a custom column: "Append-Only" File Upload

I'm trying to make a custom column (for a custom list), where the users can upload files without overwriting the previous - this way they can keep past versions of the files and upload newer ones and the new ones append. There already exist "append only" comment columns and file upload columns that I can see.
I'm working with Sharepoint designer 2007 (2010 doesn't work with the site), and I'm referencing this code I found online somewhere (http://pastebin.com/raw.php?i=0qN89meu), trying to research the Sharepoint documentation on MSDN. I can open the site in designer, but don't know where to go from there (it's already running on a web server, not opening it locally).
I'm just not clear on how to start, I thought there'd be a simple "right+click -> new column" feature but I can't find it. If someone could point me in the right direction to where I could start creating columns on the site, that would be great. Thanks!
An untested idea :
Create a document library with a lookup column to the custom list.
Create an event receiver (ItemAdded and ItemUpdated) than will take the attached files and move them to the other list (with the correct lookup value). --> Code with Visual Studio
Grant to this document library only read permissions.
Adapt the view to display the related documents in the dispform of the custom list.
Advantages:
this seems to answer to your need
you gain all the usability of a document library (nothing prevent you to grant edit rights to other users, force check out, etc.)
Disadvantages:
you have to play with lookup. Can be tricky sometimes, if you play with features
you split one business entity to two entities. You will have to deal with cascading delete (if you need it).

What are the best practices for database scripts under code control

We are currently reviewing how we store our database scripts (tables, procs, functions, views, data fixes) in subversion and I was wondering if there is any consensus as to what is the best approach?
Some of the factors we'd need to consider include:
Should we checkin 'Create' scripts or checkin incremental changes with 'Alter' scripts
How do we keep track of the state of the database for a given release
It should be easy to build a database from scratch for any given release version
Should a table exist in the database listing the scripts that have run against it, or the version of the database etc.
Obviously it's a pretty open ended question, so I'm keen to hear what people's experience has taught them.
After a few iterations, the approach we took was roughly like this:
One file per table and per stored procedure. Also separate files for other things like setting up database users, populating look-up tables with their data.
The file for a table starts with the CREATE command and a succession of ALTER commands added as the schema evolves. Each of these commands is bracketed in tests for whether the table or column already exists. This means each script can be run in an up-to-date database and won't change anything. It also means that for any old database, the script updates it to the latest schema. And for an empty database the CREATE script creates the table and the ALTER scripts are all skipped.
We also have a program (written in Python) that scans the directory full of scripts and assembles them in to one big script. It parses the SQL just enough to deduce dependencies between tables (based on foreign-key references) and order them appropriately. The result is a monster SQL script that gets the database up to spec in one go. The script-assembling program also calculates the MD5 hash of the input files, and uses that to update a version number that is written in to a special table in the last script in the list.
Barring accidents, the result is that the database script for a give version of the source code creates the schema this code was designed to interoperate with. It also means that there is a single (somewhat large) SQL script to give to the customer to build new databases or update existing ones. (This was important in this case because there would be many instances of the database, one for each of their customers.)
There is an interesting article at this link:
https://blog.codinghorror.com/get-your-database-under-version-control/
It advocates a baseline 'create' script followed by checking in 'alter' scripts and keeping a version table in the database.
The upgrade script option
Store each change in the database as a separate sql script. Store each group of changes in a numbered folder. Use a script to apply changes a folder at a time and record in the database which folders have been applied.
Pros:
Fully automated, testable upgrade path
Cons:
Hard to see full history of each individual element
Have to build a new database from scratch, going through all the versions
I tend to check in the initial create script. I then have a DbVersion table in my database and my code uses that to upgrade the database on initial connection if necessary. For example, if my database is at version 1 and my code is at version 3, my code will apply the ALTER statements to bring it to version 2, then to version 3. I use a simple fallthrough switch statement for this.
This has the advantage that when you deploy a new version of your application, it will automatically upgrade old databases and you never have to worry about the database being out of sync with the software. It also maintains a very visible change history.
This isn't a good idea for all software, but variations can be applied.
You could get some hints by reading how this is done with Ruby On Rails' migrations.
The best way to understand this is probably to just try it out yourself, and then inspecting the database manually.
Answers to each of your factors:
Store CREATE scripts. If you want to checkout version x.y.z then it'd be nice to simply run your create script to setup the database immediately. You could add ALTER scripts as well to go from the previous version to the next (e.g., you commit version 3 which contains a version 3 CREATE script and a version 2 → 3 alter script).
See the Rails migration solution. Basically they keep the table version number in the database, so you always know.
Use CREATE scripts.
Using version numbers would probably be the most generic solution — script names and paths can change over time.
My two cents!
We create a branch in Subversion and all of the database changes for the next release are scripted out and checked in. All scripts are repeatable so you can run them multiple times without error.
We also link the change scripts to issue items or bug ids so we can hold back a change set if needed. We then have an automated build process that looks at the issue items we are releasing and pulls the change scripts from Subversion and creates a single SQL script file with all of the changes sorted appropriately.
This single file is then used to promote the changes to the Test, QA and Production environments. The automated build process also creates database entries documenting the version (branch plus build id.) We think this is the best approach with enterprise developers. More details on how we do this can be found HERE
The create script option:
Use create scripts that will build you the latest version of the database from scratch, which is empty except the default lookup data.
Use standard version control techniques to store,branch,tag versions and view histories of your objects.
When upgrading a live database (where you don't want to loose data), create a blank second copy of the database at the new version and use a tool like red-gate's link text
Pros:
Changes to files are tracked in a standard source-code like manner
Cons:
Reliance on manual use of a 3rd party tool to do actual upgrades (no/little automation)
Our company checks them in simply because someone decided to put it in some SOX document that we do. It makes no sense to me at all, except possible as a reference document. I can't see a time we'd pull them out and try and use them again, and if we did we'd have to know which one ran first and which one to run after which. Backing up the database is much more important then keeping the Alter scripts.
for every release we need to give one update.sql file which contains all the new table scripts, alter statements, new/modified packages,roles,etc. This file is used to upgrade the database from 1 version to 2.
What ever we include in update.sql file above one all this statements need to go to individual respective files. like alter statement has to go to table as a new column (table script has to be modifed not Alter statement is added after create table script in the file) in the same way new tables, roles etc.
So whenever if user wants to upgrade he will use the first update.sql file to upgrade.
If he want to build from scrach then he will use the build.sql which already having all the above statements, it makes the database in sync.
sriRamulu
Sriramis4u#yahoo.com
In my case, I build a SH script for this work: https://github.com/reduardo7/db-version-updater
How is an open question
In my case I am trying to create something simple that is easy to use for developers and I do it under the following scheme
Things I tested:
File-based script handling in git using GitlabCI
It does not work, collisions are created and the Administration part has to be done by hand in case of disaster and the development part is too complicated
Use of permissions and access via mysql clients
There is no traceability on changes to the database and the transition to production is manual
Use of programs mentioned here
They require uploading the structures and many adaptations and usually you end up with change control just like the word
Repository usage
Could not control the DRP part
I could not properly control the backups
I don't think it is a good idea to have the backups on the same server and you generate high lasgs for the process
This was what worked best
Manage permissions per user and generate traceability of everything that is sent to the database
Multi platform
Use of development-Production-QA database
Always support before each modification
Manage an open repository for change control
Multi-server
Deactivate / Activate access to the web page or App through Endpoints
the initial project is in:
In case the comment manager reads this part, I understand the self-promotion but please just remove this part and leave the rest since I think it complies with the answer to the question reacted in the post ...
https://hub.docker.com/r/arelis/gitdb
I hope this reaches you since I see that several
There is an interesting article with new URL at: https://blog.codinghorror.com/get-your-database-under-version-control/
It a bit old but the concepts are still there. Good Read!

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