I have a Bugzilla installation and I would like to clean the bugs, projects, components etc from it to start clean. But I would like to keep the users and other settings. How would I best do this so I don't fragment the installation?
The fastest way, for me, was simply to delete all the tables in the database. Most of the settings are kept in other places. Then run ./check-setup.pl script again and it will create the tables again. You could save the users table and add the users back once the script is done to avoid having to create all of the users again if you have many.
Related
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?
I have multiple databases in my local which I do not need. Can I run a curl script or a REST API command where I can delete the database, it's servers and all of the forests so that I can use gradle to just deploy them again?
I have tried to manually delete the server first, then the database and then the forests. This is a lengthy process.
I want a single command to do the whole job for me instead of manually having to delete the components one by one which is possible through the admin interface.
Wagner Michael has a fair point in his comment. If you already used (ml-)Gradle to create servers and databases, why not use its mlUndeploy -Pconfirm=true task to get rid of them? You could potentially even use a fake project, with stub configs to get rid of a fairly random set of databases and servers, though that still takes some manual work.
By far the quickest way to reset your entire MarkLogic, is to stop it, and wipe its data directory. This SO question gives instructions on how to do it, as part of a solution to recover when you lost your admin password:
https://stackoverflow.com/a/27803923/918496
HTH!
I've inherited the maintenance of a DotNetNuke (v6.2.0.1610) site, and one of the things I'd like to do is to tidy up the database tables being used.
It looks like there might have been two installations of DNN into the same database (I'm guessing, I don't know its history and cannot find out), I'm making this assumption because there are two sets of DotNetNuke tables.
For example, we have:
dbo.Portals, dbo.PortalSettings, dbo.Profile, dbo.Roles, etc.
However, then we also have the same set, prefixed with dnn_ -
dbo.dnn_Portals, dbo.dnn_PortalSettings, dbo.dnn_Profile, dbo.dnn_Roles, etc.
I spent a good while tearing my hair out when I could not get our portal to load, when I discovered it is because I was editing the dbo.PortalAlias table and I needed to be editing the dbo.dnn_PortalAlias table instead.
I wanted to avoid this future maintenance headache, so I backed up the database, and set about deleting all the tables without the dnn_ prefix (web.config specifies objectQualifier="dnn_"). I diligently ensured there was a matching dnn_ table before deleting any.
At first it seemed fine - the portal loaded and all the content was there, I thought I was on to a winner. However when I logged in and accessed the site admin section, that's when I started to get lots of error messages. So I figured I'd deleted too much, I restored the backup, and all is well - portal working again.
However, I really would like to get rid of the unnecessary tables, because no doubt at some point in the future I'll start doing some work on the database, forget about the dnn_ prefix and waste a bunch of time wondering why something isn't working.
So, as a bit of a DotNetNuke newbie, I'm after some help - how can I know what tables are in use, what aren't, and how can I set about tidying up the SQL Server tables? Thanks.
I suggest you to delete only the tables which have an equivalent with the "dnn_" prefix.
The DNN database should contain at least the "aspnet_" prefixed tables which are used for the authentication on the portals.
Then, you could have some extensions which could use tables without the "dnn_" prefix. It depends on the sql scripts that those extensions have used during their installation. I hope that those extensions don't run queries on the dnn tables without the "dnn_" prefix. Otherwise it could explain the errors you've encountered.
You could use the SQL Server Profiler to check it.
It turns out there was a view, dnn_Lists which was still referencing dbo.Lists without the dnn_ prefix.
I fixed this view and it's fine now.
(PS: Turns out that it's useful to set IsSuperUser = 1 in the users table for who you're logged in as, because then you get the full exception details and can fix it.)
Thanks
It would make sense to delete all tables WITHOUT "dnn_", but you said you got a problem.
If you have time and patience and is adamant about tiding things up, I would delete 1 table at a time and test the admin feature it broke last time until you find the culprit. That is a long shot, but that is how I would approach.
What might be happening here is that you may have a 3rd module installed that ignores the objectQualifier and when you deleted those tables, you then broke that module.
We are building a webapp which is shipped to several client as a debian package. Each client runs his own server. But the update and support is done by us.
We make regular releases of the product, with a clean version number. Most of the users get an automatic update (by Puppet), some others don't.
We want to keep a trace of the version of the application (in order to allow the user to check the version in an "about" section, and for our support to help the user more accurately).
We plan to store the version of the code and the version of the base in our database, and to keep the info up to date automatically.
Is that a good idea ?
The other alternative we see is a file.
EDIT : The code and database schema are updated together. ( if we update to version x.y.z , both code and database go to x.y.z )
Using a table to track every change to a schema as described in this post is a good practice that I'd definitely suggest to follow.
For the application, if it is shipped independently of the database (which is not clear to me), I'd embed a file in the package (and thus not use the database to store the version of the web application).
If not and thus if both the application and the database versions are maintained in sync, then I'd just use the information stored in the database.
As a general rule, I would have both, DB version and application version. The problem here is how "private" is the database. If the database is "private" to the application, and user never modifies the schema then your initial solution is fine. In my experience, databases which accumulate several years of data stop being private, it means that users add a table or two and access data using some reporting tool; from that point on the database is not exclusively used by the application any more.
UPDATE
One more thing to consider is users (application) not being able to connect to the DB and calling for support. For this case it would be better to have version, etc.. stored on file system.
Assuming there are no compelling reasons to go with one approach or the other, I think I'd go with keeping them in the database.
I'd put them in both places. Then when running your about function you quickly check that they are both the same, and if they aren't you can display extra information about the version mismatch. If they're the same then you will only need to display one of them.
I've generally found users can do "clever" things like revert databases back to old versions by manually copying directories around "because they can" so defensively dealing with it is always a good idea.
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!