I created a simple model and I started many processes, they are waiting the approval. While they are waiting if I update my diagram, what happens to these processes? And how can I update the diagram? I tried edit model and saved, but it didn't change.
Every definition has version. All process instances running based on definition with old version. You can migrate all runnig instances to new version of definition by org.activiti.engine.impl.cmd.SetProcessDefinitionVersionCmd.
http://forums.activiti.org/content/migrating-process-instances-newer-versions
But be careful
This command will NOT perform any migration magic and simply set the process definition version in the database, assuming that the user knows, what he or she is doing.
Related
While configuring a particular data pipeline in Mosaic Decisions, I want to try out different operations by using the available process nodes. I would like to keep the first few configured nodes for future reference and continue to add some other nodes.
To do this, I'm currently cloning the flow after each incremental change. But, due to this, many flows are getting configured and it becomes very difficult to keep track.
Is there any alternative way to save the history of these multiple configurations of the flow for future reference without cloning and executing them separately?
You can save the history of changes you have made in the flow by simply saving it as a version using Save As Version option provided in the canvas header.
You can also add a description for each of the incremental steps and edit a particular version later if you want. Later, you can also execute each of the saved versions separately by publishing that version from the Version tab and then
executing it normally.
We are facing an issue with Camunda orchestrator restarts.
We lose all decision rules of DMNs after deploying new versions of processes.
Could you please suggest if possible an out of the box solution to save rules and reload them after restart, if not possible an explanation of how to do it is OK also ?
Thanks
I guess you have one version of the dmn in your src/main/resources, so it's auto deployed on start ... and then deploy updated versions "on the fly" via REST.
You have to update the table in resources as well or disable auto-deployment to not overwrite your ad-hoc changes again.
Please also see: Camunda load BPMN XML from database
The same explanation applies to any kind of model (BPMN,DMN,CMMN)
I have some processes that ran with old process definitions. But due to requirement change the user task data has been updated with new attributes and this process definition has been deployed. I'm aware that "SetProcessDefinitionVersionCmd" can be set to "yes" to point the processes to the new definition/version.
I would like to know how to migrate the old process data to have the newly added attributes of the user task updated in them?
There is no easy way to migrate process instance data, however, when you set the version to the new process definition the instance data will go with the migrated instance.
What you have to be careful of is to make sure you include null checks for any of the data that may not be present in the migrated process instances.
Hope this helps,
Greg
Indeed there is no easy way for migration, however depending on the differences between the two definitions and to what extend you may not prefer to use SetProcessDefinitionVersionCmd, you may find DynamicBpmnService useful when combined with detecting definitions' versions inside your logic.
And yes another way would be to use SetProcessDefinitionVersionCmd but be extra cautions for tasks that were actually active prior to migration, as Activiti's database model have some redundant data (some for performance reasons), you are better studying the DB tables first for these tasks and then inspecting the before and after migration state. For example, keeping up with a simple changed attribute is much easier than an added boundary event on an active User Task, which affects the "execution tree".
I would also advice to compare SetProcessDefinitionVersionCmd's implementations between Activiti and Camunda, it is sad to have such enhancements efforts separated, but that is another story.
I work in an Oracle instance that has hundreds of schemas and multiple developers. We have a development instance where developers can integrate their work before test or production.
We want to have source control for all the DDL run in this integrated development database. Currently this is done through a product Red Gate which we run manually after we make a change to the database. Redgate finds the changes between what is in the schema and what was last checked into source control and makes a script of the differences and puts this into source control.
The problem however is of course that running regdate can take some time and people run it infrequently or not at all for small changes. Also redgate will only look in one schema at a time and it would be VERY time consuming to manually run it against all schemas to guarantee that they are up to date. However if the source controlled code cannot be relied upon it becomes less useful...
What would seem to be ideal would be to have some software that could periodically (even once a day), or when triggered by DDL being run, update the source control (preferably github as this is used by other teams) from all the schemas.
I cannot seem to see any existing software which can be simply used to do this.
Is there a problem with doing this? (there is no need to address multiple developers overwriting each others work on the same day as we have this covered in a separate process) Is anyone doing this? Can anyone recommend a way to do this?
We do this with help of a PL/SQL function, a python script and a shell script:
The PL/SQL function can generate the DDL of a whole schema and returns this as CLOB
The python script connects to the database, fetches the DDL and stores it in files
The shell script runs the Source Control to add the modifications (we use Bazaar here).
You can see the scripts on PasteBin:
The PL/SQL function is here: http://pastebin.com/AG2Fa9zL
The python program (schema_exporter.py): http://pastebin.com/nd8Lf0gK
The shell script:
The shell script:
python schema_exporter.py
d=$(date +%Y-%m-%d__%H_%M_%S)
bzr add
bzr st | grep -q -E 'added|modified' && commit -m "Database objects on $d"
exit 0
This shell script is configured to run from cron every day.
Being in the database version control space for 5 years (as director of product management at DBmaestro) and having worked as a DBA for over two decades, I can tell you the simple fact that you cannot treat the database objects as you treat your Java, C# or other files and save the changes in simple DDL scripts.
There are many reasons and I'll name a few:
Files are stored locally on the developer’s PC and the change s/he
makes do not affect other developers. Likewise, the developer is not
affected by changes made by her colleague. In database this is
(usually) not the case and developers share the same database
environment, so any change that were committed to the database affect
others.
Publishing code changes is done using the Check-In / Submit Changes /
etc. (depending on which source control tool you use). At that point,
the code from the local directory of the developer is inserted into
the source control repository. Developer who wants to get the latest
code need to request it from the source control tool. In database the
change already exists and impacts other data even if it was not
checked-in into the repository.
During the file check-in, the source control tool performs a conflict
check to see if the same file was modified and checked-in by another
developer during the time you modified your local copy. Again there
is no check for this in the database. If you alter a procedure from
your local PC and at the same time I modify the same procedure with
code form my local PC then we override each other’s changes.
The build process of code is done by getting the label / latest
version of the code to an empty directory and then perform a build –
compile. The output are binaries in which we copy & replace the
existing. We don't care what was before. In database we cannot
recreate the database as we need to maintain the data! Also the
deployment executes SQL scripts which were generated in the build
process.
When executing the SQL scripts (with the DDL, DCL, DML (for static
content) commands) you assume the current structure of the
environment match the structure when you create the scripts. If not,
then your scripts can fail as you are trying to add new column which
already exists.
Treating SQL scripts as code and manually generating them will cause
syntax errors, database dependencies errors, scripts that are not
reusable which complicate the task of developing, maintaining,
testing those scripts. In addition, those scripts may run on an
environment which is different from the one you though it would run
on.
Sometimes the script in the version control repository does not match
the structure of the object that was tested and then errors will
happen in production!
There are many more, but I think you got the picture.
What I found that works is the following:
Use an enforced version control system that enforces
check-out/check-in operations on the database objects. This will
make sure the version control repository matches the code that was
checked-in as it reads the metadata of the object in the check-in
operation and not as a separated step done manually. This also allow
several developers to work in parallel on the same database while
preventing them to accidently override each other code.
Use an impact analysis that utilize baselines as part of the
comparison to identify conflicts and identify if a difference (when
comparing the object's structure between the source control
repository and the database) is a real change that origin from
development or a difference that was origin from a different path and
then it should be skipped, such as different branch or an emergency
fix.
Use a solution that knows how to perform Impact Analysis for many
schemas at once, using UI or using API in order to eventually
automate the build & deploy process.
An article I wrote on this was published here, you are welcome to read it.
To me it seems like your way of working is backwards: developers run DDL against the DB in an unordered fashion and then you need an automated tool for inferring the changes (and the DDL) that was run.
The process would be in better control if you did the following instead:
Developers write DDL as SQL scripts, preferably using a migration tool such as Flyway (http://flywaydb.org/documentation/migration/sql.html).
Migration scripts are checked into version control
Migration scripts are periodically run against the DB (e.g. by the migration tool)
In this workflow, the DB would only get altered through automated migration scripts and no-one is allowed to do changes manually. Could this work for you?
(I develop the Oracle tools for Redgate)
Actually using the tools you can already what I think you're asking for using Schema Compare for Oracle.
You can compare multiple schemas either in the UI or via the command line - I think what you're after is automating the command line tool which can create difference scripts, sync between source and destination (live, snapshot or scripts) and generate reports.
You can automate the command line to sync to a scripts folder which is your source code checkout and then subsequently run a command to commit the changes.
I think that's all good :)
We built a commerical tool that bridges Oracle with Git. It helps you manage your database objects with Git. Basically, the database becomes the working directory for the developer. You can perform git operations in the database such as reset, commit, branch, merge etc... and the database code is updated automatically. It might be worth taking a look: https://www.gitora.com
I have a small set of scripts that manage the build/test/deployment of an app. Recently I decided I wanted to switch to Liquibase for db schema management. This script will be working both on the developer machines where it regularly blow away and rebuild their database and also on deployed environment where we will only be adding new changesets.
When this program first runs on a deployed environment I need to detect if Liquibase has run or not and then run changelogSync to sync with the existing tables.
Other than manually checking if the database changelog table exists is there a way for the Liquibase API to let me know that it has already run at least once?
I'm using the Java core library in Groovy
The easiest way is probably ((StandardChangeLogHistoryService) ChangeLogHistoryServiceFactory.getInstance().getChangeLogService(database)).hasDatabaseChangeLogTable()
The ChangeLogHistoryService interface returned by liquibase.changelog.ChangeLogHistoryServiceFactory doesn't have a method to check if the table exists, but the StandardChangeLogHistoryService implementation does.