The MMS AMP is a hosted application run atop the community version of an Alfresco Enterprise Content Management Server.
NOTE 1: AMPs for Alfresco as built from this maven project are meant to be run by Alfresco Community Edition v5.1.g (AKA 201605-GA)
Per Alfresco's documentation on Modules, Alfresco Module Packages (AMPs) are installed using the Module Management Tool MMT jar file. The latest version of the two AMPs you will be "exploding" into the "alfresco" and "share" WARs resident within the embedded Tomcat server are available via the download links leading to the two interdependent portions named "mms-repo.amp" and "mms-share.amp", relating to "alfresco.war" and "share.war", respectively.
In tandem with the EMS-Webapp (colloquially known as the View Editor), and the Magicdraw Development Kit (MDK) for MagicDraw client and Teamwork Cloud users; this github repo serves as a one-stop shop to set up the Model Management Server per the MMS-MDK-VE Compatibility Matrix.
- ElasticSearch 5.x (Up to 5.5)
- PostgreSQL 9.x (Up to 9.4 is using PostgreSQL for Alfresco)
- ActiveMQ 5.X
- Open Project with root of 'mms'
- Import Maven Project
- Open Project Structure and Import Module "mms-ent" and set to find projects recursively
- Eclipse > File > Import > General > Existing Projects into Workspace
- Set 'Root Directory' as the path to mms e.g. Browse to
$HOME/workspace/mms - In the 'Projects' list, you should see all poms. Click Finish
- Eclipse > File > Import > Maven > Existing Maven Projects
- Set 'Root Directory' as the path to mms e.g. Browse to
$HOME/workspace/mms/mms-ent - In the 'Projects' list, you should see all poms. Click Finish
- Eclipse > Window > Preferences > Maven > Installation
- Toggle Maven 3.X.X
- If Maven 3.X.X is not listed, download and install it.
- On a Mac, install it at /usr/local/Cellar/maven.
- On a Linux, anywhere in your $PATH.
- Return to Eclipse > Window > Preferences > Maven > Installation
- Choose Add...
- Browse and select Maven 3.X.X installed location.
- Location is the maven home that you can get by running the newly installed maven, with mvn -V
- Select mms-ent project
- From menu bar, choose Run > Run Configurations
- Right-click Maven Build > New
- Enter
mmsfor Name textbox - At Main tab
- Enter
${project_loc}or${workspace_loc}for Base Directory textbox - Enter
installfor Goals textbox - Enter
runfor Profiles textbox - Select Maven 3.X.X (whatever you chose to setup in step 2) for Maven Runtime
- Enter
- At JRE tab
- Select Java 8 for JRE.
- If it's not installed, download and install Java 8. Afterward, return to here and select Java 8.
- Enter
- Download ElasticSearch 5.X
- Install ElasticSearch
- Start ElasticSearch then run
mms-ent/repo-amp/src/main/resources/mms-mappings.sh
- Download PostgreSQL 9.x
- If using PostgreSQL as the database for Alfresco, PostgreSQL 9.4 is the latest supported version
- Install PostgreSQL
- Start PostgreSQL server
- Connect to the PostgreSQL server and:
- Create a
mmsuser (referenced by pg.user in yourmms-ent/mms.propertiesfile)- Ensure you set a password (referenced by pg.pass)
- Create a
mmsdatabase ( referenced by pg.name)
- Create a
- Execute
mms-ent/repo-amp/src/main/resources/mms.sql- windows CMD e.g.:
psql -h localhost -p 5432 -U mms -d mms -v schema=public < C:\path\to\mms\repo\mms.sql
- windows CMD e.g.:
- Download ActiveMQ 5.X
- Install ActiveMQ
- Start ActiveMQ service
- Select file menu Run > Run Configurations
- Expand Maven Build
- Select mms
- Click Run button
- If you get error:-Dmaven.multiModuleProjectDirectory system property is not set. Check $M2_HOME environment variable and mvn script match. Goto Window -> Preference -> Java -> Installed JREs -> Edit -> Default VM arguments set -Dmaven.multiModuleProjectDirectory=$M2_HOME
- From mms-ent directory, either run
clean-run.sh,run.sh, or./mvnw install -Prun -Ddependency.surf.version=6.3
- Enter http://localhost:8080/share/ at a browser's url address textbox.
- Enter admin for user name
- Enter admin for password
General Design
+----------------+ \
| REST API Layer | \
|----------------| \
| WebScripts | MMS
|----------------| /
|Storage | Layer | /
+----------------+ /
/\ /\
|| ||
\/ \/
+-----+ +----+
| RDB | | ES |
+-----+ +----+
(Graph) (Data)
- Global PG database called 'mms' holds configuration information per project
- Contains Org, Project, and DB Location information
-
Each project has it's own database configured in the
mmsdatabase -
All graph related information stored in relational database
-
Schema defined in mms.sql
- Nodes
- Edges
- Edge types
- Node types
- Commits
- Refs
-
Functions defined that are recursive for getting parents, children etc.
-
All access to the graph is done via the PostgresHelper that contains functions to interface with the database
-
The graph should never be manipulated directly from anywhere else
The nodes in the graph contain pointers to ElasticSearch documents which contain the real information * Same goes for other things such as configurations or commits
Each of these pointers is the “latest one” * Because for a given SYSMLID there can be multiple documents for each version of that node
The history of each node can be retrieved via a query to ElasticSearch (see ElasticHelper.java)
Nodes and edges both have a type associated with them The type must exist in the NodeTypes and EdgeTypes tables
- Correspondingly, the types also exist in the PostgresHelper code
- Each node can be assigned a particular type, by default it is just element
- Each edge can be assigned a particular type, containment being the basic type
Some assertions about the graph:
- It is always the case that each node in the graph has a single containment parent
- If you have multiple, something wrong happened!
- Multiple root parents are only possible for not containment type edges
- There should never be any orphan nodes in the graph
- Always have either children or parents
- All elastic references in the graph must exist in ES
Structure of the graph for each "project"
+---------+
+--| Commits |
+===+ | +---------+ +-------------+ +----------+
| P | | +---| Holding bin |----| Elements |
| R | | +-------+ | +-------------+ +----------+
| O | +--| Nodes |--------|
| J | | +-------+ | +----------+
| E | | +---| Elements |
| C | --| +-------+ +----------+
| T | +--| Edges |
| | | +-------+
| | |
| | | +----------------+
+===+ +--| Refs |
+----------------+
Create instance of EmsNodeUtil Get all other relevant information, validation, etc. form request Figure out if the elements are to go to the holding bin or not Calculate the qualified name and ID information for each node Add metadata for each element Store elements in ES Update graph Create JSON response and return
Create instance of EmsNodeUtil Get all other relevant information, validation, etc. form request Access PG to get the ElasticSearch IDs for all documents that we are interested in Access ES via ElasticHelper and get those IDs Create JSON response and return
Create instance of EmsNodeUtil Get all other relevant information, validation, etc. form request Understand how to:
- Add information to ES
- Update the graph with the corresponding information from ES
All the work is to be done here for each webscript. The pre and post should always be the same.
Create JSON response and return
Use the following curl commands to post an initial organization + project:
curl -w "\n%{http_code}\n" -H "Content-Type: application/json" -u admin:admin --data '{"orgs": [{"id": "vetest", "name": "vetest"}]}' -X POST "http://localhost:8080/alfresco/service/orgs"
curl -w "\n%{http_code}\n" -H "Content-Type: application/json" -u admin:admin --data '{"projects": [{"id": "123456","name": "vetest","type": "Project"}]}' -X POST "http://localhost:8080/alfresco/service/orgs/vetest/projects"
Then you can post some elements. For convenience, there is a json file in runner/src/test/robotframework/JsonData. Using the project from above:
curl -w "\n%{http_code}\n" -H "Content-Type: application/json" -u admin:admin --data @JsonData/PostNewElements.json -X POST "http://localhost:8080/alfresco/service/projects/123456/refs/master/elements"
Make sure the elements went in:
curl -w "\n%{http_code}\n" -H "Content-Type: application/json" -u admin:admin -X GET "http://localhost:8080/alfresco/service/projects/123456/refs/master/elements/123456?depth=-1"
Robot tests can be run with the following maven profiles in the mms-ent directory:
./mvnw install -Prun,robot-tests
Please note that tests should be run on a clean instance, therefore, it may be helpful to run clean.sh before running the tests
The Robotframework tests require the 'requests' and 'robotframework-requests' python modules. Install it as follows:
pip install --target=runner/src/test/robotframework/libraries requests
pip install --target=runner/src/test/robotframework/libraries robotframework-requests
OR:
pip install --target=$HOME/.m2/repository/org/robotframework/robotframework/{ROBOTPLUGINVERSION}/Lib requests
pip install --target=$HOME/.m2/repository/org/robotframework/robotframework/{ROBOTPLUGINVERSION}/Lib robotframework-requests
If you need to change debug levels on the fly, use the following endpoint.
alfresco/service/loglevel
It takes as input JSON that specifies the classes and the log levels. For example:
[
{
"classname": "gov.nasa.jpl.view_repo.webscripts.ModelGet",
"loglevel": "DEBUG"
}
]
API Documentation is located at the following endpoints:
Swagger CodeGen:
alfresco/mms/index.html
Swagger UI:
alfresco/mms/swagger-ui/index.html
Swagger YAML file:
alfresco/mms/mms.swagger.yaml
For versions after 3.2, most notably 3.3.0, an automigration step has been included to run necessary migrations automatically during the initial startup of alfresco after the upgrade. Should this migration fail for any reason, you can trigger the migration manually by accessing the following endpoint:
alfresco/service/migrate/{targetVersion}
where {targetVersion} is the version that you are upgrading to. Example:
alfresco/service/migrate/3.3.0
This operation is idempotent and can be safely run multiple times.
For deploying MMS and VE five machines are recommended + 1 optional TeamWorkCloud machine.
The given configuration below are in terms of AWS instances which define required CPU and RAM, assuming CentOS as operating system.
Data is stored using Amazon EBS volumes, where 100GB is a good start.
For Postgres Amazon's RDS service is used, where 10-15 GB is a good start.
The minimal configuration (can handle about 300k elements) is
- 1x t3.large for MMS (8GB)
- 1x t3.large for RDS postgres service (8GB)
- 3x t3.medium for Elastic cluster (4GB), t3.large for better performance.
- 1x AWS elb service - load balancer for elastic cluster
- EBS storage for data (100 GB)
For a single machine configuration you need one which is powerful enough to cover the above.
A 64 GB configuration can hold about 2 billion elements but might be slow, so you might want to switch to a powerful CPU configuration:
t3.xlarge -> r5.large -> r5.xlarge
To learn how you can get involved in a variety of ways, please see Contibuting to OpenMBEE.
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