These are the instructions for installing and using the DataStax Graph Labs preview using Docker images.
For the downloadable tarball version of the Graph preview, refer to the DataStax Labs website and download DataStax Graph (DSG). Then follow the instructions with the included README.md from the download.
The use of the software described here is subject to the DataStax Labs Terms.
The new, experimental graph engine included in this Labs package allows for users to work seamlessly across Cassandra and Graph APIs while accessing the data stored in Cassandra. This is possible because the experimental graph engine has been embedded into Cassandra's data model metadata. DataStax is calling this novel approach to graph data management, DataStax's OneModel.
Because this is an experimental preview of a new graph engine in DataStax Graph, a subset of documentation is available that describes the new concepts included in DataStax Graph.
Please review the graph-docs directory for an overview of the features, behaviors, and functionality of the experimental and new graph engine.
- DSP-19261 - T values get hidden by property keys of the same name in valueMap()
- DSP-19260 - Dev traversal source - see the github repo GettingStarted.md doc file for details
- DSP-19148 - Edge label column ordering modified to allow users to specify only a clustering column to get naturally ordered edges.
- DSP-19250 - Edge index
.inverse()syntax to allow easy creation of inverse edges. see the github repo SystemAndSchemaAPI.md#creating-indexes-manually doc for details - DSP-19149 - Fix nested tuple creation
- DSP-19085 - Geo.inside queries fixed
- DSP-19072 - Geometry types inside UDTs and Tuples fixed
- DSP-18915 - UDTs and Tuples may now be indexed using Search. see the github repo NestedAccessOnUdtAndTupleElements.md for details
- DSP-18680 - Warning if trying to query an index that is not ready (not currently visible in Studio)
- DSP-18125 - Unify authorization error behavior. (edited)
- DSP-18708 - DGF support to io() step
In addition to the documentation included here, DataStax is providing a set of Getting Started Studio Notebooks to help users understand the key concepts of the experimental graph engine build sample applications quickly.
Three different Getting Started notebooks are provided in this package:
- DataStax Graph Gremlin - start here for a pure Gremlin experience.
- DataStax Graph CQL as Graph - start here to use CQL to create a new graph.
- DataStax Graph CQL Conversion to Graph - start here to see how to convert an existing CQL keyspace into a graph.
The Studio sample notebooks are already embedded in the Studio Docker image and will be visible once the container is running.
The DataStax Graph engine available in DSE 6.7 and below is now referred to as DataStax's Classic graph engine. If you are interested in learning how to migrate from an existing graph built using the Classic graph engine into a graph that's compatible with the new, experimental graph engine included in DataStax Labs, please contact a DataStax Services professional and a member of DataStax's Graph Practice will be in touch to discuss how DataStax can help.
A simple migration example is available for review in this repo. Please review the contents under graph-migration.
Note: We intentionally do not have a 'latest' tag on the Labs Docker images. Instead they are version tagged to ensure you're using the intended preview version. See the examples below.
To run the Docker examples you must accept and agree to the DataStax
Labs Terms. Setting the DS_LICENSE variable as shown below
indicates your acceptance of those terms.
To download and run the DataStax Enterprise Labs Docker image:
docker run -e DS_LICENSE=accept --name my-dse -d datastaxlabs/datastax-graph:6.8.0.20190724 -s -k -g
This will start DataStax Enterprise Server with Graph, Search and Analytics running (the recommended combination).
After several minutes, DSE should be running. You can confirm this with a nodetool status command:
docker exec -it my-dse dsetool status
In the status message you should see confirmation that the single node is running and that Graph mode is enabled:
DC: dc1 Workload: SearchAnalytics Graph: yes Analytics Master: 172.17.0.2
====================================================================================
Status=Up/Down
|/ State=Normal/Leaving/Joining/Moving
-- Address Load Effective-Ownership Token Rack Health [0,1]
UN 172.17.0.2 124.07 KiB 100.00% -2702044001711757463 rack1 0.20
Refer to datastax/dse-server for more details about running DataStax Enterprise Server in a Docker container.
To download and run the DataStax Studio Labs Docker image:
docker run -e DS_LICENSE=accept --link my-dse --name my-studio -p 9091:9091 -d datastaxlabs/datastax-studio:6.8.0.20190711
This will start DataStax Studio and connect it with the running DataStax Enterprise Server Docker container.
Once Studio has started it should be viewable in a browser at: http://DOCKER_HOST_IP:9091
Refer to datastax/dse-studio for more details about running DataStax Studio in a Docker container.
Use the Docker Compose example file docker-compose.yml provided in
this repo to automate provisioning of a single DSE Graph node with a
single Studio node.
To use Docker Compose you must first signal your acceptance of the
DataStax Labs Terms by uncommenting the DS_LICENSE environment
variable setting under both dse and studio sections:
dse:
image: ...
environment:
- DS_LICENSE=accept
studio:
image: ...
environment:
- DS_LICENSE=accept
The combined environment can be brought up or torn down with Docker Compose commands:
docker-compose up -d
docker-compose down
Then follow the example steps listed above for working with DataStax Enterprise and DataStax Studio.
To write your own applications which work with the DataStax Graph Labs
preview, you'll need special Labs versions of the Java and Python
drivers. Visit the DataStax Labs website and download DataStax
Graph (DSG). Then expand the zip file and refer to the python-driver
and java-driver directories for further instructions.
We want to hear your feedback! Go to the Labs section of the new DataStax Community forums: https://community.datastax.com/spaces/11/index.html
You can also reach out on the Labs forums for any help needed with these installation steps.