▶️ Create a cluster of AlloyDB in GCP web console.
Certain configuration options remain editable after cluster creation, including connection settings. Access via public IP address necessitates the implementation of an authenticated network. For demonstration purposes, we may just use an plaintext connection.
Data Preparation
This tutorial is designed to be comprehensive and standalone, so it includes steps to populate data in AlloyDB. In practical scenarios, PuppyGraph can query data directly from existing tables in your AlloyDB databases.
▶️ Connect to the database in AlloyDB by tools like psql. The default username and database name are both postgres if you did not change them in the previous step.
The response shows that graph schema has been uploaded successfully:
{"Status":"OK","Message":"Schema uploaded and gremlin server restarted"}
Querying the Graph
In this tutorial we will use the Gremlin query language to query the Graph. Gremlin is a graph query language developed by Apache TinkerPop. Prior knowledge of Gremlin is not necessary to follow the tutorial. To learn more about it, visit https://tinkerpop.apache.org/gremlin.html.
▶️ Click on the Query panel the left side. The Gremlin Query tab offers an interactive environment for querying the graph using Gremlin.
Queries are entered on the left side, and the right side displays the graph visualization.
The first query retrieves the property of the person named "marko".
▶️ Copy the following query, paste it in the query input, and click on the run button.
g.V().has("name", "marko").valueMap()
The output is plain text like the following:
Rows: 1
age 29
name marko
Now let's also leverage the visualization. The next query gets all the software created by people known to "marko".
▶️ Copy the following query, paste it in the query input, and click on the run button.
The output is as follows. There are two paths in the result as "marko" knows "josh" who created "lop" and "ripple".
Alternative: Querying the graph via CLI
Alternatively, we can query the graph via CLI.
▶️ Execute the following command to access the PuppyGraph Gremlin Console
dockerexec-itpuppy./bin/console
The welcome screen appears as follows:
____ ____ _
| _ \ _ _ _ __ _ __ _ _ / ___| _ __ __ _ _ __ | |__
| |_) | | | | | | '_ \ | '_ \ | | | | | | _ | '__| / _` | | '_ \ | '_ \
| __/ | |_| | | |_) | | |_) | | |_| | | |_| | | | | (_| | | |_) | | | | |
|_| \__,_| | .__/ | .__/ \__, | \____| |_| \__,_| | .__/ |_| |_|
|_| |_| |___/ |_|
Welcome to PuppyGraph!
version: 0.26
To Learn more about the graph schema:
- Use graph.show() to list all the vertex and edge labels.
- Use graph.show('$FOO') to list all the vertex and edge labels related to $FOO.
- Use graph.describe('$BAR') to list all the attributes of the label $BAR.
See https://tinkerpop.apache.org/gremlin.html to learn more about the Gremlin query language.
Here are some example queries for exploring the graph:
- Use g.V() to list all the vertices.
- Use g.E() to list all the edges.
- Use g.V().count() to get the total number of vertices.
- Use g.E().count() to get the total number of edges.
- Use g.V('$ID').out() to find out vertices that are reachable in 1-hop from the vertex $ID. For example, g.V('person[v1]').out() will find out 1-hop reachable vertices from 'person[v1]'.
- Use g.V('$ID').out().out() similarly to find out 2-hop reachable vertices from the vertex $ID.
puppy-gremlin>
▶️ Run the following queries in the console to query the Graph.