This guide gives you a quick start to use GraphScope for graph interactive tasks on your local machine.
GIE works as the core component of GraphScope. Therefore, you should install GraphScope at first to use GIE.
GraphScope provides python interface which requires:
Python3.7 ~ 3.11
gcc 7.1+ or Apple Clang
And it is tested on the following 64-bit operating systems:
Ubuntu 18.04 or later
CentOS 7 or later
macOS 11 (Intel) / macOS 12 (Apple silicon) or later, with both Intel chip and Apple M1 chip
If your environment satisfies the above requirement, you can easily install GraphScope through pip:
python3 -m pip install graphscope --upgrade
If the download is very slow, try to use a mirror site for the pip.
python3 -m pip install graphscope --upgrade \ -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host=mirrors.aliyun.com
However, GraphScope requires specific versions for some packages, so you may meet some conflicts and errors during the installation. Therefore, we strongly recommend you to install GraphScope in a clean Python virtual environment with Python 3.9.
We refer you to the official guide for Python virtual environment, and the following is a step by step instruction:
# Create a new virtual environment python3.9 -m venv tutorial-env # Activate the virtual environment source tutorial-env/bin/activate # Install GraphScope python3.9 -m pip install graphscope # Use Graphscope python3.9 >>> import graphscope as gs >>> ......
Running GraphScope Interactive Engine on Local#
It’s fairly straightforward to run interactive queries using the
graphscope package on
your local machine. First of all, you import
graphscope in a Python session, and load
the modern graph, which has been widely used in Tinkerpop demos.
import graphscope as gs from graphscope.dataset.modern_graph import load_modern_graph gs.set_option(show_log=True) # load the modern graph as example. graph = load_modern_graph() # Hereafter, you can use the `graph` object to create an `gremlin` query session g = gs.gremlin(graph) # then `execute` any supported gremlin query. q1 = g.execute('g.V().count()') print(q1.all()) # should print  q2 = g.execute('g.V().hasLabel(\'person\')') print(q2.all()) # should print [[v, v, v, v]]
You may see something like:
... ... [INFO][coordinator:453]: Built interactive frontend xxx.xxx.xxx.xxx:pppp for graph xxx ... [INFO][op_executor:455]: execute gremlin query  ... ... [INFO][op_executor:455]: execute gremlin query [v, v, v, v] ...
The number 6 is printed, which is the number of vertices in modern graph.
What’s the Next#
As shown in the above example, it is very easy to use GraphScope to interactively query a graph using the gremlin query language on your local machine. You may find more tutorials here for the basic Gremlin usage, in which most read-only queries can be seamlessly executed with the above
In addition to the above local-machine entr’ee, we have prepared the following topics for your reference.
GIE can handle much complex cases, for example, the complex LDBC business intelligence workloads. A walk-through tutorial is here!
GIE can be deployed in a distributed environment to process very large graph. How to do that?
GIE has supported a lot of standard Gremlin steps, together with many useful syntactic sugars. Please look into the details!
Want to learn more about the technique details of GIE. This is the design and architecture of GIE!