ngdi 0.2.6

Data Intelligence Suite with 4 line code to run Graph Algo on NebulaGraph

Documentation: https://github.com/wey-gu/nebulagraph-di#documentation

Source Code: https://github.com/wey-gu/nebulagraph-di

NebulaGraph Data Intelligence Suite for Python (ngdi) is a powerful Python library that offers APIs for data scientists to effectively read, write, analyze, and compute data in NebulaGraph.

With the support of single-machine engine(NetworkX), or distributed computing environment using Spark we could perform Graph Analysis and Algorithms on top of NebulaGraph in less than 10 lines of code, in unified and intuitive API.

Quick Start in 5 Minutes

• Setup env with Nebula-Up following this guide.
• Install ngdi with pip from the Jupyter Notebook with http://localhost:8888 (password: nebula).
• Open the demo notebook and run cells one by one.
• Check the API Reference

Installation

pip install ngdi

Usage

Call from nGQL

See more details in docs

RETURN ngdi("pagerank", ["follow"], ["degree"], "spark",
    {space: "basketballplayer", max_iter: 10}, {write_mode: "insert"})

Spark Engine Examples

See also: examples/spark_engine.ipynb

Run Algorithm on top of NebulaGraph:

Note, there is also query mode, refer to examples or docs for more details.

from ngdi import NebulaReader

# read data with spark engine, scan mode
reader = NebulaReader(engine="spark")
reader.scan(edge="follow", props="degree")
df = reader.read()

# run pagerank algorithm
pr_result = df.algo.pagerank(reset_prob=0.15, max_iter=10)

Write back to NebulaGraph:

from ngdi import NebulaWriter
from ngdi.config import NebulaGraphConfig

config = NebulaGraphConfig()

properties = {"louvain": "cluster_id"}

writer = NebulaWriter(
    data=df_result, sink="nebulagraph_vertex", config=config, engine="spark")
writer.set_options(
    tag="louvain", vid_field="_id", properties=properties,
    batch_size=256, write_mode="insert",)
writer.write()

Then we could query the result in NebulaGraph:

MATCH (v:louvain)
RETURN id(v), v.louvain.cluster_id LIMIT 10;

NebulaGraph Engine Examples(not yet implemented)

Basically the same as Spark Engine, but with engine="nebula".

- reader = NebulaReader(engine="spark")
+ reader = NebulaReader(engine="nebula")

Documentation

Environment Setup

API Reference

How it works

ngdi is an unified abstraction layer for different engines, the current implementation is based on Spark, NetworkX, DGL and NebulaGraph, but it's easy to extend to other engines like Flink, GraphScope, PyG etc.

          ┌───────────────────────────────────────────────────┐
          │   Spark Cluster                                   │
          │    .─────.    .─────.    .─────.    .─────.       │
          │   ;       :  ;       :  ;       :  ;       :      │
       ┌─▶│   :       ;  :       ;  :       ;  :       ;      │
       │  │    ╲     ╱    ╲     ╱    ╲     ╱    ╲     ╱       │
       │  │     `───'      `───'      `───'      `───'        │
  Algo Spark                                                  │
    Engine└───────────────────────────────────────────────────┘
       │  ┌────────────────────────────────────────────────────┬──────────┐
       └──┤                                                    │          │
          │   NebulaGraph Data Intelligence Suite(ngdi)        │ ngdi-api │◀─┐
          │                                                    │          │  │
          │                                                    └──────────┤  │
          │     ┌────────┐    ┌──────┐    ┌────────┐   ┌─────┐            │  │
          │     │ Reader │    │ Algo │    │ Writer │   │ GNN │            │  │
 ┌───────▶│     └────────┘    └──────┘    └────────┘   └─────┘            │  │
 │        │          │            │            │          │               │  │
 │        │          ├────────────┴───┬────────┴─────┐    └──────┐        │  │
 │        │          ▼                ▼              ▼           ▼        │  │
 │        │   ┌─────────────┐ ┌──────────────┐ ┌──────────┐┌──────────┐   │  │
 │     ┌──┤   │ SparkEngine │ │ NebulaEngine │ │ NetworkX ││ DGLEngine│   │  │
 │     │  │   └─────────────┘ └──────────────┘ └──────────┘└──────────┘   │  │
 │     │  └──────────┬────────────────────────────────────────────────────┘  │
 │     │             │        Spark                                          │
 │     │             └────────Reader ────────────┐                           │
 │  Spark                   Query Mode           │                           │
 │  Reader                                       │                           │
 │Scan Mode                                      ▼                      ┌─────────┐
 │     │  ┌───────────────────────────────────────────────────┬─────────┤ ngdi-udf│◀─────────────┐
 │     │  │                                                   │         └─────────┤              │
 │     │  │  NebulaGraph Graph Engine         Nebula-GraphD   │   ngdi-GraphD     │              │
 │     │  ├──────────────────────────────┬────────────────────┼───────────────────┘              │
 │     │  │                              │                    │                                  │
 │     │  │  NebulaGraph Storage Engine  │                    │                                  │
 │     │  │                              │                    │                                  │
 │     └─▶│  Nebula-StorageD             │    Nebula-Metad    │                                  │
 │        │                              │                    │                                  │
 │        └──────────────────────────────┴────────────────────┘                                  │
 │                                                                                               │
 │    ┌───────────────────────────────────────────────────────────────────────────────────────┐  │
 │    │ RETURN ngdi("pagerank", ["follow"], ["degree"], "spark", {space: "basketballplayer"}) │──┘
 │    └───────────────────────────────────────────────────────────────────────────────────────┘
 │  ┌─────────────────────────────────────────────────────────────┐
 │  │ from ngdi import NebulaReader                               │
 │  │                                                             │
 │  │ # read data with spark engine, scan mode                    │
 │  │ reader = NebulaReader(engine="spark")                       │
 │  │ reader.scan(edge="follow", props="degree")                  │
 └──│ df = reader.read()                                          │
    │                                                             │
    │ # run pagerank algorithm                                    │
    │ pr_result = df.algo.pagerank(reset_prob=0.15, max_iter=10)  │
    │                                                             │
    └─────────────────────────────────────────────────────────────┘  

Spark Engine Prerequisites

• Spark 2.4, 3.0(not yet tested)
• NebulaGraph 3.4+
• NebulaGraph Spark Connector 3.4+
• NebulaGraph Algorithm 3.1+

NebulaGraph Engine Prerequisites

• NebulaGraph 3.4+
• NebulaGraph Python Client 3.4+
• NetworkX

License

This project is licensed under the terms of the Apache License 2.0.