一个导入 Livejournal 数据集到 Nebula Graph 图数据库，并执行 Nebula Algorithm 图算法的过程分享。

Related GitHub Repo: https://github.com/wey-gu/nebula-LiveJournal

nebula-LiveJournal

LiveJournal Dataset is a Social Network Dataset in one file with two columns(FromNodeId, ToNodeId).

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$ head soc-LiveJournal1.txt
# Directed graph (each unordered pair of nodes is saved once): soc-LiveJournal1.txt
# Directed LiveJournal friednship social network
# Nodes: 4847571 Edges: 68993773
# FromNodeId	ToNodeId
0	1
0	2
0	3
0	4
0	5
0	6

It could be accessed in https://snap.stanford.edu/data/soc-LiveJournal1.html.

1 Dataset Download and Preprocessing

1.1 Download

It is accesissiable from the official web page:

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$ cd nebula-livejournal/data
$ wget https://snap.stanford.edu/data/soc-LiveJournal1.txt.gz

Comments in data file should be removed to make the data import tool happy.

1.2 Preprocessing

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$ gzip -d soc-LiveJournal1.txt.gz
$ sed -i '1,4d' soc-LiveJournal1.txt

2 Import dataset to Nebula Graph

2.1 With Nebula Importer

Nebula-Importer is a Golang Headless import tool for Nebula Graph.

You may need to edit the config file under nebula-importer/importer.yaml on Nebula Graph’s address and credential。

Then, Nebula-Importer could be called in Docker as follow:

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$ cd nebula-livejournal

$ docker run --rm -ti \
    --network=nebula-net \
    -v nebula-importer/importer.yaml:/root/importer.yaml \
    -v data/:/root \
    vesoft/nebula-importer:v2 \
    --config /root/importer.yaml

Or if you have the binary nebula-importer locally:

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$ cd data
$ <path_to_nebula-importer_binary> --config ../nebula-importer/importer.yaml

2.2 With Nebula Exchange

Nebula-Exchange is a Spark Application to enable batch and streaming data import from multiple data sources to Nebula Graph.

To be done. (You can refer to https://siwei.io/nebula-exchange-sst-2.x/)

3 Run Algorithms with Nebula Graph

Nebula-Algorithm is a Spark/GraphX Application to run Graph Algorithms with data consumed from files or a Nebula Graph Cluster.

Supported Algorithms for now:

3.1 Ad-hoc Spark Env setup

Here I assume the Nebula Graph was bootstraped with Nebula-Up, thus nebula is running in a Docker Network named nebula-docker-compose_nebula-net.

Then let’s start a single server spark:

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docker run --name spark-master --network nebula-docker-compose_nebula-net \
    -h spark-master -e ENABLE_INIT_DAEMON=false -d \
    -v nebula-algorithm/:/root \
    bde2020/spark-master:2.4.5-hadoop2.7

Thus we could make spark application submt inside this container:

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docker exec -it spark-master bash
cd /root/
# download Nebula-Algorithm Jar Packagem, 2.0.0 for example, for other versions, refer to nebula-algorithm github repo and documentations.
wget https://repo1.maven.org/maven2/com/vesoft/nebula-algorithm/2.0.0/nebula-algorithm-2.0.0.jar

3.2 Run Algorithms

There are many altorithms supported by Nebula-Algorithm, here some of their configuration files were put under nebula-algorithm as an example.

Before using them, please first edit and change Nebula Graph Cluster Addresses and credentials.

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vim nebula-altorithm/algo-pagerank.conf

Then we could enter the spark container and call corresponding algorithms as follow.

Please adjust your --driver-memeory accordingly, i.e. pagerank altorithm:

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/spark/bin/spark-submit --master "local" --conf spark.rpc.askTimeout=6000s \
    --class com.vesoft.nebula.algorithm.Main \
    --driver-memory 16g nebula-algorithm-2.0.0.jar \
    -p pagerank.conf

After the algorithm finished, the output will be under the path insdie the container defined in conf file:

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    write:{
        resultPath:/output/
    }

题图版权：@sigmund