本文尝试分享下以最小方式(单机、容器化 Spark、Hadoop、Nebula Graph),快速趟一下 Nebula Exchange 中 SST 写入方式的步骤。本文适用于 v2.5 以上版本的 Nebula- Exchange。
原文链接:
什么是 Nebula Exchange?
之前我在 Nebula Data Import Options 之中介绍过,Nebula Exchange 是一个 Nebula Graph 社区开源的 Spark Applicaiton,它专门用来支持批量或者流式地把数据导入 Nebula Graph Database 之中。
Nebula Exchange 支持多种多样的数据源(从 Apache Parquet、ORC、JSON、CSV、HBase、Hive MaxCompute 到 Neo4j、MySQL、ClickHouse,再有 Kafka、Pulsar,更多的数据源也在不断增加之中)。
image.png如上图所示,在 Exchange 内部,从除了不同 Reader 可以读取不同数据源之外,在数据经过 Processor 处理之后通过 Writer写入(sink) Nebula Graph 图数据库的时候,除了走正常的 ServerBaseWriter 的写入流程之外,它还可以绕过整个写入流程,利用 Spark 的计算能力并行生成底层 RocksDB 的 SST 文件,从而实现超高性能的数据导入,这个 SST 文件导入的场景就是本文带大家上手熟悉的部分。
详细信息请参阅:Nebula Graph 手册:什么是 Nebula Exchange
Nebula Graph 官方博客也有更多 Nebula Exchange 的实践文章
步骤概观
- 实验环境
- 配置 Exchange
- 生成 SST 文件
- 写入 SST 文件到 Nebula Graph
实验环境准备
为了最小化使用 Nebula Exchange 的 SST 功能,我们需要:
- 搭建一个 Nebula Graph 集群,创建导入数据的 Schema,我们选择使用 Docker-Compose 方式、利用 Nebula-Up 快速部署,并简单修改其网络,以方便同样容器化的 Exchange 程序对其访问。
- 搭建容器化的 Spark 运行环境
- 搭建容器化的 HDFS
1. 搭建 Nebula Graph 集群
借助于 Nebula-Up 我们可以在 Linux 环境下一键部署一套 Nebula Graph 集群:
curl -fsSL nebula-up.siwei.io/install.sh | bash
无依赖单机尝鲜 Nebula Exchange 的 SST 导入
待部署成功之后,我们需要对环境做一些修改,这里我做的修改其实就是两点:
- 只保留一个 metaD 服务
- 起用 Docker 的外部网络
详细修改的部分参考附录一
应用 docker-compose 的修改:
cd ~/.nebula-up/nebula-docker-compose
vim docker-compose.yaml # 参考附录一
docker network create nebula-net # 需要创建外部网络
docker-compose up -d --remove-orphans
之后,我们来创建要测试的图空间,并创建图的 Schema,为此,我们可以利用 nebula-console ,同样,Nebula-Up 里自带了容器化的 nebula-console。
- 进入 Nebula-Console 所在的容器
~/.nebula-up/console.sh
/ #
- 在 console 容器里发起链接到图数据库,其中
192.168.x.y
是我所在的 Linux VM 的第一个网卡地址,请换成您的
/ # nebula-console -addr 192.168.x.y -port 9669 -user root -p password
[INFO] connection pool is initialized successfully
Welcome to Nebula Graph!
- 创建图空间(我们起名字叫
sst
),以及 schema
create space sst(partition_num=5,replica_factor=1,vid_type=fixed_string(32));
:sleep 20
use sst
create tag player(name string, age int);
示例输出
(root@nebula) [(none)]> create space sst(partition_num=5,replica_factor=1,vid_type=fixed_string(32));
Execution succeeded (time spent 1468/1918 us)
(root@nebula) [(none)]> :sleep 20
(root@nebula) [(none)]> use sst
Execution succeeded (time spent 1253/1566 us)
Wed, 18 Aug 2021 08:18:13 UTC
(root@nebula) [sst]> create tag player(name string, age int);
Execution succeeded (time spent 1312/1735 us)
Wed, 18 Aug 2021 08:18:23 UTC
2. 搭建容器化的 Spark 环境
利用 big data europe 做的工作,这个过程非常容易。
值得注意的是:
- 现在的 Nebula Exchange 对 Spark 的版本有要求,在现在的 2021 年 8 月,我是用了 spark-2.4.5-hadoop-2.7 的版本。
- 为了方便,我让 Spark 运行在 Nebula Graph 相同的机器上,并且指定了运行在同一个 Docker 网络下
docker run --name spark-master --network nebula-net \
-h spark-master -e ENABLE_INIT_DAEMON=false -d \
bde2020/spark-master:2.4.5-hadoop2.7
然后,我们就可以进入到环境中了:
docker exec -it spark-master bash
进到 Spark 容器中之后,可以像这样安装 maven:
export MAVEN_VERSION=3.5.4
export MAVEN_HOME=/usr/lib/mvn
export PATH=$MAVEN_HOME/bin:$PATH
wget http://archive.apache.org/dist/maven/maven-3/$MAVEN_VERSION/binaries/apache-maven-$MAVEN_VERSION-bin.tar.gz && \
tar -zxvf apache-maven-$MAVEN_VERSION-bin.tar.gz && \
rm apache-maven-$MAVEN_VERSION-bin.tar.gz && \
mv apache-maven-$MAVEN_VERSION /usr/lib/mvn
还可以这样在容器里下载 nebula-exchange 的 jar
包:
cd ~
wget https://repo1.maven.org/maven2/com/vesoft/nebula-exchange/2.1.0/nebula-exchange-2.1.0.jar
3. 搭建容器化的 HDFS
同样借助 big-data-euroupe 的工作,这非常简单,不过我们要做一点修改,让它的 docker-compose.yml
文件里使用 nebula-net
这个之前创建的 Docker 网络。
详细修改的部分参考附录二
git clone https://github.com/big-data-europe/docker-hadoop.git
cd docker-hadoop
vim docker-compose.yml
docker-compose up -d
配置 Exchange
这个配置主要填入的信息就是 Nebula Graph 集群本身和将要写入数据的 Space Name,以及数据源相关的配置(这里我们用 csv
作为例子),最后再配置输出(sink)为 sst
- Nebula Graph
- GraphD 地址
- MetaD 地址
- credential
- Space Name
- 数据源
-
source: csv
path
-
fields
etc.
ink: sst
-
详细的配置参考附录二
注意,这里 metaD 的地址可以这样获取,可以看到 0.0.0.0:49377->9559
表示 49377
是外部的地址。
$ docker ps | grep meta
887740c15750 vesoft/nebula-metad:v2.0.0 "./bin/nebula-metad …" 6 hours ago Up 6 hours (healthy) 9560/tcp, 0.0.0.0:49377->9559/tcp, :::49377->9559/tcp, 0.0.0.0:49376->19559/tcp, :::49376->19559/tcp, 0.0.0.0:49375->19560/tcp, :::49375->19560/tcp nebula-docker-compose_metad0_1
生成 SST 文件
1. 准备源文件、配置文件
docker cp exchange-sst.conf spark-master:/root/
docker cp player.csv spark-master:/root/
其中 player.csv
的例子:
1100,Tim Duncan,42
1101,Tony Parker,36
1102,LaMarcus Aldridge,33
1103,Rudy Gay,32
1104,Marco Belinelli,32
1105,Danny Green,31
1106,Kyle Anderson,25
1107,Aron Baynes,32
1108,Boris Diaw,36
1109,Tiago Splitter,34
1110,Cory Joseph,27
1111,David West,38
2. 执行 exchange 程序
进入 spark-master
容器,提交执行 exchange
应用。
docker exec -it spark-master bash
cd /root/
/spark/bin/spark-submit --master local \
--class com.vesoft.nebula.exchange.Exchange nebula-exchange-2.1.0.jar\
-c exchange-sst.conf
检查执行结果:
spark-submit
输出:
21/08/17 03:37:43 INFO TaskSetManager: Finished task 31.0 in stage 2.0 (TID 33) in 1093 ms on localhost (executor driver) (32/32)
21/08/17 03:37:43 INFO TaskSchedulerImpl: Removed TaskSet 2.0, whose tasks have all completed, from pool
21/08/17 03:37:43 INFO DAGScheduler: ResultStage 2 (foreachPartition at VerticesProcessor.scala:179) finished in 22.336 s
21/08/17 03:37:43 INFO DAGScheduler: Job 1 finished: foreachPartition at VerticesProcessor.scala:179, took 22.500639 s
21/08/17 03:37:43 INFO Exchange$: SST-Import: failure.player: 0
21/08/17 03:37:43 WARN Exchange$: Edge is not defined
21/08/17 03:37:43 INFO SparkUI: Stopped Spark web UI at http://spark-master:4040
21/08/17 03:37:43 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
验证 HDFS 上生成的 SST 文件:
docker exec -it namenode /bin/bash
root@2db58903fb53:/# hdfs dfs -ls /sst
Found 10 items
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/1
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/10
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/2
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/3
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/4
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/5
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/6
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/7
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/8
drwxr-xr-x - root supergroup 0 2021-08-17 03:37 /sst/9
写入 SST 到 Nebula Graph
这里的操作实际上都是参考文档:SST 导入,得来。其中就是从 console 之中执行了两步操作:
- Download
- Ingest
其中 Download 实际上是触发 Nebula Graph 从服务端发起 HDFS Client 的 download,获取 HDFS 上的 SST 文件,然后放到 storageD 能访问的本地路径下,这里,需要我们在服务端部署 HDFS 的依赖。因为我们是最小实践,我就偷懒手动做了这个 Download 的操作。
1. 手动下载
这里边手动下载我们就要知道 Nebula Graph 服务端下载的路径,实际上是 /data/storage/nebula/<space_id>/download/
,这里的 Space ID 需要手动获取一下:
这个例子里,我们的 Space Name 是 sst
,而 Space ID 是 49
。
(root@nebula) [sst]> DESC space sst
+----+-------+------------------+----------------+---------+------------+--------------------+-------------+-----------+
| ID | Name | Partition Number | Replica Factor | Charset | Collate | Vid Type | Atomic Edge | Group |
+----+-------+------------------+----------------+---------+------------+--------------------+-------------+-----------+
| 49 | "sst" | 10 | 1 | "utf8" | "utf8_bin" | "FIXED_STRING(32)" | "false" | "default" |
+----+-------+------------------+----------------+---------+------------+--------------------+-------------+-----------+
于是,下边的操作就是手动把 SST 文件从 HDFS 之中 get
下来,再拷贝到 storageD 之中。
docker exec -it namenode /bin/bash
$ hdfs dfs -get /sst /sst
exit
docker cp namenode:/sst .
docker exec -it nebula-docker-compose_storaged0_1 mkdir -p /data/storage/nebula/49/download/
docker exec -it nebula-docker-compose_storaged1_1 mkdir -p /data/storage/nebula/49/download/
docker exec -it nebula-docker-compose_storaged2_1 mkdir -p /data/storage/nebula/49/download/
docker cp sst nebula-docker-compose_storaged0_1:/data/storage/nebula/49/download/
docker cp sst nebula-docker-compose_storaged1_1:/data/storage/nebula/49/download/
docker cp sst nebula-docker-compose_storaged2_1:/data/storage/nebula/49/download/
2. SST 文件导入
- 进入 Nebula-Console 所在的容器
~/.nebula-up/console.sh
/ #
- 在 console 容器里发起链接到图数据库,其中
192.168.x.y
是我所在的 Linux VM 的第一个网卡地址,请换成您的
/ # nebula-console -addr 192.168.x.y -port 9669 -user root -p password
[INFO] connection pool is initialized successfully
Welcome to Nebula Graph!
- 执行
INGEST
开始让 StorageD 读取 SST 文件
(root@nebula) [(none)]> use sst
(root@nebula) [sst]> INGEST;
我们可以用如下方法实时查看 Nebula Graph 服务端的日志
tail -f ~/.nebula-up/nebula-docker-compose/logs/*/*
成功的 INGEST 日志:
I0817 08:03:28.611877 169 EventListner.h:96] Ingest external SST file: column family default, the external file path /data/storage/nebula/49/download/8/8-6.sst, the internal file path /data/storage/nebula/49/data/000023.sst, the properties of the table: # data blocks=1; # entries=1; # deletions=0; # merge operands=0; # range deletions=0; raw key size=48; raw average key size=48.000000; raw value size=40; raw average value size=40.000000; data block size=75; index block size (user-key? 0, delta-value? 0)=66; filter block size=0; (estimated) table size=141; filter policy name=N/A; prefix extractor name=nullptr; column family ID=N/A; column family name=N/A; comparator name=leveldb.BytewiseComparator; merge operator name=nullptr; property collectors names=[]; SST file compression algo=Snappy; SST file compression options=window_bits=-14; level=32767; strategy=0; max_dict_bytes=0; zstd_max_train_bytes=0; enabled=0; ; creation time=0; time stamp of earliest key=0; file creation time=0;
E0817 08:03:28.611912 169 StorageHttpIngestHandler.cpp:63] SSTFile ingest successfully
附录
附录一
docker-compose.yaml
diff --git a/docker-compose.yaml b/docker-compose.yaml
index 48854de..cfeaedb 100644
--- a/docker-compose.yaml
+++ b/docker-compose.yaml
@@ -6,11 +6,13 @@ services:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --local_ip=metad0
- --ws_ip=metad0
- --port=9559
- --ws_http_port=19559
+ - --ws_storage_http_port=19779
- --data_path=/data/meta
- --log_dir=/logs
- --v=0
@@ -34,81 +36,14 @@ services:
cap_add:
- SYS_PTRACE
- metad1:
- image: vesoft/nebula-metad:v2.0.0
- environment:
- USER: root
- TZ: "${TZ}"
- command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
- - --local_ip=metad1
- - --ws_ip=metad1
- - --port=9559
- - --ws_http_port=19559
- - --data_path=/data/meta
- - --log_dir=/logs
- - --v=0
- - --minloglevel=0
- healthcheck:
- test: ["CMD", "curl", "-sf", "http://metad1:19559/status"]
- interval: 30s
- timeout: 10s
- retries: 3
- start_period: 20s
- ports:
- - 9559
- - 19559
- - 19560
- volumes:
- - ./data/meta1:/data/meta
- - ./logs/meta1:/logs
- networks:
- - nebula-net
- restart: on-failure
- cap_add:
- - SYS_PTRACE
-
- metad2:
- image: vesoft/nebula-metad:v2.0.0
- environment:
- USER: root
- TZ: "${TZ}"
- command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
- - --local_ip=metad2
- - --ws_ip=metad2
- - --port=9559
- - --ws_http_port=19559
- - --data_path=/data/meta
- - --log_dir=/logs
- - --v=0
- - --minloglevel=0
- healthcheck:
- test: ["CMD", "curl", "-sf", "http://metad2:19559/status"]
- interval: 30s
- timeout: 10s
- retries: 3
- start_period: 20s
- ports:
- - 9559
- - 19559
- - 19560
- volumes:
- - ./data/meta2:/data/meta
- - ./logs/meta2:/logs
- networks:
- - nebula-net
- restart: on-failure
- cap_add:
- - SYS_PTRACE
-
storaged0:
image: vesoft/nebula-storaged:v2.0.0
environment:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --local_ip=storaged0
- --ws_ip=storaged0
- --port=9779
@@ -119,8 +54,8 @@ services:
- --minloglevel=0
depends_on:
- metad0
- - metad1
- - metad2
healthcheck:
test: ["CMD", "curl", "-sf", "http://storaged0:19779/status"]
interval: 30s
@@ -146,7 +81,7 @@ services:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --local_ip=storaged1
- --ws_ip=storaged1
- --port=9779
@@ -157,8 +92,8 @@ services:
- --minloglevel=0
depends_on:
- metad0
- - metad1
- - metad2
healthcheck:
test: ["CMD", "curl", "-sf", "http://storaged1:19779/status"]
interval: 30s
@@ -184,7 +119,7 @@ services:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --local_ip=storaged2
- --ws_ip=storaged2
- --port=9779
@@ -195,8 +130,8 @@ services:
- --minloglevel=0
depends_on:
- metad0
- - metad1
- - metad2
healthcheck:
test: ["CMD", "curl", "-sf", "http://storaged2:19779/status"]
interval: 30s
@@ -222,17 +157,19 @@ services:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --port=9669
- --ws_ip=graphd
- --ws_http_port=19669
+ - --ws_meta_http_port=19559
- --log_dir=/logs
- --v=0
- --minloglevel=0
depends_on:
- metad0
- - metad1
- - metad2
healthcheck:
test: ["CMD", "curl", "-sf", "http://graphd:19669/status"]
interval: 30s
@@ -257,17 +194,19 @@ services:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --port=9669
- --ws_ip=graphd1
- --ws_http_port=19669
+ - --ws_meta_http_port=19559
- --log_dir=/logs
- --v=0
- --minloglevel=0
depends_on:
- metad0
- - metad1
- - metad2
healthcheck:
test: ["CMD", "curl", "-sf", "http://graphd1:19669/status"]
interval: 30s
@@ -292,17 +231,21 @@ services:
USER: root
TZ: "${TZ}"
command:
- - --meta_server_addrs=metad0:9559,metad1:9559,metad2:9559
+ - --meta_server_addrs=metad0:9559
- --port=9669
- --ws_ip=graphd2
- --ws_http_port=19669
+ - --ws_meta_http_port=19559
- --log_dir=/logs
- --v=0
- --minloglevel=0
+ - --storage_client_timeout_ms=60000
+ - --local_config=true
depends_on:
- metad0
- - metad1
- - metad2
healthcheck:
test: ["CMD", "curl", "-sf", "http://graphd2:19669/status"]
interval: 30s
@@ -323,3 +266,4 @@ services:
networks:
nebula-net:
+ external: true
附录二
https://github.com/big-data-europe/docker-hadoop 的 docker-compose.yml
diff --git a/docker-compose.yml b/docker-compose.yml
index ed40dc6..66ff1f4 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -14,6 +14,8 @@ services:
- CLUSTER_NAME=test
env_file:
- ./hadoop.env
+ networks:
+ - nebula-net
datanode:
image: bde2020/hadoop-datanode:2.0.0-hadoop3.2.1-java8
@@ -25,6 +27,8 @@ services:
SERVICE_PRECONDITION: "namenode:9870"
env_file:
- ./hadoop.env
+ networks:
+ - nebula-net
resourcemanager:
image: bde2020/hadoop-resourcemanager:2.0.0-hadoop3.2.1-java8
@@ -34,6 +38,8 @@ services:
SERVICE_PRECONDITION: "namenode:9000 namenode:9870 datanode:9864"
env_file:
- ./hadoop.env
+ networks:
+ - nebula-net
nodemanager1:
image: bde2020/hadoop-nodemanager:2.0.0-hadoop3.2.1-java8
@@ -43,6 +49,8 @@ services:
SERVICE_PRECONDITION: "namenode:9000 namenode:9870 datanode:9864 resourcemanager:8088"
env_file:
- ./hadoop.env
+ networks:
+ - nebula-net
historyserver:
image: bde2020/hadoop-historyserver:2.0.0-hadoop3.2.1-java8
@@ -54,8 +62,14 @@ services:
- hadoop_historyserver:/hadoop/yarn/timeline
env_file:
- ./hadoop.env
+ networks:
+ - nebula-net
volumes:
hadoop_namenode:
hadoop_datanode:
hadoop_historyserver:
+
+networks:
+ nebula-net:
+ external: true
附录三
nebula-exchange-sst.conf
{
# Spark relation config
spark: {
app: {
name: Nebula Exchange 2.1
}
master:local
driver: {
cores: 1
maxResultSize: 1G
}
executor: {
memory:1G
}
cores:{
max: 16
}
}
# Nebula Graph relation config
nebula: {
address:{
graph:["192.168.8.128:9669"]
meta:["192.168.8.128:49377"]
}
user: root
pswd: nebula
space: sst
# parameters for SST import, not required
path:{
local:"/tmp"
remote:"/sst"
hdfs.namenode: "hdfs://192.168.8.128:9000"
}
# nebula client connection parameters
connection {
# socket connect & execute timeout, unit: millisecond
timeout: 30000
}
error: {
# max number of failures, if the number of failures is bigger than max, then exit the application.
max: 32
# failed import job will be recorded in output path
output: /tmp/errors
}
# use google's RateLimiter to limit the requests send to NebulaGraph
rate: {
# the stable throughput of RateLimiter
limit: 1024
# Acquires a permit from RateLimiter, unit: MILLISECONDS
# if it can't be obtained within the specified timeout, then give up the request.
timeout: 1000
}
}
# Processing tags
# There are tag config examples for different dataSources.
tags: [
# HDFS csv
# Import mode is sst, just change type.sink to client if you want to use client import mode.
{
name: player
type: {
source: csv
sink: sst
}
path: "file:///root/player.csv"
# if your csv file has no header, then use _c0,_c1,_c2,.. to indicate fields
fields: [_c1, _c2]
nebula.fields: [name, age]
vertex: {
field:_c0
}
separator: ","
header: false
batch: 256
partition: 32
}
]
}
本文中如有任何错误或疏漏,欢迎去 GitHub:https://github.com/vesoft-inc/nebula issue 区向我们提 issue 或者前往官方论坛:https://discuss.nebula-graph.com.cn/ 的 建议反馈
分类下提建议 👏;交流图数据库技术?加入 Nebula 交流群请先填写下你的 Nebula 名片,Nebula 小助手会拉你进群~~
网友评论