摘要:本文由社区用户 xrfinbj 贡献,主要介绍 Exchange 工具从 Hive 数仓导入数据到 Nebula Graph 的流程及相关的注意事项。
公司内部有使用图数据库的场景,内部通过技术选型确定了 Nebula Graph 图数据库,还需要验证 Nebula Graph 数据库在实际业务场景下的查询性能。所以急迫的需要导入数据到 Nebula Graph 并验证。在这个过程中发现通过 Exchange 工具从 hive 数仓导入数据到 Nebula Graph 文档不是很全,所以把这个流程中踩到的坑记录下来,回馈社区,避免后人走弯路。
本文主要基于我之前发在论坛的 2 篇帖子:
编译后生成 jar 包
CREATE SPACE test_hive(partition_num=10, replica_factor=1); --创建图空间,本示例中假设只需要一个副本
USE test_hive; --选择图空间 test
CREATE TAG tagA(idInt int, idString string, tboolean bool, tdouble double); -- 创建标签 tagA
CREATE TAG tagB(idInt int, idString string, tboolean bool, tdouble double); -- 创建标签 tagB
CREATE EDGE edgeAB(idInt int, idString string, tboolean bool, tdouble double); -- 创建边类型 edgeAB
CREATE TABLE `tagA`(
`id` bigint,
`idInt` int,
`idString` string,
`tboolean` boolean,
`tdouble` double) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\001' LINES TERMINATED BY '\n';
insert into tagA select 1,1,'str1',true,11.11;
insert into tagA select 2,2,"str2",false,22.22;
CREATE TABLE `tagB`(
`id` bigint,
`idInt` int,
`idString` string,
`tboolean` boolean,
`tdouble` double) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\001' LINES TERMINATED BY '\n';
insert into tagB select 3,3,"str 3",true,33.33;
insert into tagB select 4,4,"str 4",false,44.44;
CREATE TABLE `edgeAB`(
`id_source` bigint,
`id_dst` bigint,
`idInt` int,
`idString` string,
`tboolean` boolean,
`tdouble` double) ROW FORMAT DELIMITED FIELDS TERMINATED BY '\001' LINES TERMINATED BY '\n';
insert into edgeAB select 1,3,5,"edge 1",true,55.55;
insert into edgeAB select 2,4,6,"edge 2",false,66.66;
注意看exec、fields、nebula.fields、vertex、source、target字段映射
{
# Spark relation config
spark: {
app: {
name: Spark Writer
}
driver: {
cores: 1
maxResultSize: 1G
}
cores {
max: 4
}
}
# Nebula Graph relation config
nebula: {
address:{
graph: ["192.168.1.110:3699"]
meta: ["192.168.1.110:45500"]
}
user: user
pswd: password
space: test_hive
connection {
timeout: 3000
retry: 3
}
execution {
retry: 3
}
error: {
max: 32
output: /tmp/error
}
rate: {
limit: 1024
timeout: 1000
}
}
# Processing tags
tags: [
# Loading from Hive
{
name: tagA
type: {
source: hive
sink: client
}
exec: "select id,idint,idstring,tboolean,tdouble from nebula.taga"
fields: [id,idstring,tboolean,tdouble]
nebula.fields: [idInt,idString,tboolean,tdouble]
vertex: id
batch: 256
partition: 10
}
{
name: tagB
type: {
source: hive
sink: client
}
exec: "select id,idint,idstring,tboolean,tdouble from nebula.tagb"
fields: [id,idstring,tboolean,tdouble]
nebula.fields: [idInt,idString,tboolean,tdouble]
vertex: id
batch: 256
partition: 10
}
]
# Processing edges
edges: [
# Loading from Hive
{
name: edgeAB
type: {
source: hive
sink: client
}
exec: "select id_source,id_dst,idint,idstring,tboolean,tdouble from nebula.edgeab"
fields: [id_source,idstring,tboolean,tdouble]
nebula.fields: [idInt,idString,tboolean,tdouble]
source: id_source
target: id_dst
batch: 256
partition: 10
}
]
}
spark-submit --class com.vesoft.nebula.tools.importer.Exchange --master “local[4]” /xxx/exchange-1.0.1.jar -c /xxx/nebula_application.conf -h
./db_dump --mode=stat --space=xxx --db_path=/home/xxx/data/storage0/nebula --limit 20000000
说明:Exchange 目前还不支持 Spark 3,编译后运行报错,所以没法验证 Spark 3 环境
Spark Debug 部分参考博客:https://dzone.com/articles/how-to-attach-a-debugger-to-apache-spark
通过 Exchange 源码的学习和 Debug 能加深对 Exchange 原理的理解,同时也能发现一些文档描述不清晰的地方,比如 导入 SST 文件 和 Download and Ingest 只有结合源码看才能发现文档描述不清晰逻辑不严谨的问题。
通过源码 Debug 也能发现一些简单的参数配置问题。
进入正题:
步骤一:
export SPARK_SUBMIT_OPTS=-agentlib:jdwp=transport=dt_socket,server=y,suspend=y,address=4000
步骤二:
spark-submit --class com.vesoft.nebula.tools.importer.Exchange --master “local” /xxx/exchange-1.1.0.jar -c /xxx/nebula_application.conf -h
Listening for transport dt_socket at address: 4000
步骤三:IDEA 配置
步骤四:在 IDEA 里面点击 Debug
感谢 vesoft 提供了宇宙性能最强的 Nebula Graph 图数据库,能解决业务中很多实际问题,中途这点痛不算什么(看之前的分享,360 数科他们那个痛才是真痛)。中途遇到的问题都有幸得到社区及时的反馈解答,再次感谢
很期待 Exchange 支持 Nebula Graph 2.0
喜欢这篇文章?来来来,给我们的 GitHub 点个 star 表鼓励啦~~ 🙇♂️🙇♀️ 手动跪谢
交流图数据库技术?交个朋友,Nebula Graph 官方小助手微信:NebulaGraphbot 拉你进交流群~~
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。
原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。