elasticsearch-jdbc
环境
- Ubuntu 14.04
- JDK 1.8.0_66
- Elasticsearch 2.3.1
- Elasticsearch-jdbc 2.3.1.0
- Elasticsearch单节点环境
进入es目录~/cluster/elasticsearch-2.3.1
下载elasticsearch-jdbc包,并解压
$ wget http://xbib.org/repository/org/xbib/elasticsearch/importer/elasticsearch-jdbc/2.3.1.0/elasticsearch-jdbc-2.3.1.0-dist.zip
$ unzip elasticsearch-jdbc-2.3.1.0-dist.zip
数据库中的数据
数据位于10.110.1.47:3306下的ispider_data数据库,表名为es_test
共三条数据如下:
id name
4 zhangsan
2 lisi
3 wangwu
编辑数据导入脚本import.sh
vi import.sh
输入:
bin=/home/es/cluster/elasticsearch-2.3.1/elasticsearch-jdbc-2.3.1.0/bin
lib=/home/es/cluster/elasticsearch-2.3.1/elasticsearch-jdbc-2.3.1.0/lib
echo '{
"type" : "jdbc",
"jdbc": {
"url":"jdbc:mysql://10.110.1.47:3306/ispider_data",
"user":"root",
"password":"123456a?",
"sql":"select * from es_test",
"index" : "customer",
"type" : "external"
}}' | java
-cp "${lib}/*"
-Dlog4j.configurationFile=${bin}/log4j2.xml
org.xbib.tools.Runner
org.xbib.tools.JDBCImporter
上述,将MySQL中的数据建立为es中索引为customer,类型为external中。
查询索引
es@search1:~/cluster/elasticsearch-2.3.1$ curl 'localhost:9200/customer/external/_search?pretty&q=*'
结果显示:
{
"took" : 6,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"hits" : {
"total" : 3,
"max_score" : 1.0,
"hits" : [ {
"_index" : "customer",
"_type" : "external",
"_id" : "AVQ8--xAkvh0m5n1OUEo",
"_score" : 1.0,
"_source" : {
"id" : "4",
"name" : "zhangsan"
}
}, {
"_index" : "customer",
"_type" : "external",
"_id" : "AVQ8--xBkvh0m5n1OUEq",
"_score" : 1.0,
"_source" : {
"id" : "3",
"name" : "wangwu"
}
}, {
"_index" : "customer",
"_type" : "external",
"_id" : "AVQ8--xBkvh0m5n1OUEp",
"_score" : 1.0,
"_source" : {
"id" : "2",
"name" : "lisi"
}
} ]
}
}
可见,_source中的各个字段field,与数据库中的各列对应。
注意,_source中的id是es_test表中的id列,索引中document的id是自动生成的,二者并不一样。
至此,从数据库MySQL导入ES建立索引的过程就完成了。