Elasticsearch与MongoDB 数据同步及分布式集群搭建（一）

Elasticsearch通过River可以与多种数据源Wikipedia, MongoDB, CouchDB, RabbitMQ, RSS, Sofa, JDBC, FileSystem,Dropbox等同步，公司的业务是用 MongoDB，今天测试环境虚拟机上配置了一下Elasticsearch
与 MongoDB的同步，作个大概的过程记录，主要利用richardwilly98 / elasticsearch-river-mongodb。

River通过读取mongodb的oplog来同步数据，oplog这个表来使集群中的不同机器数据同步的，可以保证es里面的数据和mongodb里面的是一样的，所以Mongdb必须是个集群才能拥有oplog.注意：该插件只支持集群环境下的mongodb，因为集群环境下的mongodb才有oplog这个

Elasticsearch 和 MongoDB需要安装对应的版本才能实现同步，我这里用了最新的Elasticsearch 1.4.2 和 MongoDB 3.0.0,相应的版本要求参考下表





elasticsearch-mongodb

 

MongDB是一个副本集的集群，具体副本集集群的搭建不详细写了，Elasticsearch的安装配置也省略。

1.安装elasticsearch-river-mongodb

# ./elasticsearch-1.4.4/bin/plugin -install elasticsearch/elasticsearch-mapper-attachments/2.4.1

# ./elasticsearch-1.4.4/bin/plugin -i com.github.richardwilly98.elasticsearch/elasticsearch-river-mongodb/2.0.5
2.建立river

curl -XPUT "http://10.253.1.70:9200/_river/threads_mongo_river/_meta"</span> -d'

{
"type": "mongodb",
"mongodb": {
"servers":
[
{ "host": "10.253.1.71", "port": 27017}
],
"db": "threads",
"collection": "threads",
"gridfs": false
},
"index": {
"name": "test",
"type": "threads"
}
}'
这里只是简单的配置了建立连接的MongoDB以及相应的db,collection对于的elasticsearch index和type，还有详细的配置没有使用到，比如options等，具体根据业务可以配置，下面是一份详细的配置样例:

$ curl -XPUT "localhost:9200/_river/${es.river.name}/_meta" -d '
{
"type": "mongodb",
"mongodb": {
"servers":
[
{ "host": ${mongo.instance1.host}, "port": ${mongo.instance1.port} },
{ "host": ${mongo.instance2.host}, "port": ${mongo.instance2.port} }
],
"options": {
"secondary_read_preference" : true,
"drop_collection": ${mongo.drop.collection},
"exclude_fields": ${mongo.exclude.fields},
"include_fields": ${mongo.include.fields},
"include_collection": ${mongo.include.collection},
"import_all_collections": ${mongo.import.all.collections},
"initial_timestamp": {
"script_type": ${mongo.initial.timestamp.script.type},
"script": ${mongo.initial.timestamp.script}
},
"skip_initial_import" : ${mongo.skip.initial.import},
"store_statistics" : ${mongo.store.statistics},
},
"credentials":
[
{ "db": "local", "user": ${mongo.local.user}, "password": ${mongo.local.password} },
{ "db": "admin", "user": ${mongo.db.user}, "password": ${mongo.db.password} }
],
"db": ${mongo.db.name},
"collection": ${mongo.collection.name},
"gridfs": ${mongo.is.gridfs.collection},
"filter": ${mongo.filter}
},
"index": {
"name": ${es.index.name},
"throttle_size": ${es.throttle.size},
"bulk_size": ${es.bulk.size},
"type": ${es.type.name}
"bulk": {
"actions": ${es.bulk.actions},
"size": ${es.bulk.size},
"concurrent_requests": ${es.bulk.concurrent.requests},
"flush_interval": ${es.bulk.flush.interval}
}
}
}'

一些配置项的解释如下,具体可以查看github的wiki:
db为同步的数据库名，
host mongodb的ip地址（默认为localhost）
port mongodb的端口
collection 要同步的表名
fields 要同步的字段名（用逗号隔开，默认全部）
gridfs 是否是gridfs文件（如果collection是gridfs的话就设置成true）
local_db_user local数据库的用户名（没有的话不用写）
local_db_password local数据库的密码（没有的话不用写）
db_user 要同步的数据库的密码（没有的话不用写）
db_password 要同步的数据库的密码（没有的话不用写）
name 索引名（不能之前存在）
type 类型
bulk_size 批量添加的最大数
bulk_timeout 批量添加的超时时间

3.测试是否成功

我测试的库中数据较少，所以就直接都查出来看看是否能查出来吧

$ curl -XGET "http://10.253.1.70:9200/test/threads/_search" -d '

{
"took": 20,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 4,
"max_score": 1,
"hits": [
{
"_index": "test",
"_type": "threads",
"_id": "54fa32b22c44cf67cb6a9d1b",
"_score": 1,
"_source": {
"_id": "54fa32b22c44cf67cb6a9d1b",
"title": "where is my car",
"content": "ask yourself"
}
},
{
"_index": "test",
"_type": "threads",
"_id": "54fa2f5c2c44cf67cb6a9d19",
"_score": 1,
"_source": {
"_id": "54fa2f5c2c44cf67cb6a9d19",
"title": "this is title",
"content": "what is the fuck"
}
},
{
"_index": "test",
"_type": "threads",
"_id": "54fa2f892c44cf67cb6a9d1a",
"_score": 1,
"_source": {
"_id": "54fa2f892c44cf67cb6a9d1a",
"title": "are you ok",
"content": "yes,i am ok"
}
},
{
"_index": "test",
"_type": "threads",
"_id": "54fa49ccc104e2264e02deea",
"_score": 1,
"_source": {
"_id": "54fa49ccc104e2264e02deea",
"title": "hello word",
"content": "hello hello haha"
}
}
]
}
}
看来数据已经同步过来了，然后在MongoDB 添加一条记录，执行同样的操作查找对于的记录或者 total已经+1那么同步完成了。