SIREn 是一个基于 Lucene 做的，专门针对 nested object 数据做优化的方案。其官网地址：http://siren.solutions。SIREn 自己并不提供完整的软件，而是以 Solr 或者 Elasticsearch 插件的形式存在。在 SIREn 官网首页写着，自己是 trush schemaless，high performance nested query。而我之前已经写博客说过，Elasticsearch 的 schemaless 是有限制的，同一个 index 下，field 的 mapping 是必须唯一一致的。否则，或者写入失败，或者搜索异常。
那么我们来试一下这个 SIREn 看看。首先是下载运行：
# wget http://siren.solutions/download/siren-elasticsearch-1.4-bin.zip
# unzip siren-elasticsearch-1.4-bin.zip
# cd siren-elasticsearch-1.4-bin
# ./example/bin/elasticsearch然后我们尝试写入几条 mapping 有冲突的数据：
# curl -XDELETE "http://localhost:9200/napr"
# curl -XPOST "http://localhost:9200/napr"
# curl -XPUT "http://localhost:9200/napr/chargepoint/_mapping" -d '
{
"chargepoint" : {
"properties" : {
"_siren_source" : {
"analyzer" : "concise",
"postings_format" : "Siren10AFor",
"store" : "no",
"type" : "string"
}
},
"_siren" : {}
}
}'
# curl -XPUT "http://localhost:9200/napr/chargepoint/1" -d '
{
"ChargeDeviceName": "1c Design Limited, Glasgow (1)",
"Accessible24Hours": false
}'
# curl -XPUT "http://localhost:9200/napr/chargepoint/2" -d '
{
"ChargeDeviceName": "2c Design Limited, Glasgow (2)",
"Accessible24Hours": "true"
}'
# curl -XPUT "http://localhost:9200/napr/chargepoint/3" -d '
{
"ChargeDeviceName": "3c Design Limited, Glasgow (3)",
"Accessible24Hours": 123
}'
# curl -XPUT "http://localhost:9200/nepr/chargepoint/4" -d '
{
"ChargeDeviceName": "4c Design Limited, Glasgow (4)",
"Accessible24Hours": [123, 234, 345, 456]
}'ok，三条数据都写入成功了。
然后我们用原始的 Elasticsearch 语法尝试去获取『大于100』的数据：
# curl -XPOST "http://localhost:9200/nepr/_search?q=Accessible24Hours:>100"
{"took":16,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":0,"max_score":null,"hits":[]}}可以看到，搜索结果是空。
而用 SIREn 的树状结构语法获取：
# curl -XPOST "http://localhost:9200/nepr/_search" -d '
{
"query": {
"tree" : {
"node" : {
"attribute" : "Accessible24Hours",
"query" : "xsd:long([100 TO *])"
}
}
}
}'
{"took":29,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":2,"max_score":4.0,"hits":[{"_index":"nepr","_type":"chargepoint","_id":"4","_score":4.0,"_source":
{
"ChargeDeviceName": "4c Design Limited, Glasgow (4)",
"Accessible24Hours": [123, 234, 345, 456]
}},{"_index":"nepr","_type":"chargepoint","_id":"3","_score":1.0,"_source":
{
"ChargeDeviceName": "3c Design Limited, Glasgow (3)",
"Accessible24Hours": 123
}}]}}%yes，我们拿到了这条数据！
更复杂一点，我们再来:
# curl -XPOST "http://localhost:9200/nepr/_search" -d '
{
"query": {
"tree" : {
"node" : {
"attribute" : "Accessible24Hours",
"range" : [2,3],
"query" : "xsd:long([10 TO *])"
}
}
},
"aggs": {
"1": {
"terms": {
"field": "ChargeDeviceName"
}
}
}
}'这里添加了一个 range 选项，SIREn 对所有的数组默认就做 nested 处理了，所有是有序的。这个选项的意思就是，只对数组中第 2 到 3 位节点的数据做搜索请求。这下，搜索结果变成了：
{"took":9,"timed_out":false,"_shards":{"total":5,"successful":5,"failed":0},"hits":{"total":1,"max_score":2.0,"hits":[{"_index":"nepr","_type":"chargepoint","_id":"4","_score":2.0,"_source":
{
"ChargeDeviceName": "4c Design Limited, Glasgow (4)",
"Accessible24Hours": [123,234,345,456]
}}]},"aggregations":{"1":{"buckets":[{"key":"4","doc_count":1},{"key":"4c","doc_count":1},{"key":"design","doc_count":1},{"key":"glasgow","doc_count":1},{"key":"limited","doc_count":1}]}}}%可以看到，因为 _id 为 3 的文档里 Accessible24Hours 字段只有一个值，所以无法匹配上从第二个值开始的多个值的对比，也就没被过滤出来了。
不过 SIREn 目前比较尴尬的是，他只基于 ES 做了 query 部分，aggregation 部分还是老样子，必须类型一致才行，这也导致 SIREn 示例文件数据里把一些冲突日志去掉了的原因。
如果使用的是 Solr，SIREn 插件的做法是只定义两个 field，一个是 UUID，一个是 JSON。然后 siren 处理的所有数据存在这个 JSON 字段里(类似 ES 插件里的那个 _siren_source 字段)。这也就能达到全部 JSON schemaless。此外，SIREn 的 Solr 插件还实现了 nested facet 支持，也可以尝试。
总之，SIREn 扩展采用树形方式自行处理一个在 ES、Solr 看来多出来的字段，而并不影响原有字段的处理流程。所以，这对 ES 有几个影响：