最近在公司又用到了elasticsearch,也用到了查询模板,顺便写篇文章记录一下查询模板的使用。
以1个需求为例讲解es模板的使用:
页面上某个按钮在一段时间内的点击次数统计,并且可以以小时,天,月为单位进行汇总,并且需要去重。
创建索引,只定义3个字段,user_id, user_name和create_time:
-POST /$ES/event_index
{
"mappings": {
"event": {
"_ttl": {
"enabled": false
},
"_timestamp": {
"enabled": true,
"format": "yyyy-MM-dd HH:mm:ss"
},
"properties": {
"user_id": {
"type": "string",
"store": "no",
"index": "not_analyzed"
},
"create_time": {
"type": "date",
"store": "no",
"index": "not_analyzed",
"format": "yyyy-MM-dd HH:mm:ss"
},
"user_name": {
"type": "string",
"store": "no"
}
}
}
}
}
定义对应的查询模板,模板名字stats,使用了Cardinality和DateHistogram这两个Aggregation
,其中Date Histogram嵌套在Cardinality里。在定义模板的时候,{ { } } 的表示是个参数,需要调用模板的时候传递进来:
-POST /$ES/_search/template/stats
{
"template": {
"query": {
"bool": {
"must": [
{
"range": {
"create_time": {
"gte": "{{earliest}}",
"lte": "{{latest}}"
}
}
}
]
}
},
"size": 0,
"aggs": {
"stats_data": {
"date_histogram": {
"field": "create_time",
"interval": "{{interval}}"
},
"aggs": {
"time": {
"cardinality": {
"field": "user_id"
}
}
}
}
}
}
}
Cardinality Aggregation的作用就是类似sql中的distinct,去重。
Date Histogram Aggregation的作用是根据时间进行统计。内部有个interval属性表面统计的范畴。
下面加几条数据到event_index里:
-POST $ES/event_index/event
{
"user_id": "1",
"user_name": "format1",
"create_time": "2015-11-07 12:00:00"
}
-POST $ES/event_index/event
{
"user_id": "2",
"user_name": "format2",
"create_time": "2015-11-07 13:30:00"
}
-POST $ES/event_index/event
{
"user_id": "3",
"user_name": "format3",
"create_time": "2015-11-07 13:30:00"
}
-POST $ES/event_index/event
{
"user_id": "1",
"user_name": "format1",
"create_time": "2015-11-07 13:50:00"
}
-POST $ES/event_index/event
{
"user_id": "1",
"user_name": "format1",
"create_time": "2015-11-07 13:55:00"
}
11-07 12-13点有1条数据,1个用户
11-07 13-14点有4条数据,3个用户
使用模板查询:
curl -XGET "$ES/event_index/_search/template" -d‘{
"template": { "id": "stats" },
"params": { "earliest": "2015-11-07 00:00:00", "latest": "2015-11-07 23:59:59", "interval": "hour" }
}‘
结果:
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 5,
"max_score": 0,
"hits": []
},
"aggregations": {
"stats_data": {
"buckets": [
{
"key_as_string": "2015-11-07 12:00:00",
"key": 1446897600000,
"doc_count": 1,
"time": {
"value": 1
}
},
{
"key_as_string": "2015-11-07 13:00:00",
"key": 1446901200000,
"doc_count": 4,
"time": {
"value": 3
}
}
]
}
}
}
12点-13点的只有1条数据,1个用户。13-14点的有4条数据,3个用户。
以天(day)统计:
curl -XGET "$ES/event_index/_search/template" -d‘{
"template": { "id": "stats" },
"params": { "earliest": "2015-11-07 00:00:00", "latest": "2015-11-07 23:59:59", "interval": "day" }
}‘
结果:
{
"took": 4,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 5,
"max_score": 0,
"hits": []
},
"aggregations": {
"stats_data": {
"buckets": [
{
"key_as_string": "2015-11-07 00:00:00",
"key": 1446854400000,
"doc_count": 5,
"time": {
"value": 3
}
}
]
}
}
}
11-07这一天有5条数据,3个用户。
本文只是简单说明了es查询模板的使用,也简单使用了2个aggregation。更多内容可以去官网查看相关资料。