问题描述:

I am indexing Tomcat access-log data into Elasticsearch (1.7.3).

The documents that I deal with have the concept of duration, represented as end time and duration in millisec

(start time can be calculated, though I can store it as well, if it helps solve my problem).

For example:

{

ztime: "10-17-2015T04:05:00.000+02:00",

duration: 4500,

thred: "http-nio-8080-exec-14"

},

{

ztime: "10-17-2015T04:07:42.227+02:00",

duration: 3100,

thred: "http-nio-8080-exec-25"

}

My goal is to produce a histogram where I show for each second how many threads existed.

I thought of using a date_histogram that will aggregate my docs into 1 sec buckets.

GET /mindex/mtype/_search?search_type=count

{

"aggs": {

"threads_per_hr": {

"date_histogram": {

"field": "ztime",

"interval": "1s",

"min_doc_count": 1

},

"aggs": {

"per_hr_threads": {

"cardinality": {

"field": "thread"

}

}

}

}

}

}

however, thus each thread will be bucketized only once.

What I need is for each doc to be bucketized into several buckets.

For example, I will need the first document to be bucketized into the 04:05:00.000, 04:05:01.000, 04:05:02.000, 04:05:03.000 buckets.

What kind of query (Java API and/or REST API) would help me achieve this goal?

网友答案:

You need to use cardinality aggregation here. It gives the number of unique values for the field.

GET /{index}/{type}/_search?search_type=count
{
  "aggs": {
      "threads_per_hr": {
        "date_histogram": {
          "field": "ztime",
          "interval": "1s",
          "min_doc_count": 0
        },
       "aggs": {
          "per_hr_threads": {
             "cardinality": {
                "field": "thread"
             }
          }
       }
      }
  }
}
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