Query_string performance

Elastic Stack Kibana
1

Hi!

We recently upgraded Elasticsearch and Kibana from 5.3.0 to 5.4.0 and since then we experience performance issues with dashboards and visualizations. Here is the query that is generated by Kibana for a visualization on the .monitoring-es-2-* index:

{
  "query": {
    "bool": {
      "must": [
        {
          "query_string": {
            "analyze_wildcard": true,
            "query": "*"
          }
        },
        {
          "query_string": {
            "analyze_wildcard": true,
            "query": "*"
          }
        },
        {
          "range": {
            "timestamp": {
              "gte": 1495455394174,
              "lte": 1495541794174,
              "format": "epoch_millis"
            }
          }
        }
      ],
      "must_not": []
    }
  },
  "size": 0,
  "_source": {
    "excludes": []
  },
  "aggs": {
    "2": {
      "date_histogram": {
        "field": "timestamp",
        "interval": "30m",
        "time_zone": "Europe/Berlin",
        "min_doc_count": 1
      },
      "aggs": {
        "3": {
          "terms": {
            "field": "source_node.name",
            "size": 30,
            "order": {
              "1": "desc"
            }
          },
          "aggs": {
            "1": {
              "max": {
                "field": "node_stats.process.cpu.percent"
              }
            }
          }
        }
      }
    }
  },
  "version": true,
  "highlight": {
    "pre_tags": [
      "@kibana-highlighted-field@"
    ],
    "post_tags": [
      "@/kibana-highlighted-field@"
    ],
    "fields": {
      "*": {
        "highlight_query": {
          "bool": {
            "must": [
              {
                "query_string": {
                  "analyze_wildcard": true,
                  "query": "*",
                  "all_fields": true
                }
              },
              {
                "query_string": {
                  "analyze_wildcard": true,
                  "query": "*",
                  "all_fields": true
                }
              },
              {
                "range": {
                  "timestamp": {
                    "gte": 1495455394174,
                    "lte": 1495541794174,
                    "format": "epoch_millis"
                  }
                }
              }
            ],
            "must_not": []
          }
        }
      }
    },
    "fragment_size": 2147483647
  }
}

Side note: the query_string in the query and in the highlight_query are duplicated.

To analyze the problem we copied the query into the dev tools (sense) and executed them.
Using the exact same query results in a response time of 10+ seconds.
Removing the query_string blocks results in a response time of 1+ seconds.

As we experience the problem in Kibana, I decided to post it in this category, but it could be also a problem of Elasticsearch. What do you think?

I quickly compared the results with and without the query_string and I don't see any difference. Why is the query_string needed/used?

Thanks in advance for your help!

2

Hi,

This is definitely a question for Elasticsearch. Can you post it in there?

Thanks,
Bhavya

3

I added also a thread in Elasticsearch:

But the problem with the duplicated query_string blocks is on Kibana side I guess?

BTW: We just found a workaround to improve the performance by disabling the _all field and using the index.query.default_field which prevents Elasticsearch from looking into every "queryable" field.

4

This topic was automatically closed 28 days after the last reply. New replies are no longer allowed.