# Creating Search Query Based on Conditional Logic: A & B & C & (D | (E & F))

**URL:** <https://discuss.elastic.co/t/creating-search-query-based-on-conditional-logic-a-b-c-d-e-f/202555>\
**Category:** Elasticsearch\
**Tags:** elastic-stack-machine-learning\
**Created:** [October 7, 2019, 3:05pm UTC](https://discuss.elastic.co/t/creating-search-query-based-on-conditional-logic-a-b-c-d-e-f/202555 "2019-10-07T15:05:13Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![ethanwicker](https://avatars.discourse-cdn.com/v4/letter/e/e480ec/32.png) [@ethanwicker](https://discuss.elastic.co/u/ethanwicker)\
**Post date:** [October 7, 2019, 3:05pm UTC](https://discuss.elastic.co/t/creating-search-query-based-on-conditional-logic-a-b-c-d-e-f/202555/1 "2019-10-07T15:05:13Z")

</div>

Hi, thanks for your time.

I'm having a bit of trouble creating a search query based on conditional logic.

Via a search query, I am fetching anomalies from the .ml-anomalies-shared index. I have a variety of anomaly detection jobs set up - some that use the count function, and others that do not.

I want to pass my search query a list of job IDs, as well as a time range and an initial record score filter. Then, for jobs that use the count function, I only want to return results where the `actual` value is above 20. Otherwise, I want to return all anomalies.

The business need here is that for anomalies were the actual count is below 20, I want to ignore them. For other anomalies that are based on the mean function (for example), I want all anomalies return.

In pseudo-code, I am attempting something like this:

```
IF

job_id IN c('job_id_1', 'job_id_2', 'job_id_3') &
1570453375402 <= timestamp >= 1570366975399 &
initial_record_score >= 90 &
(function_description != 'count' | (function_description = 'count' & actual_count >= 20))

THEN
return anomalies

```

Below is the search query I've gotten so far. I think it is close, but not quite correct.

```
    POST /.ml-anomalies-shared/_search
{
  "size": 50,
  "query": {
    "constant_score": {
      "filter": {
        "bool": {
          "must": [
            {
              "terms": {
                "job_id": [
                  "job_id_1",
                  "job_id_2",
                  "job_id_3"
                ]
              }
            },
            {
              "range": {
                "timestamp": {
                  "from": 157037178391,
                  "to": 1570458567819
                }
              }
            },
            {
              "range": {
                "initial_record_score": {
                  "gte": 90
                }
              }
            }
          ],
          "should": [
            {
              "bool": {
                "must_not": [
                  {
                    "term": {
                      "function_description": "count"
                    }
                  }
                ],
                "must": [
                  {
                    "term": {
                      "function_description": "count"
                    }
                  },
                  {
                    "range": {
                      "actual": {
                        "gte": 20
                      }
                    }
                  }
                ]
              }
            }
          ],
          "minimum_should_match" : 1
        }
      }
    }
  }
}

```

Thank for your help and time!

---

<div class="post-metadata">

**Author:** ![richcollier](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/richcollier/32/115035_2.png) [@richcollier](https://discuss.elastic.co/u/richcollier)\
**Post date:** [October 7, 2019, 8:03pm UTC](https://discuss.elastic.co/t/creating-search-query-based-on-conditional-logic-a-b-c-d-e-f/202555/2 "2019-10-07T20:03:06Z")

</div>

> [@ethanwicker](#):
>
> The business need here is that for anomalies were the actual count is below 20, I want to ignore them

Why not just make the ML job ignore this situation with a Custom Rule? See this blog for reference:

> **[How to Capture Domain Knowledge in Elastic Machine Learning Jobs with Custom...](https://www.elastic.co/blog/how-to-capture-domain-knowledge-in-elastic-machine-learning-jobs-with-custom-rules)**
>
> Learn how to use custom rules to customize your Elastic machine learning jobs and capture domain expertise for you use case.

---

<div class="post-metadata">

**Author:** ![ethanwicker](https://avatars.discourse-cdn.com/v4/letter/e/e480ec/32.png) [@ethanwicker](https://discuss.elastic.co/u/ethanwicker)\
**Post date:** [October 7, 2019, 8:18pm UTC](https://discuss.elastic.co/t/creating-search-query-based-on-conditional-logic-a-b-c-d-e-f/202555/3 "2019-10-07T20:18:58Z")

</div>

Hey Rich, thanks for the suggestion.

I was actually just able to get the search to work as needed. In the future, I may switch over to using a Custom Rule as you suggested.

For future reference for anyone else, here's a potential solution:

```
POST /.ml-anomalies-shared/_search
{
  "size": 50,
  "query": {
"constant_score": {
  "filter": {
    "bool": {
      "must": [
        {
          "terms": {
            "job_id": [
              "job_id_1",
              "job_id_2",
              "job_id_3"
            ]
          }
        },
        {
          "range": {
            "timestamp": {
              "from": "2019-09-18T23:00:00Z",
              "to": "2019-09-19T02:00:00Z"
            }
          }
        },
        {
          "range": {
            "initial_record_score": {
              "gte": 0
            }
          }
        }
      ],
      "should": [
        {
          "range": {
            "actual": {
              "gte": 20
            }
          }
        },
        {
          "term": {
            "function": {
              "value": "mean"
            }
          }
        }
      ],
      "minimum_should_match": 1
    }
  }
}
  }
}
```

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [November 4, 2019, 8:19pm UTC](https://discuss.elastic.co/t/creating-search-query-based-on-conditional-logic-a-b-c-d-e-f/202555/4 "2019-11-04T20:19:02Z")

</div>

Closed on November 4, 2019, 8:19pm UTC

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