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Aggregations: add a min_doc_count option to terms and histogram #4662

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jpountz opened this issue Jan 8, 2014 · 3 comments
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Aggregations: add a min_doc_count option to terms and histogram #4662

jpountz opened this issue Jan 8, 2014 · 3 comments
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@jpountz
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>feature v1.0.0.RC1

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@jpountz
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jpountz commented Jan 8, 2014

Right now terms aggregations may return terms that match one hit or more. The purpose of the min_doc_count option is to make it configurable. For example, if

{
    "aggs" : {
        "tags" : {
            "terms" : {
                "field" : "tag"
            }
        }
    }
}

returns

{
    ...

    "aggregations" : {
        "tags" : {
            "buckets" : [
                {
                    "key" : "search",
                    "doc_count" : 115
                },
                {
                    "key" : "java",
                    "doc_count" : 50
                },
                {
                    "key" : "concurrency",
                    "doc_count" : 12
                }
            ]
        }
    }
}

then

{
    "aggs" : {
        "tags" : {
            "terms" : {
                "field" : "tag",
                "min_doc_count": 50
            }
        }
    }
}

would return

{
    ...

    "aggregations" : {
        "tags" : {
            "buckets" : [
                {
                    "key" : "search",
                    "doc_count" : 115
                },
                {
                    "key" : "java",
                    "doc_count" : 50
                }
            ]
        }
    }
}

The special case min_doc_count: 0 will behave similarly to the all_terms option of facets and also return terms that don't match any hit. For example, we could have the following response:

{
    ...

    "aggregations" : {
        "tags" : {
            "buckets" : [
                {
                    "key" : "search",
                    "doc_count" : 115
                },
                {
                    "key" : "java",
                    "doc_count" : 50
                },
                {
                    "key" : "concurrency",
                    "doc_count" : 12
                },
                {
                    "key" : "unit testing",
                    "doc_count" : 0
                },
                {
                    "key" : "performance",
                    "doc_count" : 0
                }
            ]
        }
    }
}

Histograms are going to support this option as well and the empty_bucket option will be removed in favor of min_doc_count: 0.
@bobrik
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bobrik commented Jan 8, 2014

If min_doc_count is going to be 0 by default it would be great.

@ghost ghost assigned jpountz Jan 8, 2014
@uboness
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uboness commented Jan 8, 2014

@bobrik currently the plan is to have 1 as the default as 0 comes with extra perf. costs and it's not necessarily the right default (really use case dependent)

@bobrik
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bobrik commented Jan 8, 2014

Sorry, I actually meant 1.

@jpountz jpountz mentioned this issue Jan 9, 2014
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jpountz added a commit to jpountz/elasticsearch that referenced this issue Jan 10, 2014
@jpountz
Add new option min_doc_count to terms and histogram aggregations.
da9063d 
`min_doc_count` is the minimum number of hits that a term or histogram key
should match in order to appear in the response.

`min_doc_count=0` replaces `compute_empty_buckets` for histograms and will
behave exactly like facets' `all_terms=true` for terms aggregations.

Close elastic#4662
@jpountz jpountz mentioned this issue Jan 10, 2014
Closed
brusic pushed a commit to brusic/elasticsearch that referenced this issue Jan 19, 2014
@jpountz @brusic
Add new option min_doc_count to terms and histogram aggregations.
a3cc97d 
`min_doc_count` is the minimum number of hits that a term or histogram key
should match in order to appear in the response.

`min_doc_count=0` replaces `compute_empty_buckets` for histograms and will
behave exactly like facets' `all_terms=true` for terms aggregations.

Close elastic#4662
This was referenced Jan 22, 2014
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Add new option min_doc_count to terms and histogram aggregations. jpountz/elasticsearch
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@bobrik @uboness @jpountz