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Significant Text Aggregation Usage
editSignificant Text Aggregation Usage
editAn aggregation that returns interesting or unusual occurrences of free-text terms in a set. It is like the significant terms aggregation but differs in that:
-
It is specifically designed for use on type
textfields - It does not require field data or doc-values
- It re-analyzes text content on-the-fly meaning it can also filter duplicate sections of noisy text that otherwise tend to skew statistics.
Re-analyzing large result sets will require a lot of time and memory. It is recommended that the significant_text aggregation is used as a child of either the sampler or diversified sampler aggregation to limit the analysis to a small selection of top-matching documents e.g. 200. This will typically improve speed, memory use and quality of results.
See the Elasticsearch documentation on significant text aggregation for more detail.
Fluent DSL example
edita => a
.SignificantText("significant_descriptions", st => st
.Field(p => p.Description)
.FilterDuplicateText()
)
Object Initializer syntax example
editnew SignificantTextAggregation("significant_descriptions")
{
Field = Infer.Field<Project>(p => p.Description),
FilterDuplicateText = true
}
Example json output.
{
"significant_descriptions": {
"significant_text": {
"field": "description",
"filter_duplicate_text": true
}
}
}
Handling Responses
editresponse.ShouldBeValid();
var sigNames = response.Aggregations.SignificantText("significant_descriptions");
sigNames.Should().NotBeNull();
sigNames.DocCount.Should().BeGreaterThan(0);
foreach (var bucket in sigNames.Buckets)
{
bucket.Key.Should().NotBeNullOrEmpty();
bucket.BgCount.Should().BeGreaterThan(0);
bucket.DocCount.Should().BeGreaterThan(0);
bucket.Score.Should().BeGreaterThan(0);
}