- .NET Clients: other versions:
- Introduction
- Installation
- Breaking changes
- API Conventions
- Elasticsearch.Net - Low level client
- NEST - High level client
- Troubleshooting
- Search
- Query DSL
- Full text queries
- Term level queries
- Exists Query Usage
- Fuzzy Date Query Usage
- Fuzzy Numeric Query Usage
- Fuzzy Query Usage
- Ids Query Usage
- Prefix Query Usage
- Date Range Query Usage
- Long Range Query Usage
- Numeric Range Query Usage
- Term Range Query Usage
- Regexp Query Usage
- Term Query Usage
- Terms Set Query Usage
- Terms List Query Usage
- Terms Lookup Query Usage
- Terms Query Usage
- Wildcard Query Usage
- Compound queries
- Joining queries
- Geo queries
- Specialized queries
- Span queries
- NEST specific queries
- Aggregations
- Metric Aggregations
- Average Aggregation Usage
- Boxplot Aggregation Usage
- Cardinality Aggregation Usage
- Extended Stats Aggregation Usage
- Geo Bounds Aggregation Usage
- Geo Centroid Aggregation Usage
- Geo Line Aggregation Usage
- Max Aggregation Usage
- Median Absolute Deviation Aggregation Usage
- Min Aggregation Usage
- Percentile Ranks Aggregation Usage
- Percentiles Aggregation Usage
- Rate Aggregation Usage
- Scripted Metric Aggregation Usage
- Stats Aggregation Usage
- String Stats Aggregation Usage
- Sum Aggregation Usage
- T Test Aggregation Usage
- Top Hits Aggregation Usage
- Top Metrics Aggregation Usage
- Value Count Aggregation Usage
- Weighted Average Aggregation Usage
- Bucket Aggregations
- Adjacency Matrix Usage
- Auto Date Histogram Aggregation Usage
- Children Aggregation Usage
- Composite Aggregation Usage
- Date Histogram Aggregation Usage
- Date Range Aggregation Usage
- Diversified Sampler Aggregation Usage
- Filter Aggregation Usage
- Filters Aggregation Usage
- Geo Distance Aggregation Usage
- Geo Hash Grid Aggregation Usage
- Geo Tile Grid Aggregation Usage
- Global Aggregation Usage
- Histogram Aggregation Usage
- Ip Range Aggregation Usage
- Missing Aggregation Usage
- Multi Terms Aggregation Usage
- Nested Aggregation Usage
- Parent Aggregation Usage
- Range Aggregation Usage
- Rare Terms Aggregation Usage
- Reverse Nested Aggregation Usage
- Sampler Aggregation Usage
- Significant Terms Aggregation Usage
- Significant Text Aggregation Usage
- Terms Aggregation Usage
- Variable Width Histogram Usage
- Pipeline Aggregations
- Average Bucket Aggregation Usage
- Bucket Script Aggregation Usage
- Bucket Selector Aggregation Usage
- Bucket Sort Aggregation Usage
- Cumulative Cardinality Aggregation Usage
- Cumulative Sum Aggregation Usage
- Derivative Aggregation Usage
- Extended Stats Bucket Aggregation Usage
- Max Bucket Aggregation Usage
- Min Bucket Aggregation Usage
- Moving Average Ewma Aggregation Usage
- Moving Average Holt Linear Aggregation Usage
- Moving Average Holt Winters Aggregation Usage
- Moving Average Linear Aggregation Usage
- Moving Average Simple Aggregation Usage
- Moving Function Aggregation Usage
- Moving Percentiles Aggregation Usage
- Normalize Aggregation Usage
- Percentiles Bucket Aggregation Usage
- Serial Differencing Aggregation Usage
- Stats Bucket Aggregation Usage
- Sum Bucket Aggregation Usage
- Matrix Aggregations
- Metric Aggregations
A newer version is available. For the latest information, see the
current release documentation.
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
text
fields - 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); }
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