ElasticSearch6.X版本Java Api中文詳解（十三）之Bucket Aggregations解析

Global Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilders
.global("agg") .subAggregation(AggregationBuilders.terms("genders").field("gender"));

Use aggregation response

導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.global.Global; // sr is here your SearchResponse object Global agg = sr.getAggregations().get("agg"); agg.getDocCount(); // Doc count

Filter Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilders .filter("agg", QueryBuilders.termQuery("gender", "male"));

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.filter.Filter; // sr is here your SearchResponse object Filter agg = sr.getAggregations().get("agg"); agg.getDocCount(); // Doc count

Filters Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.filters("agg", new FiltersAggregator.KeyedFilter("men", QueryBuilders.termQuery("gender", "male")), new FiltersAggregator.KeyedFilter("women", QueryBuilders.termQuery("gender", "female")));

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.filters.Filters; // sr is here your SearchResponse object Filters agg = sr.getAggregations().get("agg"); // For each entry for (Filters.Bucket entry : agg.getBuckets()) { String key = entry.getKeyAsString(); // bucket key long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], doc_count [{}]", key, docCount); }

結果如下:

key [men], doc_count [4982]
key [women], doc_count [5018]

Missing Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilders.missing("agg").field("gender");

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.missing.Missing; // sr is here your SearchResponse object Missing agg = sr.getAggregations().get("agg"); agg.getDocCount(); // Doc count

Nested Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilders .nested("agg", "resellers");

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.nested.Nested; // sr is here your SearchResponse object Nested agg = sr.getAggregations().get("agg"); agg.getDocCount(); // Doc count

Reverse Nested Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation = AggregationBuilders .nested("agg", "resellers") .subAggregation( AggregationBuilders .terms("name").field("resellers.name") .subAggregation( AggregationBuilders .reverseNested("reseller_to_product") ) );

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.nested.Nested; import org.elasticsearch.search.aggregations.bucket.nested.ReverseNested; import org.elasticsearch.search.aggregations.bucket.terms.Terms; // sr is here your SearchResponse object Nested agg = sr.getAggregations().get("agg"); Terms name = agg.getAggregations().get("name"); for (Terms.Bucket bucket : name.getBuckets()) { ReverseNested resellerToProduct = bucket.getAggregations().get("reseller_to_product"); resellerToProduct.getDocCount(); // Doc count }

Children Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.children("agg", "reseller"); "agg" is the name of the aggregation and "reseller" is the child type

Use aggregation response
導入聚合定義類:

import org.elasticsearch.join.aggregations.Children; // sr is here your SearchResponse object Children agg = sr.getAggregations().get("agg"); agg.getDocCount(); // Doc count

Terms Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilders .terms("genders") .field("gender");

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.terms.Terms;
// sr is here your SearchResponse object Terms genders = sr.getAggregations().get("genders"); // For each entry for (Terms.Bucket entry : genders.getBuckets()) { entry.getKey(); // Term entry.getDocCount(); // Doc count } Order Import bucket ordering strategy classes: import org.elasticsearch.search.aggregations.BucketOrder; Ordering the buckets by their doc_count in an ascending manner: AggregationBuilders .terms("genders") .field("gender") .order(BucketOrder.count(true)) Ordering the buckets alphabetically by their terms in an ascending manner: AggregationBuilders .terms("genders") .field("gender") .order(BucketOrder.key(true)) Ordering the buckets by single value metrics sub-aggregation (identified by the aggregation name): AggregationBuilders .terms("genders") .field("gender") .order(BucketOrder.aggregation("avg_height", false)) .subAggregation( AggregationBuilders.avg("avg_height").field("height") ) Ordering the buckets by multiple criteria: AggregationBuilders .terms("genders") .field("gender") .order(BucketOrder.compound( // in order of priority: BucketOrder.aggregation("avg_height", false), // sort by sub-aggregation first BucketOrder.count(true))) // then bucket count as a tie-breaker .subAggregation( AggregationBuilders.avg("avg_height").field("height") )

Significant Terms Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.significantTerms("significant_countries") .field("address.country"); // Let say you search for men only SearchResponse sr = client.prepareSearch() .setQuery(QueryBuilders.termQuery("gender", "male")) .addAggregation(aggregation) .get();

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.significant.SignificantTerms; // sr is here your SearchResponse object SignificantTerms agg = sr.getAggregations().get("significant_countries"); // For each entry for (SignificantTerms.Bucket entry : agg.getBuckets()) { entry.getKey(); // Term entry.getDocCount(); // Doc count }

Range Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.range("agg") .field("height") .addUnboundedTo(1.0f) // from -infinity to 1.0 (excluded) .addRange(1.0f, 1.5f) // from 1.0 to 1.5 (excluded) .addUnboundedFrom(1.5f); // from 1.5 to +infinity

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.range.Range; // sr is here your SearchResponse object Range agg = sr.getAggregations().get("agg"); // For each entry for (Range.Bucket entry : agg.getBuckets()) { String key = entry.getKeyAsString(); // Range as key Number from = (Number) entry.getFrom(); // Bucket from Number to = (Number) entry.getTo(); // Bucket to long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], from [{}], to [{}], doc_count [{}]", key, from, to, docCount); }

This will basically produce for the first example:

key [*-1.0], from [-Infinity], to [1.0], doc_count [9]
key [1.0-1.5], from [1.0], to [1.5], doc_count [21]
key [1.5-*], from [1.5], to [Infinity], doc_count [20]

Date Range Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.dateRange("agg") .field("dateOfBirth") .format("yyyy") .addUnboundedTo("1950") // from -infinity to 1950 (excluded) .addRange("1950", "1960") // from 1950 to 1960 (excluded) .addUnboundedFrom("1960"); // from 1960 to +infinity

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.range.Range; // sr is here your SearchResponse object Range agg = sr.getAggregations().get("agg"); // For each entry for (Range.Bucket entry : agg.getBuckets()) { String key = entry.getKeyAsString(); // Date range as key DateTime fromAsDate = (DateTime) entry.getFrom(); // Date bucket from as a Date DateTime toAsDate = (DateTime) entry.getTo(); // Date bucket to as a Date long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], from [{}], to [{}], doc_count [{}]", key, fromAsDate, toAsDate, docCount); }

This will basically produce:

key [*-1950], from [null], to [1950-01-01T00:00:00.000Z], doc_count [8]
key [1950-1960], from [1950-01-01T00:00:00.000Z], to [1960-01-01T00:00:00.000Z], doc_count [5]
key [1960-*], from [1960-01-01T00:00:00.000Z], to [null], doc_count [37]

Ip Range Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregatorBuilder<?> aggregation = AggregationBuilders .ipRange("agg") .field("ip") .addUnboundedTo("192.168.1.0") // from -infinity to 192.168.1.0 (excluded) .addRange("192.168.1.0", "192.168.2.0") // from 192.168.1.0 to 192.168.2.0 (excluded) .addUnboundedFrom("192.168.2.0"); // from 192.168.2.0 to +infinity Note that you could also use ip masks as ranges: AggregatorBuilder<?> aggregation = AggregationBuilders .ipRange("agg") .field("ip") .addMaskRange("192.168.0.0/32") .addMaskRange("192.168.0.0/24") .addMaskRange("192.168.0.0/16");

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.range.Range; // sr is here your SearchResponse object Range agg = sr.getAggregations().get("agg"); // For each entry for (Range.Bucket entry : agg.getBuckets()) { String key = entry.getKeyAsString(); // Ip range as key String fromAsString = entry.getFromAsString(); // Ip bucket from as a String String toAsString = entry.getToAsString(); // Ip bucket to as a String long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], from [{}], to [{}], doc_count [{}]", key, fromAsString, toAsString, docCount); }

This will basically produce for the first example:

key [*-192.168.1.0], from [null], to [192.168.1.0], doc_count [13]
key [192.168.1.0-192.168.2.0], from [192.168.1.0], to [192.168.2.0], doc_count [14]
key [192.168.2.0-*], from [192.168.2.0], to [null], doc_count [23]
And for the second one (using Ip masks):

key [192.168.0.0/32], from [192.168.0.0], to [192.168.0.1], doc_count [0]
key [192.168.0.0/24], from [192.168.0.0], to [192.168.1.0], doc_count [13]
key [192.168.0.0/16], from [192.168.0.0], to [192.169.0.0], doc_count [50]

Histogram Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation = AggregationBuilders .histogram("agg") .field("height") .interval(1);

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.histogram.Histogram; // sr is here your SearchResponse object Histogram agg = sr.getAggregations().get("agg"); // For each entry for (Histogram.Bucket entry : agg.getBuckets()) { Number key = (Number) entry.getKey(); // Key long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], doc_count [{}]", key, docCount); }

Date Histogram Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.dateHistogram("agg")
.field("dateOfBirth")
.dateHistogramInterval(DateHistogramInterval.YEAR);
Or if you want to set an interval of 10 days: AggregationBuilder aggregation = AggregationBuilders .dateHistogram("agg") .field("dateOfBirth") .dateHistogramInterval(DateHistogramInterval.days(10));

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.histogram.Histogram; // sr is here your SearchResponse object Histogram agg = sr.getAggregations().get("agg"); // For each entry for (Histogram.Bucket entry : agg.getBuckets()) { DateTime key = (DateTime) entry.getKey(); // Key String keyAsString = entry.getKeyAsString(); // Key as String long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], date [{}], doc_count [{}]", keyAsString, key.getYear(), docCount); }

This will basically produce for the first example:

key [1942-01-01T00:00:00.000Z], date [1942], doc_count [1]
key [1945-01-01T00:00:00.000Z], date [1945], doc_count [1]
key [1946-01-01T00:00:00.000Z], date [1946], doc_count [1]
…
key [2005-01-01T00:00:00.000Z], date [2005], doc_count [1]
key [2007-01-01T00:00:00.000Z], date [2007], doc_count [2]
key [2008-01-01T00:00:00.000Z], date [2008], doc_count [3]

Geo Distance Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation =
AggregationBuilders
.geoDistance("agg", new GeoPoint(48.84237171118314,2.33320027692004)) .field("address.location") .unit(DistanceUnit.KILOMETERS) .addUnboundedTo(3.0) .addRange(3.0, 10.0) .addRange(10.0, 500.0);

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.range.Range; // sr is here your SearchResponse object Range agg = sr.getAggregations().get("agg"); // For each entry for (Range.Bucket entry : agg.getBuckets()) { String key = entry.getKeyAsString(); // key as String Number from = (Number) entry.getFrom(); // bucket from value Number to = (Number) entry.getTo(); // bucket to value long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], from [{}], to [{}], doc_count [{}]", key, from, to, docCount); }

This will basically produce:

key [*-3.0], from [0.0], to [3.0], doc_count [161]
key [3.0-10.0], from [3.0], to [10.0], doc_count [460]
key [10.0-500.0], from [10.0], to [500.0], doc_count [4925]

Geo Hash Grid Aggregation

Prepare aggregation request
下面是一個如何創建聚合請求的例子:

AggregationBuilder aggregation = AggregationBuilders .geohashGrid("agg") .field("address.location") .precision(4);

Use aggregation response
導入聚合定義類:

import org.elasticsearch.search.aggregations.bucket.geogrid.GeoHashGrid; // sr is here your SearchResponse object GeoHashGrid agg = sr.getAggregations().get("agg"); // For each entry for (GeoHashGrid.Bucket entry : agg.getBuckets()) { String keyAsString = entry.getKeyAsString(); // key as String GeoPoint key = (GeoPoint) entry.getKey(); // key as geo point long docCount = entry.getDocCount(); // Doc count logger.info("key [{}], point {}, doc_count [{}]", keyAsString, key, docCount); }

This will basically produce:

key [gbqu], point [47.197265625, -1.58203125], doc_count [1282]
key [gbvn], point [50.361328125, -4.04296875], doc_count [1248]
key [u1j0], point [50.712890625, 7.20703125], doc_count [1156]
key [u0j2], point [45.087890625, 7.55859375], doc_count [1138]

相關文章

1. ElasticSearch6.X版本Java Api中文詳解（五）之Multi Get API、Bulk API解析
2. ElasticSearch6.X版本Java Api中文詳解（六）之Using Bulk Processor解析
3. ElasticSearch6.X版本Java Api中文詳解（七）之Update By Query API解析
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