Ealsticsearch 5.x Java API聚合string类型的时候，会报错（json的错），则需要在聚合的string类型字段的后面添加.keyword , 虽然使用watch查看聚合的es json的时候会出现以下报错，但是不会影响结果。

{ "error" : "JsonGenerationException[Can not write a field name, expecting a value]"}

1、Metrics Aggregations(度量聚合)

1)、MinAggregation(最小值聚合)

1、Prepare aggregation request

MinAggregationBuilder aggregation =

AggregationBuilders

.min("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.min.Min;

// sr is here your SearchResponse object

Min agg = sr.getAggregations().get("agg");

double value = agg.getValue();

2)、MaxAggregation(最大值聚合)

1、Prepare aggregation request

MaxAggregationBuilder aggregation =

AggregationBuilders

.max("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.max.Max;

// sr is here your SearchResponse object

Max agg = sr.getAggregations().get("agg");

double value = agg.getValue();

3)、SumAggregation(求和聚合)

1、Prepare aggregation request

SumAggregationBuilder aggregation =

AggregationBuilders

.sum("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.sum.Sum;

// sr is here your SearchResponse object

Sum agg = sr.getAggregations().get("agg");

double value = agg.getValue();

4) 、AvgAggregation(平均数聚合)

1、Prepare aggregation request

AvgAggregationBuilder aggregation =

AggregationBuilders

.avg("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.avg.Avg;

// sr is here your SearchResponse object

Avg agg = sr.getAggregations().get("agg");

double value = agg.getValue();

5)、StatsAggregation(统计聚合)

统计聚合即一次性获取最小值、最小值、平均值、求和、统计聚合的集合。

1、Prepare aggregation request

StatsAggregationBuilder aggregation =

AggregationBuilders

.stats("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.stats.Stats;

// sr is here your SearchResponse object

Stats agg = sr.getAggregations().get("agg");

double min = agg.getMin();

double max = agg.getMax();

double avg = agg.getAvg();

double sum = agg.getSum();

long count = agg.getCount();

6) 、Extended Stats Aggregation(扩展统计聚合)

1、Prepare aggregation request

ExtendedStatsAggregationBuilder aggregation =

AggregationBuilders

.extendedStats("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.stats.extended.ExtendedStats;

// sr is here your SearchResponse object

ExtendedStats agg = sr.getAggregations().get("agg");

double min = agg.getMin();

double max = agg.getMax();

double avg = agg.getAvg();

double sum = agg.getSum();

long count = agg.getCount();

double stdDeviation = agg.getStdDeviation();

double sumOfSquares = agg.getSumOfSquares();

double variance = agg.getVariance();

7) 、Values CountAggregation(值计数聚合)

1、Prepare aggregation request

ValueCountAggregationBuilder aggregation =

AggregationBuilders

.count("agg")

.field("height");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.valuecount.ValueCount;

// sr is here your SearchResponse object

ValueCount agg = sr.getAggregations().get("agg");

long value = agg.getValue();

8) 、Percentile Aggregation(百分位聚合)

1、Prepare aggregation request

PercentilesAggregationBuilder aggregation =

AggregationBuilders

.percentiles("agg")

.field("height");

自定义百分比：

PercentilesAggregationBuilder aggregation =

AggregationBuilders

.percentiles("agg")

.field("height")

.percentiles(1.0, 5.0, 10.0, 20.0, 30.0, 75.0, 95.0, 99.0);

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.percentiles.Percentile;

import org.elasticsearch.search.aggregations.metrics.percentiles.Percentiles;

// sr is here your SearchResponse object

Percentiles agg = sr.getAggregations().get("agg");

// For each entry

for (Percentile entry : agg) {

double percent = entry.getPercent();    // Percent

double value = entry.getValue();        // Value

logger.info("percent [{}], value [{}]", percent, value);

}

3、Result

percent [1.0], value [0.814338896154595]

percent [5.0], value [0.8761912455821302]

percent [25.0], value [1.173346540141847]

percent [50.0], value [1.5432023318692198]

percent [75.0], value [1.923915462033674]

percent [95.0], value [2.2273644908535335]

percent [99.0], value [2.284989339108279]

9)、Percentile Ranks Aggregation(百分等级聚合)

1、Prepare aggregation request

PercentileRanksAggregationBuilder aggregation =

AggregationBuilders

.percentileRanks("agg")

.field("height")

.values(1.24, 1.91, 2.22);

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.percentiles.Percentile;

import org.elasticsearch.search.aggregations.metrics.percentiles.PercentileRanks;

// sr is here your SearchResponse object

PercentileRanks agg = sr.getAggregations().get("agg");

// For each entry

for (Percentile entry : agg) {

double percent = entry.getPercent();    // Percent

double value = entry.getValue();        // Value

logger.info("percent [{}], value [{}]", percent, value);

}

3、Result

percent [29.664353095090945], value [1.24]

percent [73.9335313461868], value [1.91]

percent [94.40095147327283], value [2.22]

10)、Cardinality Aggregation(基数聚合)

1、Prepare aggregation request

CardinalityAggregationBuilder aggregation =

AggregationBuilders

.cardinality("agg")

.field("tags");

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.cardinality.Cardinality;

// sr is here your SearchResponse object

Cardinality agg = sr.getAggregations().get("agg");

long value = agg.getValue();

11)、Geo Bounds Aggregation(地理限制聚合)

1、Prepare aggregation request

GeoBoundsBuilder aggregation =

GeoBoundsAggregationBuilder

.geoBounds("agg")

.field("address.location")

.wrapLongitude(true);

2、Use aggregation response

import org.elasticsearch.search.aggregations.metrics.geobounds.GeoBounds;

// sr is here your SearchResponse object

GeoBounds agg = sr.getAggregations().get("agg");

GeoPoint bottomRight = agg.bottomRight();

GeoPoint topLeft = agg.topLeft();

logger.info("bottomRight {}, topLeft {}", bottomRight, topLeft);

3、Result

bottomRight [40.70500764381921, 13.952946866893775], topLeft [53.49603022435221, -4.190029308156676]

12)、Top Hits Aggregation(top n聚合)

1）、Prepare aggregation request

1、只查询分组的top 1：

AggregationBuilder aggregation = AggregationBuilders

.terms("agg").field("gender")

.subAggregation(

AggregationBuilders.topHits("top")

);

2、查询分组的top n：

AggregationBuilder aggregation = AggregationBuilders

.terms("agg").field("gender")

.subAggregation(

AggregationBuilders.topHits("top")

.explain(true)

.size(1)

.from(10)

);

2）、Use aggregation response

import org.elasticsearch.search.aggregations.bucket.terms.Terms;

import org.elasticsearch.search.aggregations.metrics.tophits.TopHits;

// sr is here your SearchResponse object

Terms agg = sr.getAggregations().get("agg");

// For each entry

for (Terms.Bucket entry : agg.getBuckets()) {

String key = entry.getKey();                    // bucket key

long docCount = entry.getDocCount();            // Doc count

logger.info("key [{}], doc_count [{}]", key, docCount);

// We ask for top_hits for each bucket

TopHits topHits = entry.getAggregations().get("top");

for (SearchHit hit : topHits.getHits().getHits()) {

logger.info(" -> id [{}], _source [{}]", hit.getId(), hit.getSourceAsString());

}

}

3）、查询结果：

key [male], doc_count [5107]

-> id [AUnzSZze9k7PKXtq04x2], _source [{"gender":"male",...}]

-> id [AUnzSZzj9k7PKXtq04x4], _source [{"gender":"male",...}]

-> id [AUnzSZzl9k7PKXtq04x5], _source [{"gender":"male",...}]

key [female], doc_count [4893]

-> id [AUnzSZzM9k7PKXtq04xy], _source [{"gender":"female",...}]

-> id [AUnzSZzp9k7PKXtq04x8], _source [{"gender":"female",...}]

-> id [AUnzSZ0W9k7PKXtq04yS], _source [{"gender":"female",...}]

13)、Scripted Metric Aggregation(脚本度量聚合)

1、maven依赖

<dependency>

<groupId>org.codehaus.groovy</groupId>

<artifactId>groovy-all</artifactId>

<version>2.3.2</version>

<classifier>indy</classifier>

</dependency>

1、Prepare aggregation request

ScriptedMetricAggregationBuilder aggregation = AggregationBuilders

.scriptedMetric("agg")

.initScript(new Script("params._agg.heights = []"))

.mapScript(new Script("params._agg.heights.add(doc.gender.value == 'male' ? doc.height.value : -1.0 * doc.height.value)"));

You can also specify a combine script which will be executed on each shard:

ScriptedMetricAggregationBuilder aggregation = AggregationBuilders

.scriptedMetric("agg")

.initScript(new Script("params._agg.heights = []"))

.mapScript(new Script("params._agg.heights.add(doc.gender.value == 'male' ? doc.height.value : -1.0 * doc.height.value)"))

.combineScript(new Script("double heights_sum = 0.0; for (t in params._agg.heights) { heights_sum += t } return heights_sum"));

You can also specify a reduce script which will be executed on the node which gets the request:

ScriptedMetricAggregationBuilder aggregation = AggregationBuilders

.scriptedMetric("agg")

.initScript(new Script("params._agg.heights = []"))

.mapScript(new Script("params._agg.heights.add(doc.gender.value == 'male' ? doc.height.value : -1.0 * doc.height.value)"))

.combineScript(new Script("double heights_sum = 0.0; for (t in params._agg.heights) { heights_sum += t } return heights_sum"))

.reduceScript(new Script("double heights_sum = 0.0; for (a in params._aggs) { heights_sum += a } return heights_sum"));

2、Use aggregation response

import org.elasticsearch.search.aggregations.bucket.terms.Terms;

import org.elasticsearch.search.aggregations.metrics.tophits.TopHits;

// sr is here your SearchResponse object

ScriptedMetric agg = sr.getAggregations().get("agg");

Object scriptedResult = agg.aggregation();

logger.info("scriptedResult [{}]", scriptedResult);

3、Result

result1:

scriptedResult object [ArrayList]

scriptedResult [ {

"heights" : [ 1.122218480146643, -1.8148918111233887, -1.7626731575142909, ... ]

}, {

"heights" : [ -0.8046067304119863, -2.0785486707864553, -1.9183567430207953, ... ]

}, {

"heights" : [ 2.092635728868694, 1.5697545960886536, 1.8826954461968808, ... ]

}, {

"heights" : [ -2.1863201099468403, 1.6328549117346856, -1.7078288405893842, ... ]

}, {

"heights" : [ 1.6043904836424177, -2.0736538674414025, 0.9898266674373053, ... ]

} ]

Result2:

scriptedResult object [ArrayList]

scriptedResult [-41.279615707402876,

-60.88007362339038,

38.823270659734256,

14.840192739445632,

11.300902755741326]

Result3:

scriptedResult object [Double]

scriptedResult [2.171917696507009]

2、Bucket Aggregations(桶聚合)

1) 、Global Aggregation(整体聚合)

1、Prepare aggregation request

AggregationBuilders

.global("agg")

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

2、Use aggregation response

import org.elasticsearch.search.aggregations.bucket.global.Global;

// sr is here your SearchResponse object

Global agg = sr.getAggregations().get("agg");

agg.getDocCount(); // Doc count

2)、FilterAggregation(过滤聚合)

1、Prepare aggregation request

AggregationBuilders

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

2、Use aggregation response

import org.elasticsearch.search.aggregations.bucket.filter.Filter;

// sr is here your SearchResponse object

Filter agg = sr.getAggregations().get("agg");

agg.getDocCount(); // Doc count

3)、FilterAggregation(多过滤聚合)

1、Prepare aggregation request

AggregationBuilder aggregation =

AggregationBuilders

.filters("agg",

new FiltersAggregator.KeyedFilter("men", QueryBuilders.termQuery("gender", "male")),

new FiltersAggregator.KeyedFilter("women", QueryBuilders.termQuery("gender", "female")));

2、Use aggregation response

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);

}

4) 、Missing Aggregation(失踪聚合)

1、Prepare aggregation request

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

2、Use aggregation response

import org.elasticsearch.search.aggregations.bucket.missing.Missing;

// sr is here your SearchResponse object

Missing agg = sr.getAggregations().get("agg");

agg.getDocCount(); // Doc count

5)、Nested Aggregation(嵌套聚合)

1、Prepare aggregation request

AggregationBuilders

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

2、Use aggregation response

import org.elasticsearch.search.aggregations.bucket.nested.Nested;

// sr is here your SearchResponse object

Nested agg = sr.getAggregations().get("agg");

agg.getDocCount(); // Doc count

6)、Reverse Nested Aggregation(反向嵌套聚合)

1、Prepare aggregation request

AggregationBuilder aggregation =

AggregationBuilders

.nested("agg", "resellers")

.subAggregation(

AggregationBuilders

.terms("name").field("resellers.name")

.subAggregation(

AggregationBuilders

.reverseNested("reseller_to_product")

)

);

2、Use aggregation response

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

}

6)、Children Aggregation(子聚合)

1、Prepare aggregation request

// "agg" is the name of the aggregation and "reseller" is the child // type

AggregationBuilder aggregation =

AggregationBuilders

.children("agg", "reseller");

2、Use aggregation response

import org.elasticsearch.join.aggregations.Children;

// sr is here your SearchResponse object

Children agg = sr.getAggregations().get("agg");

agg.getDocCount(); // Doc count

7)、Terms Aggregation(条件聚合)

1、Prepare aggregation request

AggregationBuilders

.terms("genders")

.field("gender");

2、Use aggregation response

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(true升序，false降序)

1、按照分组字段的数量排序

AggregationBuilders

.terms("genders")

.field("gender")

.order(Terms.Order.count(true))

2、按照分组字段的照字母顺序排序

AggregationBuilders

.terms("genders")

.field("gender")

.order(Terms.Order.term(true))

3、按照聚合名称标识进行排序

AggregationBuilders

.terms("genders")

.field("gender")

.order(Terms.Order.aggregation("avg_height", false))

.subAggregation(

AggregationBuilders.avg("avg_height").field("height")

)

8)、Significant Terms Aggregation(子条件聚合)

1、Prepare aggregation request

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();

2、Use aggregation response

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

}

9)、Range Aggregation(范围聚合)

1、Prepare aggregation request

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

2、Use aggregation response

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);

}

3、result

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]

10)、Date Range Aggregation(日期范围聚合)

1、Prepare aggregation request

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

2、Use aggregation response

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()) {

// Date range as key

String key = entry.getKeyAsString();

// Date bucket from as a Date

DateTime fromAsDate = (DateTime) entry.getFrom();

// Date bucket to as a Date

DateTime toAsDate = (DateTime) entry.getTo();

// Doc count

long docCount = entry.getDocCount();

logger.info("key [{}], from [{}], to [{}], doc_count [{}]", key, fromAsDate, toAsDate, docCount);

}

3、result

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]

11)、IP Range Aggregation(IP范围聚合)

1、Prepare aggregation request

AggregatorBuilder<?> aggregation =

AggregationBuilders

.ipRange("agg")

.field("ip")

// from -infinity to 192.168.1.0 (excluded)

.addUnboundedTo("192.168.1.0")

// from 192.168.1.0 to 192.168.2.0(excluded)

.addRange("192.168.1.0", "192.168.2.0")

// from 192.168.2.0 to +infinity

.addUnboundedFrom("192.168.2.0");

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");

2、Use aggregation response

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()) {

// Ip range as key

String key = entry.getKeyAsString();

// Ip bucket from as a String

String fromAsString = entry.getFromAsString();

// Ip bucket to as a String

String toAsString = entry.getToAsString();

// Doc count

long docCount = entry.getDocCount();

logger.info("key [{}], from [{}], to [{}], doc_count [{}]", key, fromAsString, toAsString, docCount);

}

3、result

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]

Result 2:

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]

12)、Histogram Aggregation(柱状图聚合)

1、Prepare aggregation request

AggregationBuilder aggregation =

AggregationBuilders

.histogram("agg")

.field("height")

.interval(1);

2、Use aggregation response

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);

}

13)、Date Histogram Aggregation(日期柱状图聚合)

1、Prepare aggregation request

AggregationBuilder aggregation =

AggregationBuilders

.dateHistogram("agg")

.field("dateOfBirth")

.dateHistogramInterval(DateHistogramInterval.YEAR);

如果想获取最近十天的数据（相对时间）：

AggregationBuilder aggregation =

AggregationBuilders

.dateHistogram("agg")

.field("dateOfBirth")

.dateHistogramInterval(DateHistogramInterval.days(10));

2、Use aggregation response

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);

}

3、result

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]

14)、Geo Distance Aggregation(地理距离聚合)

1、Prepare aggregation request

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);

2、Use aggregation response

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);

}

3、result

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]

15) 、Geo Hash Grid Aggregation(地理哈希网格聚合)

1、Prepare aggregation request

AggregationBuilder aggregation =

AggregationBuilders

.geohashGrid("agg")

.field("address.location")

.precision(4);

2、Use aggregation response

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);

}

3、result

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]

...

3、Pipeline Aggregations(管道聚合)

4、Matrix Aggregations(矩阵聚合)

Caching heavy aggregations

Returning only aggregation results

Aggregation Metadata

Returning the type of the aggregation

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