Elasticsearch 5.x Java api Aggregations(聚合)
来源:互联网 发布:dns 默认端口 编辑:程序博客网 时间:2024/05/22 00:20
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
- Elasticsearch 5.x Java api Aggregations(聚合)
- Elasticsearch 5.x Java api Aggregations(聚合)
- Elasticsearch java API (16)Aggregations 构建聚合
- Elasticsearch java API (17)Aggregations 聚合 函数
- Elasticsearch java API (18)Aggregations 聚合 Bucket
- Elasticsearch Java API(十一)--聚合(aggregations)
- ElasticSearch 的 聚合(Aggregations)
- ElasticSearch 的 聚合(Aggregations)
- ElasticSearch 的 聚合(Aggregations)
- ElasticSearch 的 聚合(Aggregations)
- Elasticsearch Java API 之Query、Filter、count、Aggregations
- [Elasticsearch] 聚合作用域(Scoping Aggregations)
- [Elasticsearch] 聚合作用域(Scoping Aggregations) 4
- 实时搜索引擎Elasticsearch(4)——Aggregations (聚合)API的使用
- 实时搜索引擎Elasticsearch(4)——Aggregations (聚合)API的使用
- ElasticSearch 5.x Java API
- ElasticSearch java API - 聚合查询
- Elasticsearch 5.X下JAVA API使用指南
- iTerm2 快捷键大全
- MAVEN手动安装jar到本地仓库mvn install
- Tensorflow学习与应用四
- 笨办法学python习题12 提示别人
- 【素数环】递归思维如层层梦境
- Elasticsearch 5.x Java api Aggregations(聚合)
- java作业
- 内存取证——volatility
- Android手机动态获取权限
- 译OpenCms-10.5.3—— 1. 背景话题【Background topics】
- 实验四 队列的基本操作
- 设计一个没有扩容负担的堆结构
- P5-C开发笔试题三道
- List集合删除元素的时候删除不掉