Elasticsearch java API (18)Aggregations 聚合 Bucket

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桶聚合编辑

全球聚合编辑

下面是如何使用 Global Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

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

// sr is here your SearchResponse objectGlobal agg = sr.getAggregations().get("agg");agg.getDocCount(); // Doc coun

过滤器聚合编辑

下面是如何使用 Filters Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

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

// sr is here your SearchResponse objectFilter agg = sr.getAggregations().get("agg");agg.getDocCount(); // Doc count

过滤器聚合编辑

下面是如何使用Filters Aggregation与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.filters.Filters

// sr is here your SearchResponse objectFilters agg = sr.getAggregations().get("agg");// For each entryfor (Filters.Bucket entry : agg.getBuckets()) {    String key = entry.getKeyAsString();            // bucket key    long docCount = entry.getDocCount();            // Doc count    logger.info("key [{}], doc_count [{}]", key, docCount);}

这将主要生产:

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

Missing聚合编辑

下面是如何使用Missing Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

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

// sr is here your SearchResponse objectMissing agg = sr.getAggregations().get("agg");agg.getDocCount(); // Doc count

嵌套式聚合编辑

下面是如何使用Nested Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

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

// sr is here your SearchResponse objectNested agg = sr.getAggregations().get("agg");agg.getDocCount(); // Doc count

反向嵌套式聚合编辑

下面是如何使用Reverse Nested Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

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 objectNested 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聚合编辑

下面是如何使用Children Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

AggregationBuilder aggregation =    AggregationBuilders        .children("agg")        .childType("reseller");

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.children.Children;

// sr is here your SearchResponse objectChildren agg = sr.getAggregations().get("agg");agg.getDocCount(); // Doc count

从聚合编辑

下面是如何使用Terms Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

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

// sr is here your SearchResponse objectTerms genders = sr.getAggregations().get("genders");// For each entryfor (Terms.Bucket entry : genders.getBuckets()) {    entry.getKey();      // Term    entry.getDocCount(); // Doc count}

订单编辑

订购他们的桶 doc_count在一个提升的方式:

AggregationBuilders    .terms("genders")    .field("gender")    .order(Terms.Order.count(true))

下令桶按字母顺序的条款以升序的方式:

AggregationBuilders    .terms("genders")    .field("gender")    .order(Terms.Order.term(true))

订购的桶单值指标sub-aggregation(被聚合的名字):

AggregationBuilders    .terms("genders")    .field("gender")    .order(Terms.Order.aggregation("avg_height", false))    .subAggregation(        AggregationBuilders.avg("avg_height").field("height")    )

重要术语的聚合编辑

下面是如何使用重要术语的聚合与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.significant.SignificantTerms;

// sr is here your SearchResponse objectSignificantTerms agg = sr.getAggregations().get("significant_countries");// For each entryfor (SignificantTerms.Bucket entry : agg.getBuckets()) {    entry.getKey();      // Term    entry.getDocCount(); // Doc count}

聚合范围编辑

下面是如何使用Range Aggregation与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.range.Range;

// sr is here your SearchResponse objectRange agg = sr.getAggregations().get("agg");// For each entryfor (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);}

基本上这将产生第一个例子:

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]

日期范围聚合编辑

下面是如何使用Date Range Aggregation与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.range.Range;

// sr is here your SearchResponse objectRange agg = sr.getAggregations().get("agg");// For each entryfor (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);}

这将主要生产:

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范围聚合编辑

下面是如何使用Ip范围聚合与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

AggregationBuilder 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

注意,您还可以使用ip面具范围:

AggregationBuilder aggregation =        AggregationBuilders                .ipRange("agg")                .field("ip")                .addMaskRange("192.168.0.0/32")                .addMaskRange("192.168.0.0/24")                .addMaskRange("192.168.0.0/16");

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.range.Range;

// sr is here your SearchResponse objectRange agg = sr.getAggregations().get("agg");// For each entryfor (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);}

基本上这将产生第一个例子:

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]

和第二个(使用Ip面具):

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]

直方图聚合编辑

下面是如何使用 Histogram Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.histogram.Histogram;

// sr is here your SearchResponse objectHistogram agg = sr.getAggregations().get("agg");// For each entryfor (Histogram.Bucket entry : agg.getBuckets()) {    Long key = (Long) entry.getKey();       // Key    long docCount = entry.getDocCount();    // Doc count    logger.info("key [{}], doc_count [{}]", key, docCount);}

日期直方图聚合编辑

下面是如何使用Date Histogram Aggregation 与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

AggregationBuilder aggregation =        AggregationBuilders                .dateHistogram("agg")                .field("dateOfBirth")                .interval(DateHistogramInterval.YEAR);

如果你想设置一个10天的时间间隔:

AggregationBuilder aggregation =        AggregationBuilders                .dateHistogram("agg")                .field("dateOfBirth")                .interval(DateHistogramInterval.days(10));

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.histogram.Histogram

// sr is here your SearchResponse objectHistogram agg = sr.getAggregations().get("agg");// For each entryfor (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);}

基本上这将产生第一个例子:

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]

地理距离聚合编辑

下面是如何使用 Geo Distance Aggregation与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.range.Range;

// sr is here your SearchResponse objectRange agg = sr.getAggregations().get("agg");// For each entryfor (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);}

这将主要生产:

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]

地理散列网格聚合编辑

下面是如何使用 Geo Hash Grid Aggregation与Java API。

准备聚合请求编辑

这里有一个例子关于如何创建聚合的要求:

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

使用聚合反应编辑

导入聚合定义类:

import org.elasticsearch.search.aggregations.bucket.geogrid.GeoHashGrid;

// sr is here your SearchResponse objectGeoHashGrid agg = sr.getAggregations().get("agg");// For each entryfor (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);}

这将主要生产:

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]...

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