ElasticSearch版本

elasticsearch-5.4.3.jar

指定 ip地址创建client

private TransportClient client = null;
    /**
     *指定 ip地址创建client
     */
    @Before
    public void init() throws Exception {
        //设置集群名称
        Settings settings = Settings.builder()
                .put("cluster.name", "my-es")
                //自动感知的功能（可以通过当前指定的节点获取所有es节点的信息）
                .put("client.transport.sniff", true)
                .build();
        //创建client
        client = new PreBuiltTransportClient(settings).addTransportAddresses(
                // Java对应的API操作的端口都是9300，记住是9300
                new InetSocketTransportAddress(InetAddress.getByName("192.168.100.211"), 9300),
                new InetSocketTransportAddress(InetAddress.getByName("192.168.100.212"), 9300),
                new InetSocketTransportAddress(InetAddress.getByName("192.168.100.213"), 9300));
    }

添加数据

/**
     *添加数据
     */
    @Test
    public void testCreate() throws IOException {
        // index可以理解为数据库；type理解为数据表；id相当于数据库表中记录的主键，是唯一的。
        IndexResponse response = client.prepareIndex("gamelog", "users", "1")
                .setSource(
                        jsonBuilder()
                                .startObject()
                                // field理解为列
                                    .field("username", "老赵")
                                    .field("gender", "male")
                                    .field("birthday", new Date())
                                    .field("fv", 9999)
                                    .field("message", "trying out Elasticsearch")
                                .endObject()
                ).get();
    }

查找一条

 /**
     *查找一条
     */
    @Test
    public void testGet() throws IOException {
        GetResponse response = client.prepareGet("gamelog", "users", "1").get();
        System.out.println(response.getSourceAsString());
    }

查找多条

 /**
     * 查找多条
     */
    @Test
    public void testMultiGet() throws IOException {
        MultiGetResponse multiGetItemResponses = client.prepareMultiGet()
                .add("gamelog", "users", "1")
                .add("gamelog", "users", "2", "3")
                .add("news", "fulltext", "1")
                .get();
        for (MultiGetItemResponse itemResponse : multiGetItemResponses) {
            GetResponse response = itemResponse.getResponse();
            if (response.isExists()) {
                String json = response.getSourceAsString();
                System.out.println(json);
            }
        }
    }

数据更新

 /**
     * 数据更新
     */
    @Test
    public void testUpdate() throws Exception {
        UpdateRequest updateRequest = new UpdateRequest();
        updateRequest.index("gamelog");
        updateRequest.type("users");
        updateRequest.id("2");
        updateRequest.doc(
                jsonBuilder()
                    .startObject()
                        .field("fv", 999.9)
                    .endObject());
        client.update(updateRequest).get();
    }

数据删除-指定ID

 /**
     * 数据删除-指定ID
     */
    @Test
    public void testDelete() {
        DeleteResponse response = client.prepareDelete("gamelog", "users", "2").get();
        System.out.println(response);
    }

数据删除--指定任意某个字段

/**
     * 数据删除--指定任意某个字段
     */
    @Test
    public void testDeleteByQuery() {
        BulkByScrollResponse response =
                DeleteByQueryAction.INSTANCE.newRequestBuilder(client)
                        //指定查询条件
                        .filter(QueryBuilders.matchQuery("username", "老段"))
                        //指定索引名称
                        .source("gamelog")
                        .get();
        long deleted = response.getDeleted();
        System.out.println(deleted);
    }

异步删除

 /**
     * 异步删除
     */
    @Test
    public void testDeleteByQueryAsync() {
        DeleteByQueryAction.INSTANCE.newRequestBuilder(client)
                .filter(QueryBuilders.matchQuery("gender", "male"))
                .source("gamelog")
                .execute(new ActionListener<BulkByScrollResponse>() {
                    @Override
                    public void onResponse(BulkByScrollResponse response) {
                        long deleted = response.getDeleted();
                        System.out.println("数据删除了");
                        System.out.println(deleted);
                    }
                    @Override
                    public void onFailure(Exception e) {
                        e.printStackTrace();
                    }
                });
        try {
            System.out.println("异步删除");
            Thread.sleep(10000);
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

范围查询

  /**
     *  范围查询
     */
    @Test
    public void testRange() {
        QueryBuilder qb = rangeQuery("fv")
                // [88.99, 10000)
                .from(88.99)
                .to(10000)
                .includeLower(true)
                .includeUpper(false);
        SearchResponse response = client.prepareSearch("gamelog").setQuery(qb).get();
        System.out.println(response);
    }

聚合查询

先添加一些数据

  /**
     * curl -XPUT 'http://192.168.5.251:9200/player_info/player/1' -d '{ "name": "curry", "age": 29, "salary": 3500,"team": "war", "position": "pg"}'
     * curl -XPUT 'http://192.168.5.251:9200/player_info/player/2' -d '{ "name": "thompson", "age": 26, "salary": 2000,"team": "war", "position": "pg"}'
     * curl -XPUT 'http://192.168.5.251:9200/player_info/player/3' -d '{ "name": "irving", "age": 25, "salary": 2000,"team": "cav", "position": "pg"}'
     * curl -XPUT 'http://192.168.5.251:9200/player_info/player/4' -d '{ "name": "green", "age": 26, "salary": 2000,"team": "war", "position": "pf"}'
     * curl -XPUT 'http://192.168.5.251:9200/player_info/player/5' -d '{ "name": "james", "age": 33, "salary": 4000,"team": "cav", "position": "sf"}'
     */

 @Test
    public void testAddPlayer() throws IOException {
        IndexResponse response = client.prepareIndex("player_info", "player", "1")
                .setSource(
                        jsonBuilder()
                                .startObject()
                                .field("name", "James")
                                .field("age", 33)
                                .field("salary", 3000)
                                .field("team", "cav")
                                .field("position", "sf")
                                .endObject()
                ).get();
    }

group by/count

例如要计算每个球队的球员数，如果使用SQL语句，应表达如下：

select team, count(*) as player_count from player group by team;

ES的java api：

@Test
    public void testAgg1() {
        //指定索引和type
        SearchRequestBuilder builder = client.prepareSearch("player_info").setTypes("player");
        //按team分组然后聚合，但是并没有指定聚合函数
        TermsAggregationBuilder teamAgg = AggregationBuilders.terms("player_count").field("team");
        //添加聚合器
        builder.addAggregation(teamAgg);
        //触发
        SearchResponse response = builder.execute().actionGet();
        //System.out.println(response);
        //将返回的结果放入到一个map中
        Map<String, Aggregation> aggMap = response.getAggregations().getAsMap();
//        Set<String> keys = aggMap.keySet();
//
//        for (String key: keys) {
//            System.out.println(key);
//        }
//        //取出聚合属性
        StringTerms terms = (StringTerms) aggMap.get("player_count");
        //
        //依次迭代出分组聚合数据
//        for (Terms.Bucket bucket : terms.getBuckets()) {
//            //分组的名字
//            String team = (String) bucket.getKey();
//            //count，分组后一个组有多少数据
//            long count = bucket.getDocCount();
//            System.out.println(team + " " + count);
//        }
        Iterator<Terms.Bucket> teamBucketIt = terms.getBuckets().iterator();
        while (teamBucketIt .hasNext()) {
            Terms.Bucket bucket = teamBucketIt.next();
            String team = (String) bucket.getKey();
            long count = bucket.getDocCount();
            System.out.println(team + " " + count);
        }
    }

group by多个field

例如要计算每个球队每个位置的球员数，如果使用SQL语句，应表达如下：

select team, position, count(*) as pos_count from player group by team, position;

ES的java api：

 /**
     * group by多个field
     * 例如要计算每个球队每个位置的球员数，如果使用SQL语句
     * select team, position, count(*) as pos_count from player group by team, position;
     */
    @Test
    public void testAgg2() {
        SearchRequestBuilder builder = client.prepareSearch("player_info").setTypes("player");
        //指定别名和分组的字段
        TermsAggregationBuilder teamAgg = AggregationBuilders.terms("team_name").field("team");
        TermsAggregationBuilder posAgg= AggregationBuilders.terms("pos_count").field("position");
        //添加两个聚合构建器
        builder.addAggregation(teamAgg.subAggregation(posAgg));
        //执行查询
        SearchResponse response = builder.execute().actionGet();
        //将查询结果放入map中
        Map<String, Aggregation> aggMap = response.getAggregations().getAsMap();
        //根据属性名到map中查找
        StringTerms teams = (StringTerms) aggMap.get("team_name");
        //循环查找结果
        for (Terms.Bucket teamBucket : teams.getBuckets()) {
            //先按球队进行分组
            String team = (String) teamBucket.getKey();
            Map<String, Aggregation> subAggMap = teamBucket.getAggregations().getAsMap();
            StringTerms positions = (StringTerms) subAggMap.get("pos_count");
            //因为一个球队有很多位置，那么还要依次拿出位置信息
            for (Terms.Bucket posBucket : positions.getBuckets()) {
                //拿到位置的名字
                String pos = (String) posBucket.getKey();
                //拿出该位置的数量
                long docCount = posBucket.getDocCount();
                //打印球队，位置，人数
                System.out.println(team + " " + pos + " " + docCount);
            }
        }
    }

max/min/sum/avg

例如要计算每个球队年龄最大/最小/总/平均的球员年龄，如果使用SQL语句，应表达如下：

select team, max(age) as max_age from player group by team;

ES的java api：

 /**
     * select team, max(age) as max_age from player group by team;
     */
    @Test
    public void testAgg3() {
        SearchRequestBuilder builder = client.prepareSearch("player_info").setTypes("player");
        //指定安球队进行分组
        TermsAggregationBuilder teamAgg = AggregationBuilders.terms("team_name").field("team");
        //指定分组求最大值
        MaxAggregationBuilder maxAgg = AggregationBuilders.max("max_age").field("age");
        //分组后求最大值
        builder.addAggregation(teamAgg.subAggregation(maxAgg));
        //查询
        SearchResponse response = builder.execute().actionGet();
        Map<String, Aggregation> aggMap = response.getAggregations().getAsMap();
        //根据team属性，获取map中的内容
        StringTerms teams = (StringTerms) aggMap.get("team_name");
        for (Terms.Bucket teamBucket : teams.getBuckets()) {
            //分组的属性名
            String team = (String) teamBucket.getKey();
            //在将聚合后取最大值的内容取出来放到map中
            Map<String, Aggregation> subAggMap = teamBucket.getAggregations().getAsMap();
            //取分组后的最大值
            InternalMax ages = (InternalMax)subAggMap.get("max_age");
            double max = ages.getValue();
            System.out.println(team + " " + max);
        }
    }

对多个field求max/min/sum/avg

例如要计算每个球队球员的平均年龄，同时又要计算总年薪，如果使用SQL语句，应表达如下：

select team, avg(age)as avg_age, sum(salary) as total_salary from player group by team;

ES的java api：

 /**
     * select team, avg(age) as avg_age, sum(salary) as total_salary from player group by team;
     */
    @Test
    public void testAgg4() {
        SearchRequestBuilder builder = client.prepareSearch("player_info").setTypes("player");
        //指定分组字段
        TermsAggregationBuilder termsAgg = AggregationBuilders.terms("team_name").field("team");
        //指定聚合函数是求平均数据
        AvgAggregationBuilder avgAgg = AggregationBuilders.avg("avg_age").field("age");
        //指定另外一个聚合函数是求和
        SumAggregationBuilder sumAgg = AggregationBuilders.sum("total_salary").field("salary");
        //分组的聚合器关联了两个聚合函数
        builder.addAggregation(termsAgg.subAggregation(avgAgg).subAggregation(sumAgg));
        SearchResponse response = builder.execute().actionGet();
        Map<String, Aggregation> aggMap = response.getAggregations().getAsMap();
        //按分组的名字取出数据
        StringTerms teams = (StringTerms) aggMap.get("team_name");
        for (Terms.Bucket teamBucket : teams.getBuckets()) {
            //获取球队名字
            String team = (String) teamBucket.getKey();
            Map<String, Aggregation> subAggMap = teamBucket.getAggregations().getAsMap();
            //根据别名取出平均年龄
            InternalAvg avgAge = (InternalAvg)subAggMap.get("avg_age");
            //根据别名取出薪水总和
            InternalSum totalSalary = (InternalSum)subAggMap.get("total_salary");
            double avgAgeValue = avgAge.getValue();
            double totalSalaryValue = totalSalary.getValue();
            System.out.println(team + " " + avgAgeValue + " " + totalSalaryValue);
        }
    }

聚合后对Aggregation结果排序

例如要计算每个球队总年薪，并按照总年薪倒序排列，如果使用SQL语句，应表达如下：

select team, sum(salary) as total_salary from player group by team order by total_salary desc;

ES的java api：

 /**
     * select team, sum(salary) as total_salary from player group by team order by total_salary desc;
     */
    @Test
    public void testAgg5() {
        SearchRequestBuilder builder = client.prepareSearch("player_info").setTypes("player");
        //按team进行分组，然后指定排序规则
        TermsAggregationBuilder termsAgg = AggregationBuilders.terms("team_name").field("team").order(Terms.Order.aggregation("total_salary ", true));
        SumAggregationBuilder sumAgg = AggregationBuilders.sum("total_salary").field("salary");
        builder.addAggregation(termsAgg.subAggregation(sumAgg));
        SearchResponse response = builder.execute().actionGet();
        Map<String, Aggregation> aggMap = response.getAggregations().getAsMap();
        StringTerms teams = (StringTerms) aggMap.get("team_name");
        for (Terms.Bucket teamBucket : teams.getBuckets()) {
            String team = (String) teamBucket.getKey();
            Map<String, Aggregation> subAggMap = teamBucket.getAggregations().getAsMap();
            InternalSum totalSalary = (InternalSum)subAggMap.get("total_salary");
            double totalSalaryValue = totalSalary.getValue();
            System.out.println(team + " " + totalSalaryValue);
        }
    }

需要特别注意的是，排序是在TermAggregation处执行的，Order.aggregation函数的第一个参数是aggregation的名字，第二个参数是boolean型，true表示正序，false表示倒序。

Aggregation结果条数的问题

默认情况下，search执行后，仅返回10条聚合结果，如果想反悔更多的结果，需要在构建TermsBuilder 时指定size：

TermsBuilder teamAgg= AggregationBuilders.terms("team").size(15);

Aggregation结果的解析/输出

得到response后：

Map<String, Aggregation> aggMap = response.getAggregations().asMap();
StringTerms teamAgg= (StringTerms) aggMap.get("keywordAgg");
Iterator<Bucket> teamBucketIt = teamAgg.getBuckets().iterator();
while (teamBucketIt .hasNext()) {
Bucket buck = teamBucketIt .next();
//球队名
String team = buck.getKey();
//记录数
long count = buck.getDocCount();
//得到所有子聚合
Map subaggmap = buck.getAggregations().asMap();
//avg值获取方法
double avg_age= ((InternalAvg) subaggmap.get("avg_age")).getValue();
//sum值获取方法
double total_salary = ((InternalSum) subaggmap.get("total_salary")).getValue();
//...
//max/min以此类推
}

总结

综上，聚合操作主要是调用了SearchRequestBuilder的addAggregation方法，通常是传入一个TermsBuilder，子聚合调用TermsBuilder的subAggregation方法，可以添加的子聚合有TermsBuilder、SumBuilder、AvgBuilder、MaxBuilder、MinBuilder等常见的聚合操作。

从实现上来讲，SearchRequestBuilder在内部保持了一个私有的 SearchSourceBuilder实例， SearchSourceBuilder内部包含一个List<AbstractAggregationBuilder>，每次调用addAggregation时会调用 SearchSourceBuilder实例，添加一个AggregationBuilder。

同样的，TermsBuilder也在内部保持了一个List<AbstractAggregationBuilder>，调用addAggregation方法（来自父类addAggregation）时会添加一个AggregationBuilder。有兴趣的读者也可以阅读源码的实现。

参考来源：https://www.elastic.co/guide/en/elasticsearch/client/java-api/5.4/index.html

参考来源：https://elasticsearch.cn/article/102

ElasticSearch: java API - 基本增删改查和聚合查询

ElasticSearch版本

指定 ip地址创建client

添加数据

查找一条

查找多条

数据更新

数据删除-指定ID

数据删除--指定任意某个字段

异步删除

范围查询

聚合查询

group by/count

group by多个field

max/min/sum/avg

对多个field求max/min/sum/avg

聚合后对Aggregation结果排序

总结

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