首先要说
java 操作 elasticsearch 有四种方式
- 调用 elasticsearch 的 restapis 接口
- 调用 java elasticsearch client 的接口
- 整合 spring data 使用 ElasticsearchTemplate 封装的方法
- 继承 ElasticsearchRepository 接口调用方法
测试准备
我们先来准备一些数据,写了一个之前的获取JoyMusic 的音乐数据的项目来说,项目的结构是这样的:
获取数据的主要代码如下,只是为了增加数据
@RunWith(SpringJUnit4ClassRunner.class)
@SpringBootTest(classes = JoylauElasticsearchApplication.class,webEnvironment = SpringBootTest.WebEnvironment.MOCK)
public class JoylauElasticsearchApplicationTests {
@Autowired
private RestTemplate restTemplate;
@Autowired
private PlaylistDAO playlistDAO;
@Autowired
private SongDAO songDAO;
@Autowired
private CommentDAO commentDAO;
@Test
public void createData() {
String personalizeds = restTemplate.getForObject("http://localhost:3003/apis/v1"+"/personalized",String.class);
JSONObject perJSON = JSONObject.parseObject(personalizeds);
JSONArray perArr = perJSON.getJSONArray("result");
List<Playlist> list = new ArrayList<>();
List<Integer> playListIds = new ArrayList<>();
for (Object o : perArr) {
JSONObject playListJSON = JSONObject.parseObject(o.toString());
Playlist playlist = new Playlist();
playlist.setId(playListJSON.getIntValue("id"));
playListIds.add(playlist.getId());
playlist.setName(playListJSON.getString("name"));
playlist.setPicURL(playListJSON.getString("picUrl"));
playlist.setPlayCount(playListJSON.getIntValue("playCount"));
playlist.setBookCount(playListJSON.getIntValue("bookCount"));
playlist.setTrackCount(playListJSON.getIntValue("trackCount"));
list.add(playlist);
}
playlistDAO.saveAll(list);
/*存储歌曲*/
List<Integer> songIds = new ArrayList<>();
List<Song> songList = new ArrayList<>();
for (Integer playListId : playListIds) {
String res = restTemplate.getForObject("http://localhost:3003/apis/v1"+"/playlist/detail?id="+playListId,String.class);
JSONArray songJSONArr = JSONObject.parseObject(res).getJSONObject("playlist").getJSONArray("tracks");
for (Object o : songJSONArr) {
JSONObject songJSON = JSONObject.parseObject(o.toString());
Song song = new Song();
song.setId(songJSON.getIntValue("id"));
songIds.add(song.getId());
song.setName(songJSON.getString("name"));
song.setAuthor(getSongAuthor(songJSON.getJSONArray("ar")));
song.setTime(songJSON.getLong("dt"));
song.setPlaylistId(playListId);
song.setPicURL(songJSON.getJSONObject("al").getString("picUrl"));
song.setAlbum(songJSON.getJSONObject("al").getString("name"));
songList.add(song);
}
}
songDAO.saveAll(songList);
/*存储评论*/
List<Comment> commentList = new ArrayList<>();
for (Integer songId : songIds) {
String res = restTemplate.getForObject("http://localhost:3003/apis/v1"+"/comment/music?id="+songId+"&offset="+300,String.class);
JSONArray commentArr = JSONObject.parseObject(res).getJSONArray("comments");
for (Object o : commentArr) {
JSONObject commentJSON = JSONObject.parseObject(o.toString());
Comment comment = new Comment();
comment.setId(commentJSON.getIntValue("commentId"));
comment.setSongId(songId);
comment.setContent(commentJSON.getString("content"));
comment.setAuthor(commentJSON.getJSONObject("user").getString("nickname"));
comment.setPicUrl(commentJSON.getJSONObject("user").getString("avatarUrl"));
comment.setTime(commentJSON.getLong("time"));
comment.setSupport(commentJSON.getIntValue("likedCount"));
commentList.add(comment);
}
}
commentDAO.saveAll(commentList);
}
/**
* 获取歌曲作者名
* @param arr arr
* @return String
*/
private String getSongAuthor(JSONArray arr){
StringBuilder author = new StringBuilder();
for (Object o : arr) {
JSONObject json = JSONObject.parseObject(o.toString());
author.append(json.getString("name"));
if (arr.size() > 1){
author.append(",");
}
}
return author.toString();
}
}
跑了起来之后, elasticsearch 增加的数据如下:
现在数据有了,接下来就是使用各种方法了
ElasticSearchTemplate 和 ElasticsearchRepository 的关系
ElasticSearchTemplate 是 spring date 对 elasticsearch 客户端 Java API 的封装,而 ElasticsearchRepository,是ElasticSearchTemplate更深层次的封装,可以使用注解,很类似以前 mybatis 的使用
ElasticSearchTemplate提供的方法更多,ElasticsearchRepository能用的方法其实全部都在而 ElasticSearchTemplate 都有实现
我们只要能熟悉调用的 ElasticSearchTemplate 里面的方法操作
ElasticsearchRepository都能够会操作
ElasticSearchTemplate
一些很底层的方法，我们最常用的就是elasticsearchTemplate.queryForList(searchQuery, class);
而这里面最主要的就是构建searchQuery，一下总结几个最常用的searchQuery以备忘
searchQuery能构建好,其他的就很简单了
queryStringQuery
单字符串全文查询
/**
* 单字符串模糊查询，默认排序。将从所有字段中查找包含传来的word分词后字符串的数据集
*/
@Test
public void queryStringQuerySong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(queryStringQuery("Time")).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}返回的结果如下
{
"query_string" : {
"query" : "Time",
"fields" : [ ],
"use_dis_max" : true,
"tie_breaker" : 0.0,
"default_operator" : "or",
"auto_generate_phrase_queries" : false,
"max_determinized_states" : 10000,
"enable_position_increments" : true,
"fuzziness" : "AUTO",
"fuzzy_prefix_length" : 0,
"fuzzy_max_expansions" : 50,
"phrase_slop" : 0,
"escape" : false,
"split_on_whitespace" : true,
"boost" : 1.0
}
}
{"album":"Time","author":"Cat naps","id":459733590,"name":"Time","picURL":"http://p1.music.126.net/9DmApLeDwutb4HpuhD_E-Q==/18624627464667106.jpg","playlistId":900228548,"time":86465}
{"album":"Go Time","author":"Mark Petrie","id":29717271,"name":"Go Time","picURL":"http://p1.music.126.net/TJe468hZr_0ndQRfTAKdqA==/3233663697760186.jpg","playlistId":636015704,"time":136071}
{"album":"Out of Time","author":"R.E.M.","id":20282663,"name":"Losing My Religion","picURL":"http://p1.music.126.net/wYtpqN8Yu2jamQwdM6ugGg==/6638851209090428.jpg","playlistId":772430182,"time":269270}
{"album":"Time Flies... 1994-2009","author":"Oasis","id":17822660,"name":"Cigarettes & Alcohol","picURL":"http://p1.music.126.net/qDgXElJRtSsuqNwsTzW8lw==/667403558069001.jpg","playlistId":772430182,"time":291853}
{"album":"Electric Warrior","author":"T. Rex","id":29848501,"name":"There Was A Time","picURL":"http://p1.music.126.net/dn1MwEBfBcL4l6isrnEwDw==/3246857839528733.jpg","playlistId":772430182,"time":60577}
{"album":"Ride On Time","author":"山下達郎","id":22693846,"name":"DAYDREAM","picURL":"http://p1.music.126.net/GaQVveQiyTIqecs7hhoYpA==/749866930165154.jpg","playlistId":900228548,"time":273476}
{"album":"The Blossom Chronicles","author":"Philter","id":21375446,"name":"Adventure Time","picURL":"http://p1.music.126.net/YjMS5_kM3u9PCUU0lcRK8g==/6657542907248762.jpg","playlistId":636015704,"time":207412}
{"album":"Decimus","author":"Audio Machine","id":36586631,"name":"Ashes of Time","picURL":"http://p1.music.126.net/7InBepjNDGCzpzH8Feyw9A==/3395291908535260.jpg","playlistId":636015704,"time":190826}
{"album":"In Time: The Best Of R.E.M. 1988-2003","author":"R.E.M.","id":20283068,"name":"Bad Day","picURL":"http://p1.music.126.net/aZXu5ulRJvH4dnoWPjxb3A==/18277181789089107.jpg","playlistId":772430182,"time":248111}
{"album":"It's a Poppin' Time","author":"山下達郎","id":22693864,"name":"HEY THERE LONELY GIRL","picURL":"http://p1.music.126.net/PGZlyXk20_-5d6E3pDEKpg==/815837627833461.jpg","playlistId":900228548,"time":325956}
{"album":"Shire Music Annual Selection - Myth","author":"Shire Music,Songs To Your Eyes,","id":34916751,"name":"Between Space And Time","picURL":"http://p1.music.126.net/CCqLd2ly2XuuSPz0IW0u-g==/3284241233077333.jpg","playlistId":636015704,"time":222456}
{"album":"Double Live Doggie Style I","author":"X-Ray Dog","id":26246058,"name":"Time Will Tell","picURL":"http://p1.music.126.net/oYEIMWnAvpuRDTk4g_l-lg==/2503587976473913.jpg","playlistId":636015704,"time":202133}
{"album":"The Ghost Of Tom Joad","author":"Bruce Springsteen","id":16657852,"name":"Straight Time (Album Version)","picURL":"http://p1.music.126.net/yK0V-aD3Myh4xorvwUtCrw==/17889054184179160.jpg","playlistId":772430182,"time":210651}
{"album":"Epic Action & Adventure Vol. 6","author":"Epic Score","id":4054121,"name":"Time Will Remember Us","picURL":"http://p1.music.126.net/uN8AYI3sQEgoECuSYmi9Eg==/658607465082090.jpg","playlistId":636015704,"time":165000}
我们修改一下排序方式，按照id从大到小排序
/**
* 单字符串模糊查询，单字段排序。
*/
@Test
public void queryStringQueryWeightSong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(queryStringQuery("Time")).withPageable(of(0,100,new Sort(Sort.Direction.DESC,"id"))).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}也可以使用注解,这么写
public void queryStringQueryWeightSong(@PageableDefault(sort = "id", direction = Sort.Direction.DESC) Pageable pageable){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(queryStringQuery("Time")).withPageable(pageable).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}返回的结果
{
"query_string" : {
"query" : "Time",
"fields" : [ ],
"use_dis_max" : true,
"tie_breaker" : 0.0,
"default_operator" : "or",
"auto_generate_phrase_queries" : false,
"max_determinized_states" : 10000,
"enable_position_increments" : true,
"fuzziness" : "AUTO",
"fuzzy_prefix_length" : 0,
"fuzzy_max_expansions" : 50,
"phrase_slop" : 0,
"escape" : false,
"split_on_whitespace" : true,
"boost" : 1.0
}
}
{"album":"Time","author":"Cat naps","id":459733590,"name":"Time","picURL":"http://p1.music.126.net/9DmApLeDwutb4HpuhD_E-Q==/18624627464667106.jpg","playlistId":900228548,"time":86465}
{"album":"Decimus","author":"Audio Machine","id":36586631,"name":"Ashes of Time","picURL":"http://p1.music.126.net/7InBepjNDGCzpzH8Feyw9A==/3395291908535260.jpg","playlistId":636015704,"time":190826}
{"album":"Shire Music Annual Selection - Myth","author":"Shire Music,Songs To Your Eyes,","id":34916751,"name":"Between Space And Time","picURL":"http://p1.music.126.net/CCqLd2ly2XuuSPz0IW0u-g==/3284241233077333.jpg","playlistId":636015704,"time":222456}
{"album":"Electric Warrior","author":"T. Rex","id":29848501,"name":"There Was A Time","picURL":"http://p1.music.126.net/dn1MwEBfBcL4l6isrnEwDw==/3246857839528733.jpg","playlistId":772430182,"time":60577}
{"album":"Go Time","author":"Mark Petrie","id":29717271,"name":"Go Time","picURL":"http://p1.music.126.net/TJe468hZr_0ndQRfTAKdqA==/3233663697760186.jpg","playlistId":636015704,"time":136071}
{"album":"Double Live Doggie Style I","author":"X-Ray Dog","id":26246058,"name":"Time Will Tell","picURL":"http://p1.music.126.net/oYEIMWnAvpuRDTk4g_l-lg==/2503587976473913.jpg","playlistId":636015704,"time":202133}
{"album":"It's a Poppin' Time","author":"山下達郎","id":22693864,"name":"HEY THERE LONELY GIRL","picURL":"http://p1.music.126.net/PGZlyXk20_-5d6E3pDEKpg==/815837627833461.jpg","playlistId":900228548,"time":325956}
{"album":"Ride On Time","author":"山下達郎","id":22693846,"name":"DAYDREAM","picURL":"http://p1.music.126.net/GaQVveQiyTIqecs7hhoYpA==/749866930165154.jpg","playlistId":900228548,"time":273476}
{"album":"The Blossom Chronicles","author":"Philter","id":21375446,"name":"Adventure Time","picURL":"http://p1.music.126.net/YjMS5_kM3u9PCUU0lcRK8g==/6657542907248762.jpg","playlistId":636015704,"time":207412}
{"album":"In Time: The Best Of R.E.M. 1988-2003","author":"R.E.M.","id":20283068,"name":"Bad Day","picURL":"http://p1.music.126.net/aZXu5ulRJvH4dnoWPjxb3A==/18277181789089107.jpg","playlistId":772430182,"time":248111}
{"album":"Out of Time","author":"R.E.M.","id":20282663,"name":"Losing My Religion","picURL":"http://p1.music.126.net/wYtpqN8Yu2jamQwdM6ugGg==/6638851209090428.jpg","playlistId":772430182,"time":269270}
{"album":"Time Flies... 1994-2009","author":"Oasis","id":17822660,"name":"Cigarettes & Alcohol","picURL":"http://p1.music.126.net/qDgXElJRtSsuqNwsTzW8lw==/667403558069001.jpg","playlistId":772430182,"time":291853}
{"album":"The Ghost Of Tom Joad","author":"Bruce Springsteen","id":16657852,"name":"Straight Time (Album Version)","picURL":"http://p1.music.126.net/yK0V-aD3Myh4xorvwUtCrw==/17889054184179160.jpg","playlistId":772430182,"time":210651}
{"album":"Epic Action & Adventure Vol. 6","author":"Epic Score","id":4054121,"name":"Time Will Remember Us","picURL":"http://p1.music.126.net/uN8AYI3sQEgoECuSYmi9Eg==/658607465082090.jpg","playlistId":636015704,"time":165000}
matchQuery
查询某个字段中模糊包含目标字符串，使用matchQuery
/**
* 单字段对某字符串模糊查询
*/
@Test
public void matchQuerySong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(matchQuery("name","Time")).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}返回结果
{
"match" : {
"name" : {
"query" : "Time",
"operator" : "OR",
"prefix_length" : 0,
"max_expansions" : 50,
"fuzzy_transpositions" : true,
"lenient" : false,
"zero_terms_query" : "NONE",
"boost" : 1.0
}
}
}
{"album":"Time","author":"Cat naps","id":459733590,"name":"Time","picURL":"http://p1.music.126.net/9DmApLeDwutb4HpuhD_E-Q==/18624627464667106.jpg","playlistId":900228548,"time":86465}
{"album":"Go Time","author":"Mark Petrie","id":29717271,"name":"Go Time","picURL":"http://p1.music.126.net/TJe468hZr_0ndQRfTAKdqA==/3233663697760186.jpg","playlistId":636015704,"time":136071}
{"album":"The Blossom Chronicles","author":"Philter","id":21375446,"name":"Adventure Time","picURL":"http://p1.music.126.net/YjMS5_kM3u9PCUU0lcRK8g==/6657542907248762.jpg","playlistId":636015704,"time":207412}
{"album":"Shire Music Annual Selection - Myth","author":"Shire Music,Songs To Your Eyes,","id":34916751,"name":"Between Space And Time","picURL":"http://p1.music.126.net/CCqLd2ly2XuuSPz0IW0u-g==/3284241233077333.jpg","playlistId":636015704,"time":222456}
{"album":"Electric Warrior","author":"T. Rex","id":29848501,"name":"There Was A Time","picURL":"http://p1.music.126.net/dn1MwEBfBcL4l6isrnEwDw==/3246857839528733.jpg","playlistId":772430182,"time":60577}
{"album":"Double Live Doggie Style I","author":"X-Ray Dog","id":26246058,"name":"Time Will Tell","picURL":"http://p1.music.126.net/oYEIMWnAvpuRDTk4g_l-lg==/2503587976473913.jpg","playlistId":636015704,"time":202133}
{"album":"Decimus","author":"Audio Machine","id":36586631,"name":"Ashes of Time","picURL":"http://p1.music.126.net/7InBepjNDGCzpzH8Feyw9A==/3395291908535260.jpg","playlistId":636015704,"time":190826}
{"album":"The Ghost Of Tom Joad","author":"Bruce Springsteen","id":16657852,"name":"Straight Time (Album Version)","picURL":"http://p1.music.126.net/yK0V-aD3Myh4xorvwUtCrw==/17889054184179160.jpg","playlistId":772430182,"time":210651}
{"album":"Epic Action & Adventure Vol. 6","author":"Epic Score","id":4054121,"name":"Time Will Remember Us","picURL":"http://p1.music.126.net/uN8AYI3sQEgoECuSYmi9Eg==/658607465082090.jpg","playlistId":636015704,"time":165000}
matchPhraseQuery
PhraseMatch查询，短语匹配
/**
* 单字段对某短语进行匹配查询，短语分词的顺序会影响结果
*/
@Test
public void phraseMatchSong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(matchPhraseQuery("name","Time")).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}termQuery
这个是最严格的匹配，属于低级查询，不进行分词的，参考这篇文章 http://www.cnblogs.com/muniaofeiyu/p/5616316.html
/**
* term匹配，即不分词匹配，你传来什么值就会拿你传的值去做完全匹配
*/
@Test
public void termQuerySong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(termQuery("name","Time")).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}multiMatchQuery
多个字段匹配某字符串,如果我们希望name，author两个字段去匹配某个字符串，只要任何一个字段包括该字符串即可，就可以使用multiMatchQuery。
/**
* 多字段匹配
*/
@Test
public void multiMatchQuerySong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(multiMatchQuery("time","name","author")).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}完全包含查询
之前的查询中，当我们输入“我天”时，ES会把分词后所有包含“我”和“天”的都查询出来，如果我们希望必须是包含了两个字的才能被查询出来，那么我们就需要设置一下Operator。
/**
* 单字段包含所有输入
*/
@Test
public void matchQueryOperatorSong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(matchQuery("name","真的").operator(Operator.AND)).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}无论是matchQuery，multiMatchQuery，queryStringQuery等，都可以设置operator。默认为Or，设置为And后，就会把符合包含所有输入的才查出来。
如果是and的话，譬如用户输入了5个词，但包含了4个，也是显示不出来的。我们可以通过设置精度来控制。
/**
* 单字段包含所有输入(按比例包含)
*/
@Test
public void matchQueryOperatorWithMinimumShouldMatchSong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(matchQuery("name","time").operator(Operator.AND).minimumShouldMatch("80%")).withPageable(of(0,100)).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}minimumShouldMatch可以用在match查询中，设置最少匹配了多少百分比的能查询出来。
合并查询
即boolQuery，可以设置多个条件的查询方式。它的作用是用来组合多个Query，有四种方式来组合，must，mustnot，filter，should。
must代表返回的文档必须满足must子句的条件，会参与计算分值；
filter代表返回的文档必须满足filter子句的条件，但不会参与计算分值；
should代表返回的文档可能满足should子句的条件，也可能不满足，有多个should时满足任何一个就可以，通过minimum_should_match设置至少满足几个。
mustnot代表必须不满足子句的条件。
譬如我想查询name包含“XXX”，且userId=“2345098”，且time最好小于165000的结果。那么就可以使用boolQuery来组合。
/**
* 多字段合并查询
*/
@Test
public void boolQuerySong(){
SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(boolQuery().must(termQuery("userId", "2345098"))
.should(rangeQuery("time").lt(165000)).must(matchQuery("name", "time"))).build();
System.out.println(searchQuery.getQuery().toString());
List<Song> songList = songDAO.search(searchQuery).getContent();
for (Song song : songList) {
System.out.println(JSONObject.toJSONString(song));
}
}详细点的看这篇 http://blog.csdn.net/dm_vincent/article/details/41743955
boolQuery使用场景非常广泛，应该是主要学习的知识之一。
Query和Filter的区别
query和Filter都是QueryBuilder，也就是说在使用时，你把Filter的条件放到withQuery里也行，反过来也行。那么它们两个区别在哪？
查询在Query查询上下文和Filter过滤器上下文中，执行的操作是不一样的：
1、查询：是在使用query进行查询时的执行环境，比如使用search的时候。
在查询上下文中，查询会回答这个问题——“这个文档是否匹配这个查询，它的相关度高么？”
ES中索引的数据都会存储一个_score分值，分值越高就代表越匹配。即使lucene使用倒排索引，对于某个搜索的分值计算还是需要一定的时间消耗。
2、过滤器：在使用filter参数时候的执行环境，比如在bool查询中使用Must_not或者filter
在过滤器上下文中，查询会回答这个问题——“这个文档是否匹配？”
它不会去计算任何分值，也不会关心返回的排序问题，因此效率会高一点。
另外，经常使用过滤器，ES会自动的缓存过滤器的内容，这对于查询来说，会提高很多性能。
ElasticsearchRepository
ElasticsearchRepository接口的方法有
@NoRepositoryBean
public interface ElasticsearchRepository<T, ID extends Serializable> extends ElasticsearchCrudRepository<T, ID> {
<S extends T> S index(S var1);
Iterable<T> search(QueryBuilder var1);
FacetedPage<T> search(QueryBuilder var1, Pageable var2);
FacetedPage<T> search(SearchQuery var1);
Page<T> searchSimilar(T var1, String[] var2, Pageable var3);
}执行复杂查询最常用的就是 FacetedPage
主要是看QueryBuilder和SearchQuery两个参数，要完成一些特殊查询就主要看构建这两个参数。
我们先来看看它们之间的类关系
实际使用中，我们的主要任务就是构建NativeSearchQuery来完成一些复杂的查询的。
public NativeSearchQuery(QueryBuilder query, QueryBuilder filter, List<SortBuilder> sorts, Field[] highlightFields) {
this.query = query;
this.filter = filter;
this.sorts = sorts;
this.highlightFields = highlightFields;
} 我们可以看到要构建NativeSearchQuery，主要是需要几个构造参数
当然了，我们没必要实现所有的参数。
可以看出来，大概是需要QueryBuilder，filter，和排序的SortBuilder，和高亮的字段。
一般情况下，我们不是直接是new NativeSearchQuery，而是使用NativeSearchQueryBuilder。
通过NativeSearchQueryBuilder.withQuery(QueryBuilder1).withFilter(QueryBuilder2).withSort(SortBuilder1).withXXXX().build();这样的方式来完成NativeSearchQuery的构建。
从名字就能看出来，QueryBuilder主要用来构建查询条件、过滤条件，SortBuilder主要是构建排序。
很幸运的 ElasticsearchRepository 里的 SearchQuery 也就是上述描述的 temple 的 SearchQuery，2 者可以共用
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