ElasticSearch6.5.0【Java客户端之TransportClient】
说明
TransportClient：网上流传最多的客户端，目前最新版本
Java REST Client：官方推荐的客户端，
官方：我们要在Elasticsearch 7.0的版本中不赞成使用TransportClient，在Elasticsearch 8.0的版本中完全移除TransportClient。转而使用Java REST Client
照这个势头看，现在都6.5了，8.0还会远嘛。使用客户端要注意版本对应的问题，最好版本完全一致，实在不行也要保障主版本一致，比如5.X 、 6.X
官方文档要对比着来看，我觉得好理解一些
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/index.html
* https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
TransportClient
依赖
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>transport</artifactId>
<version>6.5.0</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>2.11.1</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-to-slf4j</artifactId>
<version>2.11.1</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>1.7.25</version>
</dependency> <dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-client</artifactId>
<version>6.5.0</version>
</dependency>
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-high-level-client</artifactId>
<version>6.5.0</version>
</dependency>
连接
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.transport.TransportAddress;
import org.elasticsearch.transport.client.PreBuiltTransportClient; import java.net.InetAddress;
import java.net.UnknownHostException; public class TransportClientFactory { private TransportClientFactory(){} private static class Inner{
private static final TransportClientFactory instance = new TransportClientFactory();
} public static TransportClientFactory getInstance(){
return Inner.instance;
} public TransportClient getClient() throws UnknownHostException {
Settings settings = Settings.builder()
.put("cluster.name", "my-elasticsearch") // 默认的集群名称是elasticsearch，如果不是要指定
.build();
return new PreBuiltTransportClient(settings)
//.addTransportAddress(new TransportAddress(InetAddress.getByName("localhost"), 9301))
.addTransportAddress(new TransportAddress(InetAddress.getByName("localhost"), 9300));
} }
Index
1. 添加文档
public static TransportClient addDoc1() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
// 构建对象
XContentBuilder builder = jsonBuilder()
.startObject()
.field("brand", "ANTA")
.field("color", "red")
.field("model", "S")
.field("postDate", new Date())
.endObject();
// 转成JSON格式
String json = Strings.toString(builder);
/**
* 参数1：index
* 参数2：type
* 参数3：id
*/
IndexRequestBuilder indexRequestBuilder = client.prepareIndex("clothes", "young", "1");
IndexResponse response = indexRequestBuilder.setSource(json, XContentType.JSON).get();
System.out.println("Index:" + response.getIndex() + "," +
"Type:" + response.getType() + "," +
"ID:" + response.getId() + "," +
"Version:" + response.getVersion() + "," +
"Status:" + response.status().name()
);
return client;
}
执行结果：
Index:clothes,Type:young,ID:1,Version:1,Status:CREATED
2. 添加文档还可以不指定id，这个时候默认生成一个唯一id
public static TransportClient addDoc2() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
// 构建对象
XContentBuilder builder = jsonBuilder()
.startObject()
.field("brand", "YISHION")
.field("color", "Blue")
.field("model", "S")
.field("postDate", new Date())
.endObject();
// 转成JSON格式
String json = Strings.toString(builder);
/**
* 参数1：index
* 参数2：type
*/
IndexRequestBuilder indexRequestBuilder = client.prepareIndex("clothes", "young");
IndexResponse response = indexRequestBuilder.setSource(json, XContentType.JSON).get();
System.out.println("Index:" + response.getIndex() + "," +
"Type:" + response.getType() + "," +
"ID:" + response.getId() + "," +
"Version:" + response.getVersion() + "," +
"Status:" + response.status().name()
);
return client;
}
执行结果：
Index:clothes,Type:young,ID:J5uAoWcBb9TcvgEh2GJ3,Version:1,Status:CREATED
3. 根据id获取文档
/**
* 根据id获取
* @throws IOException
*/
public static TransportClient getDoc() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
// prepareGet 参数分别为index、type、id
GetResponse response = client.prepareGet("clothes", "young", "1").get();
String id = response.getId();
String index = response.getIndex();
Map<String, DocumentField> fields = response.getFields();
// 返回的source，也就是数据源
Map<String, Object> source = response.getSource();
System.out.println("ID:" + id + ",Index:" + index);
Set<String> fieldKeys = fields.keySet();
for (String s : fieldKeys){
DocumentField documentField = fields.get(s);
String name = documentField.getName();
List<Object> values = documentField.getValues();
System.out.println(name + ":" + values.toString());
}
System.out.println("==========");
Set<String> sourceKeys = source.keySet();
for(String s : sourceKeys){
Object o = source.get(s);
System.out.println(s + ":" + o);
}
return client;
}
执行结果：
ID:1,Index:clothes
==========
color:red
postDate:2018-12-12T08:18:21.509Z
model:S
brand:ANTA
4. 根据id删除，我们删除那个默认生成的那个id
/**
* 根据id删除
* @throws IOException
*/
public static TransportClient delDoc() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
DeleteResponse response = client.prepareDelete("clothes", "young", "J5uAoWcBb9TcvgEh2GJ3").get();
String id = response.getId();
String index = response.getIndex();
String status = response.status().name();
System.out.println("ID:" + id + ",Index:" + index + ",Status:" + status);
return client;
}
执行结果：
ID:J5uAoWcBb9TcvgEh2GJ3,Index:clothes,Status:OK
5. 根据条件删除
/**
* 根据条件删除
* @throws IOException
*/
public static TransportClient delDocByQuery() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
BulkByScrollResponse response = DeleteByQueryAction.INSTANCE.newRequestBuilder(client)
.filter(QueryBuilders.matchQuery("brand", "ANTA")) // 属性-值
.source("clothes") // index
.get();
long deleted = response.getDeleted();
System.out.println(deleted);
return client;
}
执行结果：
1
这里第一次遇到QueryBuilders，这个东西很常用，回头我介绍这个类。
根据条件删除还可以指定type
DeleteByQueryRequestBuilder builder = DeleteByQueryAction.INSTANCE.newRequestBuilder(client);
builder.filter(QueryBuilders.matchQuery("brand", "ANTA")) // 属性-值
.source("clothes") // index
.source().setTypes("young"); // type
BulkByScrollResponse response = builder.get();
6. 批量插入（这个bulk不仅可以批量创建，也可以更新或者删除）
/**
* 批量插入
* @throws IOException
*/
public static TransportClient bulkDoc() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
BulkRequestBuilder bulk = client.prepareBulk();
bulk.add(client.prepareIndex("car", "model", "1")
.setSource(jsonBuilder()
.startObject()
.field("name", "法拉利488")
.field("price", "315.50-418.80万")
.field("postDate", new Date())
.endObject()
)
);
bulk.add(client.prepareIndex("car", "model", "2")
.setSource(jsonBuilder()
.startObject()
.field("name", "法拉利LaFerrari")
.field("price", "2250.00万")
.field("postDate", new Date())
.endObject()
)
);
bulk.add(client.prepareIndex("car", "model", "3")
.setSource(jsonBuilder()
.startObject()
.field("name", "法拉利GTC4Lusso")
.field("price", "322.80-485.80万")
.field("postDate", new Date())
.endObject()
)
);
BulkResponse responses = bulk.get();
String status = responses.status().name();
System.out.println(status);
return client;
}
执行结果：
OK
7. 获取多个结果
/**
* 批量获取
* @throws IOException
*/
public static TransportClient multiGetDoc() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
MultiGetResponse multiGetItemResponses = client.prepareMultiGet()
// 可以指定多个index，多个id
.add("clothes", "young", "1", "2")
.add("car", "model", "1","2","3")
.get(); for (MultiGetItemResponse itemResponse : multiGetItemResponses) {
GetResponse response = itemResponse.getResponse();
if (response.isExists()) {
String json = response.getSourceAsString();
System.out.println(json);
}
}
return client;
}
执行结果：由于之前clothes里面没数据了，所以只显示了下面三条数据
{"name":"法拉利488","price":"315.50-418.80万","postDate":"2018-12-12T08:38:09.107Z"}
{"name":"法拉利LaFerrari","price":"2250.00万","postDate":"2018-12-12T08:38:09.129Z"}
{"name":"法拉利GTC4Lusso","price":"322.80-485.80万","postDate":"2018-12-12T08:38:09.129Z"}
8. 更新
/**
* 更新方式一：通过UpdateRequest
* @throws IOException
* @throws ExecutionException
* @throws InterruptedException
*/
public static TransportClient updateDoc1() throws IOException, ExecutionException, InterruptedException {
TransportClient client = TransportClientFactory.getInstance().getClient();
UpdateRequest updateRequest = new UpdateRequest();
updateRequest.index("car"); // 指定index
updateRequest.type("model");// 指定type
updateRequest.id("3"); // 指定id
// 更新内容
updateRequest.doc(jsonBuilder()
.startObject()
.field("name", "Aventador")
.field("price", "630.00-755.94万")
.field("postDate", new Date())
.field("extra", "Extra Data") // 不存在的会自动添加
.endObject());
UpdateResponse updateResponse = client.update(updateRequest).get();
System.out.println(updateResponse.status().name());
return client;
}
执行结果：
OK
在Kibana上查看结果：GET /car/model/3
客户端有两种请求方式，一种是***Request（比如UpdateRequest ），另一种是prepare***（比如prepareUpdate），我更喜欢用prepare***
/**
* 更新方式二：通过prepareUpdate
* @throws IOException
*/
public static TransportClient updateDoc2() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
client.prepareUpdate("car", "model", "1")
.setDoc(jsonBuilder()
.startObject()
.field("name", "法拉利812 Superfast")
.field("price", "498.80万")
.field("postDate", new Date())
.endObject()
)
.get();
return client;
}
9. upset更新
/**
* 文档存在则更新doc，不存在则添加upsert
* @throws IOException
* @throws ExecutionException
* @throws InterruptedException
*/
public static TransportClient upsert() throws IOException, ExecutionException, InterruptedException {
TransportClient client = TransportClientFactory.getInstance().getClient();
IndexRequest indexRequest = new IndexRequest("clothes", "young", "3")
.source(jsonBuilder()
.startObject()
.field("brand", "Pierre Cardin")
.field("color", "Black")
.field("model", "L")
.field("postDate", new Date())
.endObject());
UpdateRequest updateRequest = new UpdateRequest("clothes", "young", "3")
.doc(jsonBuilder()
.startObject()
.field("model", "XL")
.endObject())
.upsert(indexRequest);
UpdateResponse response = client.update(updateRequest).get();
System.out.println(response.status().name());
return client;
}
什么意思呢，如果文档存在，则只更新model字段，相反会添加IndexRequest里面的内容。
第一次执行：（文档不存在）
CREATED
GET /clothes/young/3
第二次执行：
OK
查看Kibana
10. bulkProcessor 另外一个批量工具
基本的配置
.setBulkActions(10000) // 每10000个request，bulk一次
.setBulkSize(new ByteSizeValue(5, ByteSizeUnit.MB)) // 每5M的数据刷新一次
.setFlushInterval(TimeValue.timeValueSeconds(5)) // 每5s刷新一次，而不管有多少数据量
.setConcurrentRequests(0) // 设置并发请求的数量。值为0意味着只允许执行一个请求。值为1意味着在积累新的批量请求时允许执行1个并发请求。
.setBackoffPolicy( // 设置一个自定义的重试策略，该策略最初将等待100毫秒，按指数增长，最多重试3次。当一个或多个批量项请求失败时，如果出现EsRejectedExecutionException异常，将尝试重试，该异常表明用于处理请求的计算资源太少。要禁用backoff，请传递BackoffPolicy.noBackoff()。
BackoffPolicy.exponentialBackoff(TimeValue.timeValueMillis(100), 3))
测试
/**
* 造数据
* @throws IOException
*/
public static TransportClient scrollSearchPreData() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
BulkProcessor bulkProcessor = BulkProcessor.builder(
client,
new BulkProcessor.Listener() {
@Override
public void beforeBulk(long executionId, BulkRequest request) {
// bulk 执行之前
System.out.println("beforeBulk-----" + request.getDescription());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
BulkResponse response) {
// bulk 执行之后
System.out.println("afterBulk------" + request.getDescription() + ",是否有错误：" + response.hasFailures());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
Throwable failure) {
//bulk 失败
System.out.println("报错-----" + request.getDescription() + "," + failure.getMessage());
}
})
.setBulkActions(100) // 每100个request，bulk一次
.setConcurrentRequests(0) // 设置并发请求的数量。值为0意味着只允许执行一个请求。值为1意味着在积累新的批量请求时允许执行1个并发请求。
.build();
Random random = new Random();
for (int i = 1; i <= 1000; i++){
bulkProcessor.add(new IndexRequest("book", "elasticsearch", i+"").source(jsonBuilder()
.startObject()
.field("name", "book_" + i)
.field("price", random.nextDouble()*1000)
.field("postDate", new Date())
.endObject()));
}
bulkProcessor.flush();
bulkProcessor.close();
return client;
}
执行结果：1000条数据，bulk10次
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
beforeBulk-----requests[100], indices[book]
afterBulk------requests[100], indices[book],是否有错误：false
11. scroll（让数据都滚出来）
/**
* 当搜索请求返回一个结果的“页面”时，滚动API可以用于从一个搜索请求检索大量的结果(甚至所有结果)
* 其方式与在传统数据库中使用游标非常类似。滚动不是为了实时的用户请求，而是为了处理大量的数据
* @throws UnknownHostException
*/
public static TransportClient scrollSearch() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse response = client.prepareSearch("book")
.addSort("price", SortOrder.ASC)
.setScroll(new TimeValue(30000))
.setSize(1000).get(); // 每次滚出1000条就返回
do {
System.out.println("========Begin=======");
for (SearchHit hit : response.getHits().getHits()) {
System.out.println(hit.getSourceAsString());
}
System.out.println("========End=======");
response = client.prepareSearchScroll(response.getScrollId()).setScroll(new TimeValue(30000)).execute().actionGet();
} while(response.getHits().getHits().length != 0);
return client;
}
执行结果：
========Begin=======
{"name":"book_233","price":0.7903630819869889,"postDate":"2018-12-12T09:27:32.629Z"}
{"name":"book_46","price":1.9862330698061648,"postDate":"2018-12-12T09:27:30.722Z"}
{"name":"book_18","price":2.8024592316934216,"postDate":"2018-12-12T09:27:30.721Z"}
{"name":"book_512","price":3.5739663933835875,"postDate":"2018-12-12T09:27:33.275Z"}
{"name":"book_275","price":5.449351054677254,"postDate":"2018-12-12T09:27:32.632Z"}
{"name":"book_112","price":8.035476335226166,"postDate":"2018-12-12T09:27:32.424Z"}
...此处省略
========End=======
12. 根据查询更新
/**
* 当版本匹配时，updateByQuery更新文档并增加版本号。
* 所有更新和查询失败都会导致updateByQuery中止。这些故障可从BulkByScrollResponse#getBulkFailures方法中获得。
* 任何成功的更新都会保留并不会回滚。当第一个失败导致中止时，响应包含由失败的批量请求生成的所有失败。
* 当文档在快照时间和索引请求过程时间之间发生更改时，就会发生版本冲突
* 为了防止版本冲突导致updateByQuery中止，设置abortOnVersionConflict(false)。
* ScriptType.INLINE:在大量查询中指定内联脚本并动态编译。它们将基于脚本的lang和代码进行缓存。
* ScriptType.STORED:存储的脚本作为{@link org.elasticsearch.cluster.ClusterState}的一部分保存基于用户请求。它们将在查询中首次使用时被缓存。
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/java-docs-update-by-query.html
* https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-update-by-query.html
* @throws UnknownHostException
*/
public static TransportClient updateByQuery() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
UpdateByQueryRequestBuilder updateByQuery = UpdateByQueryAction.INSTANCE.newRequestBuilder(client);
updateByQuery.source("book")
.size(100) // 尝试获取的最大文档数
.filter(QueryBuilders.termsQuery("name","book_233", "book_46", "book_18", "book_512")) // 注意term，value要变成小写！！
// 以下脚本：保留id=781的，删除id=316的，其它的价格都变为79
.script(new Script(
ScriptType.INLINE,Script.DEFAULT_SCRIPT_LANG,
"if (ctx._source['id'] == 781) {"
+ " ctx.op='noop'" // ctx.op='noop' 不做处理
+ "} else if (ctx._source['id'] == '316') {"
+ " ctx.op='delete'" // ctx.op='delete'删除
+ "} else {"
+ "ctx._source['price'] = 79}",
Collections.emptyMap()))
.abortOnVersionConflict(false); // 版本冲突策略：abortOnVersionConflict 版本冲突时不终止
// .source().setTypes("young") // 指定type
// .setSize(10) // 返回搜索的命中数
// .addSort("postDate", SortOrder.DESC);
BulkByScrollResponse response = updateByQuery.get();
System.out.println("Deleted:" + response.getDeleted() + ",Created:" +
response.getCreated() + ",Updated:" + response.getUpdated() + ",Noops:" + response.getNoops()); List<BulkItemResponse.Failure> failures = response.getBulkFailures();
System.out.println(failures.size());
// 如果目标值是Cat，更新内容也是Cat，则不会去更新
return client;
}
执行结果：（这个term查询有点坑，value必须为小写，并且不能带-，我之前生成的格式为book-100，结果查询不出来。。。）
Deleted:0,Created:0,Updated:4,Noops:0
0
查看数据：
GET /book/elasticsearch/_mget
{
"ids" : ["", "", "", ""]
}
结果：
{
"docs" : [
{
"_index" : "book",
"_type" : "elasticsearch",
"_id" : "",
"_version" : ,
"found" : true,
"_source" : {
"price" : ,
"name" : "book_233",
"postDate" : "2018-12-12T09:27:32.629Z"
}
},
{
"_index" : "book",
"_type" : "elasticsearch",
"_id" : "",
"_version" : ,
"found" : true,
"_source" : {
"price" : ,
"name" : "book_46",
"postDate" : "2018-12-12T09:27:30.722Z"
}
},
{
"_index" : "book",
"_type" : "elasticsearch",
"_id" : "",
"_version" : ,
"found" : true,
"_source" : {
"price" : ,
"name" : "book_18",
"postDate" : "2018-12-12T09:27:30.721Z"
}
},
{
"_index" : "book",
"_type" : "elasticsearch",
"_id" : "",
"_version" : ,
"found" : true,
"_source" : {
"price" : ,
"name" : "book_512",
"postDate" : "2018-12-12T09:27:33.275Z"
}
}
]
}
13. 简单查询
/**
* 简单查询【通配符查询，筛选价格范围，设定返回数量，排序】
* @throws UnknownHostException
*/
public static TransportClient search() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse response = client.prepareSearch("book") // index,可以多个
.setSearchType(SearchType.DFS_QUERY_THEN_FETCH)
.setQuery(QueryBuilders.wildcardQuery("name", "*book_1*")) // Query
.setPostFilter(QueryBuilders.rangeQuery("price").from(800).to(900)) // Filter
.setFrom(0).setSize(100).setExplain(true).addSort("postDate", SortOrder.DESC)
.get();
response.getHits().forEach(e ->{
System.out.println(e.getSourceAsString());
});
return client;
}
执行结果：
{"name":"book_1000","price":811.3812414198577,"postDate":"2018-12-12T09:27:34.095Z"}
{"name":"book_194","price":828.6484294585816,"postDate":"2018-12-12T09:27:32.433Z"}
{"name":"book_171","price":839.1475764183831,"postDate":"2018-12-12T09:27:32.432Z"}
{"name":"book_170","price":869.7835076374234,"postDate":"2018-12-12T09:27:32.431Z"}
{"name":"book_161","price":838.5131747806441,"postDate":"2018-12-12T09:27:32.429Z"}
{"name":"book_153","price":805.041724108352,"postDate":"2018-12-12T09:27:32.429Z"}
{"name":"book_154","price":893.982844708382,"postDate":"2018-12-12T09:27:32.429Z"}
{"name":"book_105","price":883.039302643907,"postDate":"2018-12-12T09:27:32.424Z"}
{"name":"book_19","price":877.0523728410054,"postDate":"2018-12-12T09:27:30.721Z"}
14. 多个查询MultiSearch
/**
* 多个查询
*/
public static TransportClient multiSearch() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
// 第一个查询
SearchRequestBuilder srb1 = client
.prepareSearch("book")
.setQuery(QueryBuilders.queryStringQuery("book_9*").field("name"))
.setFrom(0) // 开始位置
.setSize(10); // 设置返回的最大条数
// 第二个查询
SearchRequestBuilder srb2 = client
.prepareSearch("car")
.setQuery(QueryBuilders.queryStringQuery("*r*"))
.setSize(10);
// 组合
MultiSearchResponse sr = client.prepareMultiSearch()
.add(srb1)
.add(srb2)
.get(); // You will get all individual responses from MultiSearchResponse#getResponses()
long nbHits = 0;
for (MultiSearchResponse.Item item : sr.getResponses()) {
SearchResponse response = item.getResponse();
response.getHits().forEach(e ->{
System.out.println(e.getSourceAsString());
});
long hits = response.getHits().getTotalHits();
System.out.println("Hits:" + hits);
nbHits += hits;
}
System.out.println("Total:" + nbHits);
return client;
}
执行结果：
{"name":"book_92","price":176.35847694096162,"postDate":"2018-12-12T09:27:30.724Z"}
{"name":"book_98","price":611.4318589503413,"postDate":"2018-12-12T09:27:30.724Z"}
{"name":"book_99","price":214.4653626273969,"postDate":"2018-12-12T09:27:30.724Z"}
{"name":"book_900","price":973.3382073380857,"postDate":"2018-12-12T09:27:33.892Z"}
{"name":"book_915","price":35.30856326485343,"postDate":"2018-12-12T09:27:34.091Z"}
{"name":"book_922","price":299.58144612743064,"postDate":"2018-12-12T09:27:34.091Z"}
{"name":"book_930","price":591.6598815227311,"postDate":"2018-12-12T09:27:34.092Z"}
{"name":"book_933","price":287.18727780940037,"postDate":"2018-12-12T09:27:34.092Z"}
{"name":"book_935","price":693.6036227965725,"postDate":"2018-12-12T09:27:34.092Z"}
{"name":"book_942","price":701.4129722487066,"postDate":"2018-12-12T09:27:34.092Z"}
Hits:111
{"name":"法拉利LaFerrari","price":"2250.00万","postDate":"2018-12-12T08:38:09.129Z"}
{"name":"Aventador","price":"630.00-755.94万","postDate":"2018-12-12T08:49:01.736Z","extra":"Extra Data"}
Hits:2
Total:113
聚合
15. 聚合查询
/**
* 聚合查询
* 搜索是查找某些具体的文档.然而聚合就是对这些搜索到的文档进行统计
* https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations.html
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/java-aggs.html
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/java-search-aggs.html
* 可以在聚合中定义子聚合
* @return
* @throws UnknownHostException
*/
public static TransportClient aggregationsSearch() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse sr = client.prepareSearch("book")
.setQuery(QueryBuilders.matchAllQuery())
.addAggregation(
AggregationBuilders.stats("agg1").field("price")
)
.addAggregation(
AggregationBuilders.dateHistogram("agg2")
.field("postDate")
.dateHistogramInterval(DateHistogramInterval.YEAR)
)
.get(); // Short version of execute().actionGet(). // Get your facet results
Aggregation agg1 = sr.getAggregations().get("agg1");
System.out.println(agg1.getClass()); // class org.elasticsearch.search.aggregations.metrics.stats.InternalStats
Aggregation agg2 = sr.getAggregations().get("agg2");
System.out.println(agg2.getClass()); // class org.elasticsearch.search.aggregations.bucket.histogram.InternalDateHistogram
return client;
}
15.1 metrics聚合
/**
* metrics聚合
* 主要为了统计信息
* org.elasticsearch.search.aggregations.metrics.percentiles.Percentiles
* org.elasticsearch.search.aggregations.metrics.percentiles.PercentileRanks
* org.elasticsearch.search.aggregations.metrics.cardinality.Cardinality
* 地理位置聚合：https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/_metrics_aggregations.html#java-aggs-metrics-geobounds
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/_metrics_aggregations.html#java-aggs-metrics-tophits
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/_metrics_aggregations.html#java-aggs-metrics-scripted-metric
* @return
* @throws UnknownHostException
*/
public static TransportClient metricsAggregationsSearch() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse sr = client.prepareSearch("book")
.setQuery(QueryBuilders.matchAllQuery())
.addAggregation(
AggregationBuilders.min("agg1").field("price")
)
.addAggregation(
AggregationBuilders.max("agg2").field("price")
)
.addAggregation(
AggregationBuilders.sum("agg3").field("price")
)
.addAggregation(
AggregationBuilders.avg("agg4").field("price")
)
.addAggregation(
AggregationBuilders.count("agg5").field("price")
)
.addAggregation(
AggregationBuilders.stats("agg6").field("price")
)
.get();
Min agg1 = sr.getAggregations().get("agg1");
Max agg2 = sr.getAggregations().get("agg2");
Sum agg3 = sr.getAggregations().get("agg3");
Avg agg4 = sr.getAggregations().get("agg4");
ValueCount agg5 = sr.getAggregations().get("agg5");
Stats agg6 = sr.getAggregations().get("agg6");
System.out.println("Min:" + agg1.getValue() + ",Max:" + agg2.getValue() + ",Sum:" + agg3.getValue() + ",Avg:" + agg4.getValue() + ",Count:" + agg5.getValue() +
",Stats:(" + agg6.getMin() + "," + agg6.getMax() + "," + agg6.getSum() + "," + agg6.getAvg() + "," + agg6.getCount() + ")");
return client;
}
执行结果：
Min:5.449350833892822,Max:999.3211669921875,Sum:502966.58267736435,Avg:502.96658267736433,Count:1000,Stats:(5.449350833892822,999.3211669921875,502966.58267736435,502.96658267736433,1000)
15.2地理位置聚合（计算坐标的左上/右下边界值）
/**
* 准备地理位置信息
* @return
* @throws IOException
*/
public static TransportClient geoSearchPreData() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
// 建立索引
CreateIndexResponse indexResponse = client.admin().indices().prepareCreate("area")
.setSettings(Settings.builder()
.put("index.number_of_shards", 1) // 分片
.put("index.number_of_replicas", 1) // 副本
)
.addMapping("hospital", "message", "type=text", "location", "type=geo_point")
.get();
System.out.println("Index:" + indexResponse.index() + ",ACK:" + indexResponse.isAcknowledged());
BulkProcessor bulkProcessor = BulkProcessor.builder(
client,
new BulkProcessor.Listener() {
@Override
public void beforeBulk(long executionId, BulkRequest request) {
// bulk 执行之前
System.out.println("beforeBulk-----" + request.getDescription());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
BulkResponse response) {
// bulk 执行之后
System.out.println("afterBulk------" + request.getDescription() + ",hasFailures：" + response.hasFailures());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
Throwable failure) {
//bulk 失败
System.out.println("报错-----" + request.getDescription() + "," + failure.getMessage());
}
})
.setBulkActions(100) // 每100个request，bulk一次
.setConcurrentRequests(0) // 设置并发请求的数量。值为0意味着只允许执行一个请求。值为1意味着在积累新的批量请求时允许执行1个并发请求。
.build();
Random random = new Random();
for (int i = 1; i <= 200; i++){
String lo = new DecimalFormat("#.############").format(random.nextDouble() * 100);
String la = new DecimalFormat("#.############").format(random.nextDouble() * 100);
bulkProcessor.add(new IndexRequest("area", "hospital", i+"").source(jsonBuilder()
.startObject()
.field("name", "hospital-" + i)
.field("location", lo + "," + la)
.endObject()));
}
bulkProcessor.flush();
bulkProcessor.close();
return client;
} /**
* 地理信息查询
* @return
* @throws UnknownHostException
*/
public static TransportClient geoAggregation() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse sr = client.prepareSearch("area")
.setQuery(QueryBuilders.matchQuery("name", "hospital-1"))
.addAggregation(
AggregationBuilders.geoBounds("agg").field("location").wrapLongitude(true)
)
.get();
GeoBounds agg = sr.getAggregations().get("agg");
GeoPoint left = agg.topLeft();
GeoPoint right = agg.bottomRight();
System.out.println(left + " | " + right);
return client;
}
执行结果：
89.9911705031991, 0.03342803567647934 | 0.049703302793204784, 99.9249867349863
15.3桶聚合
/**
* 桶聚合,我这里只列举了部分
* https://www.elastic.co/guide/en/elasticsearch/client/java-api/current/_bucket_aggregations.html
* @return
* @throws UnknownHostException
*/
public static TransportClient bucketAggregationsSearch() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse sr = client.prepareSearch()
.setQuery(QueryBuilders.matchAllQuery())
// .addAggregation(AggregationBuilders
// .global("agg0")
// .subAggregation(AggregationBuilders.terms("sub_agg").field("name"))
// )
.addAggregation(AggregationBuilders
.filter("agg1", QueryBuilders.termQuery("name", "book_199")))
.addAggregation(AggregationBuilders
.filters("agg2",
new FiltersAggregator.KeyedFilter("key1", QueryBuilders.termQuery("name", "book_1")),
new FiltersAggregator.KeyedFilter("key2", QueryBuilders.termQuery("name", "book_52"))
))
.get(); // Global agg0 = sr.getAggregations().get("agg0");
// System.out.println("GlobalCount:" + agg0.getDocCount()); Filter agg1 = sr.getAggregations().get("agg1");
System.out.println("FilterCount:" + agg1.getDocCount()); Filters agg2 = sr.getAggregations().get("agg2");
for (Filters.Bucket entry : agg2.getBuckets()) {
String key = entry.getKeyAsString(); // bucket key
long docCount = entry.getDocCount(); // Doc count
System.out.println("key [" + key + "], doc_count ["+ docCount +"]");
}
return client;
}
执行结果：Global会屏蔽其它的Agg
FilterCount:1
key [key1], doc_count [1]
key [key2], doc_count [1]
查询DSL
16. Query DSL
16.1 MatchAll，最简单的查询，它会匹配所有文档
client.prepareSearch().setQuery(QueryBuilders.matchAllQuery());
16.2 全文检索【高级全文查询通常用于在全文字段(如电子邮件正文)上运行全文查询，在执行之前有分析的过程。】
16.2.1 Match Query（全文查询的标准查询，包括模糊匹配和短语或邻近查询）
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("book")
.setQuery(QueryBuilders
.matchQuery("name", "book_1")
.fuzziness(Fuzziness.AUTO) // 模糊查询
.zeroTermsQuery(MatchQuery.ZeroTermsQuery.ALL) // 与MatchAll等价，匹配所有文档。默认none，不匹配任何文档
).get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：（为什么会命中250条呢？这是因为模糊查询，如果你注释掉模糊查询，就只会查到一条）
{"name":"book_1","price":541.5683324629698,"postDate":"2018-12-12T09:27:30.695Z"}
{"name":"book_2","price":859.0268161692424,"postDate":"2018-12-12T09:27:30.720Z"}
{"name":"book_4","price":666.0331749730802,"postDate":"2018-12-12T09:27:30.720Z"}
{"name":"book_6","price":797.3826369337273,"postDate":"2018-12-12T09:27:30.720Z"}
{"name":"book_15","price":764.0761667524818,"postDate":"2018-12-12T09:27:30.721Z"}
{"name":"book_51","price":969.2863955131567,"postDate":"2018-12-12T09:27:30.722Z"}
{"name":"book_3","price":467.29468328850055,"postDate":"2018-12-12T09:27:30.720Z"}
{"name":"book_11","price":365.2274741512962,"postDate":"2018-12-12T09:27:30.720Z"}
{"name":"book_17","price":498.8900836459158,"postDate":"2018-12-12T09:27:30.721Z"}
{"name":"book_31","price":377.2822748558652,"postDate":"2018-12-12T09:27:30.721Z"}
命中：250
16.2.2 Multi Match Query（标准查询的多字段版本）
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
// 关键字Aventador，匹配多个字段*ame、brand。字段名称可以使用通配符
.setQuery(QueryBuilders.multiMatchQuery("Aventador", "*ame","brand"))
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
{"name":"Aventador","price":"630.00-755.94万","postDate":"2018-12-12T08:49:01.736Z","extra":"Extra Data"}
命中：1
16.2.3 Common Terms Query（一个更专业的查询，偏好不常见的关键字）
...待补充
16.2.4 Query String Query（解析输入并围绕操作符拆分文本，每个文本部分都是独立分析的）
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
// 关键字和字段【均可以】可以使用通配符（?匹配一个字符，*匹配0个或多个字符，AND，OR）等等
// 有一些您不希望作为操作符的必须转义处理：+ - = && || > < ! ( ) { } [ ] ^ " ~ * ? : \ /
//.setQuery(QueryBuilders.queryStringQuery("(book_111) OR (book_999)")) // or
//.setQuery(QueryBuilders.queryStringQuery("(book_111) AND (book_999)")) // AND
//.setQuery(QueryBuilders.queryStringQuery("(book_111) && (book_999)")) // AND与&&等价
//.setQuery(QueryBuilders.queryStringQuery("(book_111) & (book_999)")) // &不会短路计算
//.setQuery(QueryBuilders.queryStringQuery("book_1?1").field("name")) // ? 并且指定字段
//.setQuery(QueryBuilders.queryStringQuery("name:book_1?1 OR color:B*")) // 在查询里指定字段
//.setQuery(QueryBuilders.queryStringQuery("name:book_1?1 | color:B*"))
//.setQuery(QueryBuilders.queryStringQuery("name:book_1?1 || color:B*")) // OR与||等价
//.setQuery(QueryBuilders.queryStringQuery("price:[990 TO *]")) // 范围查询
// 默认情况下操作符都是可选的，有两个特殊的->首选操作符是：+(这一项必须存在)和-(这一项必须不存在)
.setQuery(QueryBuilders.queryStringQuery("price:[990 TO *] -book*")) // 不显示book*的数据
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
{"name":"法拉利LaFerrari","price":"2250.00万","postDate":"2018-12-12T08:38:09.129Z"}
{"name":"法拉利488","price":"315.50-418.80万","postDate":"2018-12-12T08:38:09.107Z"}
{"name":"Aventador","price":"630.00-755.94万","postDate":"2018-12-12T08:49:01.736Z","extra":"Extra Data"}
命中：3
16.2.5 Simple Query String Query（查询永远不会抛出异常，并丢弃查询的无效部分）
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("book")
// + 表示与操作
// | 表示或操作
// - 表示否定
// * 在关键字末尾表示前缀查询
// 小括号()表示优先级
// 这里通配符失效！！比如book_1?1或者book_1*1只会查出一条记录
.setQuery(QueryBuilders.simpleQueryStringQuery("book_11*")
// .flags(SimpleQueryStringFlag.AND,SimpleQueryStringFlag.OR,SimpleQueryStringFlag.NOT) // 指定启用哪些解析功能，默认全部启用ALL。SimpleQueryStringFlag
)
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
这个功能感觉有点鸡肋，不如QueryStringQuery
执行结果：
{"name":"book_110","price":562.7866825701938,"postDate":"2018-12-12T09:27:32.424Z"}
{"name":"book_116","price":764.6107139750268,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_119","price":612.4310597411385,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_113","price":693.0418946151275,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_117","price":955.1701411798869,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_114","price":255.65009974873198,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_118","price":915.8228473795552,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_111","price":185.85669328040666,"postDate":"2018-12-12T09:27:32.424Z"}
{"name":"book_112","price":8.035476335226166,"postDate":"2018-12-12T09:27:32.424Z"}
{"name":"book_115","price":651.4301559069825,"postDate":"2018-12-12T09:27:32.425Z"}
{"name":"book_11","price":365.2274741512962,"postDate":"2018-12-12T09:27:30.720Z"}
命中：11
16.3 Term level queries【查询通常用于数字、日期和枚举等结构化数据，而不是全文字段。或者，它们允许您在分析过程之前处理低级查询】
造一些结构化数据
/**
* 准备结构化数据
* @return
* @throws IOException
*/
public static TransportClient structuredData() throws IOException {
TransportClient client = TransportClientFactory.getInstance().getClient();
AdminClient admin = client.admin();
IndicesAdminClient indicesAdminClient = admin.indices(); // 指数管理
CreateIndexResponse createIndexResponse = indicesAdminClient.prepareCreate("school")
.setSettings(Settings.builder()
.put("index.number_of_shards", 1) // 分片
.put("index.number_of_replicas", 1) // 副本
)
.addMapping("student", "sName", "type=text", "sAge", "type=integer",
"sClass", "type=keyword", "sTime", "type=date") // mapping
.get();
System.out.println("创建索引：" + createIndexResponse.isAcknowledged());
BulkProcessor bulkProcessor = BulkProcessor.builder(
client,
new BulkProcessor.Listener() {
@Override
public void beforeBulk(long executionId, BulkRequest request) {
// bulk 执行之前
System.out.println("beforeBulk-----" + request.getDescription());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
BulkResponse response) {
// bulk 执行之后
System.out.println("afterBulk------" + request.getDescription() + ",是否有错误：" + response.hasFailures());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
Throwable failure) {
//bulk 失败
System.out.println("报错-----" + request.getDescription() + "," + failure.getMessage());
}
})
.setBulkActions(300) // 每300个request，bulk一次
.setConcurrentRequests(0) // 设置并发请求的数量。值为0意味着只允许执行一个请求。值为1意味着在积累新的批量请求时允许执行1个并发请求。
.build();
Random random = new Random();
for (int i = 1; i <= 1000; i++){
bulkProcessor.add(new IndexRequest("school", "student", i+"").source(jsonBuilder()
.startObject()
.field("sName", "Student_" + i)
.field("sAge", random.nextInt(100))
.field("sClass", "Class_" + (i % 20))
.field("sTime", new Date())
.endObject()));
}
bulkProcessor.flush();
bulkProcessor.close();
return client;
}
查看索引数据：GET /school/_search
注意我这里面有大写字母
查看索引信息：GET /school
16.3.1 Term Query
这里有很多彩蛋~
正确写法：
下面我们查询class字段
正确写法：
代码：
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
//.setQuery(QueryBuilders.termQuery("sName", "student_1")) // 使用term查询类型为text的字段的时候，内容要全部小写
.setQuery(QueryBuilders.termQuery("sClass", "Class_2")) // 使用term查询类型为keyword的字段的时候，内容区分大小写
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
为什么会出现上述彩蛋呢？
类型为text，会解析其中的内容，比如 "Hey Guy"，倒排索引会包括以下术语[hey,guy]
类型为keyword，在倒排索引中会出现以下术语[Hey Guy]
所以，查询全文字段就用match，因为它知道如何分析，term比较傻，只知道精确值，擅长结构化的字段。
16.3.2 TermsQuery
多个查询关键字
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 一个字段，多个value
.setQuery(QueryBuilders.termsQuery("sName","student_1","student_2"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
{"sName":"Student_1","sAge":28,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.666Z"}
{"sName":"Student_2","sAge":20,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.689Z"}
命中：2
16.3.3 RangeQuery 范围查询
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
.setQuery(QueryBuilders.rangeQuery("sAge")
// .gte(10) // 大于等于
// .gt(10) // 大于
// .lte(20) // 小于等于
// .lt(20) // 小于
.from(0)
.to(5)
.includeLower(true) // 包含下限
.includeUpper(true) // 包含上限
)
// .setQuery(QueryBuilders.rangeQuery("sTime")
// .lte("now") // 小于等于当前时间
// .timeZone("-01:00")) // 时区
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
...省略
{"sName":"Student_340","sAge":5,"sClass":"Class_0","sTime":"2018-12-13T08:39:57.821Z"}
{"sName":"Student_372","sAge":1,"sClass":"Class_12","sTime":"2018-12-13T08:39:57.822Z"}
{"sName":"Student_428","sAge":2,"sClass":"Class_8","sTime":"2018-12-13T08:39:57.823Z"}
{"sName":"Student_432","sAge":0,"sClass":"Class_12","sTime":"2018-12-13T08:39:57.823Z"}
命中：52
16.3.4 ExistQuery
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
.setQuery(QueryBuilders.existsQuery("sName"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
...省略
{"sName":"Student_18","sAge":72,"sClass":"Class_18","sTime":"2018-12-13T08:39:57.690Z"}
{"sName":"Student_19","sAge":43,"sClass":"Class_19","sTime":"2018-12-13T08:39:57.690Z"}
{"sName":"Student_20","sAge":93,"sClass":"Class_0","sTime":"2018-12-13T08:39:57.690Z"}
命中：1000
全命中了，什么意思呢？
这个方法的作用：对于某个字段，返回至少含有一个非空值的所有文档 。
套用官方解释，比如：查询user字段，可以返回下面格式的数据【有值，空字符串，长度大于0的数组】
然而下面这些就不行了【null，空数组，非查询字段】
16.3.5 Prefix Query 前缀查询（顾名思义，肯定是把关键字作为前缀啦）
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
.setQuery(QueryBuilders.prefixQuery("sName", "student_19"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
{"sName":"Student_19","sAge":43,"sClass":"Class_19","sTime":"2018-12-13T08:39:57.690Z"}
{"sName":"Student_190","sAge":53,"sClass":"Class_10","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_191","sAge":45,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_192","sAge":2,"sClass":"Class_12","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_193","sAge":9,"sClass":"Class_13","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_194","sAge":67,"sClass":"Class_14","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_195","sAge":62,"sClass":"Class_15","sTime":"2018-12-13T08:39:57.696Z"}
{"sName":"Student_196","sAge":77,"sClass":"Class_16","sTime":"2018-12-13T08:39:57.696Z"}
{"sName":"Student_197","sAge":82,"sClass":"Class_17","sTime":"2018-12-13T08:39:57.696Z"}
{"sName":"Student_198","sAge":38,"sClass":"Class_18","sTime":"2018-12-13T08:39:57.696Z"}
{"sName":"Student_199","sAge":50,"sClass":"Class_19","sTime":"2018-12-13T08:39:57.696Z"}
命中：11
16.3.6 Wildcard Query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 支持通配符查询[?,*]，不建议以通配符开头，那样会很慢
.setQuery(QueryBuilders.wildcardQuery("sName", "student_1?1"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
{"sName":"Student_101","sAge":87,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.692Z"}
{"sName":"Student_111","sAge":98,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.693Z"}
{"sName":"Student_121","sAge":96,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.693Z"}
{"sName":"Student_131","sAge":89,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.694Z"}
{"sName":"Student_141","sAge":90,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.694Z"}
{"sName":"Student_151","sAge":52,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.694Z"}
{"sName":"Student_161","sAge":21,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_171","sAge":76,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_181","sAge":18,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_191","sAge":45,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.695Z"}
命中：10
16.3.7 Regexp Query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// regexp查询的性能在很大程度上取决于所选择的正则表达式。匹配诸如.*之类的所有内容非常慢。*?+ 主要降低性能
.setQuery(QueryBuilders.regexpQuery("sName", "student_.*0"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
...省略
{"sName":"Student_170","sAge":14,"sClass":"Class_10","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_180","sAge":16,"sClass":"Class_0","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_190","sAge":53,"sClass":"Class_10","sTime":"2018-12-13T08:39:57.695Z"}
{"sName":"Student_200","sAge":12,"sClass":"Class_0","sTime":"2018-12-13T08:39:57.696Z"}
命中：100
16.3.8 Fuzzy Query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 模糊查询https://www.elastic.co/guide/en/elasticsearch/reference/current/common-options.html#fuzziness
.setQuery(QueryBuilders.fuzzyQuery("sName", "student_33"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
...省略
{"sName":"Student_83","sAge":94,"sClass":"Class_3","sTime":"2018-12-13T08:39:57.692Z"}
{"sName":"Student_93","sAge":88,"sClass":"Class_13","sTime":"2018-12-13T08:39:57.692Z"}
{"sName":"Student_133","sAge":34,"sClass":"Class_13","sTime":"2018-12-13T08:39:57.694Z"}
{"sName":"Student_233","sAge":90,"sClass":"Class_13","sTime":"2018-12-13T08:39:57.696Z"}
命中：50
16.3.9 Type Query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
.setQuery(QueryBuilders.typeQuery("student"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
就是查询type下的内容..
...省略
{"sName":"Student_18","sAge":72,"sClass":"Class_18","sTime":"2018-12-13T08:39:57.690Z"}
{"sName":"Student_19","sAge":43,"sClass":"Class_19","sTime":"2018-12-13T08:39:57.690Z"}
{"sName":"Student_20","sAge":93,"sClass":"Class_0","sTime":"2018-12-13T08:39:57.690Z"}
命中：1000
16.3.10 Ids Query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 根据多个id查询
.setQuery(QueryBuilders.idsQuery("student").addIds("1","111","999"))
.setSize(20) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println(e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
{"sName":"Student_1","sAge":28,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.666Z"}
{"sName":"Student_111","sAge":98,"sClass":"Class_11","sTime":"2018-12-13T08:39:57.693Z"}
{"sName":"Student_999","sAge":6,"sClass":"Class_19","sTime":"2018-12-13T08:39:58.120Z"}
命中：3
17. Compound queries（复合查询）
17.1 constant_score query
比如查询好吃的水果，提高桃子的权重
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 通过设置boost提高查询的权重
.setQuery(QueryBuilders.boolQuery()
.should(QueryBuilders.constantScoreQuery(QueryBuilders.termQuery("sName","student_1")).boost(3.0f))
.should(QueryBuilders.constantScoreQuery(QueryBuilders.termQuery("sName","student_2")).boost(0.3f)))
.setSize(10) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
Score:3.0,Source:{"sName":"Student_1","sAge":28,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.666Z"}
Score:0.3,Source:{"sName":"Student_2","sAge":20,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.689Z"}
命中：2
17.2 bool query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 查询上下文
.setQuery(QueryBuilders.boolQuery()
// (查询结果)必须出现在匹配的文档中，并将有助于得分
.must(QueryBuilders.rangeQuery("sAge").lte(30))
// (查询结果)不能出现在匹配的文档中，评分被忽略
.mustNot(QueryBuilders.termsQuery("sName","student_2","student_4"))
// (查询结果)应该出现在匹配的文档中。如果bool查询位于查询上下文中，并且具有must或filter子句，should查询将失效；
// 如果bool查询位于筛选上下文，或者既没有must也没有filter，那么至少应该有一个查询必须匹配文档以匹配bool查询
//.should(QueryBuilders.termQuery("sClass","Class_1"))
// (查询结果)必须出现在匹配的文档中，然而，与must不同的是，查询的分数将被忽略
.filter(QueryBuilders.rangeQuery("sAge").gte(5)))
.setSize(500) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
如果只有must查询，我测试查询出304条结果；加上mustNot查询，筛选出302条数据；加上should，仍然是302条数据，因为有must；不要should，加上filter筛选出256条数据。
...省略
Score:1.0,Source:{"sName":"Student_992","sAge":16,"sClass":"Class_12","sTime":"2018-12-13T08:39:58.120Z"}
Score:1.0,Source:{"sName":"Student_997","sAge":14,"sClass":"Class_17","sTime":"2018-12-13T08:39:58.120Z"}
Score:1.0,Source:{"sName":"Student_999","sAge":6,"sClass":"Class_19","sTime":"2018-12-13T08:39:58.120Z"}
命中：256
下面测试筛选上下文
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
.setQuery(QueryBuilders.boolQuery()
.must(QueryBuilders.rangeQuery("sAge").gte(10))
// 筛选上下文
.filter(QueryBuilders.boolQuery()
// (查询结果)必须出现在匹配的文档中，并将有助于得分
.must(QueryBuilders.rangeQuery("sAge").lte(30))
// (查询结果)不能出现在匹配的文档中，评分被忽略
.mustNot(QueryBuilders.termsQuery("sName","student_2","student_4"))
// (查询结果)应该出现在匹配的文档中。如果bool查询位于查询上下文中，并且具有must或filter子句，should查询将失效；
// 如果bool查询位于筛选上下文，或者既没有must也没有filter，那么至少应该有一个查询必须匹配文档以匹配bool查询
.should(QueryBuilders.termQuery("sClass","Class_1"))
))
.setSize(500) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
Score:1.0,Source:{"sName":"Student_1","sAge":28,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.666Z"}
Score:1.0,Source:{"sName":"Student_81","sAge":23,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.692Z"}
Score:1.0,Source:{"sName":"Student_161","sAge":21,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.695Z"}
Score:1.0,Source:{"sName":"Student_181","sAge":18,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.695Z"}
Score:1.0,Source:{"sName":"Student_281","sAge":21,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.698Z"}
Score:1.0,Source:{"sName":"Student_341","sAge":19,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.822Z"}
Score:1.0,Source:{"sName":"Student_361","sAge":14,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.822Z"}
Score:1.0,Source:{"sName":"Student_381","sAge":11,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.822Z"}
Score:1.0,Source:{"sName":"Student_501","sAge":23,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.825Z"}
Score:1.0,Source:{"sName":"Student_541","sAge":21,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.826Z"}
Score:1.0,Source:{"sName":"Student_601","sAge":27,"sClass":"Class_1","sTime":"2018-12-13T08:39:58.045Z"}
Score:1.0,Source:{"sName":"Student_901","sAge":15,"sClass":"Class_1","sTime":"2018-12-13T08:39:58.119Z"}
命中：12
query&filter
17.3 dis_max query
...待补充
17.4 function_score query（function_score允许您修改查询检索的文档的得分）
...待补充
17.5 boosting query
public static TransportClient queryDSL() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// 一种复合查询，分为positive子查询和negitive子查询，两者的查询结构都会返回
// positive子查询的score保持不变，negative子查询的值将会根据negative_boost的值做相应程度的降低。
.setQuery(QueryBuilders.boostingQuery(QueryBuilders.termQuery("sName","student_1"),
QueryBuilders.termQuery("sClass","Class_1")).negativeBoost(0.3f))
.setSize(500) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
Score:1.950987,Source:{"sName":"Student_1","sAge":28,"sClass":"Class_1","sTime":"2018-12-13T08:39:57.666Z"}
命中：1
18 Joining queries
18.1 嵌套查询
...待补充
18.2 Has Child Query
...待补充
18.3 Has Parent Query
...待补充
19. Geo queries（地理查询）
地理形状查询需要相关依赖
<dependency>
<groupId>org.locationtech.spatial4j</groupId>
<artifactId>spatial4j</artifactId>
<version>0.7</version>
</dependency> <dependency>
<groupId>org.locationtech.jts</groupId>
<artifactId>jts-core</artifactId>
<version>1.16.0</version>
<exclusions>
<exclusion>
<groupId>xerces</groupId>
<artifactId>xercesImpl</artifactId>
</exclusion>
</exclusions>
</dependency>
关于geo_point
PUT my_index
{
"mappings": {
"_doc": {
"properties": {
"location": {
"type": "geo_point"
}
}
}
}
} PUT my_index/_doc/1
{
"text": "Geo-point as an object",
"location": {
"lat": 41.12, // 纬度
"lon": -71.34 // 经度
}
} PUT my_index/_doc/2
{
"text": "Geo-point as a string",
"location": "41.12,-71.34" // 纬度,经度
} PUT my_index/_doc/3
{
"text": "Geo-point as an array",
"location": [ -71.34, 41.12 ] // 经度,纬度
} GET my_index/_search
{
"query": {
"geo_bounding_box": { // 查询落在框中的所有点
"location": {
"top_left": {
"lat": 42,
"lon": -72
},
"bottom_right": {
"lat": 40,
"lon": -74
}
}
}
}
}
19.1 geo_shape查询
查找与指定的地理形状相交、包含或不相交的地理形状的文档。
19.2 geo_bounding_box查询
查找落在指定矩形中的文档
初始化数据：数据文件点击这里
/**
* 从文件读取地理位置
* 地理位置选择：http://www.gpsspg.com/maps.htm
* @return
* @throws IOException
*/
private static List<String> getChinaCity() throws IOException {
List<String> list = new ArrayList<>();
FileInputStream in = new FileInputStream("China.txt");
BufferedReader reader = new BufferedReader(new InputStreamReader(in));
String s = null;
while ((s = reader.readLine()) != null){
list.add(s);
}
System.out.println("读取【" + list.size() + "】条数据");
reader.close();
in.close();
return list;
} /**
* 初始化地理数据
* @return
* @throws IOException
*/
public static TransportClient geoPointData() throws IOException {
List<String> list = getChinaCity();
TransportClient client = TransportClientFactory.getInstance().getClient();
AdminClient admin = client.admin();
IndicesAdminClient indicesAdminClient = admin.indices(); // 指数管理
CreateIndexResponse createIndexResponse = indicesAdminClient.prepareCreate("china_index")
.setSettings(Settings.builder()
.put("index.number_of_shards", 1) // 分片
.put("index.number_of_replicas", 1) // 副本
)
.addMapping("city", "pName", "type=keyword","cName", "type=text", "location", "type=geo_point") // mapping
.get();
System.out.println("创建索引：" + createIndexResponse.isAcknowledged());
BulkProcessor bulkProcessor = BulkProcessor.builder(
client,
new BulkProcessor.Listener() {
@Override
public void beforeBulk(long executionId, BulkRequest request) {
// bulk 执行之前
System.out.println("beforeBulk-----" + request.getDescription());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
BulkResponse response) {
// bulk 执行之后
System.out.println("afterBulk------" + request.getDescription() + ",是否有错误：" + response.hasFailures() + ",Msg:" + response.buildFailureMessage());
} @Override
public void afterBulk(long executionId,
BulkRequest request,
Throwable failure) {
//bulk 失败
System.out.println("报错-----" + request.getDescription() + "," + failure.getMessage());
}
})
.setBulkActions(300) // 每300个request，bulk一次
.setConcurrentRequests(0) // 设置并发请求的数量。值为0意味着只允许执行一个请求。值为1意味着在积累新的批量请求时允许执行1个并发请求。
.build();
int i = 1;
for (String s : list){
String[] data = s.split(",");
Double latitude,longitude;
// [经度：-180~180；纬度：-90~90]
latitude = Double.parseDouble(data[3]);
longitude = Double.parseDouble(data[2]);
bulkProcessor.add(new IndexRequest("china_index", "city", i++ +"").source(jsonBuilder()
.startObject()
.field("pName", data[0])
.field("cName", data[1])
.field("location", new GeoPoint(latitude, longitude))
.endObject()));
}
bulkProcessor.flush();
bulkProcessor.close();
return client;
}
执行之后：
GET /china_index/_search
.
下面查询：
public static TransportClient geoBoundingBoxQuery() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("china_index")
// top、left、bottom、right 围成一个矩形，查询这个矩形里面的位置
.setQuery(QueryBuilders.geoBoundingBoxQuery("location").setCorners(40.3800284025,114.8730468750,38.8568201347,118.9599609375))
.setSize(100) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
查询结果：
Score:1.0,Source:{"pName":"北京市","cName":"东城区","location":{"lat":39.92855,"lon":116.41637}}
Score:1.0,Source:{"pName":"北京市","cName":"西城区","location":{"lat":39.91231,"lon":116.36611}}
Score:1.0,Source:{"pName":"北京市","cName":"朝阳区","location":{"lat":39.927289,"lon":116.4498}}
Score:1.0,Source:{"pName":"北京市","cName":"丰台区","location":{"lat":39.85856,"lon":116.28616}}
Score:1.0,Source:{"pName":"北京市","cName":"石景山区","location":{"lat":39.90569,"lon":116.22299}}
Score:1.0,Source:{"pName":"北京市","cName":"海淀区","location":{"lat":39.95933,"lon":116.29845}}
Score:1.0,Source:{"pName":"北京市","cName":"顺义区","location":{"lat":40.13012,"lon":116.65477}}
Score:1.0,Source:{"pName":"北京市","cName":"通州区","location":{"lat":39.916195,"lon":116.662852}}
Score:1.0,Source:{"pName":"北京市","cName":"大兴区","location":{"lat":39.72684,"lon":116.34159}}
Score:1.0,Source:{"pName":"北京市","cName":"房山区","location":{"lat":39.74788,"lon":116.14294}}
Score:1.0,Source:{"pName":"北京市","cName":"门头沟区","location":{"lat":39.94048,"lon":116.10146}}
Score:1.0,Source:{"pName":"北京市","cName":"昌平区","location":{"lat":40.22077,"lon":116.23128}}
Score:1.0,Source:{"pName":"北京市","cName":"平谷区","location":{"lat":40.14062,"lon":117.12141}}
Score:1.0,Source:{"pName":"北京市","cName":"密云区","location":{"lat":40.37625,"lon":116.84317}}
Score:1.0,Source:{"pName":"北京市","cName":"怀柔区","location":{"lat":40.316,"lon":116.63177}}
Score:1.0,Source:{"pName":"天津市","cName":"和平区","location":{"lat":39.11712,"lon":117.2147}}
Score:1.0,Source:{"pName":"天津市","cName":"河东区","location":{"lat":39.12827,"lon":117.25228}}
Score:1.0,Source:{"pName":"天津市","cName":"河西区","location":{"lat":39.10954,"lon":117.22336}}
Score:1.0,Source:{"pName":"天津市","cName":"南开区","location":{"lat":39.13815,"lon":117.15011}}
Score:1.0,Source:{"pName":"天津市","cName":"河北区","location":{"lat":39.14784,"lon":117.19674}}
Score:1.0,Source:{"pName":"天津市","cName":"红桥区","location":{"lat":39.16734,"lon":117.15161}}
Score:1.0,Source:{"pName":"天津市","cName":"滨海新区","location":{"lat":39.0032,"lon":117.71071}}
Score:1.0,Source:{"pName":"天津市","cName":"东丽区","location":{"lat":39.08652,"lon":117.31428}}
Score:1.0,Source:{"pName":"天津市","cName":"西青区","location":{"lat":39.14111,"lon":117.00739}}
Score:1.0,Source:{"pName":"天津市","cName":"津南区","location":{"lat":38.9375,"lon":117.3571}}
Score:1.0,Source:{"pName":"天津市","cName":"北辰区","location":{"lat":39.22393,"lon":117.13544}}
Score:1.0,Source:{"pName":"天津市","cName":"武清区","location":{"lat":39.38326,"lon":117.04412}}
Score:1.0,Source:{"pName":"天津市","cName":"宝坻区","location":{"lat":39.71755,"lon":117.30983}}
Score:1.0,Source:{"pName":"天津市","cName":"宁河区","location":{"lat":39.33091,"lon":117.82478}}
Score:1.0,Source:{"pName":"天津市","cName":"静海区","location":{"lat":38.94737,"lon":116.97428}}
Score:1.0,Source:{"pName":"天津市","cName":"蓟州区","location":{"lat":40.04577,"lon":117.40829}}
Score:1.0,Source:{"pName":"天津市","cName":"天津","location":{"lat":39.13,"lon":117.2}}
Score:1.0,Source:{"pName":"天津市","cName":"宁河","location":{"lat":39.33,"lon":117.83}}
Score:1.0,Source:{"pName":"天津市","cName":"静海","location":{"lat":38.93,"lon":116.92}}
Score:1.0,Source:{"pName":"天津市","cName":"蓟县","location":{"lat":40.05,"lon":117.4}}
Score:1.0,Source:{"pName":"天津市","cName":"宝坻","location":{"lat":39.75,"lon":117.3}}
Score:1.0,Source:{"pName":"天津市","cName":"武清","location":{"lat":39.4,"lon":117.05}}
Score:1.0,Source:{"pName":"河北省","cName":"唐山","location":{"lat":39.63,"lon":118.02}}
Score:1.0,Source:{"pName":"河北省","cName":"涞水","location":{"lat":39.39,"lon":115.71}}
Score:1.0,Source:{"pName":"河北省","cName":"涿县","location":{"lat":39.48,"lon":115.98}}
Score:1.0,Source:{"pName":"河北省","cName":"定兴","location":{"lat":39.28,"lon":115.78}}
Score:1.0,Source:{"pName":"河北省","cName":"容城","location":{"lat":39.06,"lon":115.86}}
Score:1.0,Source:{"pName":"河北省","cName":"安新","location":{"lat":38.92,"lon":115.92}}
Score:1.0,Source:{"pName":"河北省","cName":"易县","location":{"lat":39.35,"lon":115.49}}
Score:1.0,Source:{"pName":"河北省","cName":"新城","location":{"lat":39.34,"lon":115.84}}
Score:1.0,Source:{"pName":"河北省","cName":"雄县","location":{"lat":38.98,"lon":116.1}}
Score:1.0,Source:{"pName":"河北省","cName":"徐水","location":{"lat":39.02,"lon":115.65}}
Score:1.0,Source:{"pName":"河北省","cName":"满城","location":{"lat":38.95,"lon":115.45}}
Score:1.0,Source:{"pName":"河北省","cName":"涿鹿","location":{"lat":40.37,"lon":115.2}}
Score:1.0,Source:{"pName":"河北省","cName":"迁西","location":{"lat":40.15,"lon":118.3}}
Score:1.0,Source:{"pName":"河北省","cName":"迁安","location":{"lat":40.02,"lon":118.69}}
Score:1.0,Source:{"pName":"河北省","cName":"卢龙","location":{"lat":39.89,"lon":118.85}}
Score:1.0,Source:{"pName":"河北省","cName":"滦南","location":{"lat":39.49,"lon":118.67}}
Score:1.0,Source:{"pName":"河北省","cName":"玉田","location":{"lat":39.9,"lon":117.9}}
Score:1.0,Source:{"pName":"河北省","cName":"唐海","location":{"lat":39.31,"lon":118.54}}
Score:1.0,Source:{"pName":"河北省","cName":"遵化","location":{"lat":40.2,"lon":117.97}}
Score:1.0,Source:{"pName":"河北省","cName":"乐亭","location":{"lat":39.43,"lon":118.9}}
Score:1.0,Source:{"pName":"河北省","cName":"滦县","location":{"lat":39.74,"lon":118.73}}
Score:1.0,Source:{"pName":"河北省","cName":"丰南","location":{"lat":39.58,"lon":118.1}}
Score:1.0,Source:{"pName":"河北省","cName":"丰润","location":{"lat":39.82,"lon":118.13}}
Score:1.0,Source:{"pName":"河北省","cName":"廊坊","location":{"lat":39.53,"lon":116.7}}
Score:1.0,Source:{"pName":"河北省","cName":"安次","location":{"lat":39.52,"lon":116.69}}
Score:1.0,Source:{"pName":"河北省","cName":"三河","location":{"lat":39.97,"lon":117.06}}
Score:1.0,Source:{"pName":"河北省","cName":"香河","location":{"lat":39.76,"lon":117.0}}
Score:1.0,Source:{"pName":"河北省","cName":"霸县","location":{"lat":39.12,"lon":116.38}}
Score:1.0,Source:{"pName":"河北省","cName":"固安","location":{"lat":39.44,"lon":116.29}}
Score:1.0,Source:{"pName":"河北省","cName":"文安","location":{"lat":38.87,"lon":116.45}}
Score:1.0,Source:{"pName":"河北省","cName":"永清","location":{"lat":39.32,"lon":116.48}}
Score:1.0,Source:{"pName":"河北省","cName":"大厂","location":{"lat":39.98,"lon":116.98}}
命中：
我通过这个网站找出两个点，用来测试数据 http://www.gpsspg.com/maps.htm
19.3 geo_distance查询
查找固定中心，指定半径范围内的文档
public static TransportClient geoBoundingBoxQuery() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("china_index")
// top、left、bottom、right 围成一个矩形，查询这个矩形里面的位置
//.setQuery(QueryBuilders.geoBoundingBoxQuery("location").setCorners(40.3800284025,114.8730468750,38.8568201347,118.9599609375))
// 查找以北京为中心，半径为200千米范围内的城市
.setQuery(QueryBuilders.geoDistanceQuery("location").point(39.6056881783,116.6748046875).distance(20, DistanceUnit.KILOMETERS))
.setSize(100) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果：
Score:1.0,Source:{"pName":"河北省","cName":"廊坊","location":{"lat":39.53,"lon":116.7}}
Score:1.0,Source:{"pName":"河北省","cName":"安次","location":{"lat":39.52,"lon":116.69}}
命中：
19.4 geo_polygon查询
查找指定多边形内的文档
我先选择一个多边形的几个点
23.6042618471,113.0932617188
22.3703963443,112.4780273438
21.4530686331,113.7963867188
22.8571947010,115.1147460938
下面查询
public static TransportClient geoPolygonQuery() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
List<GeoPoint> list = new ArrayList<>();
list.add(new GeoPoint(23.6042618471,113.0932617188));
list.add(new GeoPoint(22.3703963443,112.4780273438));
list.add(new GeoPoint(21.4530686331,113.7963867188));
list.add(new GeoPoint(22.8571947010,115.1147460938));
SearchResponse searchResponse = client.prepareSearch()
.setIndices("china_index")
// 查找多边形内的城市
.setQuery(QueryBuilders.geoPolygonQuery("location", list))
.setSize(100) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果
Score:1.0,Source:{"pName":"广东省","cName":"广州","location":{"lat":23.12908,"lon":113.26436}}
Score:1.0,Source:{"pName":"广东省","cName":"越秀","location":{"lat":23.12901,"lon":113.2668}}
Score:1.0,Source:{"pName":"广东省","cName":"荔湾","location":{"lat":23.12586,"lon":113.24428}}
Score:1.0,Source:{"pName":"广东省","cName":"海珠","location":{"lat":23.08331,"lon":113.3172}}
Score:1.0,Source:{"pName":"广东省","cName":"天河","location":{"lat":23.12463,"lon":113.36199}}
Score:1.0,Source:{"pName":"广东省","cName":"白云","location":{"lat":23.157032,"lon":113.273238}}
Score:1.0,Source:{"pName":"广东省","cName":"黄埔","location":{"lat":23.18139,"lon":113.48067}}
Score:1.0,Source:{"pName":"广东省","cName":"花都","location":{"lat":23.40391,"lon":113.22026}}
Score:1.0,Source:{"pName":"广东省","cName":"番禺","location":{"lat":22.93772,"lon":113.38424}}
Score:1.0,Source:{"pName":"广东省","cName":"南沙","location":{"lat":22.80169,"lon":113.52497}}
Score:1.0,Source:{"pName":"广东省","cName":"增城","location":{"lat":23.26093,"lon":113.8109}}
Score:1.0,Source:{"pName":"广东省","cName":"深圳","location":{"lat":22.54286,"lon":114.05956}}
Score:1.0,Source:{"pName":"广东省","cName":"福田","location":{"lat":22.52291,"lon":114.05454}}
Score:1.0,Source:{"pName":"广东省","cName":"罗湖","location":{"lat":22.54836,"lon":114.13166}}
Score:1.0,Source:{"pName":"广东省","cName":"南山","location":{"lat":22.53325,"lon":113.93069}}
Score:1.0,Source:{"pName":"广东省","cName":"盐田","location":{"lat":22.557,"lon":114.23679}}
Score:1.0,Source:{"pName":"广东省","cName":"宝安","location":{"lat":22.55329,"lon":113.88308}}
Score:1.0,Source:{"pName":"广东省","cName":"龙岗","location":{"lat":22.71991,"lon":114.24779}}
Score:1.0,Source:{"pName":"广东省","cName":"龙华","location":{"lat":22.696694,"lon":114.044612}}
Score:1.0,Source:{"pName":"广东省","cName":"坪山","location":{"lat":22.69084,"lon":114.34632}}
Score:1.0,Source:{"pName":"广东省","cName":"珠海","location":{"lat":22.27073,"lon":113.57668}}
Score:1.0,Source:{"pName":"广东省","cName":"香洲","location":{"lat":22.265939,"lon":113.543202}}
Score:1.0,Source:{"pName":"广东省","cName":"斗门","location":{"lat":22.20903,"lon":113.29658}}
Score:1.0,Source:{"pName":"广东省","cName":"金湾","location":{"lat":22.14589,"lon":113.3642}}
Score:1.0,Source:{"pName":"广东省","cName":"佛山","location":{"lat":23.02185,"lon":113.12192}}
Score:1.0,Source:{"pName":"广东省","cName":"禅城","location":{"lat":23.00944,"lon":113.12249}}
Score:1.0,Source:{"pName":"广东省","cName":"高明","location":{"lat":22.90026,"lon":112.89262}}
Score:1.0,Source:{"pName":"广东省","cName":"三水","location":{"lat":23.15585,"lon":112.89672}}
Score:1.0,Source:{"pName":"广东省","cName":"南海","location":{"lat":23.02882,"lon":113.14278}}
Score:1.0,Source:{"pName":"广东省","cName":"顺德","location":{"lat":22.80536,"lon":113.29321}}
Score:1.0,Source:{"pName":"广东省","cName":"江门","location":{"lat":22.57865,"lon":113.08161}}
Score:1.0,Source:{"pName":"广东省","cName":"江海","location":{"lat":22.56028,"lon":113.11103}}
Score:1.0,Source:{"pName":"广东省","cName":"蓬江","location":{"lat":22.59514,"lon":113.07845}}
Score:1.0,Source:{"pName":"广东省","cName":"新会","location":{"lat":22.45877,"lon":113.03231}}
Score:1.0,Source:{"pName":"广东省","cName":"台山","location":{"lat":22.25156,"lon":112.7939}}
Score:1.0,Source:{"pName":"广东省","cName":"鹤山","location":{"lat":22.7653,"lon":112.96436}}
Score:1.0,Source:{"pName":"广东省","cName":"开平","location":{"lat":22.37638,"lon":112.69851}}
Score:1.0,Source:{"pName":"广东省","cName":"惠州","location":{"lat":23.11075,"lon":114.41679}}
Score:1.0,Source:{"pName":"广东省","cName":"惠城","location":{"lat":23.08383,"lon":114.38273}}
Score:1.0,Source:{"pName":"广东省","cName":"惠阳","location":{"lat":22.78851,"lon":114.45646}}
Score:1.0,Source:{"pName":"广东省","cName":"惠东","location":{"lat":22.98486,"lon":114.71999}}
Score:1.0,Source:{"pName":"广东省","cName":"东莞","location":{"lat":23.02067,"lon":113.75179}}
Score:1.0,Source:{"pName":"广东省","cName":"中山","location":{"lat":22.51595,"lon":113.3926}}
Score:1.0,Source:{"pName":"澳门","cName":"澳门","location":{"lat":22.13,"lon":113.33}}
Score:1.0,Source:{"pName":"香港","cName":"香港","location":{"lat":22.2,"lon":114.1}}
命中：
20 脚本查询
public static TransportClient scriptQuery() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
Map<String, Object> parameters = new HashMap<>();
parameters.put("param1", "Class_2");
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
// inlined script
//.setQuery(QueryBuilders.scriptQuery(new Script("doc['sName'].value == 'Student_666'")))
// 带参数的
.setQuery(QueryBuilders.scriptQuery(new Script(ScriptType.INLINE,"painless",
"doc['sClass'].value == params.param1",parameters)))
.setSize() // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果
Score:1.0,Source:{"sName":"Student_2","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.689Z"}
Score:1.0,Source:{"sName":"Student_22","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.690Z"}
Score:1.0,Source:{"sName":"Student_42","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.690Z"}
Score:1.0,Source:{"sName":"Student_62","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.691Z"}
Score:1.0,Source:{"sName":"Student_82","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.692Z"}
Score:1.0,Source:{"sName":"Student_102","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.693Z"}
Score:1.0,Source:{"sName":"Student_122","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.693Z"}
Score:1.0,Source:{"sName":"Student_142","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.694Z"}
Score:1.0,Source:{"sName":"Student_162","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.695Z"}
Score:1.0,Source:{"sName":"Student_182","sAge":,"sClass":"Class_2","sTime":"2018-12-13T08:39:57.695Z"}
命中：
21 Span 查询
Span查询是低级的位置查询，提供对指定术语的顺序和接近程度的专业控制。这些通常用于实现对法律文件或专利的非常具体的查询。
public static TransportClient spanQuery() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
SearchResponse searchResponse = client.prepareSearch()
.setIndices("school")
.setQuery(QueryBuilders.spanTermQuery("sName","student_666"))
.setSize(10) // 返回数量
.get();
searchResponse.getHits().forEach(e -> {
System.out.println("Score:" + e.getScore() + ",Source:" + e.getSourceAsString());
});
System.out.println("命中：" + searchResponse.getHits().totalHits);
return client;
}
执行结果
Score:6.5032897,Source:{"sName":"Student_666","sAge":10,"sClass":"Class_6","sTime":"2018-12-13T08:39:58.046Z"}
命中：1
22 Administration
22.1 添加索引
public static TransportClient createIndex() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
AdminClient admin = client.admin();
IndicesAdminClient indicesAdminClient = admin.indices(); // 指数管理
// 创建index
CreateIndexResponse createIndexResponse = indicesAdminClient.prepareCreate("twitter")
.setSettings(Settings.builder()
.put("index.number_of_shards", 3) // 分片
.put("index.number_of_replicas", 2) // 副本
)
.addMapping("_doc", "message", "type=text") // mapping
.addAlias(new Alias("twitter_alias"))
.get();
System.out.println(createIndexResponse.isAcknowledged());
return client;
}
返回true
22.2 查看索引信息
public static TransportClient getIndex() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
AdminClient admin = client.admin();
IndicesAdminClient indicesAdminClient = admin.indices(); // 指数管理
// 获取index
GetIndexResponse getIndexResponse = indicesAdminClient.prepareGetIndex().addIndices("twitter").get();
getIndexResponse.getMappings().forEach(e -> {
String key = e.key;
ImmutableOpenMap<String, MappingMetaData> map = e.value;
System.out.println("Index:" + key);
map.forEach(n -> {
String type = n.key;
MappingMetaData metaData = n.value;
System.out.println(type + "|" + metaData.getSourceAsMap());
});
});
System.out.println("**********************************");
getIndexResponse.getAliases().forEach(e -> {
String key = e.key;
List<AliasMetaData> value = e.value;
System.out.println("----" + key + "----");
value.forEach(a -> {
System.out.println(a.alias());
});
});
System.out.println("**********************************");
getIndexResponse.getSettings().forEach(e -> {
String key = e.key;
Settings value = e.value;
System.out.println("----" + key + "----");
value.keySet().forEach(k -> {
System.out.println(k + ":" + value.get(k));
});
});
return client;
}
执行结果
Index:twitter
_doc|{properties={message={type=text}}}
**********************************
----twitter----
twitter_alias
**********************************
----twitter----
index.creation_date:1545383477041
index.number_of_replicas:2
index.number_of_shards:3
index.provided_name:twitter
index.uuid:Zggv0JmiSGCM27S2A_D-og
index.version.created:6050099
22.3 删除索引
public static TransportClient delIndex() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
AcknowledgedResponse response = client.admin().indices().prepareDelete("twitter").get();
System.out.println(response.isAcknowledged());
return client;
}
返回true
22.4 如果你建立好索引，想要添加mapping【已经建立好的mapping字段不允许修改】
public static TransportClient putIndexMapping() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
AdminClient admin = client.admin();
IndicesAdminClient indicesAdminClient = admin.indices(); // 指数管理
// 增加新的mapping
AcknowledgedResponse response = indicesAdminClient.preparePutMapping("twitter")
.setType("_doc")
.setSource("afterAdd", "type=keyword")
.get();
System.out.println(response.isAcknowledged());
return client;
}
返回true
再来看index信息（通过getIndex）
Index:twitter
_doc|{properties={afterAdd={type=keyword}, message={type=text}}}
**********************************
----twitter----
twitter_alias
**********************************
----twitter----
index.creation_date:1545383985875
index.number_of_replicas:2
index.number_of_shards:3
index.provided_name:twitter
index.uuid:K2_5S8pIR4mqLGga7-0ZHQ
index.version.created:6050099
23 集群信息
/**
* 集群信息，节点信息，索引信息，状态信息
* @return
* @throws UnknownHostException
*/
public static TransportClient clusterInfo() throws UnknownHostException {
TransportClient client = TransportClientFactory.getInstance().getClient();
AdminClient admin = client.admin();
// 集群管理
ClusterHealthResponse healths = admin.cluster().prepareHealth().get();
String clusterName = healths.getClusterName();
int numberOfDataNodes = healths.getNumberOfDataNodes();
int numberOfNodes = healths.getNumberOfNodes();
System.out.println("集群名称：" + clusterName);
System.out.println("数据节点数：" + numberOfDataNodes);
System.out.println("节点数：" + numberOfNodes);
for (ClusterIndexHealth health : healths.getIndices().values()) {
String index = health.getIndex();
int numberOfShards = health.getNumberOfShards();
int numberOfReplicas = health.getNumberOfReplicas();
ClusterHealthStatus status = health.getStatus();
System.out.println("索引：" + index + ",分片数：" + numberOfShards + ",副本数：" + numberOfReplicas + ",状态：" + status.name());
} return client;
}
执行结果
集群名称：my-elasticsearch
数据节点数：
节点数：
索引：area,分片数：,副本数：,状态：YELLOW
索引：china_index,分片数：,副本数：,状态：YELLOW
索引：book,分片数：,副本数：,状态：YELLOW
索引：test_ik_index,分片数：,副本数：,状态：YELLOW
索引：posts,分片数：,副本数：,状态：YELLOW
索引：.kibana_1,分片数：,副本数：,状态：GREEN
索引：clothes,分片数：,副本数：,状态：YELLOW
索引：all_books,分片数：,副本数：,状态：YELLOW
索引：twitter,分片数：,副本数：,状态：YELLOW
索引：it_book,分片数：,副本数：,状态：YELLOW
索引：car,分片数：,副本数：,状态：YELLOW
索引：school,分片数：,副本数：,状态：YELLOW
索引：story,分片数：,副本数：,状态：YELLOW
TransportClient到此为止，下面是ES新API--Rest Client
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