文章目录
- 搜索管理
- 准备环境
- DSL搜索
- 查询所有文档
- 分页查询
- Term Query
- 根据id精确匹配
- match Query
- multi Query
- 布尔查询
- 过滤器
- 排序
- 高亮显示
- 集群管理
- 集群结构
- 搭建集群
- 集群的健康
- green 所有主分片和副分片都正常运行.
- yellow:所有的主分片正常运行,但是有些副分片不正常
- red:存在主分片不正常运行
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准备环境
创建映射
插入原始数据
插入三条原始数据
具体数据:
创建映射：
post：http://localhost:9200/xc_course/doc/_mapping
{"properties": {"description": {"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"name": {"type": "text",
"analyzer": "ik_max_word",
"search_analyzer": "ik_smart"
},
"pic":{"type":"text",
"index":false
},
"price": {"type": "float"
},
"studymodel": {"type": "keyword"
},
"timestamp": {"type": "date",
"format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis"
}
}
}
初始化文档：
http://localhost:9200/xc_course/doc/1
{"name": "Bootstrap开发",
"description": "Bootstrap是由Twitter推出的一个前台页面开发框架，是一个非常流行的开发框架，此框架集成了多种页面效果。此开发框架包含了大量的CSS、JS程序代码，可以帮助开发者（尤其是不擅长页面开发的程序人员）轻松的实现一个不受浏览器限制的精美界面效果。",
"studymodel": "201002",
"price":38.6,
"timestamp":"2018-04-25 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
http://localhost:9200/xc_course/doc/2
{"name": "java编程基础",
"description": "java语言是世界第一编程语言，在软件开发领域使用人数最多。",
"studymodel": "201001",
"price":68.6,
"timestamp":"2018-03-25 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
http://localhost:9200/xc_course/doc/3
{"name": "spring开发基础",
"description": "spring 在java领域非常流行，java程序员都在用。",
"studymodel": "201001",
"price":88.6,
"timestamp":"2018-02-24 19:11:35",
"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg"
}
简单搜索
DSL搜索
DSL(Domain Specific Language)是es提出的专门面向JSon数据的搜索方式,在搜索时通过json格式完成索引.
DSL比Url搜索方式功能强大,在项目中建议使用DSL方式完成搜索.
查询所有文档
postman:
{"query":{"match_all":{}//搜索方法
},
"_source":["name","studymodel"]//内容定向
}
搜索结果:
{"took": 46,
"timed_out": false,
"_shards": {"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {"total": 3,
"max_score": 1.0,
"hits": [
{"_index": "xc_andrew",
"_type": "doc",
"_id": "1",
"_score": 1.0,
"_source": {"studymodel": "201002",
"name": "Bootstrap开发"
}
},
{"_index": "xc_andrew",
"_type": "doc",
"_id": "2",
"_score": 1.0,
"_source": {"studymodel": "201001",
"name": "java编程基础"
}
},
{"_index": "xc_andrew",
"_type": "doc",
"_id": "3",
"_score": 1.0,
"_source": {"studymodel": "201001",
"name": "spring开发基础"
}
}
]
}
}
}
结果说明
took:本次操作花费的时间,单位毫秒.
timed_out:请求是否超时
_shards:说明本次操作共搜索了那些内容
total:集群部署中的分片数量
hits:搜索命中的记录
hits.total:符合条件的文档总数
hits.hits:匹配度较高的n个文档
hits.max_score:文档匹配得分,这里为最高分
_score:分割文档都有一个匹配得分,这里按照从高到低
_source:显示文档内容
在java中使用
@Test
public void testSearch() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
分页查询
postman分页
{ "from":0,"size":1,
"query":{
"match_all":{}
},
"_source":["name","studymodel"]
}
java分页
//分页测试
@Test
public void testSearchByPage() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
int page = 1;
int size = 1;
int from = (page - 1) * size;
searchSourceBuilder.from(from);
searchSourceBuilder.size(size);
searchSourceBuilder.query(QueryBuilders.matchAllQuery());
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
Term Query
根据任一项查询
postman
{
"query":{ "term":{"name":"spring"
}
},
"_source":["name","studymodel"]
}
java
//termQuery
@Test
public void testTermQuery() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders.termQuery("name","spring"));
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
根据id精确匹配
postman:
{
"query":{"ids":{ "type":"doc",
"values":["1","2"]
}}}
这里的values注意后面还有一个s
java:
@Test
public void testQueryById() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
String[] ids = new String[]{"1","2"};
searchSourceBuilder.query(QueryBuilders.termsQuery("_id",ids));
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
注意这里的QueryBuilder.termsQuery的方法,而不是termQuery,和根据任意项选择有区别
match Query
搜索的时候分词
postman
{
"query":{"match":{"description":{"query":"spring 开发",
"operator":"or"
}
}
}}
这里的operator表示or的时候是有一个词就可以搜出
表示and的时候表示只都在的时候才可以搜出
java
//MatchQuery
@Test
public void testQueryMatch() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders.matchQuery("description","spring开发").operator(Operator.OR));
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
postman:
{
"query":{"match":{"description":{"query":"spring 开发",
"minimum_should_match":"80%"
}
}
}}
这里的变量minimum是搜索重复率如果达到总占比的80%,就搜出
multi Query
可以在多个属性中查找,避免如termQuery只能在一个属性中查找的缺点
postman
{"query":{"multi_match":{"query":"spring css",
"minimum_should_match":"50%",
"fields":["name^10","description"]
}
}
}
java:
//Multi_Match
@Test
public void testMultiMatch() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(QueryBuilders.multiMatchQuery("spring css","name","description")
.minimumShouldMatch("50%")
.field("name",10));
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
postman里的^10代表比重提高10倍,因为标题中的比重大于文章中的比重
而在java中使用field.(name,boot)中的boost表示比重.
布尔查询
布尔查询对应Lucene的BooleanQuery查询,实现将多个查询结合起来
如果要包含以上的多个条件一起查询,应该怎么操作?
就要使用boolean查询了
这样子比较复杂,不过有前面的基础,可以很快掌握,理解
postman:
{"_source":["name","description"],
"from":0,
"size":1,
"query":{"bool":{"must":[
{"multi_match":{"query":"spring 开发",
"minimum_should_match":"50%",
"fields":["name","description"]
}},
{"term":{"studymodel":"201001"
}
}
]
}
}
}
java:
//BoolerMatch
@Test
public void testBoolerMatch() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring css", "name", "description")
.minimumShouldMatch("50%")
.field("name", 10);
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201001");
BoolQueryBuilder builder = new BoolQueryBuilder();
builder.must(multiMatchQueryBuilder);
builder.must(termQueryBuilder);
searchSourceBuilder.query(builder);
searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},
new String[]{} );
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
}
must：表示必须，多个查询条件必须都满足。（通常使用must）
should：表示或者，多个查询条件只要有一个满足即可。
must_not：表示非。
过滤器
过虑是针对搜索的结果进行过虑，过虑器主要判断的是文档是否匹配，不去计算和判断文档的匹配度得分，所以过虑器性能比查询要高，且方便缓存，推荐尽量使用过虑器去实现查询或者过虑器和查询共同使用。
过虑器在布尔查询中使用，下边是在搜索结果的基础上进行过虑：
postman:
{"query":{"bool":{"must":[
{"multi_match":{"query":"spring 开发",
"minimum_should_match":"50%",
"fields":["name","description"]
}},
{"term":{"studymodel":"201001"
}
}
],
"filter":[
{"term":{"studymodel":"201001"}},
{"range":{"price":{"gte":60,"lte":100}}}
]
}
}
}
注意,filter和must同级,在must[],后面加filter
Java:
//FilterMatch
@Test
public void testFilterMatch() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring css", "name", "description")
.minimumShouldMatch("50%")
.field("name", 10);
BoolQueryBuilder builder = new BoolQueryBuilder();
builder.must(multiMatchQueryBuilder);
builder.filter(QueryBuilders.termQuery("studymodel", "201001"));
builder.filter(QueryBuilders.rangeQuery("price").gte(90).lte(100) );
searchSourceBuilder.query(builder);
searchSourceBuilder.fetchSource(new String[]{"name", "studymodel", "price", "timestamp"},
new String[]{});
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(price);
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
排序
可以在字段上添加一个或多个排序，支持在keyword、date、float等类型上添加，text类型的字段上不允许添加排序。
发送POSThttp://localhost:9200/xc_course/doc/_search
过虑0–10元价格范围的文档，并且对结果进行排序，先按studymodel降序，再按价格升序
postman:
{"query":{"bool":{
"filter":[
{"range":{"price":{"gte":0,"lte":100}}}
]
}
},
"sort":[
{"studymodel":"DESC",
"price":"ASC"
}
]
java:
//OrderMatch
@Test
public void testOrderMatch() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
BoolQueryBuilder builder = new BoolQueryBuilder();
builder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100) );
searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC));
searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC));
searchSourceBuilder.query(builder);
searchSourceBuilder.fetchSource(new String[]{"name", "studymodel", "price", "timestamp"},
new String[]{});
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(price);
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
高亮显示
高亮显示可以将搜索结果一个或多个字突出显示，以便向用户展示匹配关键字的位置。在搜索语句中添加highlight即可实现，如下：
Post：http://127.0.0.1:9200/xc_course/doc/_search
postman:
{"query":{"bool":{ "must":[
{"multi_match":{"query":"spring 开发",
"minimum_should_match":"50%",
"fields":["name","description"]
}},
{"term":{"studymodel":"201001"
}
}
],
"filter":[
{"range":{"price":{"gte":0,"lte":100}}}
]
}
},
"sort":[
{"studymodel":"DESC",
"price":"ASC"
}
],
"highlight":
{"pre_tags":[""],
"post_tags":[""],
"fields":{"name":{},
"description":{}
}
}
}
java:
//HighLight
@Test
public void testHighLight() throws IOException, ParseException {SearchRequest searchRequest = new SearchRequest("xc_andrew");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring 开发", "name", "description")
.minimumShouldMatch("50%")
.field("name", 10);
BoolQueryBuilder builder = new BoolQueryBuilder();
builder.must(multiMatchQueryBuilder );
builder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100) );
searchSourceBuilder.query(builder);
searchSourceBuilder.fetchSource(new String[]{"name", "studymodel", "price", "timestamp"},
new String[]{});
HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.preTags("");
highlightBuilder.postTags("");
highlightBuilder.fields().add(new HighlightBuilder.Field("name"));
searchSourceBuilder.highlighter(highlightBuilder);
searchRequest.source(searchSourceBuilder);
SearchResponse search = restHighLevelClient.search(searchRequest);
SearchHits hits = search.getHits();
long totalHits = hits.totalHits;
SearchHit[] searchHits = hits.getHits();
SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
for (SearchHit hit : searchHits) {String id = hit.getId();
MapsourceAsMap = hit.getSourceAsMap();
String name = (String) sourceAsMap.get("name");
MaphighlightFields = hit.getHighlightFields();
if (highlightFields!=null){HighlightField nameField = highlightFields.get("name");
if (nameField!=null){StringBuffer sb = new StringBuffer();
Text[] fragments = nameField.getFragments();
for (Text fragment : fragments) {sb.append(fragment.string());
}
name = sb.toString();
}
}
String description = (String) sourceAsMap.get("description");
// String studymodel = (String) sourceAsMap.get("studymodel");
Double price = (Double) sourceAsMap.get("price");
Date timestamp = simpleDateFormat.parse((String) sourceAsMap.get("timestamp"));
System.out.println(price);
System.out.println(name);
// System.out.println(studymodel);
System.out.println(timestamp);
System.out.println(description);
}
}
这个高亮设置,一定是要有检索内容才可以添加的,应为高亮添加的就是你的检索内容的词汇
集群管理
集群结构
es通常以集群的方式部署,工作,这样不仅可以提高处理PB及数据的能力,还可以很好的增加系统的容错性和可用性.
ES集群结构图:
每一个es服务器可以看作是一个节点,
而节点有主节点和副节点直接点负责集群管理,
索引可以分布在不同的片上,片也分主片和副片,当主片失效时,可以由副片分担,这样实现了高可用性,和高容错性,使得ES可以成为PB级数据的处理器,一个搜索请求过来时,就会分片取查询,最后将结果返回非用户.
一个及集群中会有多个主节点,主节点管理集群,比如增加节点,移除节点,主节点挂掉之后,ES会重新选择一个节点.
节点转发,每个节点都知道其他节点的信息,我们可以对任意节点发起请求,接受请求的节点会转发给其他节点查询数据.
搭建集群
复制之前的集群节点,然后进入config中修改elasticsearch.yml
将其中的name修改,本身的端口加一,
然后点击bin中的elasticsearch.bat,即可.
我这里部署了三个,分成两篇,由于不同节点之间可以转发,所以在任何一个节点上,都可以看到全部的内容.
集群的健康
通过访问Get /_cluster/health来查看Elasticsearch的集群健康情况
用三种颜色表示健康的状态:green,yellow,red
green 所有主分片和副分片都正常运行.
yellow:所有的主分片正常运行,但是有些副分片不正常
这里是我关掉node_3后的情况.
red:存在主分片不正常运行
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