Elasticsearch的RESTful API
接上一篇搭建文章中,nginx.conf 定义的log格式是:
log_format main '$remote_addr - $remote_user [$time_local] "$request" '
'$status $body_bytes_sent "$http_referer" '
'"$http_user_agent" "$http_x_forwarded_for"';
实际的nginx日志实例如下:
192.168.1.137 - - [23/May/2022:14:33:18 +0800] "GET /index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1 HTTP/1.1" 200 5 "http://192.168.1.240:10003/index.php?m=bug&f=browse&productID=2" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36 Edg/100.0.1185.50"
所以Logstash中filter的grok表达式是:
%{IPORHOST:remote_ip} - %{DATA:user_name} \[%{HTTPDATE:time}\] \"%{WORD:method} %{DATA:url} HTTP/%{NUMBER:http_version}\" %{NUMBER:response_code} %{NUMBER:body_sent:bytes} \"%{DATA:referrer}\" \"%{DATA:user_agent}\"
ELK的版本是7.16.1
1.Elasticsearch的RESTful API
1.1 RESTful API介绍
es的RESTful API提供了众多的api和丰富的功能;常用的API分为如下几类
- Document APIs :es的文档的CRUD操作相关API
- Search APIs:查询检索相关的API
- Indices APIs:索引管理相关API
- cat APIs:集群健康状态、索引信息、分片信息等等,输出的是在命令行界面下更友好的制表信息
- Cluster APIs:es集群查看和管理配置相关API
想要系统性的了解请参考:
www.elastic.co/guide/en/elasticsearch/reference/7.16/index.html
1.2 常用RESTful API使用
让我们借助Kibana的 Dev Tools工具来了解一下常用的API使用。
GET /
响应结果如下:
#! Elasticsearch built-in security features are not enabled. Without authentication, your cluster could be accessible to anyone. See https://www.elastic.co/guide/en/elasticsearch/reference/7.16/security-minimal-setup.html to enable security.
{
"name" : "node-1",
"cluster_name" : "es-cluster",
"cluster_uuid" : "fx1Mm_OlQ6KCA41PQdLtHw",
"version" : {
"number" : "7.16.1",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "5b38441b16b1ebb16a27c107a4c3865776e20c53",
"build_date" : "2021-12-11T00:29:38.865893768Z",
"build_snapshot" : false,
"lucene_version" : "8.10.1",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}
可以查看es的简单信息包括版本号、集群名称、lucene版本号等。
GET nginx-access-log*
可以查看到es对应的index的aliases,mappings,settings信息。其中重要的是mappings,mapping是es中定义文档和字段是如何被存储和索引的,例如定义哪些字符串字段应被视为全文字段;哪些字段包含数字、日期、地理位置;日期字段的日期格式以及对动态增加的字段的一些自定义规则。
mappings 返回数据片段举例
{
"nginx-access-log-2022.05.23" : {
"aliases" : { },
"mappings" : { // mappings 都有哪些属性
"properties" : {
"@timestamp" : { // @timestamp字段是日期类型
"type" : "date"
},
"@version" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"agent" : {
"properties" : {
"ephemeral_id" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"hostname" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"id" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
......
}
}
}
1.3 Search APIs的常见用法
GET nginx-access-log*/_search
查询nginx-access-log为前缀的索引全部数据(默认只返回前10条数据),查询结果如下
{
"took" : 620, //查询所花费的毫秒数
"timed_out" : false,
"_shards" : {
"total" : 2, //查询了几个分片
"successful" : 2, //查询执行成功的分片数
"skipped" : 0,
"failed" : 0
},
"hits" : { //查询命中的数据
"total" : {
"value" : 10000, //indexpattern下的查询命中的全部数据条数
"relation" : "gte"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "nginx-access-log-2022.05.23", //表示数据来自那个索引
"_type" : "_doc",
"_id" : "f-FB8IABH99_gnUyqP4c",
"_score" : 1.0,
"_source" : { //表示原始数据
"log" : {
"offset" : 6699146,
"file" : {
"path" : "/var/log/nginx/zentaopms.access.log"
}
},
"http_version" : "1.1",
"body_sent" : "5",
"input" : {
"type" : "log"
},
"remote_ip" : "192.168.1.35",
"agent" : {
"id" : "dbfdd21f-edf6-4e04-beca-78d20dbea316",
"type" : "filebeat",
"version" : "7.16.1",
"ephemeral_id" : "35990523-3475-4235-bbae-a577c583b46e",
"name" : "69760ea94693",
"hostname" : "69760ea94693"
},
"host" : {
"name" : "69760ea94693"
},
"user_name" : "-",
"response_code" : "200",
"referrer" : "http://192.168.1.240:10003/index.php?m=bug&f=browse&root=1&branch=&type=byModule¶m=1",
"method" : "GET",
"ecs" : {
"version" : "1.12.0"
},
"@timestamp" : "2022-05-23T09:31:14.322Z",
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"@version" : "1",
"tags" : [
"_jsonparsefailure",
"beats_input_codec_json_applied"
],
"fields" : {
"log_source" : "nginx"
},
"time" : "09/Nov/2021:14:43:24 +0800",
"user_agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.81 Safari/537.36"
}
},
]
}
}
如果想要查询status=200的最近1条数据应该怎么写呢?我们可以分别使用URI search和Request body两种查询方式。
GET nginx-access-log*/_search?q=response_code:200&size=1&sort=@timestamp:desc
加上参数q=status:200 表示查询status字段值为200的数据,size=1表示只返回前1条数据,sort=@timestamp:desc表示使用@timestamp字段倒序排序
使用URI search的查询方式,更多内容请参考www.elastic.co/guide/en/elasticsearch/reference/7.16/search.html
#! Elasticsearch built-in security features are not enabled. Without authentication, your cluster could be accessible to anyone. See https://www.elastic.co/guide/en/elasticsearch/reference/7.16/security-minimal-setup.html to enable security.
{
"took" : 9,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "z-JI9YABH99_gnUyL-CT",
"_score" : null,
"_source" : {
"log" : {
"offset" : 25277051,
"file" : {
"path" : "/var/log/nginx/zentaopms.access.log"
}
},
"http_version" : "1.1",
"body_sent" : "5",
"input" : {
"type" : "log"
},
"remote_ip" : "192.168.1.100",
"agent" : {
"type" : "filebeat",
"id" : "dbfdd21f-edf6-4e04-beca-78d20dbea316",
"version" : "7.16.1",
"ephemeral_id" : "35990523-3475-4235-bbae-a577c583b46e",
"name" : "69760ea94693",
"hostname" : "69760ea94693"
},
"host" : {
"name" : "69760ea94693"
},
"user_name" : "-",
"response_code" : "200",
"referrer" : "http://192.168.1.240:10003/index.php?m=bug&f=view&bugID=431",
"method" : "GET",
"ecs" : {
"version" : "1.12.0"
},
"@timestamp" : "2022-05-24T08:56:27.847Z",
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"@version" : "1",
"tags" : [
"_jsonparsefailure",
"beats_input_codec_json_applied"
],
"fields" : {
"log_source" : "nginx"
},
"time" : "24/May/2022:16:56:25 +0800",
"user_agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36"
},
"sort" : [
1653382587847
]
}
]
}
}
如果我们只想查询_source中的某些字段,而不想要全部字段时,可以加上_source:[“字段1”,”字段2”]
进行过滤
GET nginx-access-log*/_search?q=response_code:200&size=2&sort=@timestamp:desc
{
"_source": ["url", "user_agent"]
}
或者
GET nginx-access-log*/_search
{
"size":2,
"_source": ["url", "user_agent"],
"query":{
"term":{
"response_code":200
}
},
"sort": [
{
"@timestamp": {
"order": "desc"
}
}
]
}
返回结果如下:
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "z-JI9YABH99_gnUyL-CT",
"_score" : null,
"_source" : {
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"user_agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36"
},
"sort" : [
1653382587847
]
},
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "zuJD9YABH99_gnUyruDP",
"_score" : null,
"_source" : {
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"user_agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36"
},
"sort" : [
1653382292775
]
}
]
}
}
_source还可以有如下用法
"_source": {
"includes": [ "http*", "geoip.*" ], //包含的字段,http开头的字段,geoip的嵌套类型字段
"excludes": [ "xxx" ] //排除哪些字段
}
"_source": false, //不显示_source内容
如果我们只想要统计数量而不需要查询数据,可以使用 Count API
GET nginx-access-log*/_count
{
"query":{
"term":{
"response_code":200
}
}
}
上面的查询会返回如下内容,count表示查询命中的数量
{
"count" : 76381,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
}
}
如果我们想要查询的数据比较多,我们可以利用scroll来进行游标查询;scroll=5m表示游标查询窗口会保持5分钟
GET nginx-access-log*/_search?scroll=5m
{
"size":2,
"_source": ["url", "user_agent"],
"query":{
"term":{
"response_code":200
}
},
"sort": [
{
"@timestamp": {
"order": "desc"
}
}
]
}
上面的查询会得到如下结果
{
"_scroll_id" : "FGluY2x1ZGVfY29udGV4dF91dWlkDnF1ZXJ5VGhlbkZldGNoAhZqMFRDR09mcVFnLWk5cjM5WGpRVlNBAAAAAAABUlQWRTNaTGY5RFVRT1doMVUyVzFNWng1URZqMFRDR09mcVFnLWk5cjM5WGpRVlNBAAAAAAABUlMWRTNaTGY5RFVRT1doMVUyVzFNWng1UQ==",
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 76384,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "3uJd9YABH99_gnUyIuDL",
"_score" : null,
"_source" : {
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"user_agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36"
},
"sort" : [
1653383961174
]
},
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "3eJY9YABH99_gnUyouCP",
"_score" : null,
"_source" : {
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"user_agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.67 Safari/537.36"
},
"sort" : [
1653383666111
]
}
]
}
}
上面的返回结果中有一个 _scroll_id 字段,要基于这个游标继续遍历数据只需要像下面这样,调用 /_search/scroll 接口,将前面返回结果的_scroll_id作为scroll_id参数值;scroll:5m表示将当前的scroll_id查询窗口再次延长5分钟。这样就可以一直查询,直到数据为空
GET /_search/scroll
{
"scroll":"5m",
"scroll_id":"FGluY2x1ZGVfY29udGV4dF91dWlkDnF1ZXJ5VGhlbkZldGNoAhZqMFRDR09mcVFnLWk5cjM5WGpRVlNBAAAAAAABUlQWRTNaTGY5RFVRT1doMVUyVzFNWng1URZqMFRDR09mcVFnLWk5cjM5WGpRVlNBAAAAAAABUlMWRTNaTGY5RFVRT1doMVUyVzFNWng1UQ=="
}
游标超过时间窗口会自动清理,也可以通过 DELETE /_search/scroll 来清理一个游标
DELETE /_search/scroll
{
"scroll_id" : "FGluY2x1ZGVfY29udGV4dF91dWlkDnF1ZXJ5VGhlbkZldGNoAhZqMFRDR09mcVFnLWk5cjM5WGpRVlNBAAAAAAABUlQWRTNaTGY5RFVRT1doMVUyVzFNWng1URZqMFRDR09mcVFnLWk5cjM5WGpRVlNBAAAAAAABUlMWRTNaTGY5RFVRT1doMVUyVzFNWng1UQ=="
}
返回结果如下:
{
"succeeded" : true,
"num_freed" : 2
}
查询结果高亮,更多内容请参考 www.elastic.co/guide/en/elasticsearch/reference/7.16/highlighting.html
GET nginx-access-log*/_search
{
"size":15,
"_source": [ "url", "remote_ip","response_code" ],
"query":{
"term":{
"response_code":200
}
},
"highlight": {
"fields": {"response_code":{}}
},
"sort": [
{
"@timestamp": {
"order": "desc"
}
}
]
}
运行结果如下:
#! Elasticsearch built-in security features are not enabled. Without authentication, your cluster could be accessible to anyone. See https://www.elastic.co/guide/en/elasticsearch/reference/7.16/security-minimal-setup.html to enable security.
{
"took" : 13,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "4uJv9YABH99_gnUyduBw",
"_score" : null,
"_source" : {
"response_code" : "200",
"remote_ip" : "192.168.1.100",
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1"
},
"highlight" : {
"response_code" : [
"<em>200</em>"
]
},
"sort" : [
1653385161394
]
},
{
"_index" : "nginx-access-log-2022.05.24",
"_type" : "_doc",
"_id" : "4eJq9YABH99_gnUyzuA5",
"_score" : null,
"_source" : {
"response_code" : "200",
"remote_ip" : "192.168.1.100",
"url" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1"
},
"highlight" : {
"response_code" : [
"<em>200</em>"
]
},
"sort" : [
1653384856313
]
}
]
}
}
其中:
"highlight" : {
"response_code" : [
"<em>200</em>"
]
},
为高亮内容。
1.4 Aggregation聚合查询
如果想要统计某索引每天(每小时)的数量、按照某个字段计数等类似的查询就要用到aggregation聚合查询
例如我们想要知道每天的请求数量,可像下面这样写:
- aggs表示聚合查询;
- “day_count”是我们自定义的一个聚合的名称(aggs可以有多个和多层所以需要指定一个名称);
- date_histogram表示是一个日期分布器,是按照“@timestamp”这个日期字段按照1d(1天)的时间间隔进行分布的;
- size:0 表示不返回具体的记录,hits部分是空数组
GET nginx-access-log*/_search
{
"aggs": {
"day_count": {
"date_histogram": {
"field": "@timestamp",
"interval": "1d"
}
}
},
"size": 0
}
返回数据会出现一个aggreations部分;day_count就是我们自定义的聚合名称,buckets表示按照日期分布到了那几个“桶”里。
{
"took" : 22,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"day_count" : {
"buckets" : [
{
"key_as_string" : "2022-05-23T00:00:00.000Z",
"key" : 1653264000000,
"doc_count" : 78953
},
{
"key_as_string" : "2022-05-24T00:00:00.000Z",
"key" : 1653350400000,
"doc_count" : 303
}
]
}
}
}
如果我们想要固定查询的日期范围,并且只查询status=404的数量,可以在查询增加query部分,如下:
GET nginx-access-log*/_search
{
"aggs": {
"day_count": {
"date_histogram": {
"field": "@timestamp",
"interval": "1d"
}
}
},
"size": 0,
"query": {
"bool": {
"must": [
{"range": { //一个range查询
"@timestamp": { //查询1月20到1月25时间范围
"gte": "2022-05-23",
"lte": "2022-05-24",
"format": "yyyy-MM-dd"
}
}
},{
"match": { //只匹配status=200的记录
"response_code": 404
}
}
]
}
}
}
查询结果如下:
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 28,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"day_count" : {
"buckets" : [
{
"key_as_string" : "2022-05-23T00:00:00.000Z",
"key" : 1653264000000,
"doc_count" : 28
}
]
}
}
}
我们也可以按照terms进行聚合,比如统计一天内接口调用次数,只需要将aggs部分修改成如下,interface.keyword 就是interface的全文字段,size:5 表示只展示前面5个(默认是按照doc_count倒序排序)
GET nginx-access-log*/_search
{
"aggs": {
"interface_count": {
"terms": {
"field": "url.keyword",
"size": 5
}
}
},
"size": 0,
"query": {
"bool": {
"must": [
{"range": {
"@timestamp": {
"gte": "2022-05-23",
"lte": "2022-05-24",
"format": "yyyy-MM-dd"
}
}
},{
"match": {
"response_code": 200
}
}
]
}
}
}
统计结果如下:
{
"took" : 33,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"interface_count" : {
"doc_count_error_upper_bound" : 373,
"sum_other_doc_count" : 30492,
"buckets" : [
{
"key" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"doc_count" : 39031
},
{
"key" : "/index.php?m=project&f=index&locate=no",
"doc_count" : 1826
},
{
"key" : "/index.php?m=product&f=index&locate=no",
"doc_count" : 1748
},
{
"key" : "/index.php?m=my&f=index",
"doc_count" : 1695
},
{
"key" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=0",
"doc_count" : 1603
}
]
}
}
}
那么,如果我们想要看每个接口一天内每个小时的调用数量改怎么办呢?
GET nginx-access-log*/_search
{
"aggs": {
"interface_count": {
"terms": {
"field": "url.keyword",
"size": 5
},
"aggs" :{
"hours" : {
"date_histogram": {
"field": "@timestamp",
"interval": "1h" //按照1小时间隔分布
}
}
}
}
},
"size": 0,
"query": {
"bool": {
"must": [
{"range": {
"@timestamp": {
"gte": "2022-05-23",
"lte": "2022-05-24",
"format": "yyyy-MM-dd"
}
}
},{
"match": {
"response_code": 200
}
}
]
}
}
}
只需要在上面的interface_count aggs基础上再嵌套一个date_histogram类型的聚合
返回结果中在interface_count里面有增加了一层“hours”的聚合,展示了“key”(即接口名)按照每个小时的分布计数结果
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 2,
"successful" : 2,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10000,
"relation" : "gte"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"interface_count" : {
"doc_count_error_upper_bound" : 373,
"sum_other_doc_count" : 30492,
"buckets" : [
{
"key" : "/index.php?m=message&f=ajaxGetMessage&t=html&windowBlur=1",
"doc_count" : 39032,
"hours" : {
"buckets" : [
{
"key_as_string" : "2022-05-23T09:00:00.000Z",
"key" : 1653296400000,
"doc_count" : 38672
},
{
"key_as_string" : "2022-05-23T10:00:00.000Z",
"key" : 1653300000000,
"doc_count" : 22
},
{
"key_as_string" : "2022-05-23T11:00:00.000Z",
"key" : 1653303600000,
"doc_count" : 11
},
......
2.利用kibana进行日志查询与分析
2.1 基础过滤查询
对于在上面通过grok匹配存储在Elasticsearch中的字段都是可以使用Kibana的 Discover菜单的中 “Add a filter” 进行查询。
“字段名” 和 “字段名.keyword” 两种过滤方式
在查询里,有“字段名” 和 “字段名.keyword” 两种过滤方式。两种过滤方式,这两者的区别是:
- 使用“字段名”可以进行分词查询,比如:
- 而interface.keyword意思是使用interface整体进行查询不支持分词,使用时Kibana时也会弹出下拉列表。
单字段多词查询
当想要查询一个字段的多个值可以使用 “is one of” 或者 “is not one of” ,用来表示要查询的分词在其中或者不在其中:
多过滤条件查询
可以进行多个字段查询,它们之间的关系是 and 关系,例如查询的是“url包含index.php关键字的并且response_code是200的”
2.2 在Kibana中使用kuery-query和Lucene进行高阶查询
Kibana使用的查询语法既包括Lucene的查询语法,也包括其kibana自身的查询语言增强kuery-query,这样在应用在相对复杂查询时,在kibana查询框内的自定义内容查询。
下面了解下简单的Lucene查询语法,通过几个不同的示例,帮助我们在日常工作中更好的使用Kibana的进行日志和数据查询。
参考文档:
www.elastic.co/guide/en/elasticsearch/reference/7.16/query-dsl-query-string-query.html#query-string-syntax
www.elastic.co/guide/en/kibana/7.16/lucene-query.html
www.elastic.co/guide/en/kibana/7.16/kuery-query.html
全文搜索:
直接在搜索框输入想查询的内容:
${content} 或者 “${content}”
引号在这里起到的作用是对搜索内容的限制,如果不写引号,那么搜索内容将按照分词处理,不区分内容顺序,比如你可能得到"quick fox brown"这样的结果
字段搜索:
field:value 或者field:“value”
通配符:
? 匹配单个字符,如app?d
* 匹配0到多个字符,如searc*h
注意通配符都不可用作表示第一个字符,如*test,?test
正则搜索:
支持简单的正则搜索,但效率很低,不推荐使用,使用时用"/"引用
[name:/joh?n(ath[oa]n)/](http://name/joh?n(ath[oa]n)/)
模糊搜索:
quikc~ brwn~ foks~
~:在一个单词后面加上~启用模糊搜索,可以搜到一些拼写错误的单词
first~ 这种也能匹配到 frist
还可以设置编辑距离(整数),指定需要多少相似度
cromm~1 会匹配到 from 和 chrome
默认2,越大越接近搜索的原始值,设置为1基本能搜到80%拼写错误的单词
近似搜索:
在短语后加上~,可以搜到被隔开或顺序不同的单词
“fox quick”~5,表示fox和quick中间可以隔5个单词,可以搜索到"quick brown fox"
范围搜索:
All days in 2012:
date:[2012-01-01 TO 2012-12-31]
Numbers 1…5
count:[1 TO 5]
Tags between alpha and omega, excluding alpha and omega:
tag:{alpha TO omega}
Numbers from 10 upwards
count:[10 TO *]
Dates before 2012
date:{* TO 2012-01-01}
1~5,但不包括5
[1,5}
可以简化成以下写法:
age:>10
age:<=10
age:(>=10 AND <20)
age:(+>=10 +<20)
优先级:
使用^表示,使一个词语比另一个搜索优先级更高,默认为1,可以为0~1之间的浮点数,来降低优先级
quick^2 fox
逻辑操作:
AND OR + -
+:搜索结果中必须包含此项
-:不能含有此项
+appid -s-ppid aaa bbb ccc:结果中必须存在appid,不能有s-ppid,剩余部分尽量都匹配到
逻辑操作符kibana6也支持写为 && ,|| ,!,但不推荐使用
逻辑组合示例:((quick AND fox) OR (brown AND fox) OR fox) AND NOT news
转义特殊字符:
+ - = && || > < ! ( ) { } [ ] ^ " ~ * ? : \ /
以上字符当作值搜索的时候需要用\转义,其中< 和 > 根本无法规避,如果包含这两个字符只能另寻他法
(1+1)=2用来查询(1+1)=2
2.3数据统计
比如想要知道某个接口最近1小时都有哪些用户和他们的ip都来自哪些城市。这里就用到了kibana Visualize,点击Visualize + 按钮,新增一个视图。
如果想要统计一些字段并有可能需要在别的地方使用这些字段,应该使用 Data Table数据表视图,它可以下载成csv格式的文件
在这个基础之上我们在增加一个rows
在此基础上,添加一列method.keyword 请求方式。
可以给每个metric和rows起别名,然后下载成csv文件
打开的csv文件如下: