个人中心
文章发布
退出
作者热门文章
- html - 出于某种原因，IE8 对我的 Sass 文件中继承的 html5 CSS 不友好？
- JMeter 在响应断言中使用 span 标签的问题
- html - 在 :hover and :active? 上具有不同效果的 CSS 动画
- html - 相对于居中的 html 内容固定的 CSS 重复背景？
25
4
我是Elastic Search的新手，在实现某些查询时遇到一些问题。以下是我的索引结构
{
"cl_1" : {
"aliases" : { },
"mappings" : {
"properties" : {
"@timestamp" : {
"type" : "date"
},
"@version" : {
"type" : "long"
},
"class" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"file" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"level" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"line_number" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"logger_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"mdc" : {
"type" : "object"
},
"message" : {
"properties" : {
"connectionStats" : {
"properties" : {
"activeConnections" : {
"type" : "long"
},
"idleConnections" : {
"type" : "long"
},
"maxConnections" : {
"type" : "long"
},
"minConnections" : {
"type" : "long"
},
"pendingConnections" : {
"type" : "long"
},
"totalConnections" : {
"type" : "long"
}
}
},
"dbhistogram" : {
"type" : "nested",
"properties" : {
"histogramName" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"snapshot" : {
"properties" : {
"max" : {
"type" : "float"
},
"mean" : {
"type" : "float"
},
"median" : {
"type" : "float"
},
"min" : {
"type" : "float"
},
"percentile75" : {
"type" : "float"
},
"percentile95" : {
"type" : "float"
},
"percentile98" : {
"type" : "float"
},
"percentile99" : {
"type" : "float"
},
"percentile99_9" : {
"type" : "float"
},
"sd" : {
"type" : "float"
}
}
},
"totalCount" : {
"type" : "long"
}
}
},
"healthy" : {
"type" : "boolean"
},
"meters" : {
"properties" : {
"meterName" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"meterRate" : {
"properties" : {
"fifteenMinRate" : {
"type" : "float"
},
"fiveMinRate" : {
"type" : "float"
},
"meanRate" : {
"type" : "float"
},
"oneMinRate" : {
"type" : "float"
}
}
},
"totalCount" : {
"type" : "long"
}
}
},
"timers" : {
"properties" : {
"meterRate" : {
"properties" : {
"fifteenMinRate" : {
"type" : "float"
},
"fiveMinRate" : {
"type" : "float"
},
"meanRate" : {
"type" : "float"
},
"oneMinRate" : {
"type" : "float"
}
}
},
"snapshot" : {
"properties" : {
"max" : {
"type" : "float"
},
"mean" : {
"type" : "float"
},
"median" : {
"type" : "float"
},
"min" : {
"type" : "float"
},
"percentile75" : {
"type" : "float"
},
"percentile95" : {
"type" : "float"
},
"percentile98" : {
"type" : "float"
},
"percentile99" : {
"type" : "float"
},
"percentile99_9" : {
"type" : "float"
},
"sd" : {
"type" : "float"
}
}
},
"timerName" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"totalCount" : {
"type" : "long"
}
}
}
}
},
"method" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"source_host" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
},
"thread_name" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
}
},
"settings" : {
"index" : {
"creation_date" : "1590152167021",
"number_of_shards" : "1",
"number_of_replicas" : "1",
"uuid" : "Aa-KrQinQyiY_racF-Kuxg",
"version" : {
"created" : "7070099"
},
"provided_name" : "cl_1"
}
}
}
}
{
"_index" : "cl_1",
"_type" : "_doc",
"_id" : "1545",
"_version" : 1,
"_seq_no" : 1544,
"_primary_term" : 1,
"found" : true,
"_source" : {
"@timestamp" : "2020-05-19T05:18:53.318Z",
"source_host" : "127.0.0.1",
"file" : "DBConnectionMetricsTask.java",
"method" : "run",
"level" : "INFO",
"line_number" : "135",
"thread_name" : "Timer-1",
"@version" : 1,
"logger_name" : "DBConnectionMetricsTask",
"message" : {
"counters" : [ ],
"connectionStats" : [
{
"pendingConnections" : 0,
"activeConnections" : 0,
"idleConnections" : 3,
"maxConnections" : 1000,
"minConnections" : 2,
"totalConnections" : 3
}
],
"timers" : [
{
"timerName" : "controller.pool.Wait",
"totalCount" : 254246,
"meterRate" : {
"fiveMinRate" : 2.475461869555687,
"fifteenMinRate" : 2.3810523391920393,
"oneMinRate" : 2.472677418621866,
"meanRate" : 5.486619709297191
},
"snapshot" : {
"percentile75" : 2344164.0,
"percentile95" : 3486516.0,
"percentile98" : 7008980.0,
"percentile99" : 1.0038282E7,
"percentile99_9" : 4.8125997E7,
"min" : 538.0,
"max" : 4.8125997E7,
"mean" : 2156193.438475141,
"median" : 2023267.0,
"sd" : 3169808.0894894
}
}
],
"meters" : [
{
"totalCount" : 0,
"meterName" : "controller.pool.ConnectionTimeoutRate",
"meterRate" : {
"fiveMinRate" : 0.0,
"fifteenMinRate" : 0.0,
"oneMinRate" : 0.0,
"meanRate" : 0.0
}
}
],
"dbhistogram" : [
{
"histogramName" : "controller.pool.ConnectionCreation",
"totalCount" : 167,
"snapshot" : {
"percentile75" : 102.0,
"percentile95" : 102.0,
"percentile98" : 102.0,
"percentile99" : 102.0,
"percentile99_9" : 131.0,
"min" : 62.0,
"max" : 1234.0,
"mean" : 100.04099508328834,
"median" : 98.0,
"sd" : 2.633890647922372
}
},
{
"histogramName" : "controller.pool.Usage",
"totalCount" : 254246,
"snapshot" : {
"percentile75" : 1.0,
"percentile95" : 9.0,
"percentile98" : 36.0,
"percentile99" : 89.0,
"percentile99_9" : 178.0,
"min" : 0.0,
"max" : 772.0,
"mean" : 3.5603336398866645,
"median" : 1.0,
"sd" : 15.699410900677693
}
}
],
"healthy" : true
},
"class" : "DBConnectionMetricsTask",
"mdc" : { }
}
}
message.dbhistogram中查询数据
histogramName : controller.pool.ConnectionCreation。由于
dbhistogram是Json对象的数组，我的目的是仅从数组中检索该对象，该对象会通过过滤器。
GET cl_1/_search
{
"_source": "message.dbhistogram.*",
"query": {
"nested": {
"path": "message.dbhistogram",
"query": {
"bool": {
"must": [
{
"term": {
"message.dbhistogram.histogramName.keyword": {
"value": "controller.pool.ConnectionCreation"
}
}
}
]
, "must_not": [
{
"term": {
"message.dbhistogram.histogramName.keyword": {
"value": "controller.pool.Usage"
}
}
}
]
}
}
}
}
}
GET cl_1/_search
{
"_source": "message.dbhistogram.*",
"query": {
"nested": {
"path": "message.dbhistogram",
"query": {
"bool": {
"must": [
{
"match": {
"message.dbhistogram.histogramName": "controller.pool.ConnectionCreation"
}
}
]
,
"must_not": [
{
"match": {
"message.dbhistogram.histogramName.keyword": "controller.pool.Usage"
}
}
]
}
}
}
}
}
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1545,
"relation": "eq"
},
"max_score": 0.6931471,
"hits": [
{
"_index": "cl_1",
"_type": "_doc",
"_id": "57",
"_score": 0.6931471,
"_source": {
"message": {
"dbhistogram": [
{
"totalCount": 10,
"histogramName": "controller.pool.ConnectionCreation",
"snapshot": {
"sd": 35.86065,
"percentile98": 270,
"percentile99": 270,
"min": 139,
"percentile99_9": 270,
"median": 270,
"percentile75": 270,
"max": 597,
"mean": 258.89444,
"percentile95": 270
}
}
]
}
}
}
]
}
}
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1545,
"relation" : "eq"
},
"max_score" : 0.6931471,
"hits" : [
{
"_index" : "cl_1",
"_type" : "_doc",
"_id" : "57",
"_score" : 0.6931471,
"_source" : {
"message" : {
"dbhistogram" : [
{
"totalCount" : 10,
"histogramName" : "controller.pool.ConnectionCreation",
"snapshot" : {
"sd" : 35.86065030723722,
"percentile98" : 270.0,
"percentile99" : 270.0,
"min" : 139.0,
"percentile99_9" : 270.0,
"median" : 270.0,
"percentile75" : 270.0,
"max" : 597.0,
"mean" : 258.89444519213833,
"percentile95" : 270.0
}
},
{
"totalCount" : 564,
"histogramName" : "controller.pool.Usage",
"snapshot" : {
"sd" : 51.226141120564726,
"percentile98" : 206.0,
"percentile99" : 236.0,
"min" : 0.0,
"percentile99_9" : 361.0,
"median" : 12.0,
"percentile75" : 22.0,
"max" : 56021.0,
"mean" : 23.500496339350214,
"percentile95" : 105.0
}
}
]
}
}
}
]
}
}
最佳答案
@jaspreet是正确的-尽管nested子文档被视为单独的文档，但_source仍将检索给定路径下的所有内容。
因此，请使用 inner_hits 并注意我们也在_source中提及了它们:
GET cl_1/_search
{
"_source": "inner_hits.message.dbhistogram.*",
"query": {
"nested": {
"inner_hits": {},
"path": "message.dbhistogram",
"query": {
"bool": {
"must": [
{
"match": {
"message.dbhistogram.histogramName": "controller.pool.ConnectionCreation"
}
}
],
"must_not": [
{
"match": {
"message.dbhistogram.histogramName.keyword": "controller.pool.Usage"
}
}
]
}
}
}
}
}
named inner_hits，以防您在不同的位置多次使用
inner_hits:
GET cl_1/_search
{
"_source": "inner_hits__message_dbhistogram.message.dbhistogram.*",
"query": {
"nested": {
"inner_hits": {
"name": "inner_hits__message_dbhistogram"
},
"path": "message.dbhistogram",
"query": {
"bool": {
"must": [
{
"match": {
"message.dbhistogram.histogramName": "controller.pool.ConnectionCreation"
}
}
],
"must_not": [
{
"match": {
"message.dbhistogram.histogramName.keyword": "controller.pool.Usage"
}
}
]
}
}
}
}
}
关于elasticsearch - ElasticSearch:嵌套查询未返回期望的结果，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/61960319/
25
4
0
我有三张 table 。表 A 有选项名称(即颜色、尺寸)。表 B 有选项值名称(即蓝色、红色、黑色等)。表C通过将选项名称id和选项名称值id放在一起来建立关系。 我的查询需要显示值和选项的名称，而
在mysql中，如何计算一行中的非空单元格？我只想计算某些列之间的单元格，比如第 3-10 列之间的单元格。不是所有的列...同样，仅在该行中。 最佳答案 如果你想这样做，只能在 sql 中使用名称而
关闭。这个问题需要多问focused 。目前不接受答案。 想要改进此问题吗？更新问题，使其仅关注一个问题 editing this post . 已关闭 7 年前。 Improve this ques
我正在为版本7.6进行Elasticsearch查询 我的查询是这样的: { "query": { "bool": { "should": [ {
关闭。这个问题需要多问focused 。目前不接受答案。 想要改进此问题吗？更新问题，使其仅关注一个问题 editing this post . 已关闭 7 年前。 Improve this ques
是否可以编写一个查询来检查任一子查询(而不是一个子查询)是否正确？ SELECT * FROM employees e WHERE NOT EXISTS (
我找到了很多关于我的问题的答案，但问题没有解决 我有表格，有数据，例如: Data 1 Data 2 Data 3
以下查询返回错误: 查询: SELECT Id, FirstName, LastName, OwnerId, PersonEmail FROM Account WHERE lower(PersonEm
以下查询返回错误: 查询: SELECT Id, FirstName, LastName, OwnerId, PersonEmail FROM Account WHERE lower(PersonEm
我从 EditText 中获取了 String 值。以及提交查询的按钮。 String sql=editQuery.getText().toString();// SELECT * FROM empl
我有一个或多或少有效的查询(关于结果)，但处理大约需要 45 秒。这对于在 GUI 中呈现数据来说肯定太长了。 所以我的需求是找到一个更快/更高效的查询(几毫秒左右会很好)我的数据表大约有 3000
这是我第一次使用 Stack Overflow，所以我希望我以正确的方式提出这个问题。 我有 2 个 SQL 查询，我正在尝试比较和识别缺失值，尽管我无法将 NULL 字段添加到第二个查询中以识别缺失
什么是动态 SQL 查询？何时需要使用动态 SQL 查询？我使用的是 SQL Server 2005。 最佳答案 这里有几篇文章: Introduction to Dynamic SQL Dynami
include "mysql.php"; $query= "SELECT ID,name,displayname,established,summary,searchlink,im
我有一个查询要“转换”为 mysql。这是查询: select top 5 * from (select id, firstName, lastName, sum(fileSize) as To
通过我的研究，我发现至少从 EF 4.1 开始，EF 查询上的 .ToString() 方法将返回要运行的 SQL。事实上，这对我来说非常有用，使用 Entity Framework 5 和 6。 但
我在构造查询来执行以下操作时遇到问题: 按activity_type_id过滤联系人，仅显示最近事件具有所需activity_type_id或为NULL(无事件)的联系人 表格结构如下: 一个联系人可
如何让我输入数据库的信息在输入数据 5 分钟后自行更新？ 假设我有一张 table : +--+--+-----+ |id|ip|count| +--+--+-----+ |
我正在尝试搜索正好是 4 位数字的 ID，我知道我需要使用 LENGTH() 字符串函数，但找不到如何使用它的示例。我正在尝试以下(和其他变体)但它们不起作用。 SELECT max(car_id)
我有一个在 mysql 上运行良好的 sql 查询(查询 + 连接): select sum(pa.price) from user u , purchase pu , pack pa where (
我是一名优秀的程序员,十分优秀！