ElasticSearch8.x操作记录
文档内容来自于尚硅谷海波老师的ElasticSearch教程课，在Kibana中的一些操作演示
以下为在文档中的相关操作记录
1.索引操作
#创建索引
#PUT 索引名称
PUT test_index
#PUT 索引
#增加配置：JSON格式的主题内容
PUT test_index_1
{
"aliases": {
"test1": {}
}
}
#删除索引
#delete 索引名称
DELETE test_index_1
#修改索引配置
#ES不允许修改索引信息
POST test_index_1
{
"aliases": {
"test1": {}
}
}
#HEAD索引 （判读索引是否存在）HTTP状态码 200， 404
HEAD test_index
#查询索引
GET test_index
GET test_index_1
GET test1
#查询所有索引
GET _cat/indices
#创建文档（索引数据）--增加唯一性标识(手动：PUT，后面需要自己添加/自动；POST自动生成，不需要再后面添加)
#首先需要先创建索引
PUT index_doc
PUT index_doc/_doc/1001
{
"id": 1001,
"name": "zhangsan",
"age": 30
}
POST index_doc/_doc
{
"id": 1002,
"name": "lisi",
"age": 14
}
2.文档操作
#查询文档
GET index_doc/_doc/1001
#查询当前索引中所有的文档数据
GET index_doc/_search
#修改文档数据
PUT index_doc/_doc/1001
{
"id": 100111,
"name": "zhangsan",
"age": 30,
"tel": "15123392594"
}
#POST修改数据
POST index_doc/_doc/okBdhIQB7PHEeADHmDqa
{
"id": 1003,
"name": "wangwu",
"age": 22
}
#删除数据
DELETE index_doc/_doc/okBdhIQB7PHEeADHmDqa
#以下操作是不被允许的
DELETE index_doc/_doc
3.文档搜索
#增加索引
PUT test_query
DELETE test_query
#添加数据
PUT test_query/_bulk
{"index":{"_index": "test_query", "_id":"1001"}}
{"id":"1001", "name": "zhang san", "age": 30}
{"index":{"_index": "test_query", "_id":"1002"}}
{"id":"1002", "name": "li si", "age": 40}
{"index":{"_index": "test_query", "_id":"1003"}}
{"id":"1003", "name": "wang wu", "age": 50}
{"index":{"_index": "test_query", "_id":"1004"}}
{"id":"1004", "name": "zhangsan", "age": 30}
{"index":{"_index": "test_query", "_id":"1005"}}
{"id":"1005", "name": "lisi", "age": 40}
{"index":{"_index": "test_query", "_id":"1006"}}
{"id":"1006", "name": "wangwu", "age": 50}
#Match是分词查询，ES会将数据分词（关键词）保存
#zhang san
GET test_query/_search
{
"query": {
"match": {
"name": "zhang san"
}
}
}
GET test_query/_search
{
"query": {
"term": {
"name": {
"value": "zhang san"
}
}
}
}
#对查询结果字段进行限制
GET test_query/_search
{
"_source": ["name", "age"],
"query": {
"match": {
"name": "zhang san"
}
}
}
#组合多个条件 or
GET test_query/_search
{
"query": {
"bool": {
"should": [
{
"match": {
"name": "zhang"
}
},
{
"match": {
"age": "40"
}
}
]
}
}
}
# 排序后查询
GET test_query/_search
{
"query": {
"match": {
"name": "zhang li"
}
},
"sort": [
{
"age": {
"order": "desc"
}
}
]
}
#分页查询
GET test_query/_search
{
"query": {
"match_all": {}
},
"from": 4,
"size": 2
}
4.聚合搜索
# 分组查询
GET test_query/_search
{
"aggs": {
"ageGroup": {
"terms": {
"field": "age"
}
}
},
"size": 0
}
# 分组后聚合（求和）
GET test_query/_search
{
"aggs": {
"ageGroup": {
"terms": {
"field": "age"
},
"aggs": {
"ageSum": {
"sum": {
"field": "age"
}
}
}
}
},
"size": 0
}
# 求年龄平均值
GET test_query/_search
{
"aggs": {
"avgAge": {
"avg": {
"field": "age"
}
}
},
"size": 0
}
# 获取前几名操作
GET test_query/_search
{
"aggs": {
"top3": {
"top_hits": {
"sort": [
{
"age": {
"order": "desc"
}
}
],
"size": 3
}
}
},
"size": 0
}
5.索引模板
PUT test_temp
GET test_temp
PUT test_temp_1
{
"settings": {
"number_of_shards": 2
}
}
GET test_temp_1
#创建模板
PUT _template/mytemplate
{
"index_patterns": [
"my*"
],
"settings": {
"index": {
"number_of_shards" : "2"
}
},
"mappings": {
"properties": {
"now": {
"type": "date",
"format": "yyyy/MM/dd"
}
}
}
}
#查看模板
GET _template/mytemplate
PUT test_temp_2
GET test_temp_2
# 匹配模板规则，以my开头
PUT my_test_temp
GET my_test_temp
#删除模板
DELETE _template/mytemplate
6.中文分词
#分词操作
GET _analyze
{
"analyzer": "standard",
"text": ["zhang san"]
}
# 分词操作(不带插件情况下，中文拆分逻辑太适合)
GET _analyze
{
"analyzer": "chinese",
"text": ["我是一个三好学生"]
}
# 集成了IK插件后提供的分词
GET _analyze
{
"analyzer": "ik_smart",
"text": ["我是一个三好学生"]
}
# 集成了IK插件后提供的分词，相较于上者，分得更加精细
GET _analyze
{
"analyzer": "ik_max_word",
"text": ["我是一个三好学生"]
}
7.文档评分机制
PUT test_score
PUT test_score/_doc/1001
{
"text": "zhang kai shou bi, yin jie tai yang"
}
PUT test_score/_doc/1002
{
"text": "zhang san"
}
GET test_score/_search?explain=true
{
"query": {
"match": {
"text": "zhang"
}
}
}
# 公式如下
boost * idf * tf = 2.2 * 0.18232156 * 0.6024096
PUT itwluo
PUT itwluo/_doc/1001
{
"text": "java"
}
GET itwluo/_search
{
"query": {
"match": {
"text": "java"
}
}
}
#result
{
"took": 992,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.2876821,
"hits": [
{
"_index": "itwluo",
"_id": "1001",
"_score": 0.2876821,
"_source": {
"text": "java"
}
}
]
}
}
#详细结果
{
"took": 3,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.2876821,
"hits": [
{
"_shard": "[itwluo][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "itwluo",
"_id": "1001",
"_score": 0.2876821,
"_source": {
"text": "java"
},
"_explanation": {
"value": 0.2876821,
"description": "weight(text:java in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.2876821,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 0.2876821,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 1,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 1,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.45454544,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 1,
"description": "dl, length of field",
"details": []
},
{
"value": 1,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
}
]
}
}
#新增数据后，观察分值变化
PUT itwluo/_doc/1002
{
"text": "java bigdata"
}
#查询文档数据
GET itwluo/_search?explain=true
{
"query": {
"match": {
"text": "java"
}
}
}
#详细结果
{
"took": 609,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 0.21110919,
"hits": [
{
"_shard": "[itwluo][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "itwluo",
"_id": "1001",
"_score": 0.21110919,
"_source": {
"text": "java"
},
"_explanation": {
"value": 0.21110919,
"description": "weight(text:java in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.21110919,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 0.18232156,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 2,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 2,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.5263158,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 1,
"description": "dl, length of field",
"details": []
},
{
"value": 1.5,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
},
{
"_shard": "[itwluo][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "itwluo",
"_id": "1002",
"_score": 0.160443,
"_source": {
"text": "java bigdata"
},
"_explanation": {
"value": 0.160443,
"description": "weight(text:java in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.160443,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 0.18232156,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 2,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 2,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.40000004,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 2,
"description": "dl, length of field",
"details": []
},
{
"value": 1.5,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
}
]
}
}
# 在上述数据基础上继续添加数据，分析结果
PUT itwluo/_doc/1003
{
"text": "bigdata",
"content": "java bigdata"
}
# 详细计算结果
{
"took": 599,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 0.52354836,
"hits": [
{
"_shard": "[itwluo][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "itwluo",
"_id": "1001",
"_score": 0.52354836,
"_source": {
"text": "java"
},
"_explanation": {
"value": 0.52354836,
"description": "weight(text:java in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.52354836,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 0.47000363,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 2,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 3,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.50632906,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 1,
"description": "dl, length of field",
"details": []
},
{
"value": 1.3333334,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
},
{
"_shard": "[itwluo][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "itwluo",
"_id": "1002",
"_score": 0.39019167,
"_source": {
"text": "java bigdata"
},
"_explanation": {
"value": 0.39019167,
"description": "weight(text:java in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.39019167,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 0.47000363,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 2,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 3,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.37735844,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 2,
"description": "dl, length of field",
"details": []
},
{
"value": 1.3333334,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
}
]
}
# 通过提高权重，从而提高分数，使排名靠前
DELETE test_score
PUT test_score
PUT /test_score/_doc/1001
{
"title": "Hadoop is a FrameWork",
"content": "Hadoop 是一个大数据基础框架"
}
PUT /test_score/_doc/1002
{
"title": "Hive is a SQL Tools",
"content": "Hive是一个SQL工具"
}
PUT /test_score/_doc/1003
{
"title": "Spark is a FrameWork",
"content": "Spark 是一个分布式计算引擎"
}
GET test_score/_search?explain=true
{
"query": {
"bool": {
"should": [
{
"match": {
"title": {
"query": "Hadoop", "boost": 1
}
}
},
{
"match": {
"title": {
"query": "Hive", "boost": 2
}
}
},
{
"match": {
"title": {
"query": "Spark", "boost": 1
}
}
}
]
}
}
}
# 详细结果分析
{
"took": 4,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 3,
"relation": "eq"
},
"max_score": 2.2458146,
"hits": [
{
"_shard": "[test_score][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "test_score",
"_id": "1002",
"_score": 2.2458146,
"_source": {
"title": "Hive is a SQL Tools",
"content": "Hive是一个SQL工具"
},
"_explanation": {
"value": 2.2458146,
"description": "sum of:",
"details": [
{
"value": 2.2458146,
"description": "weight(title:hive in 0) [PerFieldSimilarity], result of:",
"details": [
{
"value": 2.2458146,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 4.4,
"description": "boost",
"details": []
},
{
"value": 1.2039728,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 1,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 4,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.42394012,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 5,
"description": "dl, length of field",
"details": []
},
{
"value": 4.25,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
]
}
},
{
"_shard": "[test_score][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "test_score",
"_id": "1003",
"_score": 1.2336599,
"_source": {
"title": "Spark is a FrameWork",
"content": "Spark 是一个分布式计算引擎"
},
"_explanation": {
"value": 1.2336599,
"description": "sum of:",
"details": [
{
"value": 1.2336599,
"description": "weight(title:spark in 2) [PerFieldSimilarity], result of:",
"details": [
{
"value": 1.2336599,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 1.2039728,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 1,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 4,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.46575344,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 4,
"description": "dl, length of field",
"details": []
},
{
"value": 4.25,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
]
}
},
{
"_shard": "[test_score][0]",
"_node": "EX7ZCQpSRLu-OWEZjQazog",
"_index": "test_score",
"_id": "1001",
"_score": 0.7102385,
"_source": {
"title": "Hadoop is a FrameWork",
"content": "Hadoop 是一个大数据基础框架"
},
"_explanation": {
"value": 0.7102385,
"description": "sum of:",
"details": [
{
"value": 0.7102385,
"description": "weight(title:hadoop in 1) [PerFieldSimilarity], result of:",
"details": [
{
"value": 0.7102385,
"description": "score(freq=1.0), computed as boost * idf * tf from:",
"details": [
{
"value": 2.2,
"description": "boost",
"details": []
},
{
"value": 0.6931472,
"description": "idf, computed as log(1 + (N - n + 0.5) / (n + 0.5)) from:",
"details": [
{
"value": 2,
"description": "n, number of documents containing term",
"details": []
},
{
"value": 4,
"description": "N, total number of documents with field",
"details": []
}
]
},
{
"value": 0.46575344,
"description": "tf, computed as freq / (freq + k1 * (1 - b + b * dl / avgdl)) from:",
"details": [
{
"value": 1,
"description": "freq, occurrences of term within document",
"details": []
},
{
"value": 1.2,
"description": "k1, term saturation parameter",
"details": []
},
{
"value": 0.75,
"description": "b, length normalization parameter",
"details": []
},
{
"value": 4,
"description": "dl, length of field",
"details": []
},
{
"value": 4.25,
"description": "avgdl, average length of field",
"details": []
}
]
}
]
}
]
}
]
}
}
]
}
}
# 当boost指定为2时， 权重值翻倍
: 1,
“description”: “freq, occurrences of term within document”,
“details”: []
},
{
“value”: 1.2,
“description”: “k1, term saturation parameter”,
“details”: []
},
{
“value”: 0.75,
“description”: “b, length normalization parameter”,
“details”: []
},
{
“value”: 4,
“description”: “dl, length of field”,
“details”: []
},
{
“value”: 4.25,
“description”: “avgdl, average length of field”,
“details”: []
}
]
}
]
}
]
}
]
}
}
]
}
}文章来源：https://www.toymoban.com/news/detail-436256.html
当boost指定为2时， 权重值翻倍
文章来源地址https://www.toymoban.com/news/detail-436256.html
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