不指定 ID，即自动生成ID，ID 是一行数据的唯一键。 语法：POST /index/_doc # 创建索引
PUT testid
# 默认情况下自动生成ID
POST / testid/ _doc
{
"test_field" : "test"
}
# 返回
{
"_index" : "testid" ,
"_type" : "_doc" ,
"_id" : "pyxXs5MBW--orQEFRZhH" ,
"_version" : 1 ,
"result" : "created" ,
"_shards" : {
"total" : 2 ,
"successful" : 1 ,
"failed" : 0
} ,
"_seq_no" : 0 ,
"_primary_term" : 1
}
场景：如果导入 ES 的数据想使用外部定义的 ID，需要在添加文档数据的时候指定 ID。 语法：POST /index/_doc/id # 指定ID
POST / testid/ _doc/ 1
{
"test_field" : "testid"
}
# 返回 1 是指定的ID
{
"_index" : "testid" ,
"_type" : "_doc" ,
"_id" : "1" ,
"_version" : 1 ,
"result" : "created" ,
"_shards" : {
"total" : 2 ,
"successful" : 1 ,
"failed" : 0
} ,
"_seq_no" : 1 ,
"_primary_term" : 1
}
# 创建索引
PUT teacher
POST / teacher/ _doc/ 001
{
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
POST / teacher/ _doc/ 002
{
"name" : "lisi" ,
"nickname" : "lisi" ,
"sex" : "男" ,
"age" : 20
}
POST / teacher/ _doc/ 003
{
"name" : "wangwu1" ,
"nickname" : "wangwu2" ,
"sex" : "女" ,
"age" : 40
}
POST / teacher/ _doc/ 004
{
"name" : "zhaoliu1" ,
"nickname" : "zhaoliu2" ,
"sex" : "女" ,
"age" : 50
}
POST / teacher/ _doc/ 005
{
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
POST / teacher/ _doc/ 006
{
"name" : "zhangsan222" ,
"nickname" : "zhangsan222" ,
"sex" : "女" ,
"age" : 30
}
ES中提供了一种强大的检索数据方式，这种检索方式称之为Query DSL,Query DSL是利用Rest API传递JSON格式的请求体与ES进行交互，这种方式的丰富查询语法让ES检索变得更强大，更简洁。 使用_search 表示查询 # 请求
Get / teacher/ _search
{
"query" : {
"match_all" : { }
}
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "002" ,
"_score" : 1.0 ,
"_source" : {
"name" : "lisi" ,
"nickname" : "lisi" ,
"sex" : "男" ,
"age" : 20
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "003" ,
"_score" : 1.0 ,
"_source" : {
"name" : "wangwu1" ,
"nickname" : "wangwu2" ,
"sex" : "女" ,
"age" : 40
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "004" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhaoliu1" ,
"nickname" : "zhaoliu2" ,
"sex" : "女" ,
"age" : 50
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "005" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "006" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan222" ,
"nickname" : "zhangsan222" ,
"sex" : "女" ,
"age" : 30
}
}
]
}
}
返回的结果说明：
took：这个字段表示查询执行所花费的毫秒数。在这个例子中，查询执行花费了0毫秒。timed_out：这个字段表示查询是否超时。false表示查询没有超时。_shards：这个字段包含了关于分片的信息。
total：查询被分发到的分片总数。successful：成功处理的分片数。skipped：被跳过的分片数。failed：处理失败的分片数。hits：这个字段包含了查询结果的相关信息。
total：匹配的文档总数。value表示总数，relation表示总数的类型，这里是eq，表示精确匹配。max_score：所有匹配文档中最高的相关性得分，这里是1.0。hits：实际匹配的文档列表，每个文档包含以下信息：
_index：文档所在的索引名称。_type：文档的类型（在Elasticsearch 7.x之后，类型被标记为废弃）。_id：文档的唯一标识符。_score：文档的相关性得分。_source：文档的原始数据，包含了文档的所有字段和值。在hits数组中，每个元素都是一个文档，包含了文档的元数据（如索引名、类型、ID、得分）和文档的内容（在_source字段中）。这个例子中返回了6个文档，每个文档都有name、nickname、sex和age字段。 match查询用于在单个字段上执行全文检索。它会使用指定字段的分词器（analyzer）来处理查询文本，然后搜索与这些词元匹配的文档。只有 text 类型的字段才会进行分词查询。 # 请求
GET / teacher/ _search
{
"query" : {
"match" : {
"name" : "zhangsan"
}
}
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
}
]
}
}
term查询用于精确匹配，不进行分词处理，适用于关键字（keyword）、数字、日期等精确值字段。# 请求
GET / teacher/ _search
{
"query" : {
"term" : {
"name" : {
"value" : "zhangsan"
}
}
}
}
# 返回
{
"took" : 1 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
}
]
}
}
# 请求
GET / teacher/ _search
{
"query" : {
"range" : {
"age" : {
"gte" : 30 ,
"lte" : 30
}
}
}
}
# 返回
{
"took" : 1 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 3 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "005" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "006" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan222" ,
"nickname" : "zhangsan222" ,
"sex" : "女" ,
"age" : 30
}
}
]
}
}
# 请求
GET / teacher/ _search
{
"query" : {
"prefix" : {
"name" : {
"value" : "zhangsan"
}
}
}
}
# 返回
{
"took" : 7 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 3 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "005" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "006" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan222" ,
"nickname" : "zhangsan222" ,
"sex" : "女" ,
"age" : 30
}
}
]
}
}
# 请求
GET / teacher/ _search
{
"query" : {
"wildcard" : {
"name" : {
"value" : "*san*"
}
}
}
}
# 返回
{
"took" : 6 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 3 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "005" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "006" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan222" ,
"nickname" : "zhangsan222" ,
"sex" : "女" ,
"age" : 30
}
}
]
}
}
# 请求
GET / teacher/ _search
{
"query" : {
"ids" : {
"values" : [ "001" , "003" , "005" ]
}
}
}
#返回
{
"took" : 1 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 3 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "003" ,
"_score" : 1.0 ,
"_source" : {
"name" : "wangwu1" ,
"nickname" : "wangwu2" ,
"sex" : "女" ,
"age" : 40
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "005" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
}
]
}
}
Elasticsearch中的fuzzy查询允许用户搜索包含与指定查询词相似的文档，即使它们不完全相同。这种查询特别适用于处理近似或不精确的搜索词，例如用户可能打错字或输入同一词的不同变体的情况。 以下是fuzzy查询的一些关键点：
编辑距离（Edit Distance） ：fuzzy查询使用Levenshtein编辑距离来衡量搜索词之间的相似度。编辑距离是指将一个词转换成另一个词所需的单字符更改次数，包括改变一个字符、删除一个字符、插入一个字符或交换两个相邻字符。创建变体（Creating Variations） ：fuzzy查询在指定的编辑距离内创建搜索词的所有可能变体，然后返回每个变体的精确匹配。参数配置 ：
fuzziness：允许的最大编辑距离，默认为AUTO。可以设置为AUTO或一个整数，表示允许的编辑次数。max_expansions：创建的变体的最大数量，默认为50。高值可能会导致性能问题，因为会检查大量的变体。prefix_length：在创建变体时保持不变的开始字符数，默认为0。transpositions：是否包括两个相邻字符的置换作为编辑，默认为true。rewrite：用于重写查询的方法，如果fuzziness参数不为0，默认使用top_terms_blended_freqs_${max_expansions}。性能考虑 ：由于fuzzy查询可能会生成大量的变体，特别是当max_expansions参数值较高且prefix_length参数值为0时，可能会影响查询性能。因此，合理配置这些参数对于保持Elasticsearch查询性能至关重要。使用场景 ：fuzzy查询是term查询的模糊等价物，通常不会直接使用，但理解其工作原理有助于在更高级的match查询中使用模糊匹配。不进行分析 ：与match查询不同，fuzzy查询是一个term级别的查询，不会对查询词进行分析，它直接在词典中查找与指定fuzziness范围内的所有项。 # 请求
GET / teacher/ _search
{
"query" : {
"fuzzy" : {
"name" : "zhangsan"
}
}
}
# 返回
{
"took" : 2 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 2 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "005" ,
"_score" : 1.3478894 ,
"_source" : {
"name" : "zhangsan2" ,
"nickname" : "zhangsan2" ,
"sex" : "女" ,
"age" : 30
}
}
]
}
}
must: 相当于&& 同时成立 should: 相当于|| 成立一个就行 must_not: 相当于! 不能满足任何一个
GET /teacher/_search
{
"query" : {
"bool" : {
"must" : [
{
"match" : {
"name" : "zhangsan"
}
}
] ,
"must_not" : [
{
"match" : {
"age" : "40"
}
}
] ,
"should" : [
{
"match" : {
"sex" : "男"
}
}
]
}
}
}
{
"took" : 3 ,
"timed_out" : false,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 2.5700645 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 2.5700645 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
}
]
}
}
multi_match查询允许你在多个字段上执行全文检索。与match查询类似，它也会进行分词，但是可以在多个字段上搜索给定的文本# 请求
GET / teacher/ _search
{
"query" : {
"multi_match" : {
"query" : "zhangsan" ,
"fields" : [ "name" , "nickname" ]
}
}
}
# 返回
{
"took" : 6 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
}
]
}
}
terms 查询和 term 查询一样，但它允许你指定多值进行匹配。类似 SQL 中的 in。 # 请求
GET / teacher/ _search
{
"query" : {
"terms" : {
"name" : [ "zhangsan" , "lisi" ]
}
}
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 2 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "002" ,
"_score" : 1.0 ,
"_source" : {
"name" : "lisi" ,
"nickname" : "lisi" ,
"sex" : "男" ,
"age" : 20
}
}
]
}
}
Elasticsearch中的query_string查询是一个强大的全文搜索查询，它允许用户使用一个查询字符串来构造复杂的查询。这个查询字符串可以包含多个字段、逻辑操作符（如AND, OR, NOT）以及通配符等。query_string查询非常灵活，可以模拟其他查询类型，如match、bool等。 以下是query_string查询的一些关键点：
查询语法：
支持布尔操作符：AND, OR, NOT。 支持通配符查询：*（匹配任意字符）。 支持短语搜索：使用双引号""包围短语。 支持前缀搜索：使用问号?表示单个字符，使用星号*表示任意长度的字符。 支持正则表达式：使用正斜杠/包围正则表达式。 字段选择：可以在查询中指定一个或多个字段进行搜索。 分析器：默认使用字段的搜索分析器（search analyzer），但也可以使用查询分析器（query analyzer）。 默认操作：默认的布尔操作是AND，意味着如果查询字符串中没有指定布尔操作符，那么查询会将所有条件视为AND连接。 字段名和值的转义：如果需要在查询中使用特殊字符，可以使用反斜杠\进行转义。 性能：由于query_string查询的复杂性，它可能比简单的match查询更消耗资源。因此，在性能敏感的应用中需要谨慎使用。 # 请求
GET / teacher/ _search
{
"query" : {
"query_string" : {
"query" : "name:zhansan OR sex:男"
}
}
}
# 返回
{
"took" : 9 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 2 ,
"relation" : "eq"
} ,
"max_score" : 1.0296195 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0296195 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "002" ,
"_score" : 1.0296195 ,
"_source" : {
"name" : "lisi" ,
"nickname" : "lisi" ,
"sex" : "男" ,
"age" : 20
}
}
]
}
}
分析器的使用：这个查询使用standard分析器来处理查询字符串。 # 请求
GET / teacher/ _search
{
"query" : {
"query_string" : {
"query" : "name:zhangsan" ,
"analyzer" : "standard"
}
}
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
}
]
}
}
Elasticsearch中的高亮（highlight）功能允许你在搜索结果中突出显示与查询条件匹配的文本片段，以便用户能够快速定位到关键信息。 以下是关于Elasticsearch高亮功能的详细介绍：
高亮参数：
Elasticsearch提供了多种高亮参数，包括字段设置、自定义标签、片段大小等。 默认情况下，Elasticsearch使用<em></em>标签来标记高亮的关键字。 自定义高亮片段：
用户可以自定义高亮标签，比如使用<b></b>标签来代替默认的<em></em>标签。 通过pre_tags和post_tags参数，用户可以指定高亮前后的标签。 多字段高亮：
高亮功能可以应用于一个或多个字段，只需在highlight字段中添加相应的字段名称。 高亮性能分析：
高亮功能需要字段的实际内容，如果字段未存储（映射未设置store为true），则需要从_source中加载实际值并从中提取相关字段。 高亮查询示例： # 请求
GET / teacher/ _search
{
"query" : {
"term" : {
"name" : {
"value" : "zhangsan"
}
}
} ,
"highlight" : {
"fields" : {
"*" : { }
}
}
}
# 返回
{
"took" : 33 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
} ,
"highlight" : {
"name" : [
"<em>zhangsan</em>"
]
}
}
]
}
}
# 请求
GET / teacher/ _search
{
"query" : {
"term" : {
"name" : {
"value" : "zhangsan"
}
}
} ,
"highlight" : {
"pre_tags" : "<font color='red'>" ,
"post_tags" : "</font>" ,
"fields" : {
"name" : { }
}
}
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 1 ,
"relation" : "eq"
} ,
"max_score" : 1.540445 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.540445 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
} ,
"highlight" : {
"name" : [
"<font color='red'>zhangsan</font>"
]
}
}
]
}
}
# 请求
GET / teacher/ _search
{
"query" : {
"match_all" : { }
} ,
"size" : 2
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "002" ,
"_score" : 1.0 ,
"_source" : {
"name" : "lisi" ,
"nickname" : "lisi" ,
"sex" : "男" ,
"age" : 20
}
}
]
}
}
size：取多少条数据 from：从哪条数据开始 size+from 合起来实现分页效果 # 请求
GET / teacher/ _search
{
"query" : {
"match_all" : { }
} ,
"size" : 2 ,
"from" : 2
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "003" ,
"_score" : 1.0 ,
"_source" : {
"name" : "wangwu1" ,
"nickname" : "wangwu2" ,
"sex" : "女" ,
"age" : 40
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "004" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhaoliu1" ,
"nickname" : "zhaoliu2" ,
"sex" : "女" ,
"age" : 50
}
}
]
}
}
文本字段（text字段）默认不适用于需要逐文档字段数据的操作，如聚合（aggregations）和排序（sorting）。这是因为text字段会被分词器分词，存储的是词元（tokens），而不是完整的原始字符串。 # 请求
GET / teacher/ _search
{
"query" : {
"terms" : {
"name" : [ "zhangsan" , "lisi" ]
}
} ,
"sort" : [
{
"age" : {
"order" : "desc"
}
}
]
}
# 返回
{
"took" : 5 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 2 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : null ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan" ,
"sex" : "男" ,
"age" : 30
} ,
"sort" : [
30
]
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "002" ,
"_score" : null ,
"_source" : {
"name" : "lisi" ,
"nickname" : "lisi" ,
"sex" : "男" ,
"age" : 20
} ,
"sort" : [
20
]
}
]
}
}
includes：来指定想要显示的字段 excludes：来指定不想要显示的字段 # 请求
GET / teacher/ _search
{
"query" : {
"terms" : {
"name" : [ "zhangsan" , "lisi" ]
}
} ,
"_source" : {
"includes" : [ "name" , "nickname" ]
}
}
# 返回
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 2 ,
"relation" : "eq"
} ,
"max_score" : 1.0 ,
"hits" : [
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "001" ,
"_score" : 1.0 ,
"_source" : {
"name" : "zhangsan" ,
"nickname" : "zhangsan"
}
} ,
{
"_index" : "teacher" ,
"_type" : "_doc" ,
"_id" : "002" ,
"_score" : 1.0 ,
"_source" : {
"name" : "lisi" ,
"nickname" : "lisi"
}
}
]
}
}
aggs：表示聚合
size：0 表示返回聚合结果不返回详细数据 # 请求
GET / teacher/ _search
{
"aggs" : {
"max_age" : {
"max" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回
{
"took" : 4 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"max_age" : {
"value" : 50.0
}
}
}
# 请求
GET / teacher/ _search
{
"aggs" : {
"min_age" : {
"min" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回值
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"min_age" : {
"value" : 20.0
}
}
}
# 请求
GET / teacher/ _search
{
"aggs" : {
"avg_age" : {
"avg" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回值
{
"took" : 3 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"avg_age" : {
"value" : 33.333333333333336
}
}
}
# 请求
GET / teacher/ _search
{
"aggs" : {
"sum_age" : {
"sum" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回值
{
"took" : 0 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"sum_age" : {
"value" : 200.0
}
}
}
# 请求
GET / teacher/ _search
{
"aggs" : {
"cardinality_age" : {
"cardinality" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回值
{
"took" : 10 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"cardinality_age" : {
"value" : 4
}
}
}
# 请求
GET / teacher/ _search
{
"aggs" : {
"stats_age" : {
"stats" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回值
{
"took" : 2 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"stats_age" : {
"count" : 6 ,
"min" : 20.0 ,
"max" : 50.0 ,
"avg" : 33.333333333333336 ,
"sum" : 200.0
}
}
}
# 请求
GET / teacher/ _search
{
"aggs" : {
"terms_age" : {
"terms" : { "field" : "age" }
}
} ,
"size" : 0
}
# 返回值
{
"took" : 2 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"terms_age" : {
"doc_count_error_upper_bound" : 0 ,
"sum_other_doc_count" : 0 ,
"buckets" : [
{
"key" : 30 ,
"doc_count" : 3
} ,
{
"key" : 20 ,
"doc_count" : 1
} ,
{
"key" : 40 ,
"doc_count" : 1
} ,
{
"key" : 50 ,
"doc_count" : 1
}
]
}
}
}
# 请求
GET / teacher/ _search? size= 0
{
"aggs" : {
"group_by_field" : {
"terms" : {
"field" : "age"
} ,
"aggs" : {
"average_value" : {
"avg" : {
"field" : "age"
}
}
}
}
}
}
# 返回值
{
"took" : 1 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"group_by_field" : {
"doc_count_error_upper_bound" : 0 ,
"sum_other_doc_count" : 0 ,
"buckets" : [
{
"key" : 30 ,
"doc_count" : 3 ,
"average_value" : {
"value" : 30.0
}
} ,
{
"key" : 20 ,
"doc_count" : 1 ,
"average_value" : {
"value" : 20.0
}
} ,
{
"key" : 40 ,
"doc_count" : 1 ,
"average_value" : {
"value" : 40.0
}
} ,
{
"key" : 50 ,
"doc_count" : 1 ,
"average_value" : {
"value" : 50.0
}
}
]
}
}
}
GET / teacher/ _search? size= 0
{
"aggs" : {
"group_by_field" : {
"terms" : {
"field" : "age" ,
"order" : { "average_value" : "desc" }
} ,
"aggs" : {
"average_value" : {
"avg" : {
"field" : "age"
}
}
}
}
}
}
# 返回值
{
"took" : 4 ,
"timed_out" : false ,
"_shards" : {
"total" : 1 ,
"successful" : 1 ,
"skipped" : 0 ,
"failed" : 0
} ,
"hits" : {
"total" : {
"value" : 6 ,
"relation" : "eq"
} ,
"max_score" : null ,
"hits" : [ ]
} ,
"aggregations" : {
"group_by_field" : {
"doc_count_error_upper_bound" : 0 ,
"sum_other_doc_count" : 0 ,
"buckets" : [
{
"key" : 50 ,
"doc_count" : 1 ,
"average_value" : {
"value" : 50.0
}
} ,
{
"key" : 40 ,
"doc_count" : 1 ,
"average_value" : {
"value" : 40.0
}
} ,
{
"key" : 30 ,
"doc_count" : 3 ,
"average_value" : {
"value" : 30.0
}
} ,
{
"key" : 20 ,
"doc_count" : 1 ,
"average_value" : {
"value" : 20.0
}
}
]
}
}
}
