使用kibana7.0.0的控制檯Dev Tools操作ES數據的基本語法入門示例
因爲使用的是本地啓動的ES庫，所以需要先啓動ES，然後啓動kibana，直接從官網上下載安裝啓動即可，說明一點就是需先啓動ES，在啓動kibana，該部分效果以及添加官方示例數據已在之前一篇文章中寫過，此處不再重複。
直接點擊Dev Tools，來看基本操作
1，輸入：GET /
在右側將看到和啓動完ES後在瀏覽器輸入localhost:9200相同的內容
2，創建索引
輸入：
說明：因爲7版本之後，ES不再支持一個索引（index）可以創建多個類型（type），所以cmcc/後邊不再需要寫入類型名稱，而是統一使用_create代替即可，同樣的，查詢操作使用_doc代替即可，右側看到如下圖所示類似形式表示創建成功
3，查看剛纔創建的索引
輸入：GET cmcc/_doc/1
右側將顯示剛纔創建的內容，其中_index是剛纔創建的索引名稱；_type是類型，7版本統一爲_doc；_id爲創建時的ID，如果創建索引的時候不設置ID，那麼ES將默認分配一個ID，不過樣式會比較長，不好記憶；_version爲版本號，如果我們之後對該數據進行了修改，那麼他會隨之變化；_source裏邊就是我們剛纔加進去的數據內容
4，刪除索引
輸入：DELETE cmcc
只需要在DELETE後邊加上索引名稱即可
5，修改數據
輸入：
這裏我們修改了"name"值，把"province"和"conutry"值改爲中文，並添加了一個新屬性"xingbie"，執行之後我們再次執行獲取數據內容命令GET cmcc/_doc/1，如下，可以看到數據已經被修改，版本號變成了2
6，bulk方法批量插入數據
輸入：
使用POST方法，然後每一條數據的格式是一致的，首先第一行輸入 {"index":{"_index":"cmcc"}} ，也就是索引名稱，第二行輸入要插入的完整數據，這裏特別提醒下，插入的這條數據不能使用剛纔創建數據時的那種多行形式，只能使用沒有回車的一條數據，否則會報錯如下：
{
"error": {
"root_cause": [
{
"type": "json_e_o_f_exception",
"reason": "Unexpected end-of-input: expected close marker for Object (start marker at [Source: org.elasticsearch.transport.netty4.ByteBufStreamInput@154857fc; line: 1, column: 1])\n at [Source: org.elasticsearch.transport.netty4.ByteBufStreamInput@154857fc; line: 1, column: 3]"
}
],
"type": "json_e_o_f_exception",
"reason": "Unexpected end-of-input: expected close marker for Object (start marker at [Source: org.elasticsearch.transport.netty4.ByteBufStreamInput@154857fc; line: 1, column: 1])\n at [Source: org.elasticsearch.transport.netty4.ByteBufStreamInput@154857fc; line: 1, column: 3]"
},
"status": 500
}
執行完畢後，我們再次獲取數據看一下，輸入：GET cmcc/_search
結果如下：（不截長圖了，就直接貼結果吧>_<）
{
"took" : 374,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 5,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "dunkking",
"age" : 27,
"location" : "SG",
"province" : "河北",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9vD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "points",
"age" : 23,
"location" : "PG",
"province" : "江蘇",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9_D-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "rebound",
"age" : 24,
"location" : "SF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-PD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "center",
"age" : 23,
"location" : "C",
"province" : "北京",
"country" : "中國",
"xingbie" : "femela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-fD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "assist",
"age" : 21,
"location" : "PF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "famela"
}
}
]
}
}
7，按照條件查詢
輸入：
也就是查詢數據中屬性"province"爲"廣州"的數據，結果如下：
{
"took" : 10,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.7509375,
"hits" : [
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9_D-3moBmjOHTfOJtVLL",
"_score" : 1.7509375,
"_source" : {
"name" : "rebound",
"age" : 24,
"location" : "SF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-fD-3moBmjOHTfOJtVLL",
"_score" : 1.7509375,
"_source" : {
"name" : "assist",
"age" : 21,
"location" : "PF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "famela"
}
}
]
}
}
8，當同一個屬性滿足邏輯或時的查詢
輸入：
這裏是查詢屬性"age"等於21或者23的數據，如果看着不舒服，我們可以點擊運行按鈕右側的扳手，選擇Auto indent，輸入效果就會直觀一些，
其中，116行固定輸入"query"，117行固定輸入"bool"，118行輸入爲"should"，表示是邏輯或的關係，120行爲"match"，121行爲所要查詢的屬性名與屬性值
執行結果如下
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9vD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "points",
"age" : 23,
"location" : "PG",
"province" : "江蘇",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-PD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "center",
"age" : 23,
"location" : "C",
"province" : "北京",
"country" : "中國",
"xingbie" : "femela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-fD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "assist",
"age" : 21,
"location" : "PF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "famela"
}
}
]
}
}
9，多條件查詢
輸入：
這裏是查詢屬性"age"等於23，並且屬性"country"爲“中國”的數據，這裏和上一條查詢的關鍵區別就在於第98行由"should"改爲"must"，執行結果如下：
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 1.1740228,
"hits" : [
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9vD-3moBmjOHTfOJtVLL",
"_score" : 1.1740228,
"_source" : {
"name" : "points",
"age" : 23,
"location" : "PG",
"province" : "江蘇",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-PD-3moBmjOHTfOJtVLL",
"_score" : 1.1740228,
"_source" : {
"name" : "center",
"age" : 23,
"location" : "C",
"province" : "北京",
"country" : "中國",
"xingbie" : "femela"
}
}
]
}
}
10，範圍查詢並進行排序
輸入：
這裏，151行使用"range"，152行輸入屬性名，153行"gte"和154行"lte"表示查詢屬性"age"在20-25範圍的數據，然後158行表示排序，160行表示排序的屬性是"age"，161“order”表示排序爲倒序"desc"，執行結果如下：
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 4,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9_D-3moBmjOHTfOJtVLL",
"_score" : null,
"_source" : {
"name" : "rebound",
"age" : 24,
"location" : "SF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "mela"
},
"sort" : [
24
]
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9vD-3moBmjOHTfOJtVLL",
"_score" : null,
"_source" : {
"name" : "points",
"age" : 23,
"location" : "PG",
"province" : "江蘇",
"country" : "中國",
"xingbie" : "mela"
},
"sort" : [
23
]
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-PD-3moBmjOHTfOJtVLL",
"_score" : null,
"_source" : {
"name" : "center",
"age" : 23,
"location" : "C",
"province" : "北京",
"country" : "中國",
"xingbie" : "femela"
},
"sort" : [
23
]
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "-fD-3moBmjOHTfOJtVLL",
"_score" : null,
"_source" : {
"name" : "assist",
"age" : 21,
"location" : "PF",
"province" : "廣州",
"country" : "中國",
"xingbie" : "famela"
},
"sort" : [
21
]
}
]
}
}
11，聚合查詢
輸入：
使用聚合查詢，格式是：170行使用"aggs"，171行爲所要查詢的屬性名，這裏查詢"age"，173行"field"後邊輸入屬性名，174行爲範圍，分別在"from"和"to"後邊輸入要分段的範圍，這條請求實現的是統計屬性"age"按照20-23,23-25,25-30劃分的數據條數分別爲多少，如果想要查看滿足條件的數據，則將169行"size"值置爲非零數，貌似應大於查詢條數，具體還沒查，這裏是不顯示滿足條件的具體數據，直接置零即可，執行結果如下：
{
"took" : 9,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 5,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"age" : {
"buckets" : [
{
"key" : "20.0-23.0",
"from" : 20.0,
"to" : 23.0,
"doc_count" : 1
},
{
"key" : "23.0-25.0",
"from" : 23.0,
"to" : 25.0,
"doc_count" : 3
},
{
"key" : "25.0-30.0",
"from" : 25.0,
"to" : 30.0,
"doc_count" : 1
}
]
}
}
}
聚合查詢的另外一個示例
輸入：
這條請求是查詢屬性"province"的統計結果，這裏是統計5條數據，並顯示其中2條，並在197行"field"後輸入屬性名，並在其後添加 .keyword，查詢結果如下
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 5,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"name" : "dunkking",
"age" : 27,
"location" : "SG",
"province" : "河北",
"country" : "中國",
"xingbie" : "mela"
}
},
{
"_index" : "cmcc",
"_type" : "_doc",
"_id" : "9vD-3moBmjOHTfOJtVLL",
"_score" : 1.0,
"_source" : {
"name" : "points",
"age" : 23,
"location" : "PG",
"province" : "江蘇",
"country" : "中國",
"xingbie" : "mela"
}
}
]
},
"aggregations" : {
"province" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "廣州",
"doc_count" : 2
},
{
"key" : "北京",
"doc_count" : 1
},
{
"key" : "江蘇",
"doc_count" : 1
},
{
"key" : "河北",
"doc_count" : 1
}
]
}
}
}
暫時寫這麼多，剛開始學，很多不熟悉的，後續有時間慢慢補充