Create indexes
First, we opened our Kibana tool to execute ES commands. ES commands are Restful, that is, PUT, GET, POST, and DELETE. You can think of ES as a database, where test1 is the database name, user is the table name, and 1 is the field
PUT /test1/user/1 {"name": "love Java programmer ", "age": 22}Copy the code
Get the value
GET /test1 GET the data of a document GET /test1/user/1 GET a field of the data of a document GET /user_index/_doc/1? GET /user_index/_doc/1/_source Queries all information about the specified index. GET /user_index/_search queries test_index data and sorts the data in descending order by age
GET /test_index/_search
{
"query": {"match_all": {}},
"sort": [
{
"age": {
"order": "desc"
}
}
]
}
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Query test_index data descending and paging
GET /test_index/_search
{
"query": {"match_all": {}},
"sort": [
{
"age": {
"order": "desc"
}
}
],
"from": 0,
"size": 2
}
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Fuzzy match word segmentation query
GET/test_index / _search {" query ": {" match" : {" name ":" * * "}}}Copy the code
Range queries
GET /test_index/_search
{
"query": {
"bool": {
"must": { "match_all": {} },
"filter": {
"range": {
"age": {
"gte": 15,
"lte": 25
}
}
}
}
}
}
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Term Accurate matching query
GET /test_index/_search
{
"query": {
"term": {
"age": "18"
}
}
}
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Queries documents with the specified prefix
GET/test_index / _search {" query ": {" prefix" : {" name ":" zhang "}}}Copy the code
Support wildcard query
GET/test_index / _search {" query ": {" wildcard" : {" name ":" greetings * "}}}Copy the code
Match will split the keyword when matching, and then search according to the word segmentation match, while term will directly search the keyword. General fuzzy lookups use match, while exact lookups use term
Modify the value
Change the age to 21
POST /test1/user/1/_update
{
"doc": {
"age": 21
}
}
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Delete the value
DELETE document 1 DELETE /test1/user/1 DELETE index test1 DELETE /test1