Elasticsearch: CRUD for Elasticsearch

Document the CRUD

Elasticsearch CRUD documents through REST apisCopy the code

Test the API

There is a development tool in the Kibana sidebar that allows you to test the Elasticsearch API. We imported a movie index data in the previous section, so let's use it as an example to test the related APICopy the code

The Index operation

PUT /movies/_doc/1 
{
  "genre" : [
      "Adventure"."Animation"."Children"."Comedy"."Fantasy"]."year" : 1995."id" : "1"."@version" : "1"."title" : "Toy Story"} The response results are as follows: {"_index" : "movies"."_type" : "_doc"."_id" : "1"."_version" : 2."result" : "updated"."_shards" : {
    "total" : 2."successful" : 1."failed" : 0
  },
  "_seq_no" : 9743."_primary_term" : 1
}
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The Create operation

PUT /movies/_create/1# create document, error if document exists {"genre" : [
      "Adventure"."Animation"."Children"."Comedy"."Fantasy"]."year" : 1995."id" : "1"."@version" : "1"."title" : "Toy Story"} The response results are as follows: {"error" : {
    "root_cause": [{"type" : "version_conflict_engine_exception"."reason" : "[1]: version conflict, document already exists (current version [2])"."index_uuid" : "Km35tJDlTPGjIjnmNgPQ4A"."shard" : "0"."index" : "movies"}]."type" : "version_conflict_engine_exception"."reason" : "[1]: version conflict, document already exists (current version [2])"."index_uuid" : "Km35tJDlTPGjIjnmNgPQ4A"."shard" : "0"."index" : "movies"
  },
  "status" : 409
}

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Read operation

 GET movies/_doc/1Select * from movies where id = 01The document data response results are as follows: {"_index" : "movies"."_type" : "_doc"."_id" : "1"."_version" : 1."_seq_no" : 128."_primary_term" : 1."found" : true."_source" : {
    "genre" : [
      "Adventure"."Animation"."Children"."Comedy"."Fantasy"]."year" : 1995."id" : "1"."@version" : "1"."title" : "Toy Story"}}Copy the code

The Update operation

The # update operation can modify the values of old fields or add new fields, but overall requests need to POST movies/_update/ wrapped under doc1
{
  "doc": {
   "genre" : [
        "Adventure1"."Animation1"."Children1"."Comedy1"."Fantasy1"]."year" : 1995."id" : "1"."@version" : "2"."title" : "Toy Story"}} The response results are as follows: {"_index" : "movies"."_type" : "_doc"."_id" : "1"."_version" : 3."result" : "updated"."_shards" : {
    "total" : 2."successful" : 1."failed" : 0
  },
  "_seq_no" : 9744."_primary_term" : 1
}

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The Delete operation

DELETE /movies/_doc/1The response results are as follows: {"_index" : "movies"."_type" : "_doc"."_id" : "1"."_version" : 4."result" : "deleted"."_shards" : {
    "total" : 2."successful" : 1."failed" : 0
  },
  "_seq_no" : 9745."_primary_term" : 1
}
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Bulk API

The Rest API needs to re-establish connections each time a request is generated, which can consume high performance. The Bulk API supports four types of operations:  1. Index 2. Create 3. Update 4. Delete
The Bulk API can know the Index in the URL or specify it in the request body. The failure of a single operation does not affect other operation results. 3. The returned result contains the result of each operationCopy the code

The sample

POST _bulk # Create an index named test with the document ID as1, the data is {"field1":"value1"} index {"index": {"_index":"test"."_id":"1"}}
{"field1":"value1"} # delete from test where id = 12File (does not exist at this time, will report an error, but does not affect the success of other execution) {"delete": {"_index":"test"."_id":2}} # create index test23, the data is {"field1":"value3"} index {"create": {"_index":"test2"."_id":"3"}}
{"field1":"value3"Alter table test2 alter table test2 alter table test2"update": {"_index":"test"."_id":"1"}} 
{"doc": {"field1":"value2"}} The response result is as follows: For each operation, there is a response result {"took" : 522."errors" : false."items": [{"index" : {
        "_index" : "test"."_type" : "_doc"."_id" : "1"."_version" : 3."result" : "updated"."_shards" : {
          "total" : 2."successful" : 1."failed" : 0
        },
        "_seq_no" : 2."_primary_term" : 1."status" : 200}}, {"delete" : {
        "_index" : "test"."_type" : "_doc"."_id" : "2"."_version" : 1."result" : "not_found"."_shards" : {
          "total" : 2."successful" : 1."failed" : 0
        },
        "_seq_no" : 3."_primary_term" : 1."status" : 404}}, {"create" : {
        "_index" : "test2"."_type" : "_doc"."_id" : "3"."_version" : 1."result" : "created"."_shards" : {
          "total" : 2."successful" : 1."failed" : 0
        },
        "_seq_no" : 0."_primary_term" : 1."status" : 201}}, {"update" : {
        "_index" : "test"."_type" : "_doc"."_id" : "1"."_version" : 4."result" : "updated"."_shards" : {
          "total" : 2."successful" : 1."failed" : 0
        },
        "_seq_no" : 4."_primary_term" : 1."status" : 200}}}]Copy the code

Batch read MGET

# 1.Mysql > alter table test2; mysql > alter table test2; mysql > alter table test21Document GET _mget {"docs":[
    {"_index":"test"."_id":"1"
    },
    {
      "_index":"test2"."_id":"1"}]} the response is as follows: {"docs": [{"_index" : "test"."_type" : "_doc"."_id" : "1"."_version" : 4."_seq_no" : 4."_primary_term" : 1."found" : true."_source" : {
        "field1" : "value2"}}, {"_index" : "test2"."_type" : "_doc"."_id" : "1"."found" : false}}]Copy the code

Search API

1.Queries are a big piece of content, which I'll cover in detail in the next section due to space constraintsCopy the code

Common error return