Elasticsearch在建立索引時指定主分片個數

Elasticsearch 是優秀的文檔數據庫，在咱們使用集羣方式建立咱們的文檔數據時，須要根據集羣node數量合理設置分片個數 從而提升數據查詢、讀取 效率；

下面是分片設置塊

"settings": {
      "number_of_shards": 12,#分片個數，在建立索引不指定時 默認爲 5；
      "number_of_replicas": 1 #數據副本，通常設置爲1；
    },

 

下面是一個建立索引並設置分片的例子:

curl -X PUT \
  http://$1:9200/your_index_name/ \
  -H 'content-type: application/json' \
  -d '{
  "settings": {
      "number_of_shards": 12,
      "number_of_replicas": 1
    },
    "mappings": {
      "sms_up": {
        "dynamic_templates": [
          {
            "strings_as_keywords": {
              "match_mapping_type": "string",
              "mapping": {
                "type": "keyword"
              }
            }
          }
        ],
        "properties": {
          "account_id": {
            "type": "long"
          },
          "date": {
            "type": "date",
            "format": "yyyy-MM-dd"
          },
          "is_push_sms_up": {
            "type": "short"
          },
          "mobile": {
            "type": "keyword"
          },
          "push_sms_up_time": {
            "type": "date",
            "format": "yyyy-MM-dd HH:mm:ss"
          },
          "request_id": {
            "type": "keyword"
          },
          "request_time": {
            "type": "date",
            "format": "epoch_second"
          },
          "sms_account_primary": {
            "type": "integer"
          },
          "sms_content": {
            "type": "keyword"
          },
          "sms_exno": {
            "type": "keyword"
          },
          "sms_facilitator_id": {
            "type": "integer"
          },
          "sms_msgid": {
            "type": "keyword"
          },
          "sms_sign_id": {
            "type": "integer"
          },
          "sms_spno": {
            "type": "keyword"
          },
          "sms_type": {
            "type": "long"
          },
          "sms_up_rtime": {
            "type": "date",
            "format": "yyyy-MM-dd HH:mm:ss"
          }
        }
      }
    }
}'