在Elasticsearch中，索引模板（Index Templates）是用來預定義新創建索引的設置和映射的一種機制。當你創建了一個索引模板，它會包含一系列的默認設置和映射規則，這些規則會在滿足一定條件的新索引被創建時自動應用。

索引模板通過index_patterns字段來指定模板適用的索引名稱模式。當一個新的索引被創建，Elasticsearch會查找是否有任何模板的index_patterns與該索引名稱匹配。如果有匹配的模板，那么該模板的設置和映射將被應用到新創建的索引上。

因此，如果你創建了一個名為content_erp_nlp_help_online的索引模板，并且在其中定義了index_patterns為["content_erp_nlp_help_online"]，那么當你嘗試創建一個確切名稱為content_erp_nlp_help_online的索引時，該模板將會被應用，從而自動配置索引的設置和映射。

但是，需要注意的是，如果在創建索引時顯式指定了某些設置或映射，那么這些顯式指定的值將優先于模板中的值。此外，一旦索引已經被創建，索引模板的更改將不會影響到已經存在的索引。

索引模板還可以通過通配符模式來匹配多個索引。例如，如果模板的index_patterns為["content_*"]，那么所有以content_開頭的索引都會應用該模板。

總結來說，索引模板是一種策略，它允許你預設一組設置和映射，以便在創建符合特定命名模式的新索引時自動應用這些預設。這極大地簡化了管理大量索引的過程，尤其是當這些索引具有相似的特性時。

ES 8.14 新的創建模板的方法：

PUT /_index_template/content_erp_nlp_help
{"index_patterns": ["content_erp*"],"priority": 100,"template": {"settings": {"analysis": {"analyzer": {"my_ik_analyzer": {"type": "ik_smart"}}},"number_of_shards": 1},"mappings": {"properties": {"id": {"type": "long"},"content": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"content_vector": {"type": "dense_vector","similarity": "cosine","index": true,"dims": 768,"element_type": "float","index_options": {"type": "hnsw","m": 16,"ef_construction": 128}},"content_answer": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"title": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"param": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"type": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"questionId": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"createTime": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"updateTime": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"hitCount": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"answerPattern": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"nearQuestionVOList": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"questionEnclosureVOList": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"questionRelationVOList": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"},"rmsRoutingAnswerVos": {"type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart"}}}}
}

查詢模板：

GET /_index_template/*

GET /_index_template/content_erp_nlp_help

Java實現的代碼：

public int createIndexTemp(String indexTempName) throws Exception {// 創建RestClient實例RestClientBuilder builder = RestClient.builder(new HttpHost("127.0.0.1", 9200, "http"));RestClient restClient = builder.build();// 定義請求體String requestBody = "{\n" +"  \"index_patterns\": [\"content_erp*\"],\n" +"  \"priority\": 100,\n" +"  \"template\": {\n" +"    \"settings\": {\n" +"      \"analysis\": {\n" +"        \"analyzer\": {\n" +"          \"my_ik_analyzer\": {\n" +"            \"type\": \"ik_smart\"\n" +"          }\n" +"        }\n" +"      },\n" +"      \"number_of_shards\": 1\n" +"    },\n" +"    \"mappings\": {\n" +"      \"properties\": {\n" +"        \"id\": {\"type\": \"long\"},\n" +"        \"content\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"content_vector\": {\"type\": \"dense_vector\",\"similarity\": \"cosine\",\"index\": true,\"dims\": 768,\"element_type\": \"float\",\"index_options\": {\"type\": \"hnsw\",\"m\": 16,\"ef_construction\": 128}},\n" +"        \"content_answer\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"title\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"param\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"type\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"questionId\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"createTime\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"updateTime\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"hitCount\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"answerPattern\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"nearQuestionVOList\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"questionEnclosureVOList\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"questionRelationVOList\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"},\n" +"        \"rmsRoutingAnswerVos\": {\"type\": \"text\",\"analyzer\": \"ik_max_word\",\"search_analyzer\": \"ik_smart\"}\n" +"      }\n" +"    }\n" +"  }\n" +"}";// 構建請求Request request = new Request("PUT", "/_index_template/" + indexTempName);request.setJsonEntity(requestBody);// 發送請求并獲取響應Response response = restClient.performRequest(request);// 處理響應int statusCode = response.getStatusLine().getStatusCode();System.out.println("Response status: " + statusCode);// 關閉RestClientrestClient.close();return statusCode;}