我是elasticsearch的新手，当我需要匹配多个搜索词以及匹配嵌套文档时，我的查询速度很慢，基本上第一次查询需要7-10秒，之后由于elasticsearch缓存的原因需要5-6秒，但是对于只匹配的非嵌套对象的查询速度很快，即在100毫秒内。
我在aws示例中运行ElasticSearch，有250gbram和500gbdisk空间，我有一个模板和204个索引，总共索引了1.07亿个文档，每个索引在一个节点上有2个碎片，我保持了30gb的堆大小。
以下是我的内存使用情况：

我可以有超过50k的嵌套对象，所以我已经将长度增加到500k，在这个嵌套对象上搜索花费了太多的时间，在嵌套对象以外的字段上的任何or（应该匹配）操作也需要时间，有什么方法可以提高嵌套对象的查询性能吗？或者我的配置有什么问题吗？有什么方法可以让我的第一个查询也更快？

{
  "index_patterns": [
    "product_*"
  ],
  "template": {
    "settings": {
      "index.store.type": "mmapfs",
      "number_of_shards":2,
      "number_of_replicas": 0,
      "index": {
        "store.preload": [
          "*"
        ],
        "mapping.nested_objects.limit": 500000,
        "analysis": {
          "analyzer": {
            "cust_product_name": {
              "type": "custom",
              "tokenizer": "standard",
              "filter": [
                "lowercase",
                "english_stop",
                "name_wordforms",
                "business_wordforms",
                "english_stemmer",
                "min_value"
              ],
              "char_filter": [
                "html_strip"
              ]
            },
            "entity_name": {
              "type": "custom",
              "tokenizer": "standard",
              "filter": [
                "lowercase",
                "english_stop",
                "business_wordforms",
                "name_wordforms",
                "english_stemmer"
              ],
              "char_filter": [
                "html_strip"
              ]
            },
            "cust_text": {
              "type": "custom",
              "tokenizer": "standard",
              "filter": [
                "lowercase",
                "english_stop",
                "name_wordforms",
                "english_stemmer",
                "min_value"
              ],
              "char_filter": [
                "html_strip"
              ]
            }
          },
          "filter": {
            "min_value": {
              "type": "length",
              "min": 2
            },
            "english_stop": {
              "type": "stop",
              "stopwords": "_english_"
            },
            "business_wordforms": {
              "type": "synonym",
              "synonyms_path": "<some path>/business_wordforms.txt"
            },
            "name_wordforms": {
              "type": "synonym",
              "synonyms_path": "<some path>/name_wordforms.txt"
            },
            "english_stemmer": {
              "type": "stemmer",
              "language": "english"
            }
          }
        }
      }
    },
    "mappings": {
      "dynamic": "strict",
      "properties": {
        "product_number": {
          "type": "text",
          "analyzer": "keyword"
        },
        "product_name": {
          "type": "text",
          "analyzer": "cust_case_name"
        },
        "first_fetch_date": {
          "type": "date",
          "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||yyyy-MM||yyyy"
        },
        "last_fetch_date": {
          "type": "date",
          "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||yyyy-MM||yyyy"
        },
        "review": {
          "type": "nested",
          "properties": {
            "text": {
              "type": "text",
              "analyzer": "cust_text"
            },
            "review_date": {
              "type": "date",
              "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||yyyy-MM||yyyy"
            }
          }
        }
      }
    },
    "aliases": {
      "all_products": {}
    }
  },
  "priority": 200,
  "version": 1,
}

如果我在评论文本中搜索任何特定的词，那么回复就花费了太多的时间。

{
    "_source":{
        "excludes":["review"]
    },
    "size":1,
    "track_total_hits":true,
    "query":{
        "nested":{
            "path":"review",
            "query":{
                "match":{
                    "review.text":{
                        "query":"good",
                        "zero_terms_query":"none"
                    }
                }
            }
        }
    },
    "highlight":{
        "pre_tags":[
            "<b>"
        ],
        "post_tags":[
            "</b>"
        ],
        "fields":{
            "product_name":{

            }
        }
    }
}

我肯定我遗漏了一些明显的东西。