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ES的index数据结构示例(aliases mappings

ES的index数据结构示例(aliases mappings

作者: commafu | 来源:发表于2021-06-11 11:26 被阅读0次
    {
      "community_user_index_2020": {
        "aliases": {
          "community_user_index": {}
        },
        "mappings": {
          "properties": {
            "accountStatus": {
              "type": "integer"
            },
            "gmtCreate": {
              "type": "long"
            },
            "gmtLevelUp": {
              "type": "long"
            },
            "gmtModify": {
              "type": "long"
            },
            "introduction": {
              "type": "text",
              "term_vector": "with_positions_offsets",
              "analyzer": "ik_smart"
            },
            "levelId": {
              "type": "integer"
            },
            "limitLevel": {
              "type": "integer"
            },
            "name": {
              "type": "keyword",
              "fields": {
                "ik": {
                  "type": "text",
                  "term_vector": "with_positions_offsets",
                  "similarity": "BM25",
                  "analyzer": "ik_max_word"
                },
                "ngram": {
                  "type": "text",
                  "term_vector": "with_positions_offsets",
                  "similarity": "BM25",
                  "analyzer": "ngram_analyzer"
                },
                "pinyin": {
                  "type": "text",
                  "term_vector": "with_positions_offsets",
                  "similarity": "BM25",
                  "analyzer": "ngram_pinyin_analyzer"
                }
              }
            },
            "pinyin": {
              "type": "keyword"
            },
            "remark": {
              "type": "text",
              "term_vector": "with_positions_offsets",
              "analyzer": "ik_smart"
            },
            "signature": {
              "type": "text",
              "term_vector": "with_positions_offsets",
              "analyzer": "ik_smart"
            },
            "status": {
              "type": "integer"
            },
            "userId": {
              "type": "long"
            },
            "vip": {
              "type": "integer"
            }
          }
        },
        "settings": {
          "index": {
            "max_ngram_diff": "20",
            "number_of_shards": "5",
            "provided_name": "community_user_index_2020",
            "creation_date": "1590052024046",
            "analysis": {
              "filter": {
                "pinyin_filter": {
                  "keep_joined_full_pinyin": "true",
                  "lowercase": "true",
                  "first_letter": "only",
                  "keep_original": "false",
                  "remove_duplicated_term": "true",
                  "keep_separate_first_letter": "false",
                  "type": "pinyin",
                  "limit_first_letter_length": "20",
                  "keep_none_chinese_in_first_letter": "true",
                  "keep_none_chinese_in_joined_full_pinyin": "true",
                  "keep_first_letter": "true",
                  "keep_none_chinese": "false",
                  "keep_full_pinyin": "false"
                },
                "my_multiplexer": {
                  "type": "multiplexer",
                  "filters": [
                    "word_delimiter_graph",
                    "edge_ngram_filter"
                  ]
                },
                "edge_ngram_filter": {
                  "type": "edge_ngram",
                  "min_gram": "1",
                  "max_gram": "20"
                }
              },
              "analyzer": {
                "default": {
                  "type": "ik_smart",
                  "tokenizer": "standard"
                },
                "ngram_analyzer": {
                  "type": "custom",
                  "tokenizer": "my_ngram"
                },
                "search_pinyin_analyzer": {
                  "filter": [
                    "word_delimiter_graph"
                  ],
                  "type": "custom",
                  "tokenizer": "my_pinyin"
                },
                "ngram_pinyin_analyzer": {
                  "filter": [
                    "pinyin_filter"
                  ],
                  "type": "custom",
                  "tokenizer": "my_ngram"
                },
                "pinyin_analyzer": {
                  "filter": [
                    "my_multiplexer"
                  ],
                  "type": "custom",
                  "tokenizer": "my_pinyin"
                }
              },
              "tokenizer": {
                "my_ngram": {
                  "token_chars": [
                    "letter",
                    "digit",
                    "punctuation",
                    "symbol"
                  ],
                  "min_gram": "1",
                  "type": "ngram",
                  "max_gram": "20"
                },
                "my_pinyin": {
                  "keep_joined_full_pinyin": "true",
                  "lowercase": "true",
                  "first_letter": "only",
                  "keep_original": "false",
                  "remove_duplicated_term": "true",
                  "keep_separate_first_letter": "false",
                  "type": "pinyin",
                  "limit_first_letter_length": "20",
                  "keep_none_chinese_in_first_letter": "true",
                  "keep_none_chinese_in_joined_full_pinyin": "true",
                  "keep_first_letter": "true",
                  "keep_none_chinese": "false",
                  "keep_full_pinyin": "true"
                }
              }
            },
            "number_of_replicas": "0",
            "uuid": "_DYRtOnIQoSxZu3kx15H4w",
            "version": {
              "created": "7000099"
            }
          }
        }
      }
    }
    

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