# must，有算分

# Filter。不参与算分，结果的score是0

# 改变数据模型，增加字段。解决数组包含而不是精确匹配的问题

# 嵌套，实现了 should not 逻辑

# minimum_should_match: 指定了至少应该匹配的 should 子句数量。

DELETE products

POST /products/_bulk
{ "index": { "_id": 1 }}
{ "price" : 10,"avaliable":true,"date":"2018-01-01", "productID" : "XHDK-A-1293-#fJ3" }
{ "index": { "_id": 2 }}
{ "price" : 20,"avaliable":true,"date":"2019-01-01", "productID" : "KDKE-B-9947-#kL5" }
{ "index": { "_id": 3 }}
{ "price" : 30,"avaliable":true, "productID" : "JODL-X-1937-#pV7" }
{ "index": { "_id": 4 }}
{ "price" : 30,"avaliable":false, "productID" : "QQPX-R-3956-#aD8" }


# 基本语法
POST /products/_search
{
  "query": {
    "bool" : {
      "must" : {
        "term" : { "price" : "30" }
      },
      "filter": {
        "term" : { "avaliable" : "true" }
      },
      "must_not" : {
        "range" : {
          "price" : { "lte" : 10 }
        }
      },
      "should" : [
        { "term" : { "productID.keyword" : "JODL-X-1937-#pV7" } },
        { "term" : { "productID.keyword" : "XHDK-A-1293-#fJ3" } }
      ],
      "minimum_should_match" :1
    }
  }
}

# 改变数据模型，增加字段。解决数组包含而不是精确匹配的问题
POST /newmovies/_bulk
{ "index": { "_id": 1 }}
{ "title" : "Father of the Bridge Part II","year":1995, "genre":"Comedy","genre_count":1 }
{ "index": { "_id": 2 }}
{ "title" : "Dave","year":1993,"genre":["Comedy","Romance"],"genre_count":2 }

# must，有算分
POST /newmovies/_search
{
  "query": {
    "bool": {
      "must": [
        {"term": {"genre.keyword": {"value": "Comedy"}}},
        {"term": {"genre_count": {"value": 1}}}

      ]
    }
  }
}

# Filter。不参与算分，结果的score是0
POST /newmovies/_search
{
  "query": {
    "bool": {
      "filter": [
          {"term": {"genre.keyword": {"value": "Comedy"}}},
          {"term": {"genre_count": {"value": 1}}}
        ]

    }
  }
}


# Filtering Context
POST _search
{
  "query": {
    "bool" : {
        "filter": {
        "term" : { "avaliable" : "true" }
      },
      "must_not" : {
        "range" : {
          "price" : { "lte" : 10 }
        }
      }
    }
  }
}


# Query Context
POST /products/_bulk
{ "index": { "_id": 1 }}
{ "price" : 10,"avaliable":true,"date":"2018-01-01", "productID" : "XHDK-A-1293-#fJ3" }
{ "index": { "_id": 2 }}
{ "price" : 20,"avaliable":true,"date":"2019-01-01", "productID" : "KDKE-B-9947-#kL5" }
{ "index": { "_id": 3 }}
{ "price" : 30,"avaliable":true, "productID" : "JODL-X-1937-#pV7" }
{ "index": { "_id": 4 }}
{ "price" : 30,"avaliable":false, "productID" : "QQPX-R-3956-#aD8" }

# should
POST /products/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "term": {
            "productID.keyword": {
              "value": "JODL-X-1937-#pV7"}}
        },
        {"term": {"avaliable": {"value": true}}
        }
      ]
    }
  }
}


# 嵌套，实现了 should not 逻辑
# minimum_should_match: 指定了至少应该匹配的 should 子句数量。
#                       在这里，设置为 1 表示至少需要有一个 should 子句匹配成功。
POST /products/_search
{
  "query": {
    "bool": {
      "must": {
        "term": {
          "price": "30"
        }
      },
      "should": [
        {
          "bool": {
            "must_not": {
              "term": {
                "avaliable": "false"
              }
            }
          }
        }
      ],
      "minimum_should_match": 1
    }
  }
}


# Controll the Precision
# minimum_should_match 2 匹配出数数据，1可以匹配出一条数据
POST _search
{
  "query": {
    "bool" : {
      "must" : {
        "term" : { "price" : "30" }
      },
      "filter": {
        "term" : { "avaliable" : "true" }
      },
      "must_not" : {
        "range" : {
          "price" : { "lte" : 10 }
        }
      },
      "should" : [
        { "term" : { "productID.keyword" : "JODL-X-1937-#pV7" } },
        { "term" : { "productID.keyword" : "XHDK-A-1293-#fJ3" } }
      ],
      "minimum_should_match" :2
    }
  }
}


POST /animals/_search
{
  "query": {
    "bool": {
      "should": [
        { "term": { "text": "brown" }},
        { "term": { "text": "red" }},
        { "term": { "text": "quick" }},
        { "term": { "text": "dog" }}
      ]
    }
  }
}

POST /animals/_search
{
  "query": {
    "bool": {
      "should": [
          { "term": { "text": "quick" }},
          { "term": { "text": "dog"   }},
          {
          "bool":{
            "should":[
              { "term": { "text": "brown" }},
              { "term": { "text": "brown" }}
            ]
          }
        }
      ]
    }
  }
}


DELETE blogs

POST /blogs/_bulk
{ "index": { "_id": 1 }}
{"title":"Apple iPad", "content":"Apple iPad,Apple iPad" }
{ "index": { "_id": 2 }}
{"title":"Apple iPad,Apple iPad", "content":"Apple iPad" }


POST blogs/_search
{
  "query": {
    "bool": {
      "should": [
        {
          "match": {
            "title": {
              "query": "apple,ipad",
              "boost": 1.1
            }
          }
        },
        {
          "match": {
            "content": {
              "query": "apple,ipad",
              "boost":0
            }
          }
        }
      ]
    }
  }
}


DELETE news

POST /news/_bulk
{ "index": { "_id": 1 }}
{ "content":"Apple Mac" }
{ "index": { "_id": 2 }}
{ "content":"Apple iPad" }
{ "index": { "_id": 3 }}
{ "content":"Apple employee like Apple Pie and Apple Juice" }


POST news/_search
{
  "query": {
    "bool": {
      "must": {
        "match":{"content":"apple"}
      }
    }
  }
}

POST news/_search
{
  "query": {
    "bool": {
      "must": {
        "match":{"content":"apple"}
      },
      "must_not": {
        "match":{"content":"pie"}
      }
    }
  }
}

POST news/_search
{
  "query": {
    "boosting": {
      "positive": {
        "match": {
          "content": "apple"
        }
      },
      "negative": {
        "match": {
          "content": "pie"
        }
      },
      "negative_boost": 0.5
    }
  }
}


DELETE products
DELETE newmovies
DELETE animals
DELETE blogs
DELETE news