查找Mongodb字段中存在的最常见的单词

Question

我有一个集合A和数组B，结构如下：

A

{
    "_id" : ObjectId("5160757496cc6207a37ff778"),
    "name" : "Pomegranate Yogurt Bowl",
    "description" : "A simple breakfast bowl made with Greek yogurt, fresh pomegranate juice, puffed quinoa cereal, toasted sunflower seeds, and honey."
},
{
  "_id": ObjectId("5160757596cc62079cc2db18"),
  "name": "Krispy Easter Eggs",
  "description": "Imagine the Easter Bunny laying an egg.     Wait. That’s not anatomically possible.     And anyway, the Easter Bunny is a b..."
}

B：

var names = ["egg", "garlic", "cucumber", "kale", "pomegranate", "sunflower", "fish", "pork", "apple", "sunflower", "strawberry", "banana"]

我的目标是从A返回一个文档，该文档在数组B中有最多出现的单词。在这种情况下，它应该返回第一个"_id" : ObjectId("5160757496cc6207a37ff778")。

我不知道该怎么解决这个问题

这不管用：

db.A.find({
    "description": {
      "$in": names
    }
  }, function(err, data) {
    if (err) console.log(err);
    console.log(data);
  });

Answer 1

这取决于你想用什么样的“单词”来表达，以及它们是否被认为是“停止词”，比如"a"、"the"、"with"等等，或者这些词的数量是否真的无关紧要。

如果它们不重要，那么考虑一个$text索引和搜索。

第一指数：

db.A.createIndex({ "name": "text", "description": "text" })

然后构造搜索：

var words = [
  "egg", "garlic", "cucumber", "kale", "pomegranate",
  "sunflower", "fish", "pork", "apple", "sunflower",
  "strawberry", "banana"
];

var search = words.join(" ")

db.A.find(
    { "$text": { "$search": search } },
    { "score": { "$meta": "textScore" } }
).sort({ "score": { "$meta": "textScore" }}).limit(1)

返回第一个文档，如下所示：

{
    "_id" : ObjectId("5160757496cc6207a37ff778"),
    "name" : "Pomegranate Yogurt Bowl",
    "description" : "A simple breakfast bowl made with Greek yogurt, fresh pomegranate juice, puffed quinoa cereal, toasted sunflower seeds, and honey.",
    "score" : 1.7291666666666665
}

另一方面，如果您需要计数“停止单词”，那么mapReduce可以为您找到结果：

db.A.mapReduce(
  function() {
    var words = [
      "egg", "garlic", "cucumber", "kale", "pomegranate",
      "sunflower", "fish", "pork", "apple", "sunflower",
      "strawberry", "banana"
    ];

    var count = 0;

    var fulltext = this.name.toLowerCase() + " " + this.description.toLowerCase();

    // Increment count by number of matches
    words.forEach(function(word) {
      count += ( fulltext.match(new RegExp(word,"ig")) || [] ).length;
    });

    emit(null,{ count: count, doc: this });

  },
  function(key,values) {
    // Sort largest first, return first
    return values.sort(function(a,b) {
      return a.count < b.count;
    })[0];
  },
  { "out": { "inline": 1 } }
)

其结果是：

{
    "_id" : null,
    "value" : {
        "count" : 4,
        "doc" : {
            "_id" : ObjectId("5160757496cc6207a37ff778"),
            "name" : "Pomegranate Yogurt Bowl",
            "description" : "A simple breakfast bowl made with Greek yogurt, fresh pomegranate juice, puffed quinoa cereal, toasted sunflower seeds, and honey."
        }
    }
}

因此，“文本”索引方法是根据匹配的数量“加权”，然后只返回最大的加权匹配。

mapReduce操作遍历每个文档并计算出一个分数。然后“还原者”对结果进行排序，只保留得分最高的结果。

注意，可以多次调用“还原器”，因此“不”尝试一次对集合中的所有文档进行排序。但它仍然是真正的“蛮力”。