在pymongo中通过一个查询匹配MongoDB中的多个值。

Question

我有一个集合测试，它有以下的值，我必须根据 "值 "字段得到文档，我可以很容易地从下面给出的查询中得到。

db.getCollection('test').find({"value" : 100})

但真正的问题是，我有一个 "值 "字段的列表，如[100,104,200152,......]这个列表可以是非常长的，我希望我的结果在下面给定的格式，以减少Mongo查询的数量，因为这是花费太多的时间，如果列表中包含的 "值 "是太大，那么我必须预先执行多个Mongo查询，以获取所有的记录。

{100:[
    /* 1 */

    {
        "_id" : "C1",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }

    /* 2 */
    {
        "_id" : "C2",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }

    /* 3 */
    {
        "_id" : "C3",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }

    /* 4 */
    {
        "_id" : "C4",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }

    /* 5 */
    {
        "_id" : "CO",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }

    /* 6 */
    {
        "_id" : "DD",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }

    /* 7 */
    {
        "_id" : "EX",
        "value" : 100,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }],

104:

    [{
        "_id" : "AU",
        "value" : 104,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }],
200152:

    [
    {
        "_id" : "GenFile",
        "value" : 200152,
        "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
        "timetaken" : 3.0
    }
    ]

数据库

/* 1 */
{
    "_id" : "AU",
    "value" : 104,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 2 */
{
    "_id" : "C1",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 3 */
{
    "_id" : "C2",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 4 */
{
    "_id" : "C3",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 5 */
{
    "_id" : "C4",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 6 */
{
    "_id" : "CO",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 7 */
{
    "_id" : "DD",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 8 */
{
    "_id" : "EX",
    "value" : 100,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 9 */
{
    "_id" : "GS_SEG",
    "value" : 124755350,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

/* 10 */
{
    "_id" : "GenFile",
    "value" : 200152,
    "lastUpdatedTime" : ISODate("2019-11-04T00:00:00.000Z"),
    "timetaken" : 3.0
}

Answer 1

你可以使用下面的聚合来为你做这些工作。但是，它将有值字段 100,104 作为字符串而不是数字（我不得不用 toString 操作符，否则我会收到错误信息）。)

db.collection.aggregate([
  {
    $group: {
      _id: "$value",
      root: {
        $push: "$$ROOT"
      }
    }
  },
  {
    $project: {
      k: {
        $toString: "$_id"
      },
      v: "$root",
      _id: 0
    }
  },
  {
    $group: {
      _id: null,
      x: {
        $push: "$$ROOT"
      }
    }
  },
  {
    $project: {
      _id: 0,
      x: {
        $arrayToObject: "$x"
      }
    }
  },
  {
    $replaceRoot: {
      newRoot: "$x"
    }
  }
])

以下将是输出。

[
  {
    "1.24755e+08": [
      {
        "_id": "GS_SEG",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 1.2475535e+08
      }
    ],
    "100": [
      {
        "_id": "C1",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      },
      {
        "_id": "C2",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      },
      {
        "_id": "C3",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      },
      {
        "_id": "C4",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      },
      {
        "_id": "CO",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      },
      {
        "_id": "DD",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      },
      {
        "_id": "EX",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 100
      }
    ],
    "104": [
      {
        "_id": "AU",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 104
      }
    ],
    "200152": [
      {
        "_id": "GenFile",
        "lastUpdatedTime": ISODate("2019-11-04T00:00:00Z"),
        "timetaken": 3,
        "value": 200152
      }
    ]
  }
]

Answer 2

你搜索的方向是对的, 你要防止你的代码把大部分时间花在网络请求上. pymongo的 $in 操作符选择字段值等于指定数组中任何值的文档。

在您的案例中，它看起来像这样。

# Set or build a list of the values
list_with_values =  [100, 104, 200152]

# Make one call to the DB, asking for all of the matching records.
result = db.getCollection('test').find({"value" : {"$in": list_with_values})

进一步参考如何使用 $in 操作符的工作原理。http:/docs.mongodb.orgmanualreferenceoperatorqueryin