Php 数组元素聚合中的mongodb avg

我有以下收集结构

{
   "_id": {
     "d_timestamp": NumberLong(1429949699),
     "d_isostamp": ISODate("2015-04-25T08:14:59.0Z")
   },
   "XBT-USD-cpx-okc": [
   {
       "buySpread": -1.80081
   }

{
  "_id": {
     "isodate": ISODate("2015-04-25T08:00:58.0Z")
  },
  "rsell_spread": [
     -4.49996▼
  ]
}

我运行以下聚合

$spreadName ='XBT-USD-stp-nex';
$pipe = array(
    array(
        '$match' => array(
            '_id.d_isostamp' => array(
                '$gt' => $start, '$lt' => $end
            )
        )
    ),
    array(
        '$project' => array(
            'sellSpread' =>'$'.$spreadName.'.sellSpread',
        )
    ),
    array(
        '$group' => array(
            '_id' => array(
                'isodate' => array(
                    '$minute' => '$_id.d_isostamp'
                )
            ),
            'rsell_spread' => array(
                '$avg' => '$sellSpread'
            ),
        )
    ),
);

$out = $collection->aggregate($pipe ,$options);

结果是，

rsell_spread

的值为0，而如果我在

$group

中运行

$max

而不是

$avg

，我会得到

rsell_spread

的准确值，具有以下结构

{
   "_id": {
     "d_timestamp": NumberLong(1429949699),
     "d_isostamp": ISODate("2015-04-25T08:14:59.0Z")
   },
   "XBT-USD-cpx-okc": [
   {
       "buySpread": -1.80081
   }

{
  "_id": {
     "isodate": ISODate("2015-04-25T08:00:58.0Z")
  },
  "rsell_spread": [
     -4.49996▼
  ]
}

所以我有两个问题：

1/为什么

$avg

功能不工作

2/例如，当我使用

$max

时（仅使用一个常规数字），我如何能够使结果不在数组中

组累加器操作符确实有效，只是在您的情况下，它被应用于数组中的一个元素，从而给出了“不正确”的结果

使用group accumulator运算符时，它返回将表达式应用于文档组中的每个文档所产生的最高值，因此在您的示例中，它返回了最大数组

演示这一点，考虑在蒙哥马尔的测试集合中添加一些示例文档：

db.test.insert([
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949699),
        "d_isostamp" : ISODate("2015-04-25T08:14:59.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80081
        }
    ]
},
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949710),
        "d_isostamp" : ISODate("2015-04-25T08:15:10.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80079
        }
    ]
},
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949720),
        "d_isostamp" : ISODate("2015-04-25T08:15:20.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80083
        }
    ]
},
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949730),
        "d_isostamp" : ISODate("2015-04-25T08:15:30.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80087
        }
    ]
}
])

var spreadName = "XBT-USD-stp-nex",
    start = new Date(2015, 3, 25),
    end = new Date(2015, 3, 26);
db.test.aggregate([
    {
        "$match": {
            "_id.d_isostamp": { "$gte": start, "$lte": end }
        }
    },
    {
        "$project": {
            "sellSpread": "$"+spreadName+".sellSpread"
        }
    }/*,<--- deliberately omitted the $unwind stage from the pipeline to replicate the current pipeline
    {
        "$unwind": "$sellSpread"
    }*/,
    {
        "$group": {
            "_id": {
                "isodate": { "$minute": "$_id.d_isostamp"}
            },
            "rsell_spread": {
                "$avg": "$sellSpread"
            }
        }
    }
])

现在，在mongoshell中复制上述相同操作：

db.test.insert([
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949699),
        "d_isostamp" : ISODate("2015-04-25T08:14:59.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80081
        }
    ]
},
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949710),
        "d_isostamp" : ISODate("2015-04-25T08:15:10.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80079
        }
    ]
},
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949720),
        "d_isostamp" : ISODate("2015-04-25T08:15:20.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80083
        }
    ]
},
{
    "_id" : {
        "d_timestamp" : NumberLong(1429949730),
        "d_isostamp" : ISODate("2015-04-25T08:15:30.000Z")
    },
    "XBT-USD-stp-nex" : [ 
        {
            "sellSpread" : -1.80087
        }
    ]
}
])

var spreadName = "XBT-USD-stp-nex",
    start = new Date(2015, 3, 25),
    end = new Date(2015, 3, 26);
db.test.aggregate([
    {
        "$match": {
            "_id.d_isostamp": { "$gte": start, "$lte": end }
        }
    },
    {
        "$project": {
            "sellSpread": "$"+spreadName+".sellSpread"
        }
    }/*,<--- deliberately omitted the $unwind stage from the pipeline to replicate the current pipeline
    {
        "$unwind": "$sellSpread"
    }*/,
    {
        "$group": {
            "_id": {
                "isodate": { "$minute": "$_id.d_isostamp"}
            },
            "rsell_spread": {
                "$avg": "$sellSpread"
            }
        }
    }
])

解决方案是在步骤后包括一个操作员管道阶段，这将从输入文档解构

XBT USD stp nex

数组字段，并为每个元素输出一个文档。每个输出文档都用元素值替换数组。这将使组累加器操作员能够工作

包括此项将给出聚合结果：

/* 0 */
{
    "result" : [ 
        {
            "_id" : {
                "isodate" : 15
            },
            "rsell_spread" : -1.80083
        }, 
        {
            "_id" : {
                "isodate" : 14
            },
            "rsell_spread" : -1.80081
        }
    ],
    "ok" : 1
}

因此，PHP中的最终工作聚合应该是：

$spreadName ='XBT-USD-stp-nex';
$pipe = array(
    array(
        '$match' => array(
            '_id.d_isostamp' => array(
                '$gt' => $start, '$lt' => $end
            )
        )
    ),    
    array(
        '$project' => array(
            'sellSpread' =>'$'.$spreadName.'.sellSpread',
        )
    ),
    array('$unwind' => '$sellSpread'),
    array(
        '$group' => array(
            '_id' => array(
                'isodate' => array(
                    '$minute' => '$_id.d_isostamp'
                )
            ),
            'rsell_spread' => array(
                '$avg' => '$sellSpread'
            ),
        )
    ),
);

$out = $collection->aggregate($pipe ,$options);