使用PyMongo,按一个键分组似乎没问题:
results = collection.group(key={"scan_status":0}, condition={'date': {'$gte': startdate}}, initial={"count": 0}, reduce=reducer)
结果:
{u'count': 215339.0, u'scan_status': u'PENDING'} {u'count': 617263.0, u'scan_status': u'DONE'}
但是当我尝试按多个键进行分组时,我得到一个例外:
results = collection.group(key={"scan_status":0,"date":0}, condition={'date': {'$gte': startdate}}, initial={"count": 0}, reduce=reducer)
如何正确地按多个字段进行分组?
答案 0 :(得分:3)
如果您尝试计算两个键,那么虽然可以使用.group()
,但更好的选择是通过.aggregate()
。
这使用“本机代码运算符”而不是.group()
所需的JavaScript解释代码来执行与您尝试实现的相同的基本“分组”操作。
特别是这里是$group
管道运算符:
result = collection.aggregate([
# Matchn the documents possible
{ "$match": { "date": { "$gte": startdate } } },
# Group the documents and "count" via $sum on the values
{ "$group": {
"_id": {
"scan_status": "$scan_status",
"date": "$date"
},
"count": { "$sum": 1 }
}}
])
事实上,您可能想要将“日期”缩短为不同时期的内容。如:
result = collection.aggregate([
# Matchn the documents possible
{ "$match": { "date": { "$gte": startdate } } },
# Group the documents and "count" via $sum on the values
{ "$group": {
"_id": {
"scan_status": "$scan_status",
"date": {
"year": { "$year": "$date" },
"month": { "$month" "$date" },
"day": { "$dayOfMonth": "$date" }
}
},
"count": { "$sum": 1 }
}}
])
使用此处显示的Date Aggregation Operators。
或许还有基本的“日期数学”:
import datetime
from datetime import date
result = collection.aggregate([
# Matchn the documents possible
{ "$match": { "date": { "$gte": startdate } } },
# Group the documents and "count" via $sum on the values
# use "epoch" "1970-01-01" as a base to convert to integer
{ "$group": {
"_id": {
"scan_status": "$scan_status",
"date": {
"$subtract": [
{ "$subtract": [ "$date", date.fromtimestamp(0) ] },
{ "$mod": [
{ "$subtract": [ "$date", date.fromtimestamp(0) ] },
1000 * 60 * 60 * 24
]}
]
}
},
"count": { "$sum": 1 }
}}
])
这将从“epoch”时间返回整数值,而不是compisite值对象。
但所有这些选项都优于.group()
,因为它们使用本机编码例程并以比您需要提供的JavaScript代码更快的速度执行其操作。