我们在亚马逊实例上使用MongoDB 2.6.4。我们的查询花费了过多的时间来返回结果。注意：我们正在使用10gen php驱动程序，但已提取原始查询以便对查询本身进行故障排除。
@db.instant_leads_properties.aggregate(
[
{
"$match":{
"$or":[
{
"address":{
"$regex":"Louisiana",
"$options":"i"
}
},
{
"notes":{
"$regex":"Louisiana",
"$options":"i"
}
},
{
"city":"Louisiana"
},
{
"state":"louisiana"
},
{
"zip":"71230"
}
],
"$and":[
{
"featured_expires":{
"$gt":{
"sec":1407957033,
"usec":0
}
}
}
]
}
},
{
"$sort":{
"listing_date":-1
}
},
{
"$skip":0
},
{
"$limit":10
}
]
);
如果我们直接在mongodb服务器上运行查询，则需要20秒才能返回任何内容。
似乎导致问题的具体部分如下。如果删除了这个，那么我们会得到一个包含记录的结果。
"$and":[
{
"featured_expires":{
"$gt":{
"sec":1407957033,
"usec":0
}
}
}
]
我创建了索引，复合索引，并使用10gen优化的mongodb AMI配置了amazon ec2实例。这些尝试都没有产生任何影响。我们的db统计数据如下：
{
"serverUsed": "REMOVED",
"db": "REMOVED",
"collections": 10,
"objects": 4719489,
"avgObjSize": 1222.960180646676,
"dataSize": 5.77174712E9,
"storageSize": 6.340694016E9,
"numExtents": 49,
"indexes": 39,
"indexSize": 6.506763312E9,
"fileSize": 1.4958985216E10,
"nsSizeMB": 16,
"dataFileVersion": {
"major": 4,
"minor": 6
},
"extentFreeList": {
"num": 0,
"totalSize": 0
},
"ok": 1.0
}
The stats for the collection being used (instant_leads_properies) are as follows:
{
"serverUsed": "REMOVED",
"ns": "staging.instant_leads_properties",
"count": 2204568,
"size": 5.447771456E9,
"avgObjSize": 2471,
"storageSize": 5.877628928E9,
"numExtents": 21,
"nindexes": 31,
"lastExtentSize": 1532088320,
"paddingFactor": 1.0040000000383855,
"systemFlags": 0,
"userFlags": 1,
"totalIndexSize": 6.4251096E9,
"indexSizes": {
"_id_": 71564528,
"listing_key_1": 120252608,
"state_1_property_type_1_city_1_listing_date_1": 199379936,
"state_1_property_type_1_zip_1_listing_date_1": 184082640,
"state_1_property_type_1_county_1_listing_date_1": 192258640,
"asking_price_1": 103418224,
"living_area_1": 95144112,
"living_area_1_asking_price_1": 117047616,
"listing_date_1_living_area_1_asking_price_1": 137340448,
"zip_1_living_area_1_asking_price_1": 142286928,
"longitude_1_latitude_1": 98978656,
"rem_id_1_created_at_-1": 57837024,
"rem_id_1_listing_date_-1": 54501216,
"point_2dsphere": 37740416,
"property_type_1": 66650752,
"address_1": 78890224,
"notes_1": 861096320,
"city_1": 60543280,
"state_1": 59096128,
"zip_1": 51582384,
"property_type_1_featured_expired_1": 69046320,
"property_type_1_featured_expires_1": 69054496,
"city_1_state_1_zip_1": 100303168,
"address_1_city_1_state_1_zip_1": 144159232,
"address_1_city_1_state_1_zip_1_featured_expires_1": 146423984,
"latitude_1": 112501760,
"notes_text": 2.717898624E9,
"featured_expires_1": 37724064,
"sec_1": 37724064,
"usec_1": 37724064,
"address_1_city_1_state_1_zip_1_featured_expires_1_listing_date_-1": 162857744
},
"ok": 1.0
}
以及此集合的索引列表：
{ "v" : 1 , "key" : { "_id" : 1} , "ns" : "staging.instant_leads_properties" , "name" : "_id_"}
{ "v" : 1 , "key" : { "listing_key" : 1} , "unique" : true , "ns" : "staging.instant_leads_properties" , "background" : true , "name" : "listing_key_1"}
{ "v" : 1 , "key" : { "state" : 1 , "property_type" : 1 , "city" : 1 , "listing_date" : 1} , "ns" : "staging.instant_leads_properties" , "background" : true , "name" : "state_1_property_type_1_city_1_listing_date_1"}
{ "v" : 1 , "key" : { "state" : 1 , "property_type" : 1 , "zip" : 1 , "listing_date" : 1} , "ns" : "staging.instant_leads_properties" , "background" : true , "name" : "state_1_property_type_1_zip_1_listing_date_1"}
{ "v" : 1 , "key" : { "state" : 1 , "property_type" : 1 , "county" : 1 , "listing_date" : 1} , "ns" : "staging.instant_leads_properties" , "background" : true , "name" : "state_1_property_type_1_county_1_listing_date_1"}
{ "v" : 1 , "key" : { "asking_price" : 1} , "ns" : "staging.instant_leads_properties" , "name" : "asking_price_1" , "background" : true}
{ "v" : 1 , "key" : { "living_area" : 1} , "ns" : "staging.instant_leads_properties" , "name" : "living_area_1" , "background" : true}
{ "v" : 1 , "key" : { "living_area" : 1 , "asking_price" : 1} , "ns" : "staging.instant_leads_properties" , "name" : "living_area_1_asking_price_1" , "background" : true}
{ "v" : 1 , "key" : { "listing_date" : 1 , "living_area" : 1 , "asking_price" : 1} , "ns" : "staging.instant_leads_properties" , "name" : "listing_date_1_living_area_1_asking_price_1" , "background" : true}
{ "v" : 1 , "key" : { "zip" : 1 , "living_area" : 1 , "asking_price" : 1} , "ns" : "staging.instant_leads_properties" , "name" : "zip_1_living_area_1_asking_price_1" , "background" : true}
{ "v" : 1 , "key" : { "longitude" : 1.0 , "latitude" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "longitude_1_latitude_1"}
{ "v" : 1 , "key" : { "rem_id" : 1.0 , "created_at" : -1.0} , "ns" : "staging.instant_leads_properties" , "name" : "rem_id_1_created_at_-1"}
{ "v" : 1 , "key" : { "rem_id" : 1.0 , "listing_date" : -1.0} , "ns" : "staging.instant_leads_properties" , "name" : "rem_id_1_listing_date_-1"}
{ "v" : 1 , "key" : { "point" : "2dsphere"} , "ns" : "staging.instant_leads_properties" , "name" : "point_2dsphere"}
{ "v" : 1 , "key" : { "property_type" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "property_type_1"}
{ "v" : 1 , "key" : { "address" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "address_1"}
{ "v" : 1 , "key" : { "notes" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "notes_1"}
{ "v" : 1 , "key" : { "city" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "city_1"}
{ "v" : 1 , "key" : { "state" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "state_1"}
{ "v" : 1 , "key" : { "zip" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "zip_1"}
{ "v" : 1 , "key" : { "property_type" : 1.0 , "featured_expired" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "property_type_1_featured_expired_1"}
{ "v" : 1 , "key" : { "property_type" : 1.0 , "featured_expires" : 1.0} , "ns" : "staging.instant_leads_properties" , "name" : "property_type_1_featured_expires_1"}
{ "v" : 1 , "key" : { "city" : 1.0 , "state" : 1.0 , "zip" : 1.0} , "name" : "city_1_state_1_zip_1" , "ns" : "staging.instant_leads_properties"}
{ "v" : 1 , "key" : { "address" : 1.0 , "city" : 1.0 , "state" : 1.0 , "zip" : 1.0} , "name" : "address_1_city_1_state_1_zip_1" , "ns" : "staging.instant_leads_properties"}
{ "v" : 1 , "key" : { "address" : 1.0 , "city" : 1.0 , "state" : 1.0 , "zip" : 1.0 , "featured_expires" : 1.0} , "name" : "address_1_city_1_state_1_zip_1_featured_expires_1" , "ns" : "staging.instant_leads_properties"}
{ "v" : 1 , "key" : { "latitude" : 1.0} , "name" : "latitude_1" , "ns" : "staging.instant_leads_properties" , "background" : true}
{ "v" : 1 , "key" : { "_fts" : "text" , "_ftsx" : 1} , "name" : "notes_text" , "ns" : "staging.instant_leads_properties" , "weights" : { "notes" : 1} , "default_language" : "english" , "language_override" : "language" , "textIndexVersion" : 2}
{ "v" : 1 , "key" : { "featured_expires" : 1.0} , "name" : "featured_expires_1" , "ns" : "staging.instant_leads_properties"}
{ "v" : 1 , "key" : { "sec" : 1.0} , "name" : "sec_1" , "ns" : "staging.instant_leads_properties"}
{ "v" : 1 , "key" : { "usec" : 1.0} , "name" : "usec_1" , "ns" : "staging.instant_leads_properties"}
{ "v" : 1 , "key" : { "address" : 1.0 , "city" : 1.0 , "state" : 1.0 , "zip" : 1.0 , "featured_expires" : 1.0 , "listing_date" : -1.0} , "name" : "address_1_city_1_state_1_zip_1_featured_expires_1_listing_date_-1" , "ns" : "staging.instant_leads_properties"}
请告诉我其他信息可以提供哪些信息。
感谢 杰森
答案 0 :(得分：0)
我的建议是在address，notes，city和state上创建文字索引：
db.instant_lead_properties.ensureIndex({address:"text",notes:"text",city:"text", state:"text"})
并按如下方式调整聚合的匹配部分：
[...]
$match:
{
$text: { $search: "Louisiana" },
"featured_expires": { "$gt": { "sec":1407957033,"usec":0 } }
}
[...]
通过这种方式，您阻止了$or和$and的链接，根据我的经验，这会对性能产生影响。
加权结果等整洁的功能也随之而来。
此外，这两个字段的复合索引可能有所帮助，而不是为sec和usec提供两个单独的索引。
如果没有详细了解MMS监控并且不知道服务器的确切配置，我就可以从这里看到更多信息。