Mongodb聚合——排序让查询变得很慢 [英] Mongodb aggregation - sort makes the query very slow
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问题描述
Mongodb 3.2，安装在 centos 6 上，具有大量 RAM 和磁盘.我有一个包含 10K 文档的集合，其结构如下:
Mongodb 3.2, installed on centos 6, with plenty of RAM and disk. I've a collection with 10K documents of the following structure:
{
"id":5752034,
"score":7.6,
"name":"ASUS X551 15.6-inch Laptop",
"categoryId":"803",
"positiveAspects":[{
"id":30030525,
"name":"price",
"score":9.8,
"frequency":139,
"rank":100098
},
{
"id":30028399,
"name":"use",
"score":9.9,
"frequency":99,
"rank":100099
}
.
.
]
}
对于每个文档，嵌套数组 positiveAspects 有几百个元素.
For each document, the nested array positiveAspects has few hundreds of elements.
收藏品有以下索引:
{ "v" : 1, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "proddb.product_trees" }
{ "v" : 1, "key" : { "positiveAspects.id" : 1.0, "positiveAspects.score" : 1.0 }, "name" : "positiveAspects.id_1_positiveAspects.score_1", "ns" : "proddb.product_trees" }
{ "v" : 1, "key" : { "categoryId" : 1.0, "score" : 1.0 }, "name" : "categoryId_1_score_1", "ns" : "proddb.product_trees" }
{ "v" : 1, "key" : { "rank" : -1.0 }, "name" : "rank_-1", "ns" : "proddb.product_trees" }
{ "v" : 1, "key" : { "positiveAspects.rank" : -1.0 }, "name" : "positiveAspects.rank_-1", "ns" : "proddb.product_trees" }
我想运行以下聚合，大约需要 40 秒:
I would like to run the following aggregation, it takes about 40 seconds:
{
aggregate:"product_trees",
pipeline:[
{
$match:{
categoryId:"803",
score:{
$gte:8.0
}
}
},
{
$unwind:"$positiveAspects"
},
{
$match:{
positiveAspects.id:30030525,
positiveAspects.score:{
$gte:9.0
}
}
},
{
$sort:{
positiveAspects.rank:-1
}
},
{
$project:{
_id:0,
score:1,
id:1,
name:1,
positiveAspects:1
}
},
{
$limit:10
}
]
}
以下解释:
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Beginning planning...
=============================
Options = NO_BLOCKING_SORT INDEX_INTERSECTION
Canonical query:
ns=proddb.product_treesTree: $and
categoryId == "803"
score $gte 8.0
Sort: {}
Proj: {}
=============================
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Index 0 is kp: { _id: 1 } unique name: '_id_' io: { v: 1, key: { _id: 1 }, name: "_id_", ns: "proddb.product_trees" }
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Index 1 is kp: { positiveAspects.id: 1.0, positiveAspects.score: 1.0 } multikey name: 'positiveAspects.id_1_positiveAspects.score_1' io: { v: 1, key: { positiveAspects.id: 1.0, positiveAspects.score: 1.0 }, name: "positiveAspects.id_1_positiveAspects.score_1", ns: "proddb.product_trees" }
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Index 2 is kp: { categoryId: 1.0, score: 1.0 } name: 'categoryId_1_score_1' io: { v: 1, key: { categoryId: 1.0, score: 1.0 }, name: "categoryId_1_score_1", ns: "proddb.product_trees" }
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Index 3 is kp: { rank: -1.0 } name: 'rank_-1' io: { v: 1, key: { rank: -1.0 }, name: "rank_-1", ns: "proddb.product_trees" }
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Index 4 is kp: { positiveAspects.rank: -1.0 } multikey name: 'positiveAspects.rank_-1' io: { v: 1, key: { positiveAspects.rank: -1.0 }, name: "positiveAspects.rank_-1", ns: "proddb.product_trees" }
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Predicate over field 'score'
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Predicate over field 'categoryId'
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Relevant index 0 is kp: { categoryId: 1.0, score: 1.0 } name: 'categoryId_1_score_1' io: { v: 1, key: { categoryId: 1.0, score: 1.0 }, name: "categoryId_1_score_1", ns: "proddb.product_trees" }
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Rated tree:
$and
categoryId == "803" || First: 0 notFirst: full path: categoryId
score $gte 8.0 || First: notFirst: 0 full path: score
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Tagging memoID 1
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Enumerator: memo just before moving:
2016-06-01T16:10:49.140-0500 D QUERY [conn47] About to build solntree from tagged tree:
$and
categoryId == "803" || Selected Index #0 pos 0
score $gte 8.0 || Selected Index #0 pos 1
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Planner: adding solution:
FETCH
---fetched = 1
---sortedByDiskLoc = 0
---getSort = [{ categoryId: 1 }, { categoryId: 1, score: 1 }, { score: 1 }, ]
---Child:
------IXSCAN
---------keyPattern = { categoryId: 1.0, score: 1.0 }
---------direction = 1
---------bounds = field #0['categoryId']: ["803", "803"], field #1['score']: [8.0, inf.0]
---------fetched = 0
---------sortedByDiskLoc = 0
---------getSort = [{ categoryId: 1 }, { categoryId: 1, score: 1 }, { score: 1 }, ]
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Planner: outputted 1 indexed solutions.
2016-06-01T16:10:49.140-0500 D QUERY [conn47] Only one plan is available; it will be run but will not be cached. query: { categoryId: "803", score: { $gte: 8.0 } } sort: {} projection: {}, planSummary: IXSCAN { categoryId: 1.0, score: 1.0 }
2016-06-01T16:11:27.170-0500 I COMMAND [conn47] command proddb.product_trees command: aggregate { aggregate: "product_trees", pipeline: [ { $match: { categoryId: "803", score: { $gte: 8.0 } } }, { $unwind: "$positiveAspects" }, { $match: { positiveAspects.id: 30030525, positiveAspects.score: { $gte: 9.0 } } }, { $sort: { positiveAspects.rank: -1 } }, { $project: { _id: 0, score: 1, id: 1, name: 1, positiveAspects: 1 } }, { $limit: 10 } ], cursor: {} } keyUpdates:0 writeConflicts:0 numYields:226 reslen:7459 locks:{ Global: { acquireCount: { r: 906 } }, Database: { acquireCount: { r: 453 } }, Collection: { acquireCount: { r: 453 } } } protocol:op_query 38030ms
取出$sort，查询运行2秒.
你能解释一下为什么 $sort 会导致这样的性能下降，考虑到它可以使用索引吗?有没有我遗漏的索引 可以做些什么来修复?
Can you explain why the $sort cause such performance hit, considerig there is index it can use? Is there an index I missed What can be done in order to fix?
谢谢！
Mongodb 聚合 - 排序使查询非常慢
Mongodb aggregarion - sort makes the query very slow
推荐答案
这是因为$sort在聚合框架早期不使用时没有使用索引.要利用索引，必须使用 $sort 或 $match 作为第一阶段.
It's because $sort is not using index when not used in early stage of aggregation framework. To take advantage of indexing, $sort or $match must be used as first stage.
请参阅 管道运算符和索引
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