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Mongodb 3.2, installiert auf Centos 6, mit viel RAM und Festplatte. Ich habe eine Sammlung mit 10K Dokumente der folgenden Struktur:Mongodb Aggregation - Sortierung macht die Abfrage sehr langsam
{
"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
}
.
.
]
}
Für jedes Dokument, das verschachtelte Array positiveAspects hat einige hundert Elemente.
Die collectoin hat die follwing Indizes:
{ "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" }
Ich möchte folgende Aggregation laufen, dauert es etwa 40 Sekunden:
{
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
}
]
}
Mit der folgenden Erklärung:
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
Unter der $sort wird die Abfrage in 2 Sekunden ausgeführt.
Können Sie erklären, warum die $sort Ursache solcher Leistung schlagen, prüfen, gibt es Index, den es verwenden kann? Gibt es einen Index, den ich übersehen habe? Was kann getan werden, um das Problem zu beheben?
Danke!
MongoDB aggregarion - macht sortiert die Abfrage sehr langsam
versuchen Sie, das $ -Projekt so umzuordnen, dass das '$ sort' direkt vom' $ limit' folgt, da es eine Optimierung gibt, die Sie verwenden können. https://docs.mongodb.com/manual/core/aggregation-pipeline-optimization/#sort-limit-coalescence – CodeMan
Ich habe das versucht, aber es hat die Antwortzeit nicht beeinflusst. – Seffy