mongodb-indexes

问题 I want to return all IDs from a MongoDB collection and I used the code below: db.coll.find({}, { _id: 1}) But MongoDB scans the whole collection instead of reading the information from the default index { _id: 1 } . From the log: { find: "collection", filter: {}, projection: { _id: 1 } } planSummary: COLLSCAN cursorid:30463374118 keysExamined:0 docsExamined:544783 numYields:4286 nreturned:544782 reslen:16777238 locks:{ Global: { acquireCount: { r: 8574 } }, Database: { acquireCount: { r: 4287

问题 I want to return all IDs from a MongoDB collection and I used the code below: db.coll.find({}, { _id: 1}) But MongoDB scans the whole collection instead of reading the information from the default index { _id: 1 } . From the log: { find: "collection", filter: {}, projection: { _id: 1 } } planSummary: COLLSCAN cursorid:30463374118 keysExamined:0 docsExamined:544783 numYields:4286 nreturned:544782 reslen:16777238 locks:{ Global: { acquireCount: { r: 8574 } }, Database: { acquireCount: { r: 4287

问题 I'm having performance issues when querying ~12,000 user documents, indexed by 1 column, (companyId), no other filter. The whole collection only has ~27000. It took me about 12 seconds to get the ~12000 rows of data... I tried running explain for this query: db.instoreMember.find({companyId:"5b6be3e2096abd567974f924"}).explain(); result follows: { "queryPlanner" : { "plannerVersion" : 1, "namespace" : "production.instoreMember", "indexFilterSet" : false, "parsedQuery" : { "companyId" : { "$eq

问题 I'm having performance issues when querying ~12,000 user documents, indexed by 1 column, (companyId), no other filter. The whole collection only has ~27000. It took me about 12 seconds to get the ~12000 rows of data... I tried running explain for this query: db.instoreMember.find({companyId:"5b6be3e2096abd567974f924"}).explain(); result follows: { "queryPlanner" : { "plannerVersion" : 1, "namespace" : "production.instoreMember", "indexFilterSet" : false, "parsedQuery" : { "companyId" : { "$eq

问题 I have read putting indexes on low cardinality fields is pointless. Would this hold true for a compound index as such: db.perms.createIndex({"owner": 1, "object_type": 1, "target": 1}); With queries as such: db.perms.find({"owner": "me", "object_type": "square"}); db.perms.find({"owner": "me", "object_type": "circle", "target": "you"}); The amount of distinct object_type 's would grow over time (probably no more than 10 or 20 max) but would only start out with about 2 or 3. Similarly would a

问题 I have a collection of geospatial+temporal data with a few additional properties, which I'll be displaying on a map. The collection has a few million documents at this point, and will grow over time. Each document has the following fields: Location: [geojson object] Date: [Date object] ZoomLevel: [int32] EntryType: [ObjectID] I need to be able to rapidly query this collection by any combination of location (generally a geowithin query), Date (generally $gte/$lt), ZoomLevel and EntryType. What

问题 Considering I have search pannel that inculude multiple options like in the picture below: I'm working with mongo and create compound index on 3-4 properties with specific order. But when i run a different combinations of searches i see every time different order in execution plan (explain()). Sometime i see it on Collection scan (bad) , and sometime it fit right to the index (IXSCAN). The selective fields that should handle by mongo indexes are: (brand,Types,Status,Warehouse,Carries ,Search

问题 Per Mongo's latest $group documentation, there is a special optimization for $first: Optimization to Return the First Document of Each Group If a pipeline sorts and groups by the same field and the $group stage only uses the $first accumulator operator, consider adding an index on the grouped field which matches the sort order. In some cases, the $group stage can use the index to quickly find the first document of each group. It makes sense, since only the first entry in an ordered index

问题 I know, I know, hint forces MongoDB to use a specific index. I have two queries: db.mycol.find({sourceId:ObjectId("596bac5a6f473e1a042bFFFF"),myFlag:false}).count() db.mycol.find({sourceId:ObjectId("596bac5a6f473e1a042bFFFF"),myFlag:false}).hint("sourceId_-1_myFlag_-1").count() Both of these commands take different time: Without hint: 4-6 seconds With hint : 0-1 second However, both of the commands are using the same index: { "sourceId" : -1, "myFlag" : -1 } When I execute db.mycol.aggregate(

问题 According to Mongo Documentation, The { item : null } query matches documents that either contain the item field whose value is null or that do not contain the item field. I can't find documentation for this, but as far as I can tell, both cases (value is null or field is missing) are stored in the index as null . So if I do db.orders.createIndex({item: 1}) and then db.orders.find({item: null}) , I would expect an IXSCAN to find all documents that either contain the item field whose value is