在数组字段不为空的地方findMongoDBlogging
我所有的logging都有一个名为“图片”的字段。 这个字段是一个string数组。
我现在想要这个数组不是空的最新的10个logging。
我已经search了一下，但奇怪的是，我还没有发现很多。 我读过$ where选项，但是我想知道原生函数有多慢，以及是否有更好的解决scheme。
即使如此，这是行不通的：
ME.find({$where: 'this.pictures.length > 0'}).sort('-created').limit(10).execFind() 什么都不返回 离开this.pictures没有长度位的工作，但它也返回空logging，当然。
如果您还有没有钥匙的文件，您可以使用：
ME.find({ pictures: { $exists: true, $not: {$size: 0} } })
如果涉及到$ size，MongoDB不使用索引，所以这是一个更好的解决scheme：
ME.find({ pictures: { $exists: true, $ne: [] } })
此外，自从MongoDB 2.6发布以来，您可以与运营商$gt进行比较：
ME.find({ pictures: { $gt: [] } })
特别是在mongodb文件中，再加上一些令人困惑的东西，这个答案是：
ME.find({pictures: {$not: {$size: 0}}})
这可能也适用于你：
ME.find({'pictures.0': {$exists: true}});
从2.6版本开始，另一种方法是将该字段与一个空数组进行比较：
ME.find({pictures: {$gt: []}})
在shell中testing它：
> db.ME.insert([ {pictures: [1,2,3]}, {pictures: []}, {pictures: ['']}, {pictures: [0]}, {pictures: 1}, {foobar: 1} ]) > db.ME.find({pictures: {$gt: []}}) { "_id": ObjectId("54d4d9ff96340090b6c1c4a7"), "pictures": [ 1, 2, 3 ] } { "_id": ObjectId("54d4d9ff96340090b6c1c4a9"), "pictures": [ "" ] } { "_id": ObjectId("54d4d9ff96340090b6c1c4aa"), "pictures": [ 0 ] }
所以它正确地包含了pictures至less有一个数组元素的文档，排除了pictures是一个空数组，而不是一个数组，或丢失的文档。
在查询时，您关心两件事情 – 准确性和性能。 考虑到这一点，我在MongoDB v3.0.14中testing了几种不同的方法。
TL; DR db.doc.find({ nums: { $gt: -Infinity }})是最快和最可靠的（至less在我testing的MongoDB版本中）。
build立
我插入1k文档w / o列表字段，1k文档与空列表，5文档与非空列表。
for (var i = 0; i < 1000; i++) { db.doc.insert({}); } for (var i = 0; i < 1000; i++) { db.doc.insert({ nums: [] }); } for (var i = 0; i < 5; i++) { db.doc.insert({ nums: [1, 2, 3] }); } db.doc.createIndex({ nums: 1 });
我认识到这是不够的，像我在下面的testing中那样认真对待性能，但是足以呈现所选查询计划的各种查询和行为的正确性。
testing
db.doc.find({'nums': {'$exists': true}})返回错误的结果（我们正在努力完成）。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': {'$exists': true}}).count() 1005
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db.doc.find({'nums.0': {'$exists': true}})返回正确的结果，但是使用完整的集合扫描也很慢（请注意COLLSCAN阶段）。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums.0': {'$exists': true}}).count() 5 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums.0': {'$exists': true}}).explain() { "queryPlanner": { "plannerVersion": 1, "namespace": "test.doc", "indexFilterSet": false, "parsedQuery": { "nums.0": { "$exists": true } }, "winningPlan": { "stage": "COLLSCAN", "filter": { "nums.0": { "$exists": true } }, "direction": "forward" }, "rejectedPlans": [ ] }, "serverInfo": { "host": "MacBook-Pro", "port": 27017, "version": "3.0.14", "gitVersion": "08352afcca24bfc145240a0fac9d28b978ab77f3" }, "ok": 1 }
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db.doc.find({'nums': { $exists: true, $gt: { '$size': 0 }}})返回错误的结果。 这是因为无效的索引扫描没有推进文档。 如果没有这个指数，它可能会很准确，但速度会很慢
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $exists: true, $gt: { '$size': 0 }}}).count() 0 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $exists: true, $gt: { '$size': 0 }}}).explain('executionStats').executionStats.executionStages { "stage": "KEEP_MUTATIONS", "nReturned": 0, "executionTimeMillisEstimate": 0, "works": 2, "advanced": 0, "needTime": 0, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "inputStage": { "stage": "FETCH", "filter": { "$and": [ { "nums": { "$gt": { "$size": 0 } } }, { "nums": { "$exists": true } } ] }, "nReturned": 0, "executionTimeMillisEstimate": 0, "works": 1, "advanced": 0, "needTime": 0, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "docsExamined": 0, "alreadyHasObj": 0, "inputStage": { "stage": "IXSCAN", "nReturned": 0, "executionTimeMillisEstimate": 0, "works": 1, "advanced": 0, "needTime": 0, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "keyPattern": { "nums": 1 }, "indexName": "nums_1", "isMultiKey": true, "direction": "forward", "indexBounds": { "nums": [ "({ $size: 0.0 }, [])" ] }, "keysExamined": 0, "dupsTested": 0, "dupsDropped": 0, "seenInvalidated": 0, "matchTested": 0 } } }
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db.doc.find({'nums': { $exists: true, $not: { '$size': 0 }}})返回正确的结果，但是性能很差。 它在技术上做了索引扫描，但它仍然推进所有的文档，然后必须通过它们进行筛选）。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $exists: true, $not: { '$size': 0 }}}).count() 5 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $exists: true, $not: { '$size': 0 }}}).explain('executionStats').executionStats.executionStages { "stage": "KEEP_MUTATIONS", "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 2016, "advanced": 5, "needTime": 2010, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "inputStage": { "stage": "FETCH", "filter": { "$and": [ { "nums": { "$exists": true } }, { "$not": { "nums": { "$size": 0 } } } ] }, "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 2016, "advanced": 5, "needTime": 2010, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "docsExamined": 2005, "alreadyHasObj": 0, "inputStage": { "stage": "IXSCAN", "nReturned": 2005, "executionTimeMillisEstimate": 0, "works": 2015, "advanced": 2005, "needTime": 10, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "keyPattern": { "nums": 1 }, "indexName": "nums_1", "isMultiKey": true, "direction": "forward", "indexBounds": { "nums": [ "[MinKey, MaxKey]" ] }, "keysExamined": 2015, "dupsTested": 2015, "dupsDropped": 10, "seenInvalidated": 0, "matchTested": 0 } } }
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db.doc.find({'nums': { $exists: true, $ne: [] }})返回正确的结果，速度稍快，但性能仍然不理想。 它使用IXSCAN，它只提前使用现有列表字段的文档，但是必须逐个过滤掉空列表。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $exists: true, $ne: [] }}).count() 5 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $exists: true, $ne: [] }}).explain('executionStats').executionStats.executionStages { "stage": "KEEP_MUTATIONS", "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 1018, "advanced": 5, "needTime": 1011, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "inputStage": { "stage": "FETCH", "filter": { "$and": [ { "$not": { "nums": { "$eq": [ ] } } }, { "nums": { "$exists": true } } ] }, "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 1017, "advanced": 5, "needTime": 1011, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "docsExamined": 1005, "alreadyHasObj": 0, "inputStage": { "stage": "IXSCAN", "nReturned": 1005, "executionTimeMillisEstimate": 0, "works": 1016, "advanced": 1005, "needTime": 11, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "keyPattern": { "nums": 1 }, "indexName": "nums_1", "isMultiKey": true, "direction": "forward", "indexBounds": { "nums": [ "[MinKey, undefined)", "(undefined, [])", "([], MaxKey]" ] }, "keysExamined": 1016, "dupsTested": 1015, "dupsDropped": 10, "seenInvalidated": 0, "matchTested": 0 } } }
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db.doc.find({'nums': { $gt: [] }})是危险的，因为依赖于指数使用它可能会给出意想不到的结果。 这是因为索引扫描无效，没有任何文件。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $gt: [] }}).count() 0 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $gt: [] }}).hint({ nums: 1 }).count() 0 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $gt: [] }}).hint({ _id: 1 }).count() 5 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $gt: [] }}).explain('executionStats').executionStats.executionStages { "stage": "KEEP_MUTATIONS", "nReturned": 0, "executionTimeMillisEstimate": 0, "works": 1, "advanced": 0, "needTime": 0, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "inputStage": { "stage": "FETCH", "filter": { "nums": { "$gt": [ ] } }, "nReturned": 0, "executionTimeMillisEstimate": 0, "works": 1, "advanced": 0, "needTime": 0, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "docsExamined": 0, "alreadyHasObj": 0, "inputStage": { "stage": "IXSCAN", "nReturned": 0, "executionTimeMillisEstimate": 0, "works": 1, "advanced": 0, "needTime": 0, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "keyPattern": { "nums": 1 }, "indexName": "nums_1", "isMultiKey": true, "direction": "forward", "indexBounds": { "nums": [ "([], BinData(0, ))" ] }, "keysExamined": 0, "dupsTested": 0, "dupsDropped": 0, "seenInvalidated": 0, "matchTested": 0 } } }
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db.doc.find({'nums.0': { $gt: -Infinity }})返回正确的结果，但性能较差（使用完整的集合扫描）。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums.0': { $gt: -Infinity }}).count() 5 MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums.0': { $gt: -Infinity }}).explain('executionStats').executionStats.executionStages { "stage": "COLLSCAN", "filter": { "nums.0": { "$gt": -Infinity } }, "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 2007, "advanced": 5, "needTime": 2001, "needFetch": 0, "saveState": 15, "restoreState": 15, "isEOF": 1, "invalidates": 0, "direction": "forward", "docsExamined": 2005 }
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db.doc.find({'nums': { $gt: -Infinity }})令人惊讶的是，这工作得很好！ 它提供了正确的结果，而且速度很快，从索引扫描阶段推进了5个文档。
MacBook-Pro(mongod-3.0.14) test> db.doc.find({'nums': { $gt: -Infinity }}).explain('executionStats').executionStats.executionStages { "stage": "FETCH", "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 16, "advanced": 5, "needTime": 10, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "docsExamined": 5, "alreadyHasObj": 0, "inputStage": { "stage": "IXSCAN", "nReturned": 5, "executionTimeMillisEstimate": 0, "works": 15, "advanced": 5, "needTime": 10, "needFetch": 0, "saveState": 0, "restoreState": 0, "isEOF": 1, "invalidates": 0, "keyPattern": { "nums": 1 }, "indexName": "nums_1", "isMultiKey": true, "direction": "forward", "indexBounds": { "nums": [ "(-inf.0, inf.0]" ] }, "keysExamined": 15, "dupsTested": 15, "dupsDropped": 10, "seenInvalidated": 0, "matchTested": 0 } }
你可以使用下面的任何一个来达到这个目的。
两者也都处理不返回没有请求键的对象的结果：
db.video.find({pictures: {$exists: true, $gt: {$size: 0}}}) db.video.find({comments: {$exists: true, $not: {$size: 0}}})
您也可以使用助手方法存在于Mongo运算符$ exists
ME.find() .exists('pictures') .where('pictures').ne([]) .sort('-created') .limit(10) .exec(function(err, results){ ... });
ME.find({pictures: {$exists: true}})
这很简单，这对我有用。
