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Learning MongoDB 5: MongoDB query (array, embedded documentation) (2), mongodb embedded1. Introduction We introduced db in the previous article. collection. find () can be used to query conditions and specify fields returned by using the projection operator to omit this para
want to take full advantage of MongoDB performance, it is recommended to adopt the Insert method without "_id", and then index the related fields to query .8.2 Testing issues that require further attentionThe read test for MongoDB is poorly thought out, although this is just an extra test. In this test, it is necessar
also in reverse order ), and the performance of 10 records is returned after the Skip100 records. The impact of Skip and Order on the performance is measured. 7) query the performance of 100 records (that is, KB) (no sorting and no conditions). This test is to test the performance
Different query operators in MongoDB treat null values differently.The examples on this page with the Db.collection.find () method in the MONGO shell. To populate the users collection referenced in the examples, run the following in MONGO Shell:Db.users.insert ( [ {"_id":, "name": null}, {"_id": 901} ])Equality FilterThe {name:null} query matches do
Statement: The article is mainly from the "MongoDB Real Combat" a book, the main want to learn MongoDB knowledge through the book, deepen understanding, so write in their blog, as recorded in the last chapter, there will be a collection of MongoDB database application Java EE Web application.1, MongostatThis tool provides a quick view of statistics for a set of r
Lesson 5 MongoDB Data Query (II): mongodb Data Query1. Course outlineThis course continues to explain MongoDB Data Query related content, including MongoDB cursor, fuzzy query, and use
Lesson 4 MongoDB Data Query (1): mongodb Data Query1. Course outlineThis course mainly describes MongoDB Data Query related content, including the introduction and use of the find function, query operator introduction and use, emb
comparison of Hubble+sqlserver, Hubble+mongodb and lucene.net in high concurrency of stand-alone systems.Test method:Through the test code query 10 times per second, query 840 commonly used English words search, return to the first 10 title and content, sorted by matching degreeTest Case 1:In this test case, we de-hubbledotnet all the caches so that Hubbledotnet
field, and just the bo NUS field in the documents in the points array. The _id field is returned by default.Db.users.find ({status: "A"}, {name:1, status:1, "Points.bonus": 1})The operation returns the following documents:{"_id": 2, "name": "Bob", "status": "A", "points": [{"Bonus": $}, {"Bonus": 12}]} {"_id": 3, "name": "Ahn", "status": "A", "points": [{"Bonus": 8}, {"Bonus": 20}]} {"_id": 6, "name": "abc", "Status": "A", "points": [{"Bonus": 8}, {"Bonus": 7}]}Project specific array Elements i
same key" When sorting by key, the MongoDB does not enforce the value of the key, and we also encounter the same key in practice, in which a string is a number in another document, and the document is sorted in any way. In MongoDB, there is a predefined order, from small to large, followed by: (1): Minimum value (2): null (3): Digital (integral type, long integer, double precision) (4): string (5): Objects
MongoDB query, index and aggregation, MongoDB, and index aggregation Initialize the mongodb Database > Use dengswitched to db deng> db. createCollection ("jingdong") # No parameter {"OK": 1}> show collectionsjingdongsystem. indexes> userdoc1 = ({"user_id": 1, "name": "cloud", "state": "active", "actor": "user ", "e-mai
Tags: 2.4 cer first network password definition capability parameter securityMongoDB's library-level lock MongoDB is currently the most popular NoSQL database, with its natural document-type data structures, flexible data patterns, and easy-to-use horizontal scaling capabilities that have been favored by many developers. But gold is no can't pure perfect, MongoDB is not without its weaknesses, such as its l
Mongodb fuzzy query tutorial, mongodb fuzzy queryUse the RockMongo client tool for fuzzy search {"Content": "$ regex": "123456 "}Fuzzy search in other cases Query contains XXX {Name:/xxx /} Query starts with XXX {Name:/^ xxx /} Que
Query the embedded document and query the normal document is exactly the same;For example:>db.post.find () { "_id" :objectid ("54ace1394ba07ed75df68f90"), "Name" :{ "FirstName" : "Joe", "LastName" : "Schome" }, " Age ":28}{" _id ":objectid (" 54ace14a4ba07ed75df68f91 " ), "name" :{ "FirstName" : "snail", "LastName" : "Yu" NBSP;}, "Age" :29}{ "_id" :objectid (" 54ace18d4ba07ed75df68f92 ")," name ":{" FirstN
"), "id" :8, "test8" NBSP;: 8}{ "_id" :objectid ("54a970901b5afd45354fd08c"), "id" :9, "Test9" :9}{ "_id" :objectid (" 54a9709c1b5afd45354fd08d ")," id ":10," test10 ":10} { "_id" :objectid ("54aa8a90652d8bdfa0566d34"), "id" :11, "test10" :11}>db.post.find ({"id": {$mod: [5,1]}}) { "_id" :objeCtId ("54a530c3ff0df3732bac1680"), "id" :1, "name" : "Joe", "Age" NBSP;: 30, "Comments" :[ "Test2", "Test9", "test5" ], "Sex" NBSP;: 1, "School" : "Marry" }{ "_id" :objectid (" 54a970351b5afd45354fd089 "),
; Db.post.find ({"id": +}) {"_id": ObjectId ("54AA97D794DCF31069B590CB"), "id": +, "fruit": ["apple", "Kumquat", "Orange", "fruit01"]} >Returns the first two values of an array> Db.post.find ({"id": 13},{"fruit": {$slice: 2}}) {"_id": ObjectId ("54AA97D794DCF31069B590CB"), "id": "Fruit":["Apple", "Kumquat"]} >Returns the latter two values of an array> Db.post.find ({"id": 13},{"fruit": {$slice: -2}}) {"_id": ObjectId ("54AA97D794DCF31069B590CB"), "id": "Fruit":["Orange", "fruit01"]} >Returns the
MongoDB Introduction MongoDB is a database based on distributed file storage. Written by the C + + language. Designed to provide scalable, high-performance data storage solutions for WEB applications. MongoDB is a product between relational database and non relational database, and is the most powerful and relational
Chapter III index operations and performance testing The importance of indexes under big data is not much to say.The following test used a MongoDB client tool Robomongo, you can choose to download on the Internet. Inserting test dataInsert 1 million test data first for (var i=1;i1000000; i++) { var person={name: "Jack" +i,age:i,address:["Henan", "Wuhan"],course:[{name: "Shuxue", Score:i },{Name: "Wu
High Performance MySQL Reading Notes-query performance optimization, high performance mysql For high-performance database operations, it is not enough to design the optimal database table structure and build the best index. You also need to design the
array and return the document data Grammar: Example: Returns a document with a quantity of 2 You can also query Db.orders.find ({"Items.quantity": 2}) (2) $elemMatch can carry multiple query conditions Example: The quantity in our query array equals 4 and Ino equals 002, but we want to return this document with quantity equal to 4 in the array
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