MongoDB Data Query | Mongodb

1. Basic query ① Method Find (): Query db. collection name. Find ({conditional document}) ② method FindOne (): Query, returns only the first DB. Collection name. FindOne ({conditional document}) ③ method Pretty () : Formats the result of the DB. Collection name. Find ({conditional document}). Pretty () 2. The comparison operator # equals, the default is equal to the judgment, no operator # is less than, $lt Less-than # is less than or equal to, $lte less-t Han,equal # greater Than, $GT Greater-than # Less than or equal to, $gte greater-than,equal # does not equal, $ne not equal db.collecti On2.find ({name: ' Guo Jing '}) db.collection2.find ({age:{$gte: 18}}) 3. Logical operator ① logic and # default is logical Relationship # Example: Query age is greater than or equal to 18        , and the gender is true of the student Db.collection2.find ({age:{$gte: +}, gender:true}) ② logic or # using $or, the value is an array, each element in the arrays is JSON # example: Query for students older than 18, or with a gender of false Db.collection2.find ({$or: [{age:{$gt: 18}},{gender:false}]}) Note: Find () >&gt ; or condition of {} >> $or [] >> >> {condition a},{condition B} >> {domain: {logical character judgment}}③ or, Shared # example: Query age greater than 18 or name is Guo Jing, and and sex for boys Db.collection2.find ({$or: [{age:{$gt:},{name}: ' Guo Jing '}],gender:true}) 4. Scope Operator # $in | $nin # Example: Query year DB.C of students aged to 18,28Ollection2.find ({age:{$in: [18, 28]}}) # Here to note that the maximum and minimum are required in the table contains these numbers 5. Support Regular Expressions # Use//or $regex write regular Expressions # example: Db.coll  Ection2.find ({name:/^ yellow/}) Db.collection2.find ({name:{$regex: ' ^ Yellow '}}) 6. Custom Query # Use $where to write a function that returns the data that satisfies the criteria # Example: query for students greater than 30 years old Db.collection2.find ({$where: function () {return this.age >}}) 7.L Imit and Skip① Method limit (): reads the specified number of document # DB. Collection name. Find (). Limit (number) Db.collection2.find (). Limit (2) # attached: The specified parameter displays all documents in the collection ② method Skip (): Used to skip the specified number of document # DB. Collection name. Find (). Skip (number) Db.stu.find (). Skip (2) # attached: parameter n Umber indicates the number of skipped records, with the default of 0③limit () with Skip () # In order of precedence, skipping the specified number of documents, and then reading the specified number of document # query data Db.collection1.find (). Limit (4). Skip (5) Db.collection1.find (). Skip (5). Limit (4) 8. Projection--Select field to display Data #①db. Collection name. Find ({},{field name: 1, ...} ) Db.collection2.find ({},{name:1, gender:1}) # ' 1 ': Indicates that the display field is not set to show that the #② is special: The _id column is displayed by default, # If it is not displayed Need to be explicitly set to 0 Db.collecTion2.find ({},{_id:0,name:1,gender:1}) 9. Sort--Sort the result set parameter 1 to arrange the parameters in ascending order-1 bits in descending order # DB. Collection name. Find (). Sort ({field: 1.    ..}) #--According to the sex descending, and then according to the Age ascending db.collection2.find (). Sort ({gender:-1,age:1}) 10. Statistics ① Method Count (): Used to count the number of document bars in the result set 1.db. Collection Name        . Find ({condition}). Count () Db.collection2.find ({gender:true}). Count () #--Count the number of boys 2.db. Collection name. Count ({condition}) Db.collection2.count ({age:{$gt: 20}, Gender:true}) #-The number of boys with a statistical age greater than 11. de-Duplication ① method Distinct (): deduplication of field data, extraction of--db.    The collection name. Distinct (' de-weight field ', {condition}) db.collection2.distinct (' hometown ', {age:{$gt: 18}}) # Query for students older than 18 years, from which provinces # 4. Aggregate query 1. Basic syntax --Syntax db. The collection name. Aggregate ({pipe: {expression}}) attached: 1. Pipelines: In Unix and Linux, the output of the current command is generally used as input to the next command 2. Expression: Handling into the document and output 2. Common Expressions $sum: computational Synthesis, $sum: 1 is counted as one count $avg: Average $min: Gets the minimum $max: Gets the maximum value $push: Inserts a value into the result document to the first document data $fi RST: Gets the first document data $last based on the sort of the resource document: Gets the last document data according to the sort of the resource document 3. Common pipeline ① $group--Groups The documents in the collection, which can be used for statistical results--_id to represent the basis for grouping, using a     field is formatted as ' $ Field '       # count the total number of boys and girls Db.stu.aggregate ({$group: {_id:            ' $gender ', counter:{$sum: 1}})--pivot data # Statistics student gender and student name Db.stu.aggregate ({$group: {_id: ' $ Gender ', name:{$push: ' $name '}})--use $ $ROOT to To add the contents of the document to the array in the result set Db.stu.aggregate ({$group: {_id: ' $ge NDEr ', name:{$push: ' $ $ROOT '}}}) ② $match- -Modify the structure of the input document, such as renaming, adding, deleting fields, creating calculation results-for filtering data, outputting only eligible documents-using MONGODB's standard query operation # Query for students older than 20 Db.stu.agg Regate ({$match: {age:{$gt: 20}}) # Query the number of boys and girls older than 20 db.stu.aggregate ({$match:        {age:{$gt: 20}}},    {$group: {_id: ' $gender ', counter:{$sum: 1}}) ③ $project-Modify the structure of the input document, such as rename, add, delete field, create calculation result # query student's name, age db.stu.aggregate ({$proj ECT:{_ID:0,NAME:1,AGE:1}) # Query the number of boys, girls, Output db.stu.aggregate ({$group: {_id: ' $gender ', Coun        ter:{$sum: 1}}, {$project: {_id:0,counter:1}}) ④ $sort--Sort input document after output # query student information by age ascending B.stu.aggregate ({$sort: {age:1}}) # Query the number of boys and girls, descending by the number of Db.stu.aggregate ({$group: {_id: ' $gender ', cou nter:{$sum: 1}}, {$sort: {counter:-1}}) ⑤ $limit and $skip--$limit # Limit the number of documents returned by the aggregation pipeline #            Query 2 Student Information db.stu.aggregate ({$limit: 2})--$skip # Skip the specified number of documents and return the remaining documents # query student information starting with 3rd Db.stu.aggregate ({$skip: 2}) # statistics male, female number, according to the number of ascending, take 2nd data db.stu.aggregate ({$group: {_id: ' $gender ', counter:{$sum: 1}} {$sort: {counter:1}} {$skip: 1}                {$limit: 1}) ⑥ $unwind Field Split query-syntax--an array field in a document contains multiple values--split multiple bars based on the value under the field--each containing a value--db the array. The collection name. Ggregate ({$unwind: ' $ field Name '}) # $unwind Aggregation method contains two properties: Path: ' $ field name ' Preservenullandemp tyarrays:< Boolean > # do not fill in properties, default = < Boolean > False # without tag attribute name--constructs data Db.t3.insert (            [{"_id": 1, "Item": "A", "Size": ["S", "M", "L"]}, {"_id": 2, "item": "B", "Size": []}, {"_id": 3, "item": "C", "Size": "M"}, {"_id": 4, "item": "D"}, {"_id": 5, "item ":" E "," size ": null}])--View the results of the query, display the document Db.t3.aggregate ({$unwind: {path: ' $s for an empty array, no fields, NULL)  Ize ', Preservenullandemptarrays:true}})--View query results, do not display empty array, no fields, NULL document Db.t3.aggregate ({$unwind: ' $size '}) Equivalent to: Db.t3.aggregate ({$unwind: {path: ' $size ', Preservenullandemptyarrays:false}})

　　

MongoDB Data Query | Mongodb