这节来说说如何检索mongodb数据。首先向文档中插入一些数据。1. 插入数据 use ttlsa_comswitched to db ttlsa_com db.mediaCollection.insert({ "Type" : "Book", "Title" : "Definitive Guide to MongoDB, the", "ISBN" : "987-1-4302-3051-9", "Publisher"
这节来说说如何检索mongodb数据。首先向文档中插入一些数据。 1. 插入数据> use ttlsa_com switched to db ttlsa_com > db.mediaCollection.insert({ "Type" : "Book", "Title" : "Definitive Guide to MongoDB, the", "ISBN" : "987-1-4302-3051-9", "Publisher" : "Apress", "Author": [ "Membrey, Peter", "Plugge, Eelco", "Hawkins, Tim" ] }) > db.mediaCollection.insert({ "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind" }) > db.mediaCollection.insert({ "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind", "Tracklist" : [ { "Track" : "1", "Title" : "Smells like teen spirit", "Length" : "5:02" }, { "Track" : "2", "Title" : "In Bloom", "Length" : "4:15" } ]}) > db.mediaCollection.find() { "_id" : ObjectId("5353462f93efef02c962da71"), "Type" : "Book", "Title" : "Definitive Guide to MongoDB, the", "ISBN" : "987-1-4302-3051-9", "Publisher" : "Apress", "Author" : [ "Membrey, Peter", "Plugge, Eelco", "Hawkins, Tim" ] } { "_id" : ObjectId("5353462f93efef02c962da72"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind" } { "_id" : ObjectId("5353463193efef02c962da73"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind", "Tracklist" : [ { "Track" : "1", "Title" : "Smells like teen spirit", "Length" : "5:02" }, { "Track" : "2", "Title" : "In Bloom", "Length" : "4:15" } ] }2. 检索 find函数是经常用到的一个。前面的文章也有介绍到。下面看看有选择性的检索,查看你感兴趣的数据。 检索"Artist" : "Nirvana"的数据:
> db.mediaCollection.find({"Artist" : "Nirvana"}).toArray() [ { "_id" : ObjectId("5353462f93efef02c962da72"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind" }, { "_id" : ObjectId("5353463193efef02c962da73"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind", "Tracklist" : [ { "Track" : "1", "Title" : "Smells like teen spirit", "Length" : "5:02" }, { "Track" : "2", "Title" : "In Bloom", "Length" : "4:15" } ] } ]上面的查询虽说检索出"Artist" : "Nirvana"的数据,但是返回了全部列的信息,但是我只要查看Title和Tracklist.Title列
> db.mediaCollection.find({"Artist" : "Nirvana"}, {Title:1, "Tracklist.Title":1}).toArray() [ { "_id" : ObjectId("5353462f93efef02c962da72"), "Title" : "Nevermind" }, { "_id" : ObjectId("5353463193efef02c962da73"), "Title" : "Nevermind", "Tracklist" : [ { "Title" : "Smells like teen spirit" }, { "Title" : "In Bloom" } ] } ]Title:1, "Tracklist.Title":1表示只返回这两列信息。升序。也可以反着来Title:0, "Tracklist.Title":0表示返回除了这两列的其他所有列信息。 注意:_id字段总是会返回。 3. ?使用逗号 当文档结构变的复杂时,如含有数组或嵌入对象文档,就需要使用到逗号,来检索嵌入在文档中的信息。
> db.mediaCollection.find({"Tracklist.Length":"5:02"}).toArray() [ { "_id" : ObjectId("5353463193efef02c962da73"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind", "Tracklist" : [ { "Track" : "1", "Title" : "Smells like teen spirit", "Length" : "5:02" }, { "Track" : "2", "Title" : "In Bloom", "Length" : "4:15" } ] } ]查询整个内嵌文档:
> db.mediaCollection.find({Tracklist:{"Length":"5:02"}}).toArray() [ ] > db.mediaCollection.find({Tracklist:{"Track" : "1","Title" : "Smells like teen spirit","Length":"5:02"}}).toArray() [ { "_id" : ObjectId("5353463193efef02c962da73"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind", "Tracklist" : [ { "Track" : "1", "Title" : "Smells like teen spirit", "Length" : "5:02" }, { "Track" : "2", "Title" : "In Bloom", "Length" : "4:15" } ] } ] > db.mediaCollection.find({Tracklist:{"Track" : "1","Length" : "5:02","Title" : "Smells like teen spirit"}}).toArray() [ ]查询整个文档需要全部列出内嵌文档的字段,且顺序要一致,否则匹配不到。 查询内嵌文档的多个字段。如查询有joe发表且分数在5分以上:
> db.mediaCollection.insert({ "content" : "...", "comments" : [ { "author" : "joe", "score" : 3, "comment" : "nice post" }, { "author" : "mary", "score" : 6, "comment" : "terrible post" } ] }) > db.mediaCollection.find().toArray() [ { "_id" : ObjectId("5353462f93efef02c962da71"), "Type" : "Book", "Title" : "Definitive Guide to MongoDB, the", "ISBN" : "987-1-4302-3051-9", "Publisher" : "Apress", "Author" : [ "Membrey, Peter", "Plugge, Eelco", "Hawkins, Tim" ] }, { "_id" : ObjectId("5353462f93efef02c962da72"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind" }, { "_id" : ObjectId("5353463193efef02c962da73"), "Type" : "CD", "Artist" : "Nirvana", "Title" : "Nevermind", "Tracklist" : [ { "Track" : "1", "Title" : "Smells like teen spirit", "Length" : "5:02" }, { "Track" : "2", "Title" : "In Bloom", "Length" : "4:15" } ] }, { "_id" : ObjectId("5353681293efef02c962da7a"), "content" : "...", "comments" : [ { "author" : "joe", "score" : 3, "comment" : "nice post" }, { "author" : "mary", "score" : 6, "comment" : "terrible post" } ] } ] > db.mediaCollection.find({"comments" : {"author" : "joe", "score" : {"$gte" : 5}}}).toArray() [ ] > db.mediaCollection.find({"comments.author" : "joe", "comments.score" : {"$gte" : 5}}).toArray() [ { "_id" : ObjectId("5353681293efef02c962da7a"), "content" : "...", "comments" : [ { "author" : "joe", "score" : 3, "comment" : "nice post" }, { "author" : "mary", "score" : 6, "comment" : "terrible post" } ] } ]上面的查询是不对的。 要正确的指定一组条件,而不是每个键,因此要使用到$elemMatch。这样就可以用来部分指定匹配数组中的单个内嵌文档的限定条件。正确的写法如下所示:
> db.mediaCollection.find({"comments" : {"$elemMatch" : {"author" : "joe", "score" : {"$gte" : 5}}}}).toArray() [ ]对于数组:
> db.mediaCollection.find({"Author":"Membrey, Peter"}).toArray() [ { "_id" : ObjectId("5353462f93efef02c962da71"), "Type" : "Book", "Title" : "Definitive Guide to MongoDB, the", "ISBN" : "987-1-4302-3051-9", "Publisher" : "Apress", "Author" : [ "Membrey, Peter", "Plugge, Eelco", "Hawkins, Tim" ] } ]正则表达式查询:
> db.mediaCollection.find({"Title":/MongoDB/i}).toArray() [ { "_id" : ObjectId("5353462f93efef02c962da71"), "Type" : "Book", "Title" : "Definitive Guide to MongoDB, the", "ISBN" : "987-1-4302-3051-9", "Publisher" : "Apress", "Author" : [ "Membrey, Peter", "Plugge, Eelco", "Hawkins, Tim" ] } ]对检索结果进行Sort, Limit, 和Skip请看下节内容。
原文地址:mongodb查询, 感谢原作者分享。

MySQL'sBLOBissuitableforstoringbinarydatawithinarelationaldatabase,whileNoSQLoptionslikeMongoDB,Redis,andCassandraofferflexible,scalablesolutionsforunstructureddata.BLOBissimplerbutcanslowdownperformancewithlargedata;NoSQLprovidesbetterscalabilityand

ToaddauserinMySQL,use:CREATEUSER'username'@'host'IDENTIFIEDBY'password';Here'showtodoitsecurely:1)Choosethehostcarefullytocontrolaccess.2)SetresourcelimitswithoptionslikeMAX_QUERIES_PER_HOUR.3)Usestrong,uniquepasswords.4)EnforceSSL/TLSconnectionswith

ToavoidcommonmistakeswithstringdatatypesinMySQL,understandstringtypenuances,choosetherighttype,andmanageencodingandcollationsettingseffectively.1)UseCHARforfixed-lengthstrings,VARCHARforvariable-length,andTEXT/BLOBforlargerdata.2)Setcorrectcharacters

MySQloffersechar, Varchar, text, Anddenumforstringdata.usecharforfixed-Lengthstrings, VarcharerForvariable-Length, text forlarger text, AndenumforenforcingdataAntegritywithaetofvalues.

Optimizing MySQLBLOB requests can be done through the following strategies: 1. Reduce the frequency of BLOB query, use independent requests or delay loading; 2. Select the appropriate BLOB type (such as TINYBLOB); 3. Separate the BLOB data into separate tables; 4. Compress the BLOB data at the application layer; 5. Index the BLOB metadata. These methods can effectively improve performance by combining monitoring, caching and data sharding in actual applications.

Mastering the method of adding MySQL users is crucial for database administrators and developers because it ensures the security and access control of the database. 1) Create a new user using the CREATEUSER command, 2) Assign permissions through the GRANT command, 3) Use FLUSHPRIVILEGES to ensure permissions take effect, 4) Regularly audit and clean user accounts to maintain performance and security.

ChooseCHARforfixed-lengthdata,VARCHARforvariable-lengthdata,andTEXTforlargetextfields.1)CHARisefficientforconsistent-lengthdatalikecodes.2)VARCHARsuitsvariable-lengthdatalikenames,balancingflexibilityandperformance.3)TEXTisidealforlargetextslikeartic

Best practices for handling string data types and indexes in MySQL include: 1) Selecting the appropriate string type, such as CHAR for fixed length, VARCHAR for variable length, and TEXT for large text; 2) Be cautious in indexing, avoid over-indexing, and create indexes for common queries; 3) Use prefix indexes and full-text indexes to optimize long string searches; 4) Regularly monitor and optimize indexes to keep indexes small and efficient. Through these methods, we can balance read and write performance and improve database efficiency.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Dreamweaver CS6
Visual web development tools

WebStorm Mac version
Useful JavaScript development tools

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),
