MongoDB query, index and aggregation, MongoDB, and index aggregation

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-mail": "test@qq.com", "VM_num": 2, "time": [{"date": "", "hour ": "53 53 PM"}]})> userdoc2 = ({"user_id": 2, "name": "testadmin", "state": "active", "actor ": "admin", "e-mail": "test@qq.com", "VM_num": 2, "time": [{"date": "", "hour ": "06:34 AM"}]})> doc = ({"name": "peter", "position": "teacher"})> db. jingdong. insert (userdoc1) WriteResult ({"nInserted": 1})> db. jingdong. insert (userdoc2) WriteResult ({"nInserted": 1})> db. jingdong. insert (doc1) WriteResult ({"nInserted": 1 })

Query statement

Db. jingdong. find () # equivalent to select * from jingdong;

Conditional Operators

The conditional operators in mongodb include: (>) greater than-\ $ gt # greate (<) less than-\ $ lt # low (> =) greater than or equal to-\ $ gte # equal (<=) less than or equal to-\ $ lte

Example:

> db.jingdong.find({user_id:{$gt:1}})> db.jingdong.find({user_id:{$lte:2,$gt:1}})

# Type value double-precision-1 string-2 object-3 array-4 binary data-5 Object ID-7 boolean type-8 Data-9 null-10 regular expression-11JS code -13 symbols-14 JavaScript code with a scope-1532-bit integer-16 timestamp-1764--18 Min key-255Max key-127db.jingdong.find ({"name ": {$ type: 2 }}) # search for document records whose name is a string

Limit and skip

Reads a specified number of data records. shiyanlou. find (). limit (1) # Read a record. By default, the row at the top of the record is skipped during read. shiyanlou. find (). limit (1 ). skip (1)

MongoDB sorting-sort ()

Like sorting in sqlite, there are ascending and descending orders, in which the ascending order is represented by 1, and the descending order is represented by-1. jingdong. find (). sort ({"time": 1 })

Index-ensureIndex ()

Indexes can greatly improve the query efficiency. If there is no index, MongoDB must scan each file in the set and select the records that meet the query conditions when reading data. The query efficiency of this full set of scans is very low, especially when processing a large amount of data, the query can take dozens of seconds or even a few minutes, which is undoubtedly very fatal to the performance of the website. An index is a special data structure. An index is stored in a dataset that is easy to traverse and read. An index is a structure that sorts the values of one or more documents in a database set.

Db. COLLECTION_NAME.ensureIndex ({KEY: 1 |-1})> db. shiyanlou. ensureIndex ({"name": 1}) #1 indicates Ascending Order-1 indicates descending order> db. shiyanlou. ensureIndex ({"user_id": 1, "name": 1 },{ background: 1 })

The following table lists the ensureIndex parameters:

Parameters	Type	Description
Background	Boolean	Do you want to block other database operations when creating an index? The default value is false.
Unique	Boolean	Indicates whether the created index is unique. The default value is false.
Name	String	Index name. If not specified, the system automatically generates
DropDups	Boolean	Whether to delete duplicate records when creating a unique index. The default value is flase.
Sparse	Boolean	No index is enabled for fields that do not exist in the document. The default value is false.
ExpireAfterSeconds	Integer	Sets the survival time of the Set, in seconds.
V	Index version	Index version
Weights	Document	Index weight, ranging from 1 to 99999
Default-language	String	English by default
Language_override	String	The default value is language.

Aggregation-aggregate ()

db.COLLECTION_NAME.aggregate({$match:{x:1},{limit:NUM},$group:{_id:$age}})

$ Match: query, the same as find; $ limit: limit the number of displayed results; $ skip: Ignore the number of results; $ sort: sort; $ group: combine results based on a given expression.

> db.jingdong.aggregate([{$group:{_id:"$name", user:{$sum:"$user_id"}}}])

Name	Description
$ Sum	Sum
$ Avg	Calculate the average value
\ $ Min and $ max	Calculate the minimum and maximum values
$ Push	Insert values into an array in the result document
$ AddToSet	Insert a value to an array in the result document, but do not create a copy.
$ First	Obtain the first document data by sorting the resource documents
$ Last	Obtain the data of the last document by sorting the resource documents.

The aggregation pipeline of the MPs queue MongoDB delivers the results to the next MPs queue after processing the MongoDB documents in the same MPs queue. Pipeline operations can be repeated. Expression: process and output the input document. Expressions are stateless and can only be used to calculate documents in the current aggregation pipeline. They cannot process other documents. Several common operations in aggregation frameworks:

$ Project: modify the structure of the input document. It can be used to rename, add, or delete domains, or create computing results and nested documents. $ Match: used to filter data. Only documents that meet the conditions are output. $ Match uses the MongoDB standard query operation. $ Limit: used to limit the number of documents returned by the MongoDB aggregation pipeline. $ Skip: Skips a specified number of documents in the aggregation pipeline and returns the remaining documents. $ Unwind: splits an array field in the document into multiple entries, each containing a value in the array. $ Group: Groups Documents in the set for statistical results. $ Sort: Sorts input documents and outputs them. $ GeoNear: outputs ordered documents close to a certain geographical location.

> db.shiyanlou.aggregate([{$match:{user_id:{$gt:0,$lte:2}}},{$group:{_id:"user",count:{$sum:1}}}]){"_id":"user","count":2}