Non_Relational_Database

Non-Relational Database 2 | Basic MongoDB Concepts and CRUD Operations

mongodb

1. Basics of MongoDB

(1) The Definition of Documents

A record in a MongoDB collection and the basic unit of data in MongoDB. Documents are analogous to JSON objects but exist in the database in a more type-rich format known as BSON.

(2) The Definition of Collections

A grouping of MongoDB documents. A collection is the equivalent of an RDBMS table.

(3) The Definition of Fields

A name-value pair in a document. A document has zero or more fields. Fields are analogous to columns in relational databases. For example, a certain MongoDB document will be seen as follows,


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{
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   field1: value1,
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   field2: value2,
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   field3: value3,
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   ...
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   fieldN: valueN
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}

(4) Reasons for MongoDB

Ease of use: schemaless
Ease of scaling: can be used for distributed computing
Supports many features:
- CRUD
- Indexing
- Aggregration Pipeline
- File storage
- Etc.
Suports many languages/drivers

(5) Data Type of MongoDB

NULL
Boolean
Number: 8-byte double-precision float Number(), 4-byte integer NumberInt(), 8-byte integerNumberLong()
String
Date: new Date()
Array: can have different types of elements with atomic updates
Embedded Documents
Object ID: 12-byte autogenerated ID with field _id, every document must have this field
Binary data
JavaScript Code

2. Mongo DB Operations

(0) External Operations

Start service


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$ mongod --dbpath=<path>

Import JSON data file


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$ mongoimport --db <DBname> --collection <collectionname> --file <filepath>

Note that this command requires mongo-tools,


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$ conda install mongo-tools

We can also select the mode by option --mode between insert (means to allow duplicate) or upsert (means to update duplicate).

(1) Creation

Create/Choose database_name


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use database_name

Create collection_name


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db.createCollection(collection_name)

Create a document doc_name in collection collection_name


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db.collection_name.insertOne(doc_name)

Create a documents doc_name_1 and doc_name_2 in collection collection_name


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db.collection_name.insertMany([doc_name_1, doc_name_2])

Check the current database


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db

(2) Read

Return all documents match the rule {"field" : value}


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db.collection_name.find({"field" : value})

Return all documents match the rule {"field_1" : value} without returning field_2


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db.collection_name.find({"field_1" : value}, {"field_2" : false})

Return one document match the rule {"field" : value}


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db.collection_name.findOne({"field" : value})

Return all documents match the rule {"field_1" : value} without returning field_2


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db.collection_name.findOne({"field_1" : value}, {"field_2" : false})

Count the number of documents under collection_name


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db.collection_name.count()

(3) Update

Note if we need to create a new document if no current document match the matching rule, we have to set the third argument of method updateOne or updateMany to {upsert : true}

Set/Create the value of field_new as value_new in one document matching rule {"field" : value}


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db.collection_name.updateOne({"field" : value}, {$set : {"field_new" : value_new}})

Set/Create the value of field_new as value_new in all documents matching rule {"field" : value}


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db.collection_name.updateMany({"field" : value}, {$set : {"field_new" : value_new}})

Delete field field_del in one document matching rule {"field" : value}


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db.collection_name.updateOne({"field" : value}, {$unset : {"field_del" : ""}})

Delete field field_del in all documents matching rule {"field" : value}


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db.collection_name.updateMany({"field" : value}, {$unset : {"field_del" : ""}})

Increase field field_inc by 5 in all document matching rule {"field" : value}


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db.collection_name.updateMany({"field" : value}, {$inc : {"field_inc" : 5}})

Rename a field field_1 to field_2 in all documents


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db.collection_name.updateMany({}, {$rename : {"field_1" : "field_2"}})

Make a field field_min no more than 5 in all documents


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db.collection_name.updateMany({}, {$min : {"field_min" : 5}})
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// 6 -> 5
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// 4 -> 4

Make a field field_max no less than 5 in all documents


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db.collection_name.updateMany({}, {$max : {"field_max" : 5}})
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// 6 -> 6
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// 4 -> 5

Add element to the end of the array value of field field_array in all documents


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db.collection_name.updateMany({}, {$push : {"field_array" : element}})

Remove the first element in the array value of field field_array in all documents


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db.collection_name.updateMany({}, {$pop : {"field_array" : -1}})

Remove the last element in the array value of field field_array in all documents


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db.collection_name.updateMany({}, {$pop : {"field_array" : 1}})

Remove a certain element element in the array value of field field_array in all documents


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db.collection_name.updateMany({}, {$pull : {"field_array" : element}})

Update the first element to 10 in the array value of field field_array in all documents


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db.collection_name.updateMany({}, {$set : {"field_array.$" : 10}})

Update all the elements to 10 in the array value of field field_array in all documents


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db.collection_name.updateMany({}, {$set : {"field_array.$[]" : 10}})

Update all the document elements with element.score = 5 to 10 in the array value of field field_array in all documents


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db.collection_name.updateMany({},
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                              {$set : {"field_array.$[element].score" : 10}},
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                              {arrayFilters : [ {"element.score" : 5} ]})

(4) Delete

Remove one document with {"field" : value}


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db.collection_name.deleteOne({"field" : value})

Remove all the documents with {"field" : value}


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db.collection_name.deleteMany({"field" : value})

Remove the collection collection_name


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db.collection_name.drop()