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MongoDB developer cum Administrator

$750.00 $600.00

MongoDB Training – Let Agilitics bring “MongoDB Training” to life for you

Agilitics’s MongoDB Training course is a brief course on the open source document-oriented database
system Apache MongoDB. The course begins by addressing the distinguishing features of MongoDB and
a little history of its existence. The course then divulges into the topics including MongoDB’s data
modeling, indexing, aggregation, replication and sharding. Real-time examples are used throughout the
course to enable better understanding.

Course Length: 2 Days


You will Learn:

  • Basic Concepts of MongoDB
  • CRUD Operations in MongoDB
  • How to model database relationships?
  • How to create and embed indices? What are the various types of indices and their features?
  • What is the aggregation framework?
  • What are pipeline operators and their detailed functionalities?
  • How to create aggregation pipelines?
  • Replication in MongoDB
  • What is sharding? How it is implemented?
  • Query Routing and Shard Key types

Who Should Attend?
The course is for web developers, database administrators and managers who would want to understand the extensive features of the Apache MongoDB database system that offers a rich data model with easy scaling. It is tailored for those who are looking to move away from a relational database to adopt NoSQL solutions. It is however not restricted to the above, as anyone with the passion to learn can enroll as well.

Course Outline:

Section 1: Introduction : 3 hours

  • A rich data model
  • History
  • Distinguishing features of MongoDB
  • Basic Concepts
    Document Operations
  • CRUD Operations
    Creating Documents
    Reading Documents
    Updating Documents
    Deleting Documents

Section 2: Data Modeling: 3 hours

  • Considerations
  • Modeling Relationships
    Embedding Documents
    Referencing Documents
    Atomic Operations
  • TTL

Section 3: Indexing: 2 hours

  • Introduction to Indexing
  • Create indices
  • Compound Index

Indexing Embedded Documents

  • Multi-key Index
  • Covered Index
  • Sparse Index
  • Unique Index

Section 4: Aggregation : 2 hours

  • Aggregation Framework
  • Pipeline Operators
  • Creating Aggregation Pipeline
  • MapReduce
  • Output of MapReduce
  • Simple Aggregation Methods
  • Aggregation vs. MapReduce vs. Group

Section 5: Replication: 2 hours

  • MongoDB Cluster
    Replica Set
    Replica Set: Read Preference
    Replica Set: Request Association
    Write Concern

Section 6: Sharding: 2 hours

  • Why scale horizontally?
  • Scaling Load
  • Read Scaling with Replica Set
  • Sharding Writes
  • Chunk
  • Balancing
  • Sharding: Mongos
  • Sharding: Config Servers
  • Query Routing
    Targeted Query
    Scattered Query
  • Shard Key
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