Building Enterprise Solutions with MongoDB Training

MongoDB Course Outline

• Setting the Stage

  Recognising the need for NoSQL data stores

  • Justifying non-relational data stores
  • Listing the categories of NoSQL Data Stores

  Focusing on MongoDB

  • Defining the MongoDB architecture
  • Reviewing the JSON standard
  • Enumerating the MongoDB data types

  Interacting with MongoDB

  • Querying at the Command Line Interface
  • Running Scripts
  • Manipulating MongoDB data from Python and Java

• Installing MongoDB

  Surveying Cluster Topology

  • Creating a standalone mongod
  • Achieving redundancy with replica sets
  • Replicating data with the oplog

  Dissecting MongoDB Storage Strategies

  • Identifying storage engines
  • Improving data safety with journaling
  • Investigating record allocation strategies

  Storing Large Files with GridFS

  • Weighing the advantages and disadvantages of GridFS
  • Leveraging the mongofiles utility tool
  • Compressing data for economy of drive space

• Exploring the MongoDB Data and Query Model

  Organising Data

  • Storing data in Databases, collections and documents
  • Inserting and updating Documents
  • Running scripts from the Mongo Shell

  Querying Documents

  • Restricting find() with a query document
  • Specifying keys for queries to return
  • Constraining the number of results with limit and skip

  Modelling Relationships

  • Express relationships using references
  • Embedding sub-documents

• Configuring Replication and Data Consistency

  Configuring Read and Write Consistency

  • Reading from primary and secondary nodes
  • Setting the read preference level
  • Selecting the Appropriate Write Concern
  • Writing with a timeout

  Customising Write Concern and Read Preference

  • Applying tags to replicas
  • Adding logical names to write concerns
  • Reading from a tagged mongod

• Tuning Performance with Indexes

  Improving access speed with indexes

  • Investigating a query with the explain() function
  • Getting statistics from explain()
  • Choosing an index with the hint() function

  Considering the cost and benefit of indexing

  • Designing a better index
  • Opting out of using an index
  • Profiling to identify slow queries

  Taking advantage of indexes

  • Sorting and finding ranges with an index
  • Guaranteeing uniqueness with indexes
  • Skipping missing fields with a sparse index

  Managing collections with special indexes

  • Aging data out of a capped collection
  • Searching for text fragments with $text
  • Deleting documents automatically using time to live indexes
  • Permitting queries by location

• Utilising the Aggregation Framework

  Leveraging the different modes of the Aggregation Framework

  • Invoking single-purpose aggregation functions
  • Performing operations with the Aggregation Pipeline framework
  • Executing MapReduce on MongoDB