Learn to build data services powered by a MarkLogic Data Hub using JavaScript!

Developers taking this course will get a detailed look at how MarkLogic server works and will grow their programming skills through the completion of hands-on labs where you will build, deploy and test data services using the MarkLogic Data Hub platform.

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Objectives

Attendees completing this course will be able to:

  • Describe MarkLogic server architecture
  • Develop, test, deploy, and use data services
  • Use ml-gradle for managing configuration and deployment
  • Write efficient and scalable server-side code
  • Debug code
  • Build services to perform database transactions
  • Build services to power search applications
  • Iteratively curate data in a MarkLogic Data Hub to power data services

Outline

  • Building shared data services on a MarkLogic Data Hub
  • Fundamentals of REST Services
  • Understanding requests
  • Describe common application architectures for applications built with data services
  • Using the MarkLogic REST API
  • Extending the MarkLogic REST API
  • Understanding response codes, error handling, and exports
  • Develop an example service
  • Describe the components of a MarkLogic cluster
  • Deploy a data service to MarkLogic
  • Test a data service
  • Use a data service from a middle tier
  • Loading documents
  • Managing metadata
  • Working with JSON
  • Working with XML
  • Using the NodeBuilder API
  • Using XPath
  • Understanding search relevancy
  • Using the JSearch API
  • Query by Example
  • Using parse
  • Working with facet data
  • Working with aggregates
  • Geospatial search
  • Using the CTS search API
  • Understanding and configuring term list indexes
  • Filtered versus unfiltered queries
  • Word query database configuration
  • Range indexes
  • Path range indexes
  • Fields
  • Understanding commit behavior
  • Understanding Nodes and Objects
  • Updating JSON
  • Updating XML
  • Using Invoke to manage transaction context
  • Understanding system resource utilization
  • Using query analysis tools
  • Using Meters data
  • Query profiling
  • Best practices for writing scalable code
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Learning Assessments

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