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Kishan Iyer
To carry out large-scale operations on Databricks, you'll need to develop apps or scripts which can interact with this big data service. This course looks into the Databricks CLI, its REST API, and the dbutils library to automate such interactions.
Read more
To carry out large-scale operations on Databricks, you'll need to develop apps or scripts which can interact with this big data service. This course looks into the Databricks CLI, its REST API, and the dbutils library to automate such interactions.
Read more
To carry out large-scale operations on Databricks, you'll need to develop apps or scripts which can interact with this big data service. This course looks into the Databricks CLI, its REST API, and the dbutils library to automate such interactions.
While nearly every task in Databricks can be accomplished from its Web UI, to perform operations of any complexity at scale, you need to interact with this service from a script or an application. In this course, Working with Azure Databricks Programmatically, you'll learn about the Databricks command-line interface (CLI). First, you'll explore how we can create and use a personal access token for authentication, and how to construct CLI commands to perform a variety of workspace operations. Then, you'll explore the use of the Databricks REST API. Finally, you'll discover the versatility of the dbutils library in order to interact with the Databricks file system from a Python application. Once you complete this course, you'll have a clear understanding of how interactions with a Databricks service can be automated using the Databricks CLI, the REST API, and the dbutils package.
Register for this course and see more details by visiting:
OpenCourser.com/course/8cgizr/working
What's inside
Syllabus
Course Overview
Accessing Azure Databricks with the CLI
Using the Azure Databricks REST API
Managing an Azure Databricks Workspace with dbutils
Read more
Syllabus
Course Overview
Accessing Azure Databricks with the CLI
Using the Azure Databricks REST API
Managing an Azure Databricks Workspace with dbutils
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Kishan Iyer, who are recognized for their work in Azure Databricks
This course is designed for individuals who have experience with Azure Databricks and want to learn how to automate interactions with this service using the CLI, REST API, and dbutils library
Helps learners use the Databricks command-line interface (CLI) to create and use a personal access token for authentication, and how to construct CLI commands to perform a variety of workspace operations
Develops understanding of how to use the Azure Databricks REST API and the dbutils library to interact with the Databricks file system from a Python application
Suitable for students with a good understanding of Azure Databricks and Python programming
Additional resources may be required for a deeper understanding of the concepts covered in this course
Save this course
Save Working with Azure Databricks Programmatically to your list so you can find it easily later:
Save
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Working with Azure Databricks Programmatically with these
activities:
Review Azure Databricks Documentation
Show steps
Solidify your understanding of Azure Databricks by reviewing the official documentation and refreshing your knowledge of its features and capabilities.
Browse courses on
Azure Databricks
Show steps
-
Go to the Azure Databricks documentation website.
-
Review key sections such as the overview, concepts, and tutorials.
-
Focus on areas where you need additional clarification or reinforcement.
Organize Your Course Notes and Resources
Show steps
Consolidate and organize your class materials, including notes, assignments, slides, and any other resources provided by the instructor.
Show steps
-
Gather all the materials you have accumulated during the course.
-
Create a system for organizing your materials, such as folders or a digital notebook.
-
Review your materials and identify key concepts and topics.
-
Highlight or annotate important information for future reference.
Follow the Databricks CLI Tutorial
Show steps
Develop familiarity with the Databricks CLI by progressing through its official tutorial.
Show steps
-
Locate the Databricks CLI tutorial.
-
Follow the tutorial steps to set up the CLI.
-
Complete the tutorial exercises.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Practice using the Databricks CLI
Show steps
Practice using the Databricks CLI to perform various workspace operations, such as creating clusters, attaching and detaching notebooks, and managing jobs.
Show steps
-
Install the Databricks CLI
-
Create a personal access token
-
Configure the CLI with your personal access token
-
Use the CLI to create a new cluster
-
Use the CLI to attach a notebook to the cluster
Complete CLI Command Practice Problems
Show steps
Practice using the Databricks CLI to perform basic operations such as creating clusters, notebooks, and jobs.
Show steps
-
Go to the Azure Databricks documentation for the CLI.
-
Choose a few basic CLI commands to practice, such as `dbfs ls`, `dbfs cp`, and `dbfs rm`.
-
Run the commands in your terminal or command prompt, making sure to replace the placeholders with your own values.
Practice CLI commands
Show steps
Grasp the syntax and usage of the Databricks CLI through practice.
Show steps
-
Create a personal access token for authentication.
-
Construct CLI commands to create a cluster.
-
Use CLI commands to view cluster details.
-
Terminate the created cluster using CLI.
Follow Databricks Blog
Show steps
Read Databricks blog related to topics covered in the course to augment and reinforce classroom material.
Show steps
-
Visit Databricks Blog
-
Read articles on topics covered in class
-
Leave comments and ask questions to engage with community
Follow a tutorial on the Databricks REST API
Show steps
Follow a tutorial to learn how to use the Databricks REST API to programmatically interact with the Databricks service, such as creating clusters, submitting jobs, and managing notebooks.
Show steps
-
Find a tutorial on the Databricks REST API
-
Follow the tutorial to create a new cluster using the REST API
-
Follow the tutorial to submit a job using the REST API
-
Follow the tutorial to manage a notebook using the REST API
Attend a Databricks Workshop
Show steps
Enhance your practical skills by attending a Databricks workshop led by experienced professionals, where you can learn advanced concepts and solve real-world challenges.
Show steps
-
Find an upcoming Databricks workshop that aligns with your interests.
-
Register for the workshop and make arrangements to attend.
-
Actively participate in the workshop, ask questions, and engage in discussions.
Databricks REST API Exercises
Show steps
Practice using Databricks REST API to reinforce concepts and gain proficiency.
Show steps
-
Find exercises or create your own
-
Use REST API to perform various tasks
-
Compare results with expected outcomes
-
Debug and troubleshoot any errors
Create a Python script to automate Databricks operations
Show steps
Use your knowledge of the Databricks CLI, REST API, and dbutils library to create a Python script that can automate common Databricks operations, such as creating clusters, submitting jobs, and managing notebooks.
Browse courses on
Python
Show steps
-
Create a new Python script file
-
Import the necessary libraries
-
Use the Databricks CLI to create a new cluster
-
Use the Databricks REST API to submit a job
-
Use the dbutils library to manage a notebook
Write a Blog Post on REST API Usage
Show steps
Demonstrate your understanding of the Databricks REST API by creating a comprehensive blog post explaining its usage and capabilities.
Show steps
-
Research the Databricks REST API documentation.
-
Choose a specific aspect of the API to focus on, such as authentication, cluster management, or job submission.
-
Write a detailed blog post explaining the concepts, syntax, and examples of using the API.
-
Publish your blog post and share it with the community.
Create a Python script using dbutils
Show steps
Reinforce knowledge of dbutils by building a Python script that interacts with the Databricks filesystem.
Show steps
-
Write a Python script that creates a directory in the Databricks file system.
-
Add code to upload a file to the directory.
-
Include functionality to list the files in the directory.
Build a Python Script to Automate Databricks Tasks
Show steps
Apply your knowledge of the Databricks CLI, REST API, and dbutils library by creating a Python script that automates common Databricks tasks.
Browse courses on
Python Scripting
Show steps
-
Identify a repetitive or time-consuming task that you want to automate.
-
Design the workflow and logic of your script.
-
Write the Python code using the appropriate Databricks libraries and syntax.
-
Test and debug your script to ensure it works correctly.
-
Deploy and schedule your script to run automatically.
Databricks dbutils Library Project
Show steps
Create a project utilizing Databricks dbutils library to apply course concepts hands-on and build a portfolio piece.
Show steps
-
Identify a project idea
-
Design and plan project
-
Implement project using dbutils library
-
Test and iterate on project
-
Document and present project
Review Azure Databricks Documentation
Show steps
Solidify your understanding of Azure Databricks by reviewing the official documentation and refreshing your knowledge of its features and capabilities.
Browse courses on
Azure Databricks
Show steps
Show steps
Show steps
- Go to the Azure Databricks documentation website.
- Review key sections such as the overview, concepts, and tutorials.
- Focus on areas where you need additional clarification or reinforcement.
Organize Your Course Notes and Resources
Show steps
Consolidate and organize your class materials, including notes, assignments, slides, and any other resources provided by the instructor.
Show steps
Show steps
Show steps
- Gather all the materials you have accumulated during the course.
- Create a system for organizing your materials, such as folders or a digital notebook.
- Review your materials and identify key concepts and topics.
- Highlight or annotate important information for future reference.
Follow the Databricks CLI Tutorial
Show steps
Develop familiarity with the Databricks CLI by progressing through its official tutorial.
Show steps
Show steps
Show steps
- Locate the Databricks CLI tutorial.
- Follow the tutorial steps to set up the CLI.
- Complete the tutorial exercises.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Practice using the Databricks CLI
Show steps
Practice using the Databricks CLI to perform various workspace operations, such as creating clusters, attaching and detaching notebooks, and managing jobs.
Show steps
Show steps
Show steps
- Install the Databricks CLI
- Create a personal access token
- Configure the CLI with your personal access token
- Use the CLI to create a new cluster
- Use the CLI to attach a notebook to the cluster
Complete CLI Command Practice Problems
Show steps
Practice using the Databricks CLI to perform basic operations such as creating clusters, notebooks, and jobs.
Show steps
Show steps
Show steps
- Go to the Azure Databricks documentation for the CLI.
- Choose a few basic CLI commands to practice, such as `dbfs ls`, `dbfs cp`, and `dbfs rm`.
- Run the commands in your terminal or command prompt, making sure to replace the placeholders with your own values.
Practice CLI commands
Show steps
Grasp the syntax and usage of the Databricks CLI through practice.
Show steps
Show steps
Show steps
- Create a personal access token for authentication.
- Construct CLI commands to create a cluster.
- Use CLI commands to view cluster details.
- Terminate the created cluster using CLI.
Follow Databricks Blog
Show steps
Read Databricks blog related to topics covered in the course to augment and reinforce classroom material.
Show steps
Show steps
Show steps
- Visit Databricks Blog
- Read articles on topics covered in class
- Leave comments and ask questions to engage with community
Follow a tutorial on the Databricks REST API
Show steps
Follow a tutorial to learn how to use the Databricks REST API to programmatically interact with the Databricks service, such as creating clusters, submitting jobs, and managing notebooks.
Show steps
Show steps
Show steps
- Find a tutorial on the Databricks REST API
- Follow the tutorial to create a new cluster using the REST API
- Follow the tutorial to submit a job using the REST API
- Follow the tutorial to manage a notebook using the REST API
Attend a Databricks Workshop
Show steps
Enhance your practical skills by attending a Databricks workshop led by experienced professionals, where you can learn advanced concepts and solve real-world challenges.
Show steps
Show steps
Show steps
- Find an upcoming Databricks workshop that aligns with your interests.
- Register for the workshop and make arrangements to attend.
- Actively participate in the workshop, ask questions, and engage in discussions.
Databricks REST API Exercises
Show steps
Practice using Databricks REST API to reinforce concepts and gain proficiency.
Show steps
Show steps
Show steps
- Find exercises or create your own
- Use REST API to perform various tasks
- Compare results with expected outcomes
- Debug and troubleshoot any errors
Create a Python script to automate Databricks operations
Show steps
Use your knowledge of the Databricks CLI, REST API, and dbutils library to create a Python script that can automate common Databricks operations, such as creating clusters, submitting jobs, and managing notebooks.
Browse courses on
Python
Show steps
Show steps
Show steps
- Create a new Python script file
- Import the necessary libraries
- Use the Databricks CLI to create a new cluster
- Use the Databricks REST API to submit a job
- Use the dbutils library to manage a notebook
Write a Blog Post on REST API Usage
Show steps
Demonstrate your understanding of the Databricks REST API by creating a comprehensive blog post explaining its usage and capabilities.
Show steps
Show steps
Show steps
- Research the Databricks REST API documentation.
- Choose a specific aspect of the API to focus on, such as authentication, cluster management, or job submission.
- Write a detailed blog post explaining the concepts, syntax, and examples of using the API.
- Publish your blog post and share it with the community.
Create a Python script using dbutils
Show steps
Reinforce knowledge of dbutils by building a Python script that interacts with the Databricks filesystem.
Show steps
Show steps
Show steps
- Write a Python script that creates a directory in the Databricks file system.
- Add code to upload a file to the directory.
- Include functionality to list the files in the directory.
Build a Python Script to Automate Databricks Tasks
Show steps
Apply your knowledge of the Databricks CLI, REST API, and dbutils library by creating a Python script that automates common Databricks tasks.
Browse courses on
Python Scripting
Show steps
Show steps
Show steps
- Identify a repetitive or time-consuming task that you want to automate.
- Design the workflow and logic of your script.
- Write the Python code using the appropriate Databricks libraries and syntax.
- Test and debug your script to ensure it works correctly.
- Deploy and schedule your script to run automatically.
Databricks dbutils Library Project
Show steps
Create a project utilizing Databricks dbutils library to apply course concepts hands-on and build a portfolio piece.
Show steps
Show steps
Show steps
- Identify a project idea
- Design and plan project
- Implement project using dbutils library
- Test and iterate on project
- Document and present project
Career center
Learners who complete Working with Azure Databricks Programmatically will develop knowledge and skills
that may be useful to these careers:
Database Engineer
Database Engineer
A Database Engineer helps maximize the performance of an organization's database. A significant part of this involves data integration, which is critical for the effective use of data in data science and analytics. The REST API skill taught in this course directly applies to data integration. A background in Azure Databricks would thus be particularly relevant to someone in this role, especially for working with large datasets.
Software Engineer
Software Engineer
A Software Engineer designs, develops, deploys, and maintains software applications. Those involved in big data are responsible for working with large datasets, which requires expertise in parallel processing and distributed systems. These concepts are covered in this course, making it helpful for Software Engineers entering the field of big data processing.
Data Engineer
Data Engineer
Data Engineers design, construct, and maintain the infrastructure used to store and process data. They are responsible for data modeling, data integration, and data security. The REST API skill taught in this course directly applies to data integration. A background in Azure Databricks would thus be particularly relevant to someone in this role, especially for working with large datasets.
Data Architect
Data Architect
A Data Architect designs and manages an organization's data architecture, which involves managing data models, data quality, and data security. As data models are used to represent complex systems, this role requires an understanding of software engineering. The skills taught in this course, particularly in the REST API, can help a Data Architect meet the demands of designing a data architecture for big data systems.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. As many machine learning applications involve working with very large datasets, distributed computing is essential. This course covers the concepts of parallel processing and distributed systems, and can be beneficial for Machine Learning Engineers entering the field of big data processing.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and maintain artificial intelligence systems. These can involve working with very large datasets. This course covers the concepts of parallel processing and distributed systems, and can be beneficial for Artificial Intelligence Engineers entering the field of big data processing.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts translate raw data into actionable insights for businesses. This typically involves working with data from different sources, which requires proficiency in data integration. The REST API skill taught in this course directly applies to data integration.
Data Scientist
Data Scientist
Data Scientists apply scientific methods to extract knowledge from data. Data is often stored in a variety of formats and locations, making data integration a critical part of the job. This course teaches REST API, which can be useful for integrating data.
Software Development Manager
Software Development Manager
A Software Development Manager leads a team of software engineers. They are responsible for planning, organizing, and directing development efforts. A strong understanding of software development best practices is essential for a Software Development Manager. This course can help someone in this role better understand the challenges and opportunities of big data processing, enabling them to make better decisions for their team.
Data Analyst
Data Analyst
A Data Analyst collects and analyzes data to identify trends and patterns. Much of this data is stored in databases. This course teaches the CLI, which can be useful for managing databases.
IT Project Manager
IT Project Manager
An IT Project Manager plans, executes, and closes IT projects. They are responsible for ensuring that projects are completed on time, within budget, and to the required quality standards. A strong understanding of software development best practices is essential for an IT Project Manager. This course can help someone in this role better understand the challenges and opportunities of big data processing, enabling them to make better decisions for their team.
DevOps Engineer
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations teams. They work to improve communication and collaboration, and to ensure that software is deployed and maintained efficiently. A strong understanding of software development best practices is essential for a DevOps Engineer. This course can help someone in this role better understand the challenges and opportunities of big data processing, enabling them to make better decisions for their team.
Database Administrator
Database Administrator
Database Administrators are responsible for the installation, configuration, maintenance, and performance of database systems. They ensure that databases are available, reliable, and secure. This course teaches the CLI, which can be useful for managing databases.
Product Manager
Product Manager
Product Managers are responsible for the conception, development, and marketing of products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. A strong understanding of software development best practices is essential for a Product Manager. This course can help someone in this role better understand the challenges and opportunities of big data processing, enabling them to make better decisions for their team.
Technical Architect
Technical Architect
Technical Architects design and implement the technical infrastructure of an organization. They work with business leaders to understand their needs and to develop solutions that meet those needs. A strong understanding of software development best practices is essential for a Technical Architect. This course can help someone in this role better understand the challenges and opportunities of big data processing, enabling them to make better decisions for their team.
For more career information including salaries, visit:
OpenCourser.com/course/8cgizr/working
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Working with Azure Databricks Programmatically.
Save
Can serve as a basic primer for those new to Spark or big data.
For those working with Python, this book serves as a useful primer and reference for the Pandas library
May be useful for those interested in the intersection of machine learning and data analysis with Python.
Focuses on the intersection of deep learning and Python.
May be helpful for those looking for a more high-level view of data science.
Is useful for those interested in the intersection of natural language processing and Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8cgizr/working
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Time
77 hours
Level
Intermediate
Via
Pluralsight
Instructor
Kishan Iyer
Language
English
Good to know
Taught by Kishan Iyer, who are recognized for their work in Azure Databricks
This course is designed for individuals who have experience with Azure Databricks and want to learn how to automate interactions with this service using the CLI, REST API, and dbutils library
Helps learners use the Databricks command-line interface (CLI) to create and use a personal access token for authentication, and how to construct CLI commands to perform a variety of workspace operations
Develops understanding of how to use the Azure Databricks REST API and the dbutils library to interact with the Databricks file system from a Python application
Suitable for students with a good understanding of Azure Databricks and Python programming
Additional resources may be required for a deeper understanding of the concepts covered in this course
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