Microsoft Certified Azure Data Engineer Associate · Free Practice Question Medium
Question 32
Azure Databricks includes an integrated notebook interface for working with Spark. Notebooks provide an intuitive way to combine code with Markdown notes, commonly used by data scientists and data analysts.
Notebooks consist of one or more cells, each containing either code or markdown. Code cells in notebooks have some features that can help you be more productive.
Which of the following are valid features of notebooks when using Spark? (Select four)
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A
Syntax highlighting and error support.
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B
Interactive data visualizations.
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C
Develop code using Python, SQL, Scala, C#, and R.
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D
Code auto-completion.
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E
Export results and notebooks in .html, .xml, or .ipynb format.
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F
The ability to export results.
Reveal correct answers
Correct answers: A, B, D, F
Explanation
Use Spark in notebooks
Running Spark code in notebooks
Azure Databricks includes an integrated notebook interface for working with Spark. Notebooks provide an intuitive way to combine code with Markdown notes, commonly used by data scientists and data analysts. The look and feel of the integrated notebook experience within Azure Databricks is similar to that of Jupyter notebooks - a popular open-source notebook platform.
Notebooks consist of one or more cells, each containing either code or markdown. Code cells in notebooks have some features that can help you be more productive, including:
• Syntax highlighting and error support.
• Code auto-completion.
• Interactive data visualizations.
• The ability to export results.
With Azure Databricks notebooks, you can:
Customize your environment with the libraries of your choice.
Create regularly scheduled jobs to automatically run tasks, including multi-notebook workflows.
Export results and notebooks in
.htmlor.ipynbformat.Use a Git-based repository to store your notebooks with associated files and dependencies.
(Experimental) Use advanced editing capabilities.
A. Syntax highlighting and error support in notebooks help users easily identify different elements of the code, such as keywords, variables, and comments. This feature enhances code readability and makes it easier to spot syntax errors or potential bugs.
B. Interactive data visualizations within notebooks allow users to create dynamic charts, graphs, and plots that can be manipulated and explored interactively. This feature is valuable for data analysis and presentation, enabling users to visualize and understand their data more effectively.
C. Developing code in multiple languages like Python, SQL, Scala, C#, and R within the same notebook environment provides users with flexibility and versatility. This feature allows users to leverage different languages based on their specific needs and expertise.
D. Code auto-completion is a time-saving feature that suggests code snippets, function names, and variable names as users type in the code cell. This feature reduces the chances of typos and speeds up the coding process by providing quick access to available options.
E. Exporting results and notebooks in formats such as .html, .xml, or .ipynb offers users the flexibility to share their work in different ways. These formats allow users to present their findings, share their code, or collaborate with others using the most suitable file format for the task at hand.
F. The ability to export results from notebooks enables users to save their work in various formats for sharing, archiving, or further analysis. By exporting results, users can create reports, presentations, or backups of their work for future reference.
Discussion
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