Which of the following code blocks will remove the rows where the value in column age is greater than 25 from the existing Delta table my_table and save the updated table?
Which of the following code blocks will remove the rows where the value in column age is greater than 25 from the existing Delta table my_table and save the updated table?
To remove rows from an existing Delta table where the value in a specific column meets a condition, you need to use the DELETE statement. In this case, using 'DELETE FROM my_table WHERE age > 25;' will delete all rows where the age is greater than 25, thereby updating the table with only the rows where the age value is 25 or less.
A data engineer has realized that they made a mistake when making a daily update to a table. They need to use Delta time travel to restore the table to a version that is 3 days old. However, when the data engineer attempts to time travel to the older version, they are unable to restore the data because the data files have been deleted.
Which of the following explains why the data files are no longer present?
The VACUUM command in Delta Lake is used to clean up and remove unnecessary data files that are no longer needed for time travel or query purposes. When you run VACUUM with certain retention settings, it can delete older data files, which might include versions of data that are older than the specified retention period. If the data engineer is unable to restore the table to a version that is 3 days old because the data files have been deleted, it is likely because the VACUUM command was run on the table, removing the older data files as part of data cleanup.
Which of the following Git operations must be performed outside of Databricks Repos?
In Databricks Repos, several Git operations can be performed directly, such as commit, pull, push, and clone. However, merging branches is one operation that typically must be handled outside of Databricks Repos, especially for tasks like resolving merge conflicts or completing the merge process. Therefore, the correct answer is 'Merge'.
Which of the following data lakehouse features results in improved data quality over a traditional data lake?
A data lakehouse supports ACID-compliant transactions. ACID stands for Atomicity, Consistency, Isolation, and Durability, which are crucial properties for maintaining data integrity and consistency. These properties ensure that data operations are processed reliably and completely, even in the face of concurrent transactions or failures. This level of transactional reliability and consistency helps to improve data quality significantly over a traditional data lake, which often lacks such guarantees.
A data engineer needs to determine whether to use the built-in Databricks Notebooks versioning or version their project using Databricks Repos.
Which of the following is an advantage of using Databricks Repos over the Databricks Notebooks versioning?
Databricks Repos supports the use of multiple branches. This feature allows for the creation and management of different branches in a codebase, enabling parallel development, collaboration, and experimentation without interfering with the main branch. This significantly enhances collaborative efforts and version control as compared to the built-in Databricks Notebooks versioning, which does not support multiple branches.