Databricks-Certified-Data-Engineer-Associate Exam Dumps - Databricks Certified Data Engineer Associate Exam
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A data engineer is inspecting an ETL pipeline based on a Pyspark job that consistently encounters performance bottlenecks. Based on developer feedback, the data engineer assumes the job is low on compute resources. To pinpoint the issue, the data engineer observes the Spark Ul and finds out the job has a high CPU time vs Task time.
Which course of action should the data engineer take?
A data engineer has written a function in a Databricks Notebook to calculate the population of bacteria in a given medium.
Analysts use this function in the notebook and sometimes provide input arguments of the wrong data type, which can cause errors during execution.
Which Databricks feature will help the data engineer quickly identify if an incorrect data type has been provided as input?
Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?
A Databricks single-task workflow fails at the last task due to an error in a notebook. The data engineer fixes the mistake in the notebook. What should the data engineer do to rerun the workflow?
A data engineer needs to optimize the data layout and query performance for an e-commerce transactions Delta table. The table is partitioned by "purchase_date" a date column which helps with time-based queries but does not optimize searches on user statistics "customer_id", a high-cardinality column.
The table is usually queried with filters on "customer_i
d" within specific date ranges, but since this data is spread across multiple files in each partition, it results in full partition scans and increased runtime and costs.
How should the data engineer optimize the Data Layout for efficient reads?