Databricks Databricks Certifications DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE Questions & Answers

• Question 81:

  Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?

  A. Parquet files can be partitioned

  B. CREATE TABLE AS SELECT statements cannot be used on files

  C. Parquet files have a well-defined schema

  D. Parquet files have the ability to be optimized

  E. Parquet files will become Delta tables

  Correct Answer: C

  Explanation: https://www.databricks.com/glossary/what-is- parquet#:~:text=Columnar%20storage%20like%20Apache%20Parquet,compared%20to%2 0row%2Doriented%20databases. Columnar storage like Apache Parquet is designed to bring efficiency compared to row-based files like CSV. When querying, columnar storage you can skip over the non-relevant data very quickly. As a result, aggregation queries are less time-consuming compared to row-oriented databases.

• Question 82:

  In which of the following file formats is data from Delta Lake tables primarily stored?

  A. Delta

  B. CSV

  C. Parquet

  D. JSON

  E. A proprietary, optimized format specific to Databricks

  Correct Answer: C

  Explanation: https://docs.delta.io/latest/delta-faq.html

• Question 83:

  A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to compact the small files to form larger files to improve performance. Which of the following keywords can be used to compact the small files?

  A. REDUCE

  B. OPTIMIZE

  C. COMPACTION

  D. REPARTITION

  E. VACUUM

  Correct Answer: B

  OPTIMIZE can be used to club small files into 1 and improve performance.

• Question 84:

  A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run.

  Which of the following tools can the data engineer use to solve this problem?

  A. Unity Catalog

  B. Delta Lake

  C. Databricks SQL

  D. Data Explorer

  E. Auto Loader

  Correct Answer: E

  Explanation: Auto Loader incrementally and efficiently processes new data files as they arrive in cloud storage without any additional setup. https://docs.databricks.com/en/ingestion/auto-loader/index.html

• Question 85:

  A data engineer has joined an existing project and they see the following query in the project repository:

  CREATE STREAMING LIVE TABLE loyal_customers AS

  SELECT customer_id FROM STREAM(LIVE.customers)

  WHERE loyalty_level = 'high';

  Which of the following describes why the STREAM function is included in the query?

  A. The STREAM function is not needed and will cause an error.

  B. The table being created is a live table.

  C. The customers table is a streaming live table.

  D. The customers table is a reference to a Structured Streaming query on a PySpark DataFrame.

  E. The data in the customers table has been updated since its last run.

  Correct Answer: C

  https://docs.databricks.com/en/sql/load-data-streaming-table.html Load data into a streaming table

  To create a streaming table from data in cloud object storage, paste the following into the query editor, and then click Run:

  SQL

  Copy to clipboardCopy

  /* Load data from a volume */

  CREATE OR REFRESH STREAMING TABLE AS SELECT * FROM STREAM

  read_files('/Volumes/////')

  /* Load data from an external location */

  CREATE OR REFRESH STREAMING TABLE AS SELECT * FROM STREAM read_files('s3:////')

• Question 86:

  A data architect has determined that a table of the following format is necessary:

  

  Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above format regardless of whether a table already exists with this name?

  

  A. Option A

  B. Option B

  C. Option C

  D. Option D

  E. Option E

  Correct Answer: E

• Question 87:

  A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.

  The code block used by the data engineer is below:

  

  If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?

  A. processingTime(1)

  B. trigger(availableNow=True)

  C. trigger(parallelBatch=True)

  D. trigger(processingTime="once")

  E. trigger(continuous="once")

  Correct Answer: B

  Explanation: https://stackoverflow.com/questions/71061809/trigger-availablenow-for-delta- source-streaming-queries-in-pyspark-databricks