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Cloudera CDP Data Engineer - Certification Exam Sample Questions (Q155-Q160):

NEW QUESTION # 155
You're working with a large DAG that contains numerous tasks and complex dependencies. How can you improve the DAG's readability and maintainability?

A. Break down the DAG into smaller sub-DAGs with well-defined functionalities and clear naming conventions.
B. Use cryptic and abbreviated names for tasks and variables, assuming everyone understands the context.
C. Utilize comments sparingly within the DAG code, as the logic should be self-explanatory.
D. Implement extensive logging within each task, regardless of its purpose, to capture detailed execution information.

Answer: A

NEW QUESTION # 156
How does the Cloudera Optimization Framework leverage columnar storage formats for query performance improvement?

A. By encrypting data stored in columnar formats
B. By allowing more efficient data scans and operations on compressed data
C. By enabling more efficient compression and encoding schemes
D. By reducing network traffic through columnar data replication

Answer: B

Explanation:
Columnar storage formats allow for more efficient data scans and operations, especially for queries that access a subset of columns in a large dataset This efficiency comes from the ability to read, compress, and process only the necessary columns for a query, significantly reducing I/O and CPU usage compared to row-based storage.

NEW QUESTION # 157
Consider the following code snippet:# Sample DataFrame (assuming it exists) df = spark.createDataFrame(...)
# Attempt to add a new column with a case-when expression (fix the error) df = df.withColumn("category", F.when(df["price"] ] 100, "Expensive").otherwise("Cheap")) df.show() What is the error in this code, and how can it be fixed?

A. There is no error in the code snippet.
B. The error is attempting to modify the original DataFrame in-place. Fix: Use df.withColumn to create a new DataFrame with the added column.
C. The error is using the wrong syntax for case-when expressions. Fix: Use SQL-like syntax with CASE WHEN and END.
D. The error is missing parentheses around the conditions in the when function. Fix: F.when((df["price"] ] 100), "Expensive").otherwise("Cheap")

Answer: B

Explanation:
The error lies in attempting to modify the original DataFrame in-place. The correct approach is to use withColumn to create a new DataFrame with the added column, as shown in the fixed code:df = df.withColumn("category", ] 100, "Expensive").otherwise("Cheap"))

NEW QUESTION # 158
In the context of dynamic partitioning in Hive, what challenge does the use of too many dynamic partitions in a single load operation present?

A. It automatically disables the execution of map-reduce jobs.
B. It enhances data security by segmenting data into finer-grained partitions.
C. It simplifies the management of Hive metadata, reducing the load on the NameNode.
D. It can lead to an excessive number of small files, negatively impacting HDFS performance.

Answer: D

Explanation:
Using too many dynamic partitions in a single load operation can lead to the creation of an excessive number of small files. This situation is problematic because it can significantly degrade HDFS performance due to the overhead associated with managing a large number of files, including increased memory consumption on the NameNode for metadata management and potential slowdowns in data processing tasks that have to open and read many small files.

NEW QUESTION # 159
You have a PySpark application packaged as 'MyPySparkApp-0. I-py3-none-any.whl'. In your 'app.py', you utilize a function from an external library, 'numpy', listed in your 'requirements.txt'. How should you deploy this application to ensure 'numpy' is available at runtime?

A. Upload 'MyPySparkApp-0.1-py3-none-any.whl' only and submit using 'spark-submit --py-files MyPySparkApp-0.1-py3-none-any.whl'.
B. Upload 'app.py' and manually install 'numpy' on all nodes before submitting using 'spark-submit app.py'.
C. Upload both 'app.py' and 'MyPySparkApp-0.1-py3-none-any.whl' and submit using 'spark-submit --py-files MyPySparkApp-0.1-py3-none- any.whl app.py'.
D. Upload 'app.py' only and submit using 'spark-submit app.py'.

Answer: C

Explanation:
The application 'app.py' depends on the 'numpy' library, which is packaged in the wheel file 'MyPySparkApp-0.1-py3-none- any.whl'. Therefore, both the application file and the wheel file need to be uploaded. The application is then submitted with the '-- py-files' option to include the wheel file, ensuring 'numpy' is available at runtime.

NEW QUESTION # 160
......

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