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In the context of packaging a PySpark application, what is the purpose of the 'requirements.txt' file?
A. To list the environment variables needed for the application.
B. To specify the Python version required for the application.
C. To list all the third-party dependencies required by the application.
D. To define the Spark version compatible with the application.
Answer: C
Explanation:
The 'requirements.txt' file is used to list all third-party libraries (dependencies) that the PySpark application needs. These dependencies are then installed using pip.
NEW QUESTION # 151
In a meeting about Spark applications deployment on Kubernetes, your team discusses strategies for handling node failures. Which Kubernetes feature should be utilized to maintain high availability in case of node failures?
A Horizontal Pod Autoscaler
A. Resource Quotas
B. ReplicaSets
C. Pod Priority
Answer: C
Explanation:
ReplicaSets in Kubernetes are designed to maintain a stable set of replica Pods running at any given time, making them suitable for handling node failures and maintaining high availability. This ensures that if a node fails, Kubernetes can automatically redistribute the pods to other available nodes.
NEW QUESTION # 152
Which data format is recommended in PySpark for efficient storage and processing of large datasets due to its columnar storage and better compression characteristics?
A. Text File
B. Parquet
C. JSON
D. CSV
Answer: B
Explanation:
Parquet is a columnar storage format that offers efficient data compression and encoding schemes. It is optimized for use with complex data structures and is particularly beneficial in Spark and Hadoop ecosystems for large-scale data processing.
NEW QUESTION # 153
What is the primary consideration when choosing the number of buckets in a Hive table?
A. The number of rows in each partition
B. The total storage capacity of the HDFS cluster
C. The number of nodes in the Hadoop cluster
D. The expected distribution of data across the bucketing column
Answer: D
Explanation:
The primary consideration when choosing the number of buckets in a Hive table is the expected distribution of data across the bucketing column. The goal is to ensure that data is evenly distributed across buckets to avoid skew and to maximize the efficiency of operations like joins and aggregations that can leverage bucketing. An uneven distribution can lead to some buckets being much larger than others, negating the performance benefits of bucketing.
NEW QUESTION # 154
You need to process data stored in AWS S3 using SparkSQL. Which of the following options correctly reads a JSON file stored in S3 into a DataFrame and performs a SQL query on it?
A.
B.
C.
D.
Answer: C
Explanation:
Option D is correct as it uses the 's3a' protocol to read the JSON file from AWS S3, creates a temporary view, and then performs a SQL query on the DataFrame.
NEW QUESTION # 155
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