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Spark Fundamentals I Cognitive Class Course Answer

Module 1: Introduction to Spark

Question 1: For what purpose would an Engineer use Spark? Select all that apply.

• Analyzing data to obtain insights
• Programming with Spark’s API
• Transforming data into a useable form for analysis
• Developing a data processing system
• Tuning an application for a business use case

Question 2: What gives Spark its speed advantage for complex applications?

• Spark extends the MapReduce model
• Various libraries provide Spark with additional functionality
• Spark can cover a wide range of workloads under one system
• Spark makes extensive use of in-memory computations
• All of the above

Question 3: Which of the following statements are true of the Resilient Distributed Dataset (RDD)? Select all that apply.

• There are three types of RDD operations.
• RDDs allow Spark to reconstruct transformations
• RDDs only add a small amount of code due to tight integration
• RDD action operations do not return a value
• RDD is a distributed collection of elements parallelized across the cluster.

Module 2: Resilient Distributed Dataset and DataFrames

Question 1: Module 2: Resilient Distributed Dataset and DataFrames

Which of the following methods can be used to create a Resilient Distributed Dataset (RDD)? Select all that apply.

• Creating a directed acyclic graph (DAG)
• Parallelizing an existing Spark collection
• Referencing a Hadoop-supported dataset
• Using data that resides in Spark
• Transforming an existing RDD to form a new one

Question 2: Which of the following statements is true of RDD persistence? Select all that apply.

• Persistence through caching provides fault tolerance
• Future actions can be performed significantly faster
• Each partition is replicated on two cluster nodes
• RDD persistence always improves space efficiency
• By default, objects that are too big for memory are stored on the disk

Question 3: What happens when an action is executed?

• Executors prepare the data for operation in parallel
• The driver sends code to be executed on each block
• A cache is created for storing partial results in memory
• Data is partitioned into different blocks across the cluster
• All of the above

Module 3: Spark application programming

Question 1: Which of the following methods can be used to pass functions to Spark? Select all that apply.

• Transformations and actions
• Passing by reference
• Static methods in a global singleton
• Import statements
• Anonymous function syntax

Question 2: What is SparkContext?

• An object that represents the connection to a Spark cluster
• A tool for linking to nodes
• A tool that provides fault tolerance
• The built-in shell for the Spark engine
• A programming language for applications

Question 3: Which of the following is a main component of a Spark application’s source code?

• SparkContext object
• Transformations and actions
• Business Logic
• Import statements
• All of the above

Module 4: Introduction to the Spark libraries

Question 1: Which of the following is NOT an example of a Spark library?

• Hive
• MLlib
• Spark Streaming
• Spark SQL
• GraphX

Question 2: In Spark Streaming, processing begins immediately when an element of the application is executed. True or false?

• True
• False

Question 3: From which of the following sources can Spark Streaming receive data? Select all that apply.

• Kafka
• JSON
• Parquet
• HDFS
• Hive

Module 5: Spark configuration, monitoring and tuning

Question 1: What are the main locations for Spark configuration? Select all that apply.

• The SparkConf object
• The Spark Shell
• Executor Processes
• Environment variables
• Logging properties

Question 2: Which of the following techniques can improve Spark performance? Select all that apply.

• Scheduler Configuration
• Memory Tuning
• Data Serialization
• Using Broadcast variables
• Using nested structures

Question 3: Which of the following is a main component of a Spark cluster? Select all that apply.

• Driver Program
• SparkContext
• Cluster Manager
• Worker node
• Cache

Final Exam Answers Spark Fundamentals I Cognitive Class

Question 1: Spark supports which of the following programming languages?

• C++ and Python
• Scala, Java, C++, Python, Perl
• Scala, Perl, Java
• Scala, Python, Java, R
• Java and Scala

Question 2: The “local” parameter can be used to specify the number of cores to use for the application. True or false?

• True
• False

Question 3: Spark Streaming processes live streaming data in real-time. True or false?

• True
• False

Question 4: Which serialization libraries are supported in Spark? Select all that apply.

• Apache Avro
• Java Serialization
• Protocol Buffers
• Kyro Serialization
• TPL

Question 5: Spark supports which of the following libraries?

• GraphX
• Spark Streaming
• MLlib
• Spark SQL
• All of the above

Question 6: You must explicitly initialize the SparkContext when creating a Spark application. True or false?

• True
• False

Question 7: Spark SQL allows relational queries to be expressed in which of the following?

• HiveQL only
• Scala, SQL, and HiveQL
• Scala and SQL
• Scala and HiveQL
• SQL only

Question 8: Which list describes the correct order of precedence for Spark configuration, from highest to lowest?

• Properties set on SparkConf, values in spark-defaults.conf, flags passed to spark-submit
• Flags passed to spark-submit, values in spark-defaults.conf, properties set on SparkConf
• Values in spark-defaults.conf, properties set on SparkConf, flags passed to spark-submit
• Values in spark-defaults.conf, flags passed to spark-submit, properties set on SparkConf
• Properties set on SparkConf, flags passed to spark-submit, values in spark-defaults.conf

Question 9: Spark monitoring can be performed with external tools. True or false?

• True
• False

Question 10: Which of the following is a type of Spark RDD operation? Select all that apply.

• Parallelization
• Action
• Persistence
• Transformation
• Evaluation

Question 11: Which of the following operations will work improperly when using a Combiner?

• Count
• Maximum
• Minimum
• Average
• All of the above operations will work properly

Question 12: Which storage level does the cache() function use?

• MEMORY_AND_DISK_SER
• MEMORY_AND_DISK
• MEMORY_ONLY_SER
• MEMORY_ONLY

Question 13: Spark applications can ONLY be packaged using one, specific build tool. True or false?

• True
• False

Question 14: Which of the following is NOT supported as a cluster manager?

• YARN
• Helix
• Mesos
• Spark
• All of the above are supported

Question 15: What is the purpose of the GraphX library?

• To create a visual representation of the data
• To generate data-parallel models
• To create a visual representation of a directed acyclic graph (DAG)
• To perform graph-parallel computations
• To convert from data-parallel to graph-parallel algorithms

Question 16: Spark must be installed and run on top of a Hadoop cluster. True or false

• True
• False

Question 17: A transformation is evaluated immediately. True or false?

• True
• False

Question 18: Which of the following statements does NOT describe accumulators?

• They can only be read by the driver
• Programmers can extend them beyond numeric types
• They implement counters and sums
• They can only be added through an associative operation
• They are read-only

Question 19: Which of the following parameters of the “spark-submit” script determine where the application will run?

• –class
• –master
• –deploy-mode
• –conf
• None of the above

Question 20: The MLlib library contains which of the following algorithms?

• Dimensionality Reduction
• Regression
• Classification
• Clustering
• All of the above

Conclusion

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