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Here, you will find Analyzing Big Data in R using Apache Spark Exam Answers in Bold Color which are given below.
These answers are updated recently and are 100% correct✅ answers of all modules and final exam answers of Analyzing Big Data in R using Apache Spark from Cognitive Class Free Certification Course.
| Course Name | Analyzing Big Data in R using Apache Spark |
| Organization | IBM |
| Skill | Online Education |
| Level | Beginner |
| Language | English |
| Price | Free |
| Certificate | Yes |
Link for Course Enrollment: Enroll Now
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Module 1: Introduction to SparkR
Question 1: What shells are available for running SparkR??
- Spark-shell
- SparkSQL shell
- SparkR shell
- RSpark shell
- None of the options is correct
Question 2: What is the entry point into SparkR?
- SRContext
- SparkContext
- RContext
- SQLContext
Question 3: When would you need to call sparkR.init?
- using the R shell
- using the SR-shell
- using the SparkR shell
- using the Spark-shell
Module 2: Data manipulation in SparkR
Question 1: dataframes make use of Spark RDDs
- False
- True
Question 2: You need read.df to create dataframes from data sources?
- True
- False
Question 3: What does the groupBy function output??
- A AggregateOrder object
- A GroupedData object
- A OrderBy object
- A GroupBy object
Module3: Machine learning in Spark R
Question 1: What is the goal of MLlib?
- Integration of machine learning into SparkSQL
- To make practical machine learning scalable and easy
- Visualization of Machine Learning in SparkR
- Provide a development workbench for machine learning
- All of the options are correct
Question 2: What would you use to create plots? check all that apply
- pandas
- Multiplot
- Ggplot2
- matplotlib
- all of the above are correct
Question 3: Spark MLlib is a module of Apache Spark
- False
- True
Analyzing Big Data in R using Apache Spark Final Exam Answers Cognitive Class
Question 1: Which of these are NOT characteristics of Spark R?
- it supports distributed machine learning
- it provides a distributed data frame implementation
- is a cluster computing framework
- a light-weight front end to use Apache Spark from R
- None of the options is correct
Question 2: True or false? The client connection to the Spark execution environment is created by the shell for users using Spark:
- True
- False
Question 3: Which of the following are not features of Spark SQL?
- performs extra optimizations
- works with RDDs
- is a distributed SQL engine
- is a Spark module for structured data processing
- None of the options is correct
Question 4: True or false? Select returns a SparkR dataframe:
- False
- True
Question 5: SparkR defines the following aggregation functions:
- sumDistinct
- Sum
- count
- min
- All of the options are correct
Question 6: We can use SparkR sql function using the sqlContext as follows:
- head(sql(sqlContext, “SELECT * FROM cars WHERE cyl > 6”))
- SparkR:head(sql(sqlContext, “SELECT * FROM cars WHERE cyl > 6”))
- SparkR::head(sql(sqlContext, “SELECT * FROM cars WHERE cyl > 6”))
- SparkR(head(sql(sqlContext, “SELECT * FROM cars WHERE cyl > 6”)))
- None of the options is correct
Question 7: Which of the following are pipeline components?
- Transformers
- Estimators
- Pipeline
- Parameter
- All of the options are correct
Question 8: Which of the following is NOT one of the steps in implementing a GLM in SparkR:
- Evaluate the model
- Train the model
- Implement model
- Prepare and load data
- All of the options are correct
Question 9: True or false? Spark MLlib is a module SparkR to provide distributed machine learning algorithms.
- True
- False
Conclusion
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