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NPTEL Big Data Computing Assignment 3 Answer 2022 :-
Q1. Statement 1: Spark improves efficiency through in-memory computing primitives and general computation graphs.
Statement 2: Spark improves usability through high-level APIs in Java, Scala, Python and also provides an interactive shell.
- Only statement 1 is true
- Only statement 2 is true
- Both statements are true
- Both statements are false
Q.2. Resilient Distributed Datasets (RDDs) are fault-tolerant and immutable.
- True
- False.
NPTEL Big Data Computing Week 4 Assignment 4 Answers 👇
Q.3. In Spark, a ____ is a read-only collection of objects partitioned across a set of machines that can be rebuilt if a partition is lost.
- Spark Streaming
- FlatMap
- Resilient Distributed Dataset (RDD)
- Driver
Q.4. Given the following definition about the join transformation in Apache Spark:
- Answer: B
Q.5. True or False ?
Apache Spark potentially run batch–processing programs up to 100 times faster than Hadoop MapReduce in memory, or 10 times faster on disk.
- True
- False
Q.6. ______ leverages Spark Core fast scheduling capability to perform streaming analytics.
- MLlib
- GraphX
- RDDs
- Spark Streaming
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Q.7. ______ is a distributed graph processing framework on top of Spark.Only statement 1 is true
- GraphX
- MLlib
- Spark streaming
- All of the mentioned
Q.8. Which of the following are the simplest NoSQL databases ?
- Wide–column
- Key-value
- Document
- All of the mentioned
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Q.9. Consider the following statements:
Statement 1: Scale out means grow your cluster capacity by replacing with more powerful machines.
Statement 2: Scale up means incrementally grow your cluster capacity by adding more COTS machines (Components Off the Shelf).
- Only statement 1 is true
- Only statement 2 is true
- Both statements are false
- Both statements are true
Q.10. Point out the incorrect statement in the context of Cassandra:
- It is originally designed at Facebook
- It is designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure
- It is a centralized key-value store
- It uses a ring-based DHT (Distributed Hash Table) but without finger tables or routing.
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About NPTEL Big Data Computing Course:
In today’s fast-paced digital world , the incredible amount of data being generated every minute has grown tremendously from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and GPS signals from cell phone to name a few. This amount of large data with different velocities and varieties is termed as big data and its analytics enables professionals to convert extensive data through statistical and quantitative analysis into powerful insights that can drive efficient decisions.
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COURSE LAYOUT
The course structure and content covers, over a period of 8 weeks:
- Week 1 : Introduction to Big Data
- Week 2 : Introduction to Enabling Technologies for Big Data
- Week 3 : Introduction to Big Data Platforms
- Week 4 : Introduction to Big Data Storage Platforms for Large Scale Data Storage
- Week 5 : Introduction to Big Data Streaming Platforms for Fast Data
- Week 6 : Introduction to Big Data Applications (Machine Learning)
- Week 7 : Introduction of Big data Machine learning with Spark
- Week 8 : Introduction to Big Data Applications (Graph Processing)