Distributed Computing

Processing large data on multiple computers

Methods for processing large data sets by breaking them into smaller subsets and processing them on different computers in parallel.

5 minutes 5 Questions

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Big Data Scientist - Distributed Computing Example Questions

Test your knowledge of Amazon Simple Storage Service (S3)

Question 1

What is the purpose of Spark's Resilient Distributed Datasets (RDDs)?

To collect and store data in-memory within a Spark job. To visualize data within Spark. To transform data between different file formats in Spark. To model and evaluate data using statistical analysis in Spark. To allow for fault-tolerant parallel processing of data by dividing the data into partitions across a cluster of machines. To perform machine learning on data in Spark.

Correct Answer: To allow for fault-tolerant parallel processing of data by dividing the data into partitions across a cluster of machines.

Spark's Resilient Distributed Datasets (RDDs) are a fundamental data structure of Spark, allowing for fault-tolerant, parallel processing of data by dividing data into partitions across a cluster of machines.

Question 2

What is the purpose of Apache ZooKeeper?

To perform stream processing on large datasets. To visualize and analyze data. To store and manage large amounts of data. To manipulate and transform data. To run distributed computations. To manage and coordinate distributed applications by providing a centralized infrastructure and a set of API's.

Correct Answer: To manage and coordinate distributed applications by providing a centralized infrastructure and a set of API's.

Apache ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.

Question 3

What is the purpose of a data node in HDFS?

To store data in HDFS by allocating the storage space and managing data on the node. To monitor the health of the HDFS cluster. To process computation jobs in MapReduce in HDFS. To run as a client library for accessing HDFS. To manage data backup and restore in HDFS. To execute the NameNode in HDFS.

Correct Answer: To store data in HDFS by allocating the storage space and managing data on the node.

A data node stores data by allocating the storage space and managing data on the node. DataNodes also remove blocks when they are no longer needed.

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