Big Data Developer Interview Questions and Answers

AWS Glue can process petabytes of data per hour

• AWS Glue can process petabytes of data per hour, depending on the configuration and resources allocated

• It is designed to scale horizontally to handle large volumes of data efficiently

• AWS Glue can be used for ETL (Extract, Transform, Load) processes on massive datasets

Distribution in Spark refers to how data is divided across different nodes in a cluster for parallel processing.

• Distribution in Spark determines how data is partitioned across different nodes in a cluster

• It helps in achieving parallel processing by distributing the workload

• Examples of distribution methods in Spark include hash partitioning and range partitioning

Hadoop is an open-source framework for distributed storage and processing of large data sets, while HDFS is the Hadoop Distributed File System used for storing data across multiple machines.

• Hadoop is designed to handle big data by distributing the data processing tasks across a cluster of computers.

• HDFS is the primary storage system used by Hadoop, which breaks down large files into smaller blocks and distributes them across multiple nodes in a cluster.

• HDFS provides high faul...read more

Spark is a fast and general-purpose cluster computing system, while PySpark is the Python API for Spark.

• Spark is a distributed computing system that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.

• PySpark is the Python API for Spark that allows developers to write Spark applications using Python.

• Spark and PySpark are commonly used for big data processing, machine learning, and real-time analytics.

• Example: Using PySpark ...read more

Various technologies like Hadoop, Spark, Kafka, and Python were used in projects.

• Hadoop for distributed storage and processing

• Spark for real-time data processing

• Kafka for streaming data pipelines

• Python for data analysis and machine learning