Technical Interview Questions
Hadoop facilitates you to increase or decrease the number of mappers without worrying about the volume of data to be processed. Hadoop is a distributed storage and processing framework designed to handle large volumes of data across multiple nodes. It is often compared to other data processing tools, and some key differences include: Distributed Processing … Read more
HDFS data blocks are distributed across local drives of all machines in a cluster whereas, NAS data is stored on dedicated hardware. HDFS (Hadoop Distributed File System) and NAS (Network Attached Storage) are both storage solutions, but they have significant differences in terms of architecture and use cases. Architecture: HDFS (Hadoop Distributed File System): HDFS … Read more
The Logical division of data is called Input Split and physical division of data is called HDFS Block. In Hadoop, Input Splits and HDFS (Hadoop Distributed File System) Blocks are two fundamental concepts related to data storage and processing. Here’s the difference between them: HDFS Block: Definition: HDFS divides a large file into smaller blocks, … Read more
In Hadoop, A job is divided into multiple small parts known as the task. In Hadoop, the terms “job” and “task” refer to different components of the overall data processing framework. Job: A job in Hadoop typically represents a complete computation that needs to be performed on a dataset. It is the unit of work … Read more
Yes, It is possible. The input format class provides methods to insert multiple directories as input to a Hadoop job. Yes, it is possible to provide multiple inputs to Hadoop. In Hadoop, the MapReduce programming model allows the processing of large datasets by breaking them into smaller chunks and processing them in parallel across a … Read more