Hortonworks Company Quiz! Trivia

The correct answer is MapReduce and HDFS. HortonWorks is a big data software company, and MapReduce and HDFS are two core concepts in their platform. MapReduce is a programming model used for processing large datasets in parallel, while HDFS (Hadoop Distributed File System) is a distributed file system that allows for the storage and retrieval of large amounts of data across multiple nodes in a cluster. These two concepts are fundamental to the functioning of HortonWorks' platform and are essential for handling big data processing and storage efficiently.

Structured data refers to information that is organized and can be stored in a table format. This type of data follows a specific schema and has a predefined structure, making it easy to categorize, search, and analyze. It typically includes data types such as numbers, dates, and text, and can be efficiently stored and processed using database management systems. By contrast, unstructured data lacks a predefined format and is more challenging to organize and analyze. Therefore, the correct answer in this case is "Data that can be stored in a table."

In HDFS, data is stored in blocks, which are the minimum amount of data that can be written or read. Each block is typically 128 MB or 256 MB in size. The data is divided into these blocks and then distributed across multiple nodes in the Hadoop cluster for fault tolerance and parallel processing. Therefore, the correct answer is "Block".

HortonWorks is a data platform that specializes in handling big data and analytics. JSON (JavaScript Object Notation) is a lightweight data interchange format that is commonly used for transmitting data between a server and a web application. It is a popular choice for storing and processing data in big data platforms like HortonWorks due to its simplicity, flexibility, and compatibility with various programming languages. On the other hand, Docx is a file format for Microsoft Word documents, Exe is an executable file format for Windows, and BSON (Binary JSON) is a binary representation of JSON-like documents. These file formats are not typically associated with HortonWorks.

Online transactions are not considered unstructured data because they follow a specific format and structure. They typically include information such as transaction amount, date, time, and the parties involved. On the other hand, tweets, weblogs, and product reviews are examples of unstructured data as they are not organized in a predefined manner and can contain various types of information, opinions, and sentiments.

Data booting is not a step involved in deploying big data. The other three options, data processing, data storage, and data ingestion, are all essential steps in deploying big data. Data processing involves analyzing and manipulating the data to extract meaningful insights. Data storage involves storing the large volumes of data generated by big data applications. Data ingestion involves collecting and importing data from various sources into the big data infrastructure. However, data booting is not a recognized step in the process of deploying big data.

HortonWorks is a big data management framework that is powered by Apache Hadoop. Apache Hadoop is an open-source software framework that provides distributed storage and processing of large datasets across clusters of computers. It is designed to scale up from single servers to thousands of machines, offering high availability and fault tolerance. HortonWorks leverages the power of Apache Hadoop to provide a comprehensive platform for managing and analyzing big data.

HortonWorks was founded in 2011.

The port number of the NameNode in Hadoop is 50070. The NameNode is responsible for managing the file system metadata and keeps track of the data blocks in Hadoop. It acts as the central point for all the client operations and coordinates the data storage and retrieval processes. By default, the NameNode listens on port 50070 for incoming client requests and communicates with the DataNodes to ensure the availability and reliability of the data in the Hadoop cluster.

CSV (Comma Separated Values) files are ideal for exchanging data between HortonWorks and external systems because they are simple and widely supported. CSV files store tabular data in plain text, with each line representing a row and each value separated by a comma. This format allows for easy parsing and compatibility with various software applications. Additionally, CSV files are human-readable and can be easily edited using a text editor, making them a versatile choice for data exchange.