ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model. Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 94

Media Database Metadata Data Schemas 94

ProjectPro

APRIL 26, 2016

Table of Contents Hadoop Hive Interview Questions and Answers Scenario based or Real-Time Interview Questions on Hadoop Hive Other Interview Questions on Hadoop Hive Hadoop Hive Interview Questions and Answers 1) What is the difference between Pig and Hive ? Used for Structured Data Schema Schema is optional.

Hadoop 40

Hadoop Metadata SQL Database 40