Remove Data Schemas Remove Hadoop Remove Metadata
article thumbnail

100+ Big Data Interview Questions and Answers 2023

ProjectPro

Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS. Data Variety Hadoop stores structured, semi-structured and unstructured data.

article thumbnail

Top 100 Hadoop Interview Questions and Answers 2023

ProjectPro

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
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Large Scale Ad Data Systems at Booking.com using the Public Cloud

Booking.com Engineering

Our team collectively runs more than 1 million queries per month, scanning more than 2 PB of data. BigQuery saves us substantial time — instead of waiting for hours in Hive/Hadoop, our median query run time is 20 seconds for batch, and 2 seconds for interactive queries[3].

Systems 52
article thumbnail

Implementing the Netflix Media Database

Netflix Tech

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 96
article thumbnail

Hands-On Introduction to Delta Lake with (py)Spark

Towards Data Science

The main player in the context of the first data lakes was Hadoop, a distributed file system, with MapReduce, a processing paradigm built over the idea of minimal data movement and high parallelism. Delta Lake also refuses writes with wrongly formatted data (schema enforcement) and allows for schema evolution.

article thumbnail

11 Ways To Stop Data Anomalies Dead In Their Tracks

Monte Carlo

Otherwise you may produce more data anomalies than you prevent. Data Contracts Image courtesy of Andrew Jones. You can think of data contracts as circuit breakers, but for data schemas instead of the data itself. Today, data clouds have made the most precious and costly resource data engineer’s time.

Food 52
article thumbnail

Optimizing Kafka Streams Applications

Confluent

For this specific case, when the StreamBuilder#build() method is called, Streams will “push up” the repartitioning phase of the logical plan based on the captured metadata before compiling it to the processor topology. Government contractor using distributed software such as Apache Kafka, Spark and Hadoop.

Kafka 91