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

ProjectPro

JANUARY 24, 2023

Numeric data consists of four sub-types: Integer type (INT64) Numeric type (NUMERIC DECIMAL) Bignumeric type (BIGNUMERIC BIGDECIMAL) Floating point type (FLOAT64) BYTES Although they work with raw bytes rather than Unicode characters, BYTES also represent variable-length data. Q: Is BigQuery SQL or NoSQL?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

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. 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? How is Hadoop related to Big Data? Define and describe FSCK.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Rockset

AUGUST 11, 2022

They tackled the topic, “SQL versus NoSQL Databases in the Modern Data Stack.” I remember back in the day when you had to set up your clusters and run Hadoop and Kafka clusters on top, it was quite expensive. Now, we don’t have to care about bytes, but we do have to care about how many gigabytes or terabytes we are going to process.

Bytes 52

Bytes Consulting Kafka MongoDB 52

Grouparoo

OCTOBER 6, 2021

39 How to Prevent a Data Mutiny Key trends: modular architecture, declarative configuration, automated systems 40 Know the Value per Byte of Your Data Check if you are actually using your data 41 Know Your Latencies key questions: how old is data? Increase visibility. how fast are queries? how many concurrent queries can we handle?

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

ProjectPro

AUGUST 26, 2015

1998 -An open source relational database was developed by Carlo Strozzi who named it as NoSQL. However, 10 years later, NoSQL databases gained momentum with the need to process large unstructured data sets. Hadoop is an open source solution for storing and processing large unstructured data sets. billion requests every day.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

Knowledge Hut

MARCH 27, 2024

quintillion bytes of data today, and unless that data is organized properly, it is useless. Some open-source technology for big data analytics are : Hadoop. APACHE Hadoop Big data is being processed and stored using this Java-based open-source platform, and data can be processed efficiently and in parallel thanks to the cluster system.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52