Architecting Big Data Solutions Using Google Dataproc from Pluralsight

Dataproc is Google’s managed Hadoop offering on the cloud. This course teaches you how the separation of storage and compute allows you to utilize clusters more efficiently purely for processing data and not for storage.

When organizations plan their move to the Google Cloud Platform, Dataproc offers the same features but with additional powerful paradigms such as separation of compute and storage. Dataproc allows you to lift-and-shift your Hadoop processing jobs to the cloud and store your data separately on Cloud Storage buckets, thus effectively eliminating the requirement to keep your clusters always running. In this course, Architecting Big Data Solutions Using Google Dataproc, you’ll learn to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating your on-premise jobs to Dataproc clusters. First, you'll delve into creating a Dataproc cluster and configuring firewall rules to enable you to access the cluster manager UI from your local machine. Next, you'll discover how to use the Spark distributed analytics engine on your Dataproc cluster. Then, you'll explore how to write code in order to integrate your Spark jobs with BigQuery and Cloud Storage buckets using connectors. Finally, you'll learn how to use your Dataproc cluster to perform extract, transform, and load operations using Pig as a scripting language and work with Hive tables. By the end of this course, you'll have the necessary knowledge to work with Google’s managed Hadoop offering and have a sound idea of how to migrate jobs and data on your on-premise Hadoop cluster to the Google Cloud.

What's inside

Syllabus

Course Overview

Introducing Google Dataproc for Big Data on the Cloud

Running Hadoop MapReduce Jobs on Google Dataproc

Working with Apache Spark on Google Dataproc

Working with Pig and Hive on Google Dataproc

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a practical approach to using Apache Hadoop Processing on the Google Cloud Platform

Covers essential concepts like separation of compute and storage to optimize cluster usage

Focuses on real-world use cases for migrating on-premise Hadoop clusters to the Cloud

Implements industry best practices for migrating Hadoop jobs to Dataproc clusters

Provides hands-on experience using Spark, Pig, and Hive on Google Dataproc

Taught by industry professionals with experience in Big Data and Hadoop

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Architecting Big Data Solutions Using Google Dataproc with these activities:

Review machine learning fundamentals

Show steps

This course assumes a basic understanding of machine learning concepts, such as supervised learning, unsupervised learning, and model evaluation. Reviewing these concepts will help you to succeed.

Browse courses on Machine Learning

Show steps

Review online tutorials
Complete practice exercises

Review SQL basics

Show steps

This course assumes a basic understanding of SQL, so refreshing your knowledge before starting the course will help you to succeed. Specifically, review the basics of SQL, including data types, operators, and CRUD operations.

Browse courses on SQL

Show steps

Read online tutorials
Complete practice exercises

Organize your notes

Show steps

Organizing your notes will help you to stay on top of the course material and make it easier to review for exams.

Show steps

Review your notes
Identify key concepts
Organize your notes into sections
Create a study guide

Five other activities

Expand to see all activities and additional details

Show all eight activities

Follow online tutorials

Show steps

Online tutorials provide a structured and guided approach to learning new concepts and skills, which can be particularly helpful for beginners or those who want to reinforce their understanding.

Browse courses on Spark

Show steps

Search for tutorials on specific topics
Follow the step-by-step instructions
Complete the exercises and quizzes

Work through practice problems

Show steps

Practicing the syntax and concepts of each problem will help to reinforce your understanding of the fundamentals and improve your ability to apply them in real-world scenarios.

Browse courses on Hadoop

Show steps

Review the course material
Identify areas where you need additional practice
Find practice problems online or in textbooks
Work through the problems
Check your answers and identify any errors

Join a study group

Show steps

Participating in a study group will allow you to discuss the course material with other students, ask questions, and get help with difficult concepts.

Show steps

Find a study group or start your own
Meet regularly to discuss the material
Work together on assignments and projects

Create a data analytics project

Show steps

This project will allow you to apply your skills and knowledge to a real-world problem and deepen your understanding of data analytics.

Browse courses on Hadoop

Show steps

Identify a problem or opportunity
Gather and prepare data
Build and train a model
Evaluate and refine your model
Present your results

Attend meetups and conferences

Show steps

Networking events are a great way to meet other professionals in your field, learn from their experiences, and stay up-to-date on the latest trends in data analytics.

Show steps

Find industry related events
Attend events regularly
Connect with other professionals

Career center

Learners who complete Architecting Big Data Solutions Using Google Dataproc will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use scientific methods and processes to extract knowledge and insights from data. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to write code in order to integrate Spark jobs with BigQuery and Cloud Storage buckets using connectors.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning models. This course may be helpful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with Apache Spark on Google Dataproc.

See salaries and explore the career path for Machine Learning Engineer

Data Architect

Data Architects create and manage the architecture of an organization's data systems. This course may be helpful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Data Architect

Data Engineer

Data Engineers design, build, and maintain data pipelines and infrastructure. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Data Engineer

Software Engineer - Big Data

Software Engineers, Big Data design, build, and maintain software systems for processing and analyzing large datasets. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Software Engineer - Big Data

Database Administrator

Database Administrators manage and maintain databases. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Database Administrator

Cloud Architect

Cloud Architects design and implement cloud computing solutions. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Cloud Architect

Business Intelligence Analyst

Business Intelligence Analysts use data to help businesses make better decisions. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to perform extract, transform, and load operations using Pig as a scripting language and work with Hive tables.

See salaries and explore the career path for Business Intelligence Analyst

DevOps Engineer

DevOps Engineers work to bridge the gap between development and operations teams. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for DevOps Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with Pig and Hive on Google Dataproc.

See salaries and explore the career path for Data Analyst

Network Engineer

Network Engineers design, build, and maintain computer networks. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to configure firewall rules to enable access to the cluster manager UI from a local machine.

See salaries and explore the career path for Network Engineer

Technical Support Engineer

Technical Support Engineers provide technical support to users of computer systems. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Technical Support Engineer

Systems Administrator

Systems Administrators manage and maintain computer systems. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Systems Administrator

Security Analyst

Security Analysts identify and mitigate security threats. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to configure firewall rules to enable access to the cluster manager UI from a local machine.

See salaries and explore the career path for Security Analyst

Web Developer

Web Developers design and develop websites. This course may be useful in providing foundational knowledge necessary for success in this role, particularly with regards to understanding how to work with managed Hadoop on the Google Cloud and the best practices to follow for migrating on-premise jobs to Dataproc clusters.

See salaries and explore the career path for Web Developer