data_eng.tar.gz

AWS_ACCESS_KEY_ID

AWS_SECRET_ACCESS_KEY

AWS_DEFAULT_REGION

Apache_Druid

Mapreduce

aws_load_balancer

service_sharding

cqrs

apache_spark

apache_kafka

Gone are the days when monolithic applications were the norm. Most applications that we use today are too complex for that type of construction. Instead, most applications that appear as a single unit are actually built as a collection of inter-operating but independent computational components. Developers are expected to have mastery over a programming language or two. Moreover, they should also know the basics of distributed systems in order to succeed.

In this course, you’ll learn what a distributed system is, followed by the challenges unique to distributed systems. You’ll cover popular architectural patterns for achieving targets like replication and sharding. You’ll finish with a study of two popular distributed systems: Apache Spark and Apache Druid.

With the knowledge gained through this course, you’ll be able to design and develop distributed systems. You’ll be able to make optimal design and architectural choices based on the application requirements.

Introduction to Distributed Systems for Dummies

Which one of the below options is an advantage of caching?

Which one of the below options is an advantage of caching?

Which of the following is directly impacted in a write-through cache?

Which of the following is directly impacted in a write-through cache?

**(True or False)** In the LRU cache, the most frequently used items are kept.

(True or False) In the LRU cache, the most frequently used items are kept.

**(True or False)** Setting up TTL (time-to-leave) does not have any impact on a caching system.

(True or False) Setting up TTL (time-to-leave) does not have any impact on a caching system.

Which of the following caching types might incur cache miss when recently written data is reread?

Which of the following caching types might incur cache miss when recently written data is reread?

Evaluate your understanding of caching concepts in distributed systems.

Introduction

What Distributed Systems Achieve for Us

Data in Distributed Systems

Communication Between Nodes

Data Processing in Large Scale

Distributed System Architectural Patterns

Case Study 1: Apache Spark

Case Study 2: Apache Druid

Conclusion

Quick Quiz #9: Caching