Gain insights into distributed systems, learn architectural patterns like replication and sharding, and explore Apache Spark and Druid to design and develop effective distributed applications.

data_eng.tar.gz

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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

In this last lesson of the chapter, we will discuss a popular architectural pattern for distributed systems: the **command query responsibility segregation** (CQRS) pattern.

## What is CQRS?

The name pretty much gives away the meaning.

In CQRS, read and write paths are separated, and possibly there are separate databases that handle read and write requests.

**Command** means requests like create, insert, update or delete. On the other hand, **query** means read requests. In read requests, no data is changed in any way. Data is served to clients as a response to queries. In CQRS, the read and the write path are segregated. Written data is made available for reading using some sort of special mechanism.


In this last lesson of the chapter, we will discuss a popular architectural pattern for distributed systems: the **command query responsibility segregation** (CQRS) pattern.

# What is CQRS?

The name pretty much gives away the meaning.

In CQRS, read and write paths are separated, and possibly there are separate databases that handle read and write requests.

**Command** means requests like create, insert, update or delete. On the other hand, **query** means read requests. In read requests, no data is changed in any way. Data is served to clients as a response to queries. In CQRS, the read and the write path are segregated. Written data is made available for reading using some sort of special mechanism.


Learn about how the command query responsibility segregation pattern works.

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

Command Query Responsibility Segregation (CQRS)

What is CQRS?