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Building Data Streaming Applications with Apache Kafka

You're reading from  Building Data Streaming Applications with Apache Kafka

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781787283985
Pages 278 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details

Table of Contents (14) Chapters

Preface 1. Introduction to Messaging Systems 2. Introducing Kafka the Distributed Messaging Platform 3. Deep Dive into Kafka Producers 4. Deep Dive into Kafka Consumers 5. Building Spark Streaming Applications with Kafka 6. Building Storm Applications with Kafka 7. Using Kafka with Confluent Platform 8. Building ETL Pipelines Using Kafka 9. Building Streaming Applications Using Kafka Streams 10. Kafka Cluster Deployment 11. Using Kafka in Big Data Applications 12. Securing Kafka 13. Streaming Application Design Considerations

External data lookups

The first question that must be in your mind is why we need external data lookups in the stream processing pipeline. The answer is that sometimes you need to perform operations such as enrichment, data validation, or data filtering on incoming events based on some frequently changing external system data. However, in the streaming design context, these data lookups pose certain challenges. These data lookups may result in increased end-to-end latency as there will be frequent calls to external systems. You cannot hold all the external reference data in-memory as these external datasets are too big to fit in-memory. They also change too frequently, which makes refreshing memory difficult. If these external systems are down, then they will become a bottleneck for streaming solutions.

Keeping these challenges in mind, there are three important factors while...

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