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Data Lake for Enterprises

You're reading from   Data Lake for Enterprises Lambda Architecture for building enterprise data systems

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787281349
Length 596 pages
Edition 1st Edition
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Authors (3):
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Pankaj Misra Pankaj Misra
Author Profile Icon Pankaj Misra
Pankaj Misra
Tomcy John Tomcy John
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Tomcy John
Vivek Mishra Vivek Mishra
Author Profile Icon Vivek Mishra
Vivek Mishra
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction to Data FREE CHAPTER 2. Comprehensive Concepts of a Data Lake 3. Lambda Architecture as a Pattern for Data Lake 4. Applied Lambda for Data Lake 5. Data Acquisition of Batch Data using Apache Sqoop 6. Data Acquisition of Stream Data using Apache Flume 7. Messaging Layer using Apache Kafka 8. Data Processing using Apache Flink 9. Data Store Using Apache Hadoop 10. Indexed Data Store using Elasticsearch 11. Data Lake Components Working Together 12. Data Lake Use Case Suggestions

Kafka programming interface


Kafka contains two programming interface mechanisms:

  • Low level core API’s
  • REST API’s: REST interface wrapping the core API’s for easy access

Kafka core API’s

These are the core API’s in Apache Kafka, as documented in the Apache Kafka documentation:

  • Producer API: Contains a set of API’s which allows us to publish a stream of data to one or more of the named/categorized Kafka topics in the cluster.
  • Streams API: Contains relevant API’s which acts on the stream of data. They can process this stream data and can transform it from existing form to a designated form according to your use case demands. These are relatively new API's as against existing producer and consumer API’s.
  • Connect API: API’s which allows Kafka to be extensible. It contains methods which can be used to build Kafka connectors for the inputting and outputting of data into Kafka.
  • Consumer API: Contains relevant API’s to subscribe to one or more topics in the broker. Since consumer takes care of a message...
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