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Data Lake for Enterprises

You're reading from  Data Lake for Enterprises

Product type Book
Published in May 2017
Publisher Packt
ISBN-13 9781787281349
Pages 596 pages
Edition 1st Edition
Languages
Authors (3):
Vivek Mishra Vivek Mishra
Profile icon Vivek Mishra
Tomcy John Tomcy John
Profile icon Tomcy John
Pankaj Misra Pankaj Misra
Profile icon Pankaj Misra
View More author details

Table of Contents (23) Chapters

Title Page
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Part 1 - Overview
Part 2 - Technical Building blocks of Data Lake
Part 3 - Bringing It All Together
1. Introduction to Data 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

When to use Flink


Select Flink as your data processing technology when:

  • You need high performance. Flink at the moment is one of the best in performance for stream processing.
  • Your use case needs machine learning. Flink’s native closed loop iterations operators make the processing perform much faster.
  • Your use case needs graph processing. Again, because of the preceding same feature, Flink will process data faster.
  • You require high throughput rates with guaranteed consistency.
  • You need exactly one time processing. This also eliminates duplicate record processing.
  • You want to avoid handling memory manually and leave that to the framework. Flink has automatic memory management.
  • You need to deal with intermediate results and Flink follows the data flow approach making it easy to do this.
  • You need less configuration. Many aspects in Flink are abstracted away from the user and this makes configuration simple.
  • You need to deal with both batch and stream data using the same framework. Flink is a hybrid...
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