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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
Author Profile Icon Tomcy John
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

Where we stand with Data Lake

This figure shows where we have reached with our Data Lake after covering part 2 of this book:


Figure 01: Data Lake implemented so far in this book

HDFS

Distributed File Storage

MapReduce

Batch Processing Engine

YARN

Resource Negotiator

HBase

Columnar and Key Value NoSQL database that runs on HDFS

Hive

Query engine that provides SQL like access to HDFS

Impala

Fast Query Engine for analytical queries on HDFS

Sqoop

Data Acquisition and Ingestion

Flume

Data Acquisition and Ingestion via streamed flume events

Kafka

Highly Scalable Distributed Messaging Engine

Flink

All purpose Real Time data processing and ingestion with Batch Support

Spark

All purpose Fast Batch Processing and ingestion with support for real time processing via micro-batches

Elasticsearch

Fast Distributed Indexing Engine built on Lucene, also...

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