Expert techniques for architecting end-to-end big data solutions to get valuable insights /
First Statement of Responsibility
V Naresh Kumar, Prashant Shindgikar.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Birmingham :
Name of Publisher, Distributor, etc.
Packt Publishing,
Date of Publication, Distribution, etc.
2018.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (394 pages)
GENERAL NOTES
Text of Note
Table of ContentsHadoop Design Consideration Hadoop Life Cycle ManagementData Modeling in HadoopDesigning Streaming Data PipelinesBuilding Enterprise Search Platform Data Movement TechniquesEnterprise Data Architecture PrinciplesArchitecting Large Scale Data Processing Solutions using Spark Developing Application using Cloud InfrastructureDesigning Data Visualization Solutions Production Hadoop Administration and Cluster Deployment.
CONTENTS NOTE
Text of Note
Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Enterprise Data Architecture Principles; Data architecture principles; Volume; Velocity; Variety; Veracity; The importance of metadata; Data governance; Fundamentals of data governance; Data security; Application security; Input data; Big data security; RDBMS security; BI security; Physical security; Data encryption; Secure key management; Data as a Service; Evolution data architecture with Hadoop; Hierarchical database architecture; Network database architecture.
Text of Note
Add serviceService placement; Service client placement; Database creation on master; Ranger database configuration; Configuration changes; Configuration review; Deployment progress; Application restart; Apache Ranger user guide; Login to UI; Access manager; Service details; Policy definition and auditing for HDFS; Summary; Chapter 3: Hadoop Design Consideration; Understanding data structure principles; Installing Hadoop cluster; Configuring Hadoop on NameNode; Format NameNode; Start all services; Exploring HDFS architecture; Defining NameNode; Secondary NameNode; NameNode safe mode; DataNode.
Text of Note
Best practices Hadoop deploymentHadoop file formats; Text/CSV file; JSON; Sequence file; Avro; Parquet; ORC; Which file format is better?; Summary; Chapter 4: Data Movement Techniques; Batch processing versus real-time processing; Batch processing; Real-time processing; Apache Sqoop; Sqoop Import; Import into HDFS; Import a MySQL table into an HBase table; Sqoop export; Flume; Apache Flume architecture; Data flow using Flume; Flume complex data flow architecture; Flume setup; Log aggregation use case; Apache NiFi; Main concepts of Apache NiFi; Apache NiFi architecture; Key features.
Text of Note
Data replicationRack awareness; HDFS WebUI; Introducing YARN; YARN architecture; Resource manager; Node manager; Configuration of YARN; Configuring HDFS high availability; During Hadoop 1.x; During Hadoop 2.x and onwards; HDFS HA cluster using NFS; Important architecture points; Configuration of HA NameNodes with shared storage; HDFS HA cluster using the quorum journal manager; Important architecture points; Configuration of HA NameNodes with QJM; Automatic failover; Important architecture points; Configuring automatic failover; Hadoop cluster composition; Typical Hadoop cluster.
Text of Note
Relational database architectureEmployees; Devices; Department; Department and employee mapping table; Hadoop data architecture; Data layer; Data management layer; Job execution layer; Summary; Chapter 2: Hadoop Life Cycle Management; Data wrangling; Data acquisition; Data structure analysis; Information extraction; Unwanted data removal; Data transformation; Data standardization; Data masking; Substitution; Static ; Dynamic; Encryption; Hashing; Hiding; Erasing; Truncation; Variance; Shuffling; Data security; What is Apache Ranger?; Apache Ranger installation using Ambari; Ambari admin UI.
0
8
8
8
8
SUMMARY OR ABSTRACT
Text of Note
This book presents unique techniques to conquer different Big Data processing and analytics challenges using Hadoop. Practical examples are provided to boost your understanding of Big Data concepts and their implementation. By the end of the book, you will have all the knowledge and skills you need to become a true Big Data expert.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Packt Publishing
Source for Acquisition/Subscription Address
OverDrive, Inc.
Stock Number
9781787128811
Stock Number
D508DE65-BBBA-46CD-928A-49C8DFBFE6AC
OTHER EDITION IN ANOTHER MEDIUM
Title
Modern Big Data Processing with Hadoop : Expert techniques for architecting end-to-end big data solutions to get valuable insights.
TITLE USED AS SUBJECT
Apache Hadoop.
Apache Hadoop.
TOPICAL NAME USED AS SUBJECT
Electronic data processing-- Distributed processing.
COMPUTERS-- Computer Literacy.
COMPUTERS-- Computer Science.
Computers-- Data Modeling & Design.
Computers-- Data Processing.
Computers-- Database Management-- Data Mining.
COMPUTERS-- Hardware-- General.
COMPUTERS-- Information Technology.
COMPUTERS-- Machine Theory.
COMPUTERS-- Reference.
Data capture & analysis.
Data mining.
Database design & theory.
Electronic data processing-- Distributed processing.