A practical guide to realizing the seamless potential of storing and managing high-volume, high-velocity data quickly and painlessly with HBaseAbout This Book
- Learn how to use HBase efficiently to store and manage endless amounts of data
- Discover the intricacies of HBase internals, schema designing, and features like data scanning and filtration
- Optimize your big data management and BI using practical implementations
Who This Book Is For
This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. This book is also for Big Data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic, scalable database solution in the Big Data space.
What You Will Learn
- Realize the need for HBase
- Download and set up HBase cluster
- Grasp data modeling concepts in HBase and how to perform CRUD operations on data
- Perform effective data scanning and data filtration in HBase
- Understand data storage and replication in HBase
- Explore HBase counters, coprocessors, and MapReduce integration
- Get acquainted with different clients of HBase such as REST and Kundera ORM
- Learn about cluster management and performance tuning in HBase
In Detail
With an example-oriented approach, this book begins by providing you with a step-by-step learning process to effortlessly set up HBase clusters and design schemas. Gradually, you will be taken through advanced data modeling concepts and the intricacies of the HBase architecture. Moreover, you will also get acquainted with the HBase client API and HBase shell. Essentially, this book aims to provide you with a solid grounding in the NoSQL columnar database space and also helps you take advantage of the real power of HBase using data scans, filters, and the MapReduce framework. Most importantly, the book also provides you with practical use cases covering various HBase clients, HBase cluster administration, and performance tuning.
Nishant Garg
Nishant Garg has over 14 years of experience in software architecture and development in various technologies such as Java, Java Enterprise Edition, SOA, Spring, Hibernate, Hadoop, Hive, Flume, Sqoop, Oozie, Spark, Shark, YARN, Impala, Kafka, Storm, Solr/Lucene, and NoSQL databases including HBase, Cassandra, MongoDB, and MPP Databases such as GreenPlum. He received his MS degree in Software Systems from Birla Institute of Technology and Science, Pilani, India, and is currently working as a technical architect in Big Data R&D Group in Impetus Infotech Pvt. Ltd. Nishant, in his previous experience, has enjoyed working with the most recognizable names in IT services and financial industries, employing full software life cycle methodologies such as Agile and Scrum. He has also undertaken many speaking engagements on Big Data Technologies and is also the author of Apache Kafka, Packt Publishing.
