Disk-based algorithms for big data / Christopher G. Healey
Material type:
TextPublication details: Boca Raton : CRC Press, ©2017.Description: xx, 184 pages : illustrations (some color) ; 25 cmISBN: - 9781138196186
- 005.7 23 H434
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 005.7 H434 (Browse shelf(Opens below)) | Available | 138418 |
Browsing ISI Library, Kolkata shelves Close shelf browser (Hides shelf browser)
| No cover image available | No cover image available | |||||||
| 005.7 G892 Data science from scratch: first principles with Python/ | 005.7 H264 Handbook of big data analytics / | 005.7 H362 Developing power builder 5 | 005.7 H434 Disk-based algorithms for big data / | 005.7 H936 Big data applications and use cases / | 005.7 In61 Management of data | 005.7 K14 Big data computing: a guide for business and technology managers/ |
Includes index.
Chapter 1. Physical disk storage --
Chapter 2. File management --
Chapter 3. Sorting --
Chapter 4. Searching --
Chapter 5. Disk-based sorting --
Chapter 6. Disk-based searching --
Chapter 7. Storage technology --
Chapter 8. Distributed hast tables --
Chapter 9. Large file systems --
Chapter 10. NoSQL storage.
Disk-Based Algorithms for Big Data is a product of recent advances in the areas of big data, data analytics, and the underlying file systems and data management algorithms used to support the storage and analysis of massive data collections. The book discusses hard disks and their impact on data management, since Hard Disk Drives continue to be common in large data clusters. It also explores ways to store and retrieve data though primary and secondary indices. This includes a review of different in-memory sorting and searching algorithms that build a foundation for more sophisticated on-disk approaches like mergesort, B-trees, and extendible hashing.
Following this introduction, the book transitions to more recent topics, including advanced storage technologies like solid-state drives and holographic storage; peer-to-peer (P2P) communication; large file systems and query languages like Hadoop/HDFS, Hive, Cassandra, and Presto; and NoSQL databases like Neo4j for graph structures and MongoDB for unstructured document data.
Designed for senior undergraduate and graduate students, as well as professionals, this book is useful for anyone interested in understanding the foundations and advances in big data storage and management, and big data analytics.
There are no comments on this title.
