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Disk Based Algorithms for Big Data 1st Edition by Christopher Healey ISBN 9781315302850 1315302853

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ISBN 10: 1315302853
ISBN 13: 9781315302850
Author: Christopher Healey

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. About the Author Dr. Christopher G. Healey is a tenured Professor in the Department of Computer Science and the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics, both at North Carolina State University in Raleigh, North Carolina. He has published over 50 articles in major journals and conferences in the areas of visualization, visual and data analytics, computer graphics, and artificial intelligence. He is a recipient of the National Science Foundation’s CAREER Early Faculty Development Award and the North Carolina State University Outstanding Instructor Award. He is a Senior Member of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE), and an Associate Editor of ACM Transaction on Applied Perception, the leading worldwide journal on the application of human perception to issues in computer science.

Disk Based Algorithms for Big Data 1st Edition Table of contents:

CHAPTER 1 Physical Disk Storage

1.1 PHYSICAL HARD DISK

1.2 CLUSTERS

1.2.1 Block Allocation

1.3 ACCESS COST

1.4 LOGICAL TO PHYSICAL

1.5 BUFFER MANAGEMENT

CHAPTER 2  File Management

2.1 LOGICAL COMPONENTS

2.1.1 Positioning Components

2.2 IDENTIFYING RECORDS

2.2.1 Secondary Keys

2.3 SEQUENTIAL ACCESS

2.3.1 Improvements

2.4 DIRECT ACCESS

2.4.1 Binary Search

2.5 FILE MANAGEMENT

2.5.1 Record Deletion

2.5.2 Fixed-Length Deletion

2.5.3 Variable-Length Deletion

2.6 FILE INDEXING

2.6.1 Simple Indices

2.6.2 Index Management

2.6.3 Large Index Files

2.6.4 Secondary Key Index

2.6.5 Secondary Key Index Improvements

CHAPTER 3  Sorting

3.1 HEAPSORT

3.2 MERGESORT

3.3 TIMSORT

CHAPTER 4  Searching

4.1 LINEAR SEARCH

4.2 BINARY SEARCH

4.3 BINARY SEARCH TREE

4.4 k-d TREE

4.4.1 k-d Tree Index

4.4.2 Search

4.4.3 Performance

4.5 HASHING

4.5.1 Collisions

4.5.2 Hash Functions

4.5.3 Hash Value Distributions

4.5.4 Estimating Collisions

4.5.5 Managing Collisions

4.5.6 Progressive Overflow

4.5.7 Multirecord Buckets

CHAPTER 5 Disk-Based Sorting

5.1 DISK-BASED MERGESORT

5.1.1 Basic Mergesort

5.1.2 Timing

5.1.3 Scalability

5.2 INCREASED MEMORY

5.3 MORE HARD DRIVES

5.4 MULTISTEP MERGE

5.5 INCREASED RUN LENGTHS

5.5.1 Replacement Selection

5.5.2 Average Run Size

5.5.3 Cost

5.5.4 Dual Hard Drives

CHAPTER 6  Disk-Based Searching

6.1 IMPROVED BINARY SEARCH

6.1.1 Self-Correcting BSTs

6.1.2 Paged BSTs

6.2 B-TREE

6.2.1 Search

6.2.2 Insertion

6.2.3 Deletion

6.3 B* TREE

6.4 B+ TREE

6.4.1 Prefix Keys

6.5 EXTENDIBLE HASHING

6.5.1 Trie

6.5.2 Radix Tree

6.6 HASH TRIES

6.6.1 Trie Insertion

6.6.2 Bucket Insertion

6.6.3 Full Trie

6.6.4 Trie Size

6.6.5 Trie Deletion

6.6.6 Trie Performance

CHAPTER 7  Storage Technology

7.1 OPTICAL DRIVES

7.1.1 Compact Disc

7.1.2 Digital Versatile Disc

7.1.3 Blu-ray Disc

7.2 SOLID STATE DRIVES

7.2.1 Floating Gate Transistors

7.2.2 Read-Write-Erase

7.2.3 SSD Controller

7.2.4 Advantages

7.3 HOLOGRAPHIC STORAGE

7.3.1 Holograms

7.3.2 Data Holograms

7.3.3 Commercialization

7.4 MOLECULAR MEMORY

7.5 MRAM

CHAPTER 8  Distributed Hash Tables

8.1 HISTORY

8.2 KEYSPACE

8.3 KEYSPACE PARTITIONING

8.4 OVERLAY NETWORK

8.5 CHORD

8.5.1 Keyspace

8.5.2 Keyspace Partitioning

8.5.3 Overlay Network

8.5.4 Addition

8.5.5 Failure

CHAPTER 9  Large File Systems

9.1 RAID

9.1.1 Parity

9.2 ZFS

9.2.1 Fault Tolerance

9.2.2 Self-Healing

9.2.3 Snapshots

9.3 GFS

9.3.1 Architecture

9.3.2 Master Metadata

9.3.3 Mutations

9.3.4 Fault Tolerance

9.4 HADOOP

9.4.1 MapReduce

9.4.2 MapReduce Implementation

9.4.3 HDFS

9.4.4 Pig

9.4.5 Hive

9.5 CASSANDRA

9.5.1 Design

9.5.2 Improvements

9.5.3 Query Language

9.6 PRESTO

CHAPTER 10  NoSQL Storage

10.1 GRAPH DATABASES

10.1.1 Neo4j

10.1.2 Caching

10.1.3 Query Languages

10.2 DOCUMENT DATABASES

10.2.1 SQL Versus NoSQL

10.2.2 MongoDB

10.2.3 Indexing

10.2.4 Query Languages

APPENDIX A  Order Notation

A.1 ©-NOTATION

A.2 O-NOTATION

A.3 Ω-NOTATION

A.4 INSERTION SORT

A.5 SHELL SORT

APPENDIX B  Assignment 1: Search

B.1 KEY AND SEEK LISTS

B.2 PROGRAM EXECUTION

B.3 IN-MEMORY SEQUENTIAL SEARCH

B.4 IN-MEMORY BINARY SEARCH

B.5 ON-DISK SEQUENTIAL SEARCH

B.6 ON-DISK BINARY SEARCH

B.7 PROGRAMMING ENVIRONMENT

B.7.1 Reading Binary Integers

B.7.2 Measuring Time

B.7.3 Writing Results

B.8 SUPPLEMENTAL MATERIAL

B.9 HAND-IN REQUIREMENTS

APPENDIX C Assignment 2: Indices

C.1 STUDENT FILE

C.2 PROGRAM EXECUTION

C.3 IN-MEMORY PRIMARY KEY INDEX

C.4 IN-MEMORY AVAILABILITY LIST

C.4.1 First Fit

C.4.2 Best Fit

C.4.3 Worst Fit

C.5 USER INTERFACE

C.5.1 Add

C.5.2 Find

C.5.3 Del

C.5.4 End

C.6 PROGRAMMING ENVIRONMENT

C.6.1 Writing Results

C.7 SUPPLEMENTAL MATERIAL

C.8 HAND-IN REQUIREMENTS

APPENDIX D  Assignment 3: Mergesort

D.1 INDEX FILE

D.2 PROGRAM EXECUTION

D.3 AVAILABLE MEMORY

D.4 BASIC MERGESORT

D.5 MULTISTEP MERGESORT

D.6 REPLACEMENT SELECTION MERGESORT

D.7 PROGRAMMING ENVIRONMENT

D.7.1 Measuring Time

D.7.2 Writing Results

D.8 SUPPLEMENTAL MATERIAL

D.9 HAND-IN REQUIREMENTS

APPENDIX E  Assignment 4: B-Trees

E.1 INDEX FILE

E.2 PROGRAM EXECUTION

E.3 B-TREE NODES

E.3.1 Root Node Offset

E.4 USER INTERFACE

E.4.1 Add

E.4.2 Find

E.4.3 Print

E.4.4 End

E.5 PROGRAMMING ENVIRONMENT

E.6 SUPPLEMENTAL MATERIAL

E.7 HAND-IN REQUIREMENTS

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