Distributed Databases PDF

D ISTRIBUTED ATABASES INTRODUCTION Distributed computing system Consists of interconnected nodes Nodes cooperate to perform tasks efficiently 2 WHAT CONSTITUTES A DISTRIBUTED DATABASE? Connection of database nodes over a computer...

D ISTRIBUTED ATABASES INTRODUCTION Distributed computing system Consists of interconnected nodes Nodes cooperate to perform tasks efficiently 2 WHAT CONSTITUTES A DISTRIBUTED DATABASE? Connection of database nodes over a computer network Logical interrelation of connected databases Possible absence of homogeneity among nodes Distributed database management system (DDBMS) manages the distributed database 3 DIFFERENCE BETWEEN CENTRALIZED DATABASE AND DISTRIBUTED DATABASE 20XX Pitch deck title 4 TRANSPARENCY Transparency refers to hiding implementation details from end users for a seamless experience. Types of transparency: Data organization transparency Location transparency Naming transparency Replication transparency Fragmentation transparency Horizontal fragmentation Vertical fragmentation Design transparency Execution transparency 5 DISTRIBUTED DATABASES 6 AVAILABILITY AND RELIABILITY Availability: The probability that the distributed system is continuously available during a specified time interval. Reliability: The probability that the distributed system is running (not down) at a certain point in time. 7 SCALABILITY AND PARTITION TOLERANCE Horizontal scalability: expanding the number of nodes Vertical scalability: expanding capacity of individual nodes Partition tolerance: system continues operating during network partitioning 8 AUTONOMY Determines the extent to which nodes can operate independently Design autonomy: independence of data model and transaction management techniques Communication autonomy: determines sharing of information between nodes Execution autonomy: independence of user actions 9 ADVANTAGES OF DISTRIBUTED DATABASES Improved ease and flexibility of application development: Development can occur at geographically dispersed sites. Increased availability: Faults are isolated to their site of origin, ensuring availability. Improved performance: Data localization reduces network traffic and latency. Easier expansion via scalability: Adding nodes or increasing individual node capacity is easier compared to non-distributed systems. 10 DATA FRAGMENTATION, REPLICATION, AND ALLOCATION TECHNIQUES Fragments: Logical units of the database that are distributed across nodes. Horizontal fragmentation (sharding): Dividing a relation into subsets of tuples based on conditions or other methods. Vertical fragmentation: Dividing a relation vertically by columns, keeping only certain attributes. 11 HORIZONTAL FRAGMENTATION (SHARDING): Horizontal fragmentation (sharding) divides a relation into subsets of tuples, called shards, by specifying conditions on attributes or other methods. It groups rows to create these subsets. 12 VERTICAL FRAGMENTATION: Vertical fragmentation involves dividing a relation by columns, keeping only certain attributes of the relation. 13  Vertical 20XX Pitch deck title 14  Horizontal 20XX Pitch deck title 15 DATA FRAGMENTATION, REPLICATION, AND ALLOCATION TECHNIQUES CONT’D Complete horizontal fragmentation Apply UNION operation to the fragments to reconstruct relation Complete vertical fragmentation Apply OUTER JOIN operation to reconstruct relation 16  Complete vertical fragmentation Apply OUTER JOIN operation to reconstruct relation Age 25 30 User Ahmed Mohamed Complete Vertical Fragmentation: Fragment 1: B1 Fragment 2: B2 Reconstructed Relation after applying OUTER JOIN operation: R = B1 ⨝ B2 User Age Ahmed 25 Mohamed 30 20XX Pitch deck title 17  Apply UNION operation to the fragments to reconstruct relation User Age Mohamed 30 User Age Ahmed 25 Complete Horizontal Fragmentation: Fragment 1: A1 Fragment 2: A2 Reconstructed Relation after applying UNION operation: R = A1 ∪ A2 User Age Ahmed 25 Mohamed 30 20XX Pitch deck title 18 MIXED FRAGMENTATION: Combination of horizontal and vertical fragmentations 19 DATA FRAGMENTATION, REPLICATION, AND ALLOCATION TECHNIQUES CONT’D Replication and allocation: Strategies for storing fragments and replicas across nodes for performance and availability. Fully replicated distributed database: Whole database is replicated at every site. Nonredundant allocation: Each fragment is stored at exactly one site. Partial replication: Some fragments are replicated while others are not. 20 DATA FRAGMENTATION, REPLICATION, AND ALLOCATION TECHNIQUES CONT’D Data allocation involves assigning each fragment of data to a specific site within a distributed system. The choices for allocation are determined based on the system's performance and availability objectives. 21 22 23 24 TYPES OF DISTRIBUTED DATABASE SYSTEMS Homogeneous DDBMS Heterogeneous DDBM 25 TYPES OF DISTRIBUTED DATABASE SYSTEMS Homogeneous DDBMS: Uniform software across nodes. 26 TYPES OF DISTRIBUTED DATABASE SYSTEMS Heterogeneous DDBMS: Nodes with different software and configurations. 27 TYPES OF DISTRIBUTED DATABASE SYSTEMS Multi database system and federated database system (FDBS) with shared global schema. Federated database management systems issues: Differences in data models, constraints, query languages, and semantic heterogeneity. 28 CLIENT-SERVER DATABASE ARCHITECTURE It consists of clients running client software, a set of servers which provide all database functionalities and a reliable communication infrastructure. 29 CLIENT-SERVER DATABASE ARCHITECTURE It consists of clients running client software, a set of servers which provide all database functionalities and a reliable communication infrastructure. 30 THANK YOU 20XX Pitch deck title 31