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Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
Distributed databases,types of database
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Distributed databases,types of database

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  • 1. R.BOOMADEVI.,M.C.A.,M.E [A/P] CSE DEPARTMENT CHRIST THE KING ENGINEERING COLLEGE COIMBATORE
  • 2.  A distributed database system consists of loosely coupled sites that share no physical component  Appears to user as a single system  Database systems that run on each site are independent of each other  Processing maybe done at a site other than the initiator of request
  • 3.  All sites have identical software  They are aware of each other and agree to cooperate in processing user requests  It appears to user as a single system
  • 4.  A distributed system connects three databases: hq, mfg, and sales  An application can simultaneously access or modify the data in several databases in a single distributed environment.
  • 5.  In a heterogeneous distributed database system, at least one of the databases uses different schemas and software.  A database system having different schema may cause a major problem for query processing.  A database system having different software may cause a major problem for transaction processing.
  • 6.  Replication ◦ System maintains multiple copies of data, stored in different sites, for faster retrieval and fault tolerance.  Fragmentation ◦ Relation is partitioned into several fragments stored in distinct sites Replication and fragmentation can be combined • Relation is partitioned into several fragments: system maintains several identical replicas of each such fragment.
  • 7. Availability: failure of site containing relation r does not result in unavailability of r is replicas exist. Parallelism: queries on r may be processed by several nodes in parallel. Reduced data transfer: relation r is available locally at each site containing a replica of r.
  • 8. Increased cost of updates: each replica of relation r must be updated. Increased complexity of concurrency control: concurrent updates to distinct replicas may lead to inconsistent data unless special concurrency control mechanisms are implemented.  One solution: choose one copy as primary copy and apply concurrency control operations on primary copy.
  • 9.  Data can be distributed by storing individual tables at different sites  Data can also be distributed by decomposing a table and storing portions at different sites – called Fragmentation  Fragmentation can be horizontal or vertical
  • 10.  Usage - in general applications use views so it’s appropriate to work with subsets  Efficiency - data stored close to where it is most frequently used  Parallelism - a transaction can divided into several sub-queries to increase degree of concurrency  Security - data more secure - only stored where it is needed Disadvantages: Performance - may be slower Integrity - more difficult
  • 11.  Each fragment, Ti , of table T contains a subset of the rows  Each tuple of T is assigned to one or more fragments.  Horizontal fragmentation is lossless
  • 12.  A bank account schema has a relation Account-schema = (branch-name, account-number, balance).  It fragments the relation by location and stores each fragment locally: rows with branch-name = `Hillside` are stored in the Hillside in a fragment
  • 13.  Each fragment, Ti, of T contains a subset of the columns, each column is in at least one fragment, and each fragment includes the key: Ti = Πattr_listi (T) T = T1 T2 ….. Tn All schemas must contain a common candidate key (or superkey) to ensure lossless join property. A special attribute, the tuple-id attribute may be added to each schema to serve as a candidate key.
  • 14.  A employee-info schema has a relation employee-info schema = (designation, name, Employee-id, salary).  It fragments the relation to put information in two tables for security concern.
  • 15.  Commit protocols are used to ensure atomicity across sites  Atomicity states that database modifications must follow an “all or nothing” rule.  a transaction which executes at multiple sites must either be committed at all the sites, or aborted at all the sites.
  • 16.  What is this?  Two-phase commit is a transaction protocol designed for the complications that arise with distributed resource managers.  Two-phase commit technology is used for hotel and airline reservations, stock market transactions, banking applications, and credit card systems.  With a two-phase commit protocol, the distributed transaction manager employs a coordinator to manage the individual resource managers. The commit process proceeds as follows:
  • 17.  Step 1  Coordinator asks all participants to prepare to commit transaction Ti.  Ci adds the records <prepare T> to the log and forces log to stable storage (a log is a file which maintains a record of all changes to the database)  sends prepare T messages to all sites where T executed
  • 18.  Step 2  Upon receiving message, transaction manager at site determines if it can commit the transaction  if not: add a record <no T> to the log and send abort T message to Ci  if the transaction can be committed, then: 1). add the record <ready T> to the log 2). force all records for T to stable storage 3). send ready T message to Ci
  • 19.  Step 1  T can be committed of Ci received a ready T message from all the participating sites: otherwise T must be aborted.  Step 2  Coordinator adds a decision record, <commit T> or <abort T>, to the log and forces record onto stable storage. Once the record is in stable storage, it cannot be revoked (even if failures occur)  Step 3  Coordinator sends a message to each participant informing it of the decision (commit or abort)  Step 4  Participants take appropriate action locally.
  • 20.  There have been two performance issues with two phase commit: ◦ If one database server is unavailable, none of the servers gets the updates. ◦ This is correctable through network tuning and correctly building the data distribution through database optimization techniques.
  • 21.  THANK YOU

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