[A/P] CSE DEPARTMENT
CHRIST THE KING ENGINEERING COLLEGE
A distributed database system consists of
loosely coupled sites that share no physical
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
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
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.
In a heterogeneous distributed
database system, at least one of the
databases uses different schemas and
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.
◦ System maintains multiple copies of data, stored in
different sites, for faster retrieval and fault tolerance.
◦ Relation is partitioned into several fragments stored in
Replication and fragmentation can be combined
• Relation is partitioned into several fragments: system
maintains several identical replicas of each such
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.
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.
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 –
Fragmentation can be horizontal or vertical
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
Performance - may be slower
Integrity - more difficult
Each fragment, Ti , of table T contains a
subset of the rows
Each tuple of T is assigned to one or more
Horizontal fragmentation is lossless
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
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 = 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.
A employee-info schema has a relation
employee-info schema = (designation, name,
It fragments the relation to put information in two
tables for security concern.
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
What is this?
Two-phase commit is a transaction protocol designed
for the complications that arise with distributed
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:
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
Step 2 Upon receiving message, transaction
manager at site determines if it can commit the
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
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.
There have been two performance issues with two
◦ 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