Transcript Transaction Introduction to ARIES Introduction to ARIES • ARIES (Algorithm for Recovery and Isolation Exploiting Semantics) • ARIES is a recovery algorithm •

Transaction
Introduction to ARIES
Introduction to ARIES
• ARIES (Algorithm for Recovery and Isolation Exploiting Semantics)
• ARIES is a recovery algorithm
• When the recovery manager is invoked after a crash, restart
proceeds in three phases.
• Analysis phase. Determines the earliest log record from which
the next pass must start.
• It also scans the log forward from the checkpoint record to
construct a snapshot of what the system looked like at the
instant of the crash.
• Redo phase. it repeats all actions, starting from an
appropriate point in the log, and restores the database state
to what it was at the time of the crash.
• Undo phase. it undoes the actions of transactions that did not
commit, so that the database reflects only the actions of
committed transactions.
Introduction to ARIES
• In addition to the log, the following two tables contain important
recovery related information:
• Transaction Table:
• Dirty page table:
• Transaction Table: This table contains one entry for each active
transaction.
• 'The entry contains the transaction id, the status, and a field called
lastLSN, which is the LSN of the most recent log record for this
transaction.
• The status of a transaction can be that it is in progress, or aborted
• Dirty page table: This table contains one entry for each dirty page in
the buffer pool, that is, each page with changes not yet reflected on
disk.
• The entry contains a field rec LSN, which is the LSN of the first log
record that caused the page to become dirty.
Introduction to ARIES
• During normal operation, these are maintained
by the transaction manager and the buffer
manager, respectively, and during restart after a
crash, these tables are reconstructed in the
Analysis phase of restart.
Distributed Database
System
Distributed Database System
• A distributed database (DDB) is a collection of
multiple, logically interrelated databases
distributed over a computer network.
• A distributed database management system (D–
DBMS) is the software that manages the DDB
and provides an access mechanism that makes
this distribution transparent to the users.
Distributed Database System
• Implicit assumptions
• – Data stored at a number of sites each site
logically consists of a single processor
• – Processors at different sites are interconnected
by a computer network
• – DDBMS is a collections of DBMSs not a
collection of files (not a remote file system)
Distributed Database System
Distributed Database System
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Advantages:
• Higher reliability
• Improved performance
• Easier system expansion
• Transparency of distributed and replicated
data
Distributed Database System
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Advantages:
Higher reliability
• Replication of components
• No single points of failure
• e.g., a broken communication link or processing
element does not bring down the entire system
• • Distributed transaction processing guarantees
the consistency of the database and concurrency
Distributed Database System
• Advantages:
• Improved performance
• – Reduces remote access delays
• – Requires some support for fragmentation and
replication
• – Intra-query parallelism
• Easier system expansion
• • Issue is database scaling
• – Network of workstations much cheaper than a
single mainframe computer
• • Increasing database size
Distributed Database System
• Advantages:
• Transparency
• • Refers to the separation of the higher-level
semantics of the system from the lower-level
• implementation issues
• • A transparent system “hides” the
implementation details from the users.
• • A fully transparent DBMS provides high-level
support for the development of complex
applications.
Distributed Database System
• Disadvantages
• N/W connection problem: technical problem may
be generated when we want to connect dissimilar
machines
• Data security problem: security problem increases
when data are located at multiple sites
• Data integrity problem: because date are access
from many locations and perform some operations
like select, update, maintaining the integrity is a big
issue
• Cost: large communication n/w is maintained so
h/w & s/w implementation cost is high
Distributed Database System
• Distributed database design
• The design of a distributed database introduces
3 new cases
• How to partition the database into fragments?
• Which fragments to replicate?
• Where to locate those fragments?
Distributed database design
• Data fragmentation
• It allows to break a single object into two or more
segments or fragments
• The object might be database or a table
• Each fragment can be store at any site over a
computer n/w
• Data fragmentation information is stored in the
distributed data catalog
• Data fragmentation can be classified as
• Horizontal fragmentation
• Vertical fragmentation
• Mixed fragmentation
Distributed database design
• Data fragmentation
• Horizontal fragmentation
• It refers to the division of a relation into subset of
tuples (rows)
• Each fragments is stored at a different nodes
• We can use selection capability in SQL to choose
the rows in a table that we want to b returned by a
query
• Vertical fragmentation
• It refers to division of a relation into attributes
(columns) subset
• Each fragments is stored at a different nodes
• We can use projection capability in SQL to choose
the columns in a table that we want to b returned
by a query
Distributed database design
• Data fragmentation
• Mixed fragmentation
• It refers to the combination of horizontal &
vertical fragmentation. That is division of a
relation into subset of rows & columns
• Each fragments is stored at a different nodes
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Distributed database design
• Data Replication
• Refers to the storage of data copies at multiple
sites by a computer n/w
• Each copies are stored at a different nodes
• Data copies can help to reduces communication
response time
• Suppose database F is divided into two
fragments F1 & F2
• Within a replicated distributed database the
mechanism is possible
Distributed database design
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Data Replication
Fragment F1 is stored at sites S1 & S3
Fragment F2 is stored at sites S2 & S3
So in data replication the same copy of data is
available at more than one site
Distributed database design
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Data Replication
Data replication can be performed in three ways
Fully replicated database: it stores multiple copies
of each database fragments at multiple sites
Here all database fragments are replicated
Partially replicated database: it stores multiple
copies of some database fragment at multiple sites
Most DDMS are able to handle the partial
replicated database well
Unreplicated database : it stores each database
fragment at a single site