The document describes log-based recovery techniques for databases. It discusses two techniques - deferred database modification and immediate database modification. For deferred modification, writes are deferred until after commit. For immediate modification, writes can occur before commit as long as the log record is written first. The document also covers recovery with concurrent transactions using undo/redo lists and checkpoints.
This presentation discusses the following topics:
What is Recovery ?
Database Recovery techniques
System log
Working of Commit and Roll back
Recovery techniques
Backup techniques
This presentation discusses the following topics:
What is Recovery ?
Database Recovery techniques
System log
Working of Commit and Roll back
Recovery techniques
Backup techniques
Transaction is a unit of program execution that accesses and possibly updates various data items.
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A brief introduction to Process synchronization in Operating Systems with classical examples and solutions using semaphores. A good starting tutorial for beginners.
In DBMS (DataBase Management System), the relation algebra is important term to further understand the queries in SQL (Structured Query Language) database system. In it just give up the overview of operators in DBMS two of one method relational algebra used and another name is relational calculus.
Transaction is a unit of program execution that accesses and possibly updates various data items.
Usually, a transaction is initiated by a user program written in a high-level data-manipulation language or programming language (for example, SQL,COBOL, C, C++, or Java), where it is delimited by statements (or function calls) of the form begin transaction and end transaction.
A brief introduction to Process synchronization in Operating Systems with classical examples and solutions using semaphores. A good starting tutorial for beginners.
In DBMS (DataBase Management System), the relation algebra is important term to further understand the queries in SQL (Structured Query Language) database system. In it just give up the overview of operators in DBMS two of one method relational algebra used and another name is relational calculus.
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The need to perform a DB2 log-based recovery of multiple objects is a very rare event, but statistically, it is more frequent than a true disaster recovery event (flood, fire, etc). Taking regular backups is necessary but far from sufficient for anything beyond minor application recovery. If not prepared, practiced and optimised, it can lead to extended application service downtimes – possibly many hours to several days. This presentation will provide many hints and tips on how to plan, design intelligently, stress test and optimise DB2 log-based recovery.
SQL In The City - Understanding and Controlling Transaction Logs by Nigel Peter Sammy.
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: On March 30, 2016, ISE announced that it is the first regulated exchange to build and operate a cloud-based disaster recovery infrastructure as part of its disaster preparedness requirements established by the SEC. In this presentation, Rob Cornish, CIO at ISE, talks about the benefits of a cloud-hosted disaster recovery infrastructure, the business reasons behind the initiative, the production timeline, and the realized benefits.
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Modified version of Chapter 21 of the book Fundamentals_of_Database_Systems,_6th_Edition with review questions
as part of database management system course
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
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Log based and Recovery with concurrent transaction
1.
2.
3. Log-Based Recovery
A Log is the most widely used structure for recording database modifications.
Update log record: It describes a single database write. It has following fields-
Transaction identifier is the unique identifier of the transaction that performed the
write operation.
Data item identifier is the unique identifier of the data item written.
Old value is the value of the data item prior to the write.
New value is the value of the data item that it will have after the write.
Various types of log records are represented as:
< Ti start>: Transaction Ti has started.
<Ti, X, V1, V2> : Transaction Ti has performed a write on data item Xj , Xj had
value v1 before the write, and will have value v2 after the write.
<Ti commit> : Transaction Ti has committed.
<Ti abort> : Transaction Ti has aborted.
Two techniques that user s log:
Deferred database modification
Immediate database modification
4. Deferred Database Modification
The deferred database modification scheme records all
modifications to the log, but defers all the writes to after
partial commit.
Assume that transactions execute serially
Transaction starts by writing <Ti start> record to log.
A write(X) operation results in a log record <Ti, X, V>
being written, where V is the new value for X
Note: old value is not needed for this scheme
The write is not performed on X at this time, but is
deferred.
When Ti partially commits, <Ti commit> is written to the
log
Finally, the log records are read and used to actually
execute the previously deferred writes.
5. Deferred Database Modification
(Cont.)
During recovery after a crash, a transaction needs to be
redone if and only if both <Ti start> and<Ti commit>
are there in the log.
Redoing a transaction Ti ( redoTi) sets the value of all
data items updated by the transaction to the new values.
Crashes can occur while
the transaction is executing the original updates, or
while recovery action is being taken
example transactions T0 and T1 (T0 executes before T1):
T0: read (A) T1 : read (C);
A: = A – 50; C:-=C- 100;
Write (A); write (C);
read (B);
B:= B + 50;
write (B);
6. Deferred Database Modification
(Cont.)
Below we show the log as it appears at three instances of
time.
If log on stable storage at time of crash is as in case:
(a) No redo actions need to be taken
(b) redo(T0) must be performed since <T0 commit> is present
(c) redo(T0) must be performed followed by redo(T1) since
<T0 commit> and <Ti commit> are present
7. Immediate Database Modification
The immediate database modification technique allows
database modifications to be output to the database while
the transaction is still in the active state.
Update log record must be written before database item is
written
We assume that the log record is output directly to stable storage
Can be extended to postpone log record output, so long as prior to execution of
an output(B) operation for a data block B, all log records corresponding to
items B must be flushed to stable storage
Output of updated blocks can take place at any time before
or after transaction commit
Order in which blocks are output can be different from the
order in which they are written.
8. Immediate Database Modification Example
Log Write Output
<T0 start>
<T0, A, 1000, 950>
To, B, 2000, 2050
A = 950
B = 2050
<T0 commit>
<T1 start>
<T1, C, 700, 600>
C = 600
BB, BC
<T1 commit>
BA
Note: BX denotes block containing X.
x1
9. Immediate Database Modification
(Cont.)
Recovery procedure has two operations instead of one:
undo(Ti) restores the value of all data items updated by Ti to their old
values, going backwards from the last log record for Ti
redo(Ti) sets the value of all data items updated by Ti to the new values,
going forward from the first log record for Ti
Both operations must be idempotent
That is, even if the operation is executed multiple times the effect is the
same as if it is executed once
Needed since operations may get re-executed during recovery
When recovering after failure:
Transaction Ti needs to be undone if the log contains the record
<Ti start>, but does not contain the record <Ti commit>.
Transaction Ti needs to be redone if the log contains both the record <Ti
start> and the record <Ti commit>.
Undo operations are performed first, then redo
operations.
10. Immediate DB Modification Recovery Example
Below we show the log as it appears at three instances of time.
Recovery actions in each case above are:
(a) undo (T0): B is restored to 2000 and A to 1000.
(b) undo (T1) and redo (T0): C is restored to 700, and then A and B are
set to 950 and 2050 respectively.
(c) redo (T0) and redo (T1): A and B are set to 950 and 2050
respectively. Then C is set to 600
11.
12. Recovery With Concurrent
Transactions
We modify the log-based recovery schemes to allow multiple transactions to
execute concurrently.
All transactions share a single disk buffer and a single log
A buffer block can have data items updated by one or more transactions
We assume concurrency control using strict two-phase locking;
i.e. the updates of uncommitted transactions should not be visible to other
transactions
Otherwise how to perform undo if T1 updates A, then T2 updates A and
commits, and finally T1 has to abort?
Logging is done as described earlier.
Log records of different transactions may be interspersed in the log.
The checkpointing technique and actions taken on recovery have to be
changed
since several transactions may be active when a checkpoint is performed.
13. Recovery With Concurrent Transactions (Cont.)
Checkpoints are performed as before, except that the
checkpoint log record is now of the form
< checkpoint L>
where L is the list of transactions active at the time of
the checkpoint
We assume no updates are in progress while the checkpoint is carried out
(will relax this later)
When the system recovers from a crash, it first does
the following:
1. Initialize undo-list and redo-list to empty
2. Scan the log backwards from the end, stopping when the first
<checkpoint L> record is found.
For each record found during the backward scan:
if the record is <Ti commit>, add Ti to redo-list
if the record is <Ti start>, then if Ti is not in redo-list, add Ti to undo-
list
3. For every Ti in L, if Ti is not in redo-list, add Ti to undo-list
14. Recovery With Concurrent Transactions (Cont.)
At this point undo-list consists of incomplete
transactions which must be undone, and redo-list
consists of finished transactions that must be redone.
Recovery now continues as follows:
1. Scan log backwards from most recent record, stopping when
<Ti start> records have been encountered for every Ti in undo-list.
During the scan, perform undo for each log record that belongs to a
transaction in undo-list.
2. Locate the most recent <checkpoint L> record.
3. Scan log forwards from the <checkpoint L> record till the end of the log.
During the scan, perform redo for each log record that belongs to a
transaction on redo-list
15. Example of Recovery
Go over the steps of the recovery algorithm on the
following log:
<T0 start>
<T0, A, 0, 10>
<T0 commit>
<T1 start>
<T1, B, 0, 10>
<T2 start> /* Scan in Step 4 stops here */
<T2, C, 0, 10>
<T2, C, 10, 20>
<checkpoint {T1, T2}>
<T3 start>
<T3, A, 10, 20>
<T3, D, 0, 10>
<T3 commit>