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–Some part of the world about which information is stored
–Provides a mechanism to scope a problem area |
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Four components of Database system |
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1. database
2. software
3. hardware
4. people |
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•An organized collection of logically-
related persistent data |
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Used to
1. Define data types
2. populate data
3. manipulate data
4. control security |
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Largest DBMS software vendors |
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1. Oracle
2. IBM
3. Microsoft |
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–Supports the execution of the database system software. |
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–Primary: main memory/ random access memory (RAM) and cache
–Secondary: Magnetic Disks
–Tertiary: Tapes |
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–Responsible for writing application
programs that use the database typically
in a language like C, Java etc. |
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–Manage the DBMS use and ensure that
the database is functioning properly |
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–Design database structure, standards for
data in business units, architects |
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–Business manager is responsible for
quality of data |
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–Interact with the system from online
workstations or terminals |
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1. requirements analysis
2. conceptual design
3. logical design
4. physical design = schema
5. implementation = database
6. Maintenance = evolving database |
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Collection of related records |
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Group of characters with meaning |
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Record: Logically connected set of one or more fields |
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Problems with File Based Systems |
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•Limited data sharing
•Program-data dependence
•Duplication of data
•Lengthy development times
•Excessive program maintenance |
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–Program-data independence
–Minimal data redundancy
–Improved data consistency
–Improved data sharing
–Enforcement of standards
–Improved data quality
–Increased productivity of application development |
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Information Systems Architecture (ISA) |
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Blueprint for the information systems in an organization |
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Information Engineering and its steps |
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Formal methodology for developing ISA
Includes 4 steps: planning, analysis, design and implementation |
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1. data
2. processes
3. network
4. people
5. events and points in time
6. reasons for events |
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Physical Data Independence |
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The capability to change the physical storage structure without having to change conceptual schemas. |
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Logical Data Independence |
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The capability to change the conceptual schema without having to change external schemas. |
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accuracy and correctness of data in the database. |
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A type constraint is just an enumeration of the legal values of the type |
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Uniqueness: No legal value of R ever contains two distinct tuples with the same value for K. Irreducibility: No proper subset of K has the uniqueness property. |
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Any superset of a candidate key is a super key. A super key has the uniqueness property but not necessarily the irreducibility property. |
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No two tuples can have the same value of primary key Rationale Each tuple should be identifiable Primary key is used identify a tuple |
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No primary key value can be NULL |
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Referential Integrity constraint |
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Attributes of FK in R1 must have the same domain as the PK attribute of another relation R2 |
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Can violate any of four integrity constraints Domain Constraint |
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Can violate Referential Integrity |
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Can violate any of four integrity constraints |
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Relation has no multi-valued attributes |
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in 1 NF, no partial key dependencies |
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in 2 NF, no transitive dependencies |
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adequate performance data integrity security |
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1.Tables are large 2. attributes that appear in WHERE, ORDER BY and GROUP BY 3. significant variety in the values of attributes |
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partitioning the table into no.of smaller tables on the basis of rows. Eg: In an employee table, employees with salary less than $10,000 will be partitioned into different table. |
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dividing the table based on the different columns. Eg: In the same employee table, retrieving oly the name and contact number of all the employees into a different table. |
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Structured Query Language |
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Define the database CREATE, ALTER and DROP a TABLE, VIEW or INDEX |
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Manipulate the data in an existing database INSERT, UPDATE, DELETE SELECT, i.e., query |
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Control user access to an existing database GRANT and REVOKE |
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INSERT INTO table name column name VALUES values |
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DELETE FROM table name[WHERE]; |
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UPDATE table name SET
,…
[WHERE ]; |
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SELECT color, SUM(weight) FROM parts GROUP BY color; |
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FROM department, employee WHERE department.dept# = employee.dept#;
Columns are repeated Tuples in a relation R without a matching tuple in a relation S are eliminated |
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SELECT * FROM department, employee; |
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SELECT department.dept#, dname, budget, emp#, ename, salary FROM department, employee WHERE department.dept# = employee.dept#;
Columns are NOT repeated Tuples in a relation R without a matching tuple in a relation S are eliminated |
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A row in one table does not have a matching row in another table Produces rows that do not have matching values in common columns NULL values appear where there is not a match |
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Select e.ename, mgr.ename as Mgr_name from employee e, employee mgr where e.mgrid = mgr.eid;
Tuples in a relation R are joined with themselves |
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Custodian of organization’s data Overall management of data sources Establishes standards and procedures related to |
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Responsible for technical issues related to security, database performance and backup and recovery Implements the standards and procedures established by the data administrator Involved in every phase of database design Provide support to end-users involved in design of databases |
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Enforce desirable database conditions |
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controls that restrict actions that people may take when they access data |
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Password and procedure name need to be specified Procedure invokes a series of questions (e.g., mother’s maiden name) |
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Encoding or scrambling of data |
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Identify the people (physical or behavioral traits) who are accessing the data sources e.g. biometric devices, voice prints |
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A logical unit of data processing that includes one or more database access/update operations
Atomic unit of work that is completed in entirety or not done at all |
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A transaction can include two basic database access operations: |
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Properties of a transaction |
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1.Atomicity 2. consistency 3. isolation 4. durability |
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Audit trail of transaction |
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Synchronize transaction log and database DBMS writes checkpoint record to log file Snapshot of database |
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Module of DBMS that helps restore database to correct condition |
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before and after images of records |
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recovery procedure: switch |
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recovery procedure: restore/run |
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reprocess day’s transactions against backup copy of database |
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recovery procedure: backward recovery |
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DBMS backs out or undoes the unwanted changes |
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recovery procedure: forward recovery |
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start with the earlier copy of database apply good transactions to move the database to later stage |
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A schedule is serializable if its result is equivalent to some serial schedule |
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Concurrency Problem: Lost update |
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Also called write-write conflict Two transactions that access the same database item have operations interleaved that makes the value of some database item incorrect |
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Concurrency Problem: dirty read |
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Read values from a transaction that fails Also called write-read problem because a data item that is written (but not committed) by one transaction is read by another transaction |
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Concurrency Problem: unrepeateable read |
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A transaction reads an item twice and in between these two read the item has changed Also called read-write problem because a data item that is read by one transaction is written (changed) by another transaction |
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Concurrency control: pessimistic method Locking |
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A lock guarantees exclusive use of data item to a current transaction Lock Granularity |
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Concurrency control: Optimistic method Versioning |
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1. read phase (make own copy) 2. validation phase (changes will not affect integrity and consistency) 3. write phase (no conflict, changes made) |
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Specifies what is locked, i.e., database, table, page (typically 4K), row or cell |
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1. Binary: locked, unlocked - no, some T can use a data item 2. Shared/exclusive - concurrent transactions are given a read access to a data item, write permission on data item is given if data item has no other locks |
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Definition
Transaction T must issue lock (X) before read (X) or write (X) A transaction T must issue unlock (X) after read (X) and write (X) is completed in T |
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The resulting transaction may not be serializable Deadlock |
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Two transactions wait for each other to release locks |
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Deadlock prevention: DBMS look ahead (deadlock graphs) Deadlock detection: waits-for-graph tests deadlock and time-out (abort) one transaction Deadlock avoidance: transaction must obtain all locks before it can be executed |
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defines how transactions acquire and relinquish locks ensures serializability
Two phases Growing Phase: acquire locks without unlocking Shrinking Phase: transaction releases locks and cannot acquire locks |
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Definition
Intangibility (Yes/No) Nonfungibility (No) Fragility (Yes) Valuation (Yes, difficult)
Consumability (No) sharability (Yes) Copyability (yes) |
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