Transcript Database - La Salle University

Database
An introduction to database
concepts and vocabulary
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Ubiquity of Databases
• Mauchly and Eckert designed the ENIAC to
perform calculations (shell trajectories).
• After the ENIAC was built, it was used to do
thermonuclear chain reaction calculations.
• But when Mauchly and Eckert went into business,
their first customer was the census bureau.
• And ever since computers have played an
important role in filing and record keeping.
• Suffice it to say
– Databases are very important.
– Databases are all around us.
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Mauchly & Eckert and early
programmers of the ENIAC
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What do we want?
• Desired Features of our database
– Storage:
• We want to store data efficiently, have it centralized (or at least
seemingly centralized).
– Centralization (integration) are subject to bottlenecks and singlepoint-of-failure issues.
– Retrieval:
• We want to have the data at our fingertips when we want it.
– Querying:
• We want to ask various questions about the data (and get
answers in a timely manner).
• (These desires are to some extent in conflict.)
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Automating the procedure
• We would like to have the computer
perform the tedious aspects of such tasks.
• An outdated approach would be to use a
file-based system, that is, to have the data
stored in various (flat, simple text) files and
write a program that reads the files, parses
the information, does the required
searching, sorting, correlating, etc.
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Entities
• Even in the file-based approach, one must identify
units of information that will be contained in a
single file. These are known as the entities.
• An entity is somewhat similar to an object in
programming, it collects data that belongs together
in some immediate way.
• Entities also separate the data into distinct units.
• Database entities often reflect real objects/entities
(persons, buildings, courses, etc.)
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Fields
• The lower-level pieces of data gathered together to
form an entity are known as fields or attributes or
properties.
– The Person entity might consist of fields like
FirstName, LastName, JobType, SocSecNum, etc.
– Fields are analogous to properties of an object.
• Fields have a type (Text, Number, Yes/No, Memo,
Date/Time, etc.) which indicate how the
information is to be stored and interpreted.
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Relationship
• The various entities may be distinct, but
they are not completely disconnected.
– E.g. a Customer places an order
• An association between two entities is
known as a relationship.
– The Customer-places-Order relationship was
realized in Access by using the Lookup Wizard
to ensure that the two tables had a common
field (CustomerID).
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ER Diagram
• One can visualize the entities and their
relationship using an Entity-Relationship
(ER) diagram.
– The entities are represented by rectangles.
– The relationships are represented by arrows
between the rectangles.
• The arrow may include a verb to capture the nature
of the relationship (as well as other notations).
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ER Diagram Example
Customer
Places
CustomerID
CustomerFirstName
…
Order
OrderID
ShippingCost
…
Is part of
Item
ItemID
ItemDescription
…
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File-based Systems
• In a file-based approach, there would be a
file corresponding to each entity.
– (There may be more files than entities since some
relationships are realized through their own
tables/files.)
• These files must be located, read, parsed.
The data is then used to initialize some
variables and/or objects which are then
analyzed (searched, sorted, etc.) by the
remainder of the program.
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Details, details
• The programmer must have information about the
data files. For example:
– where they are to be found
– the order in which the fields occur
– the length of the fields and/or the delimiter used
• Changing the length of a field or adding a field
may require that all of the corresponding programs
be rewritten.
• Such features of the file-based approach are called
program-data dependence.
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Automating the Automation
• Since
–
–
–
–
Reading is reading
Parsing is parsing
Searching is searching
Sorting is sorting
• Why have programmers continually repeating
these tedious tasks?
• Automate and/or generalize the process.
• These are some of the aspects of a database
management system (DBMS).
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Specific Info in Database
• The generalized routines for reading,
parsing, searching, sorting etc. are in the
DBMS.
• But information specific to a particular case
(number of fields, their type, size and so on)
is still required. This data is placed together
with the “actual” data in the database.
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Meta-data
• This data about the data is known as metadata.
– Meta: a prefix meaning: after, along with or
beyond
• The meta-data describes the actual data, and
so databases are sometimes called selfdescribing.
• Related terms include: data dictionary,
system catalog and schema.
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Meta-data: Open a database file in Notepad
Some
actual
data
One can see there’s more to this file than just customer data.
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Layers
• The inclusion of the meta-data (the selfdescribing aspect of a database) allows a
separation of the data from the processing,
providing program-data independence.
• Another way to say this is that there is a
separation between the database (specific)
and the database management system
(generic).
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Database/DBMS Distinction
Database
Raw-data and meta-data
DBMS
User
Application
Users and applications interact with a database only through
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the DBMS.
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Pros of Database Approach
• Control of data
redundancy
• Data consistency
• More info from same data
• Sharing of data
• Improved data integrity
• Improved security
• Enforcement of standards
• Economy of scale
• Balancing of conflicting
requirements
• Improved accessibility and
responsiveness
• Improved maintenance
through data independence
• Increased concurrency
• Improved backup and
recovery services
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Pros
• Control of data redundancy and consistency
– If the same data is entered more than once, it is said to be
redundant.
– An obvious point is that this wastes space.
– If the data is updated, it must be updated in several places
or the data will be inconsistent.
– Relationships are realized through repeated data, but one
tries to use something like an ID# (a name might change
but an ID# does not have to).
– (Redundancy reduction and query simplicity can be at
odds, sometimes one sacrifices redundancy in order to
make querying easier, e.g. in data mining. )
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Pros (Cont.)
• More information, sharing of data and
standardization
– Because databases facilitate querying, they can
yield more information.
– A database approach often centralizes
(integrates) the records of different
departments, making more (raw) data and
information available to the users
– Integration often leads to standardization,
consistent naming schemes, consistent report
formats, etc.
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Pros (Cont.)
• Improved data integrity
– An old computing axiom says garbage in,
garbage out (GIGO). If the raw data is bad, so
too is the resulting information.
– In the database approach, one can apply
constraints to help ensure that the data is reliable.
• Access’s lookup table for the foreign keys is an
example. A foreign key is supposed to match an entry
from another table, the lookup table helps ensure that.
– We also saw that we could “Enforce Referential Integrity.”
• We also mentioned masks, which are another integrity
check.
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Pros (Cont.)
• Improved security
– Part of the meta-data can be used to
authenticate users who are allowed to access
the data.
• Different users may have different access
• Data is often not entered directly into a Table using
the DataSheet but by using Views and/or Forms,
which can hide sensitive data from certain users.
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Pros (Cont.)
• Economy of scale
– A benefit of an organization centralizing (integrating)
its record-keeping efforts is the money applied to
individual departments is pooled.
– Not only is duplication of effort reduced or eliminated,
but so too is duplication of hardware and software.
• Balancing of conflicting requirements
– Integration can lead to a resolution or at least a
balancing of different departments, which may have
conflicting goals.
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Pros (Cont.)
• Improved data accessibility and
responsiveness and increased productivity
– Because nitty-gritty details (reading, parsing,
sorting, searching, etc.) are built into the DBMS,
the database staff work at a higher level closer to
the users, responding to their particular needs.
– Again with fewer details to attend to, more work
can be accomplished.
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Pros (Cont.)
• Improved maintenance through data
independence
– Change of a field’s type or size or introduction
of a new field changes only the database and
not the DBMS.
– This layering yields independence which
simplifies maintenance. Changing the database
does not require changing the DBMS, which
was not the case in the file-based approach.
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Pros (Cont.)
• Increased concurrency
– The DBMS can handle multi-users using and
even updating the database.
– There are built-in mechanisms to prevent two
users from changing the data in conflicting
ways.
• Improved backup and recovery services
– Backing up and recovering the database may be
handled by the DBMS (that is, they are
integrated services) rather than externally.
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Cons of Database Approach
•
•
•
•
•
•
•
Complexity
Size
Cost of DBMS
Additional hardware costs
Cost of conversion
Performance
Higher impact of failure
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Cons
• Complexity and Size
– Because so many features have been integrated into the
DBMS’s, they have become complicated software
packages. One must understand these features to utilize
them properly.
– Integrating information from various departments
makes the database more complicated. Good design is
crucial.
– Integration of features into the DBMS and data into the
database means that both may become quite large.
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Cons (Cont.)
• Cost OF DBMSs and the hardware
– Again the size and complexity of the software
means that such packages are expensive.
– The larger, more complex software requires
more powerful hardware to run on.
– It also requires a knowledgeable, well-trained
(hopefully high paid) staff.
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Cons (Cont.)
• Conversion cost
– Legacy system
• Performance
– More complexity may slow down some tasks.
• Higher impact of failure.
– Integrating (centralizing) the information can
mean that everything is lost at once.
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Things in the database environment
• In addition to the data, there’s
– Hardware that stores and manipulates
the data
– Software to
• Interface with the hardware
– (actually the operating system which
interfaces with the BIOS which interfaces
with the hardware)
• Provide the data with structure
• Interface with the user and/or
applications
– People
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Hardware
• Could be:
– A single PC
– A mainframe and terminals
– A network of computers
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A scenario
Database
Database Server
Network Server
Client
Client
Network Server
Client
Client
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Network Server
Client
Client
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Client-Server
• The client-server model is a way for transactions
to take place.
– The transaction is viewed as a service.
– The client requests the service.
– The server provides the service.
• For example, to query a networked database
– A client would request the network server(s) to connect
it to the database server
– The database server queries the database
– The result is passed from database server to network
server to client.
• The client-server terminology can be applied to
both software and hardware.
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Front-end and Back-end
• In large-scale client-server interaction, there may
be many intermediate client-server interactions
(e.g. the network servers become clients of the
database server).
• The software and hardware near the beginning of
the transaction (initial request) is called front-end
while that near the ultimate providing of the
service is known as back-end.
• In the analogy of getting a meal at a restaurant,
the waiter is front-end and the cook is back-end.
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Software
• The bulk of the software is contained in the
database management system (DBMS). It
handles everything from storage and
structure to security and integrity.
• There may also be application software that
interfaces with the DBMS.
• The DBMS allows one to interface with the
database on a higher level.
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Prescriptive vs. Descriptive
• In a file-based approach, one’s program is a stepby-step procedure explicitly determining how a
question will be answered
– Read this file, parse it this way, create these objects,
search them this way
• This approach is sometimes called prescriptive
– Prescription originally meant a set of instructions for
preparing and/or taking a drug, only later did the word
become synonymous with the drug itself.
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Prescriptive vs. Descriptive (Cont.)
• In the database approach, most of the nittygritty, step-by-step instructions are hidden
in the DBMS and the user need only
describe the data (the meta-data, the selfdescribing database) and describe what he
or she wants from the data.
• This approach is sometimes called
descriptive.
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Language Generations
• People talk about generations of programming
languages or the level of a language.
– A first generation language (1GL) is machine code, that is,
a binary representation of instructions (e.g. 11001101)
– A second generation language (2GL) is assembly language,
that is, mnemonics for machine code (e.g. STA 13)
– A third generation language (3GL) is a high-level
language, which includes most compiled languages, such as
Fortran, C, BASIC, Java, etc. (e.g. int a = 13)
– A fourth generation language (4GL) is used to develop
database applications. They are designed to be closer to
natural language.
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SQL
• SQL (Structured Query Language),
pronounced S-Q-L or See-Quel, has become
the standard language for relational
databases.
• SQL is part third generation and part fourth
generation.
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SQL is the sequel to SEQUEL
• The original version was called SEQUEL
and was developed at IBM in the mid-70’s.
• However, Oracle Corporation was the first
company to use SQL in a commercial
product in 1979.
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What’s it made of?
• SQL has 3 components:
– Data Definition Language (DDL)
• The part that allows you to establish the structure of
the database
– Data Manipulation Language (DML)
• The part that allows you to enter data, update data
and ask questions of the data (queries)
– Data Control Language (DCL)
• The part that allows you to add security features
(e.g. user authentication), concurrency (multi-user)
features, recovery features, etc.
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The People: Who’s involved with this
database anyway?
• Data Administrator (DA):
–
–
–
–
–
–
Oversees data resources.
More of a hands-off role.
Deals with other managers.
Sets policies.
Handles budgets.
Plans for future.
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Who’s involved with this database
anyway? (Cont.)
• Database administrator (DBA):
– More hands-on and more technical than the
Data Administrator (DA)
– Oversees hardware and software design,
implementation and maintenance
– Responsible for security and integrity
– Ensures users have appropriate accessibility
– Etc.
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Who’s involved with this database
anyway? (Cont.)
• Database Designer:
– Logical database designer:
• Identifies entities, fields, relationships
• Applies high-level constraints including the business rules
– E.g. A Simpsons database might have a business rule that there
must be between 10 and 30 episodes in a complete season
– Physical database designer:
•
•
•
•
Actually creates tables
Implements constraints
Introduces security measures
Etc.
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Who’s involved with this database
anyway? (Cont.)
• Application Developer:
– After the overall structure of the database is laid
out and implemented, the application developer
considers the more individual needs, such as
what software does the payroll department need
– Application may involve third-generation or
fourth generation languages or a combination
• E.g. a Visual Basic program could use an SQL
statement to query a database
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Who’s involved with this database
anyway? (Cont.)
• End-Users:
– Naïve:
• Has little to no database knowledge
• Uses applications that simplify interaction with the
database
– Cashier scanning an item’s barcode
– Sophisticated:
• Knows something to a lot about databases
• May use SQL to update or query database
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References
•
•
•
•
Database Systems Rob and Coronel
Database Systems, Connolly and Begg
SQL for Dummies, Taylor
http://www.metacard.com/wp1a.html
• http://www.oracle.com/glossary/index.html?axx.html
• Concepts of Database Management, Pratt and
Adamski
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