CS 541 Review

1
CS 541Review

• December 4, 2002

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Course Outline

• Course Introduction
• Relational Data Model
• Data Modeling
• Entity-Relationship
• Constraints
• Relational Theory
• Relational Algebra
• Keys and Dependencies
• Normalization
• Using a Relational Database
• SQL, Views, Constraints, Triggers
• Storage mechanisms
• I/O cost estimation
• Putting the Data on Disk
• Block/record
• Buffer management

• Indexing
• Dense vs. Sparse
• Index Sequential files
• B-Trees
• Hashing / Bitmap Indexes
• Query Processing
• Query Optimization
• Handling Failure
• Concurrency Control
• Transaction Management
• Research topics (not on final)

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Entity/Relationship Model

• Diagrams to represent designs.
• Entity like object, thing.
• Entity set like class set of similar
  entities/objects.
• Attribute property of entities in an entity
  set, similar to fields of a struct.
• In diagrams, entity set ? rectangleattribute ?
  oval.

name
phone
ID
Students
height
4

• Complex Example
• Keys
• One to many, many to many, one to one
  relationships
• Weak entity sets

UPC
Buyer
Product
Ordered
OB
OB
OP
OP
Name
Qty Ordered
ID
Shipment
Part of
Part-of ismany-many and not a weak relationship!
Qty Shipped
5
Design Principles

• Setting client has (possibly vague) idea of what
  he/she wants. You must design a database that
  represents these thoughts and only these
  thoughts.
• Avoid redundancy
• saying the same thing more than once.
• Wastes space and encourages inconsistency.
• Example
• Good

name
addr
name
ManfBy
Beers
Manfs
6
Use Schema to Enforce Constraints

• The design schema should enforce as many
  constraints as possible.
• Don't rely on future data to follow assumptions.
• Example
• If registrar wants to associate only one
  instructor with a course, don't allow sets of
  instructors and count on departments to enter
  only one instructor per course.

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Intuitive Rule for E.S. Vs. Attribute

• Make an entity set only if it either
• Is more than a name of something i.e., it has
  nonkey attributes or relationships with a number
  of different entity sets, or
• Manfs deserves to be an E.S. because we record
  addr, a nonkey attribute.
• Is the many in a many-one relationship The
  following design illustrates both points
• Beers deserves to be an E.S. because it is at the
  many end.

name
addr
name
ManfBy
Beers
Manfs
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Don't Overuse Weak E.S.

• There is a tendency to feel that no E.S. has its
  entities uniquely determined without following
  some relationships.
• However, in practice, we almost always create
  unique ID's to compensate social-security
  numbers, VIN's, etc.
• The only times weak E.S.'s seem necessary are
  when
• We can't easily create such ID's e.g., no one is
  going to accept a species ID as part of the
  standard nomenclature (species is a weak E.S.
  supported by membership in a genus).
• There is no global authority to create them,
  e.g., crews and studios.

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Relational Model

• Table relation.
• Column headers attributes.
• Row tuple
• Beers
• Relation schema name(attributes) other
  structure info.,e.g., keys, other constraints.
  Example Beers(name, manf)
• Order of attributes is arbitrary, but in practice
  we need to assume the order given in the relation
  schema.
• Relation instance is current set of rows for a
  relation schema.
• Database schema collection of relation schemas.

name manf WinterBrew Petes BudLite A.B.
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Relational Data Model

• Set theoretic
• Domain set of values
• like a data type
• Cartesian product (or product)
• D1 ??D2 ??... ? Dn
• n-tuples (V1,V2,...,Vn)
• s.t., V1 ??D1, V2 ??D2,...,Vn ??Dn
• Relation-subset of cartesian product
• of one or more domains
• FINITE only empty set allowed
• Tuples members of a relation inst.
• Arity number of domains
• Components values in a tuple
• Domains corresp. with attributes
• Cardinality number of tuples

Relation as table Rows tuples Columns
components Names of columns attributes Set of
attribute names schema REL (A1,A2,...,An)
A1 A2 A3 ... An a1 a2 a3 an b1 b2
a3 cn a1 c3 b3 bn . . . x1 v2 d3
wn
Attributes
C a r d i n a l i t y
Tuple
Component
Arity
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Relational Design

• Simplest approach (not always best) convert each
  E.S. to a relation and each relationship to a
  relation.
• Entity Set ? Relation
• E.S. attributes become relational attributes.
• Becomes
• Beers(name, manf)

name
manf
Beers
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Functional Dependencies

• X ? A assertion about a relation R that
  whenever two tuples agree on all the attributes
  of X, then they must also agree on attribute A
• Why do we care?
• Knowing functional dependencies provides a formal
  mechanism to divide up relations (normalization)
• Saves space
• Prevents storing data that violates dependencies

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Example Functional Dependencies

• In ABC with FDs A ? B, B ? C, project onto AC.
• A ABC yields A ? B, A ? C.
• B BC yields B ? C.
• AB ABC yields AB ? C drop in favor of A ? C.
• AC ABC yields AC ? B drop in favor of A ? B.
• C C and BC BC adds nothing.
• Resulting FDs A ? B, A ? C, B ? C.
• Projection onto AC A ? C.

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Normalization

• Goal BCNF Boyce-Codd Normal Form
• all FDs follow from the fact key ?
  everything.
• Formally, R is in BCNF if for every nontrivial FD
  for R, say X ? A, then X is a superkey.
• Nontrivial right-side attribute not in left
  side.
• Why?
• 1. Guarantees no redundancy due to FDs.
• 2. Guarantees no update anomalies one
  occurrence of a fact is updated, not all.
• 3. Guarantees no deletion anomalies valid fact
  is lost when tuple is deleted.

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Decomposition to Reach BCNF

• 1. Compute X.
• Cannot be all attributes why?
• 2. Decompose R into X and (RX) ? X.
• 3. Find the FDs for the decomposed relations.
• Project the FDs from F calculate all
  consequents of F that involve only attributes
  from X or only from (R?X) ? X.

R
X
X
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3NF

• One FD structure causes problems
• If you decompose, you cant check all the FDs
  only in the decomposed relations.
• If you dont decompose, you violate BCNF.
• Abstractly AB ? C and C ? B.
• Example 1 title city ? theatre and theatre ?
  city.
• Example 2 street city ? zip,zip ? city.
• Keys A, B and A, C, but C ? B has a left
  side that is not a superkey.
• Suggests decomposition into BC and AC.
• But you cant check the FD AB ? C in only these
  relations.

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Elegant Workaround

• Define the problem away.
• A relation R is in 3NF iff (if and only if)for
  every nontrivial FD X ? A, either
• 1. X is a superkey, or
• 2. A is prime member of at least one key.
• Thus, the canonical problem goes away you dont
  have to decompose because all attributes are
  prime.

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What 3NF Gives You

• There are two important properties of a
  decomposition
• We should be able to recover from the decomposed
  relations the data of the original.
• Recovery involves projection and join, which we
  shall defer until weve discussed relational
  algebra.
• We should be able to check that the FDs for the
  original relation are satisfied by checking the
  projections of those FDs in the decomposed
  relations.
• Without proof, we assert that it is always
  possible to decompose into BCNF and satisfy (1).
• Also without proof, we can decompose into 3NF and
  satisfy both (1) and (2).
• But it is not possible to decompose into BNCF and
  get both (1) and (2).
• Street-city-zip is an example of this point.

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Multivalued Dependencies

• The multivalued dependency X ?? Y holds in a
  relation R if whenever we have two tuples of R
  that agree in all the attributes of X, then we
  can swap their Y components and get two new
  tuples that are also in R.
• X Y others

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MVD Rules

• 1. Every FD is an MVD.
• Because if X ?Y, then swapping Ys between tuples
  that agree on X doesnt create new tuples.
• Example, in Drinkers name ?? addr.
• 2. Complementation if X ?? Y, then X ?? Z, where
  Z is all attributes not in X or Y.
• Example since name ?? phonesholds in
  Drinkers, so doesname ?? addr beersLiked.

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4NF

• Eliminate redundancy due to multiplicative effect
  of MVDs.
• Roughly treat MVDs as FD's for decomposition,
  but not for finding keys.
• Formally R is in Fourth Normal Form if whenever
  MVDX ?? Y is nontrivial (Y is not a subset of X,
  and X ? Y is not all attributes), then X is a
  superkey.
• Remember, X ? Y implies X ?? Y, so 4NF is more
  stringentthan BCNF.
• Decompose R, using4NF violation X ?? Y,into XY
  and X ? (RY).

R
Y
X
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Why Decomposition Works?

• What does it mean to work? Why cant we just
  tear sets of attributes apart as we like?
• Answer the decomposed relations need to
  represent the same information as the original.
• We must be able to reconstruct the original from
  the decomposed relations.
• Projection and Join Connect the Original and
  Decomposed Relations
• Suppose R is decomposed into S and T. We project
  R onto S and onto T.

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Theorem

• Suppose we decompose a relation with schema XYZ
  into XY and XZ and project the relation for XYZ
  onto XY and XZ. Then XY XZ is guaranteed to
  reconstruct XYZ if and only if X ??Y (or
  equivalently, X ?? Z).
• Usually, the MVD is really a FD, X ? Y or X ?Z.
• BCNF When we decompose XYZ into XY and XZ, it is
  because there is a FD X ? Y or X ? Z that
  violates BCNF.
• Thus, we can always reconstruct XYZ from its
  projections onto XY and XZ.
• 4NF when we decompose XYZ into XY and XZ, it is
  because there is an MVD X ?? Y or X ?? Z that
  violates 4NF.
• Again, we can reconstruct XYZ from its
  projections onto XY and XZ.

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• Relational Algebra
• limited expressive power (subset of possible
  queries)
• good optimizer possible
• rich enough language to express enough useful
  things
• Finiteness
• ? SELECT
• p PROJECT
• X CARTESIAN PRODUCT
  FUNDAMENTAL
• U UNION BINARY
• SET-DIFFERENCE
• ? SET-INTERSECTION
  
• ? THETA-JOIN
  CAN BE DEFINED
• NATURAL JOIN
  IN TERMS OF
• DIVISION or QUOTIENT
  FUNDAMENTAL OPS

UNARY
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Extended (Nonclassical)Relational Algebra

• Adds features needed for SQL, bags.
• Duplicate-elimination operator ?.
• Extended projection.
• Sorting operator ?.
• Grouping-and-aggregation operator ?.
• Outerjoin operator o .

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SQL

• DML
• select, from, where, renaming
• set operations
• ordering
• aggregate functions
• nested subqueries
• other parts DDL, embedded SQL, auth etc

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Constraints

• Commercial relational systems allow much more
  fine-tuning
• of constraints than do the modeling languages we
  learned earlier.
• In essence SQL programming is used to describe
  constraints.
• Outline
• Primary key declarations.
• Foreign-keys referential integrity constraints.
• Attribute- and tuple-based checks constraints
  within relations.
• SQL Assertions global constraints.
• Not found in Oracle.
• Oracle Triggers.
• A substitute for assertions.

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Triggers (Oracle Version)

• Often called event-condition-action rules.
• Event a class of changes in the DB, e.g.,
  insertions into Beers.
• Condition a test as in a where-clause for
  whether or not the trigger applies.
• Action one or more SQL statements.
• Differ from checks or SQL assertions in that
• Triggers invoked by the event the system doesnt
  have to figure out when a trigger could be
  violated.
• Condition not available in checks.

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Views

• An expression that describes
• a table without creating it.
• View definition form is
• CREATE VIEW ltnamegt AS ltquerygt

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Semantics of View Use

• Example

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Modification to Views Via Triggers

• Oracle allows us to intercept a modification to
  a view through an instead-of trigger.
• Example
• Likes(drinker, beer)
• Sells(bar, beer, price)
• Frequents(drinker, bar)
• CREATE VIEW Synergy AS
• SELECT Likes.drinker, Likes.beer,
• Sells.bar
• FROM Likes, Sells, Frequents
• WHERE Likes.drinker Frequents.drinker AND
• Likes.beer Sells.beer AND
• Sells.bar Frequents.bar

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Cursors

• Declare by
• CURSOR ltnamegt IS
• select-from-where statement
• Cursor gets each tuple from the relation produced
  by the select-from-where, in turn, using a fetch
  statement in a loop.
• Fetch statement
• FETCH ltcursor namegt INTO
• variable list
• Break the loop by a statement of the form
• EXIT WHEN ltcursor namegt NOTFOUND
• True when there are no more tuples to get.
• Open and close the cursor with OPEN and CLOSE.

33
Authorization in SQL

• File systems identify certain access privileges
  on files, e.g., read, write, execute.
• In partial analogy, SQL identifies six access
  privileges on relations, of which the most
  important are
• 1. SELECT the right to query the relation.
• 2. INSERT the right to insert tuples into the
  relation may refer to one attribute, in which
  case the privilege is to specify only one column
  of the inserted tuple.
• 3. DELETE the right to delete tuples from the
  relation.
• 4. UPDATE the right to update tuples of the
  relation may refer to one attribute.

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Storage

• Secondary storage, mainly disks
• I/O times
• Time Seek Time
• Rotational Delay
• Transfer Time
• Other
• I/Os should be avoided,
• especially random ones..

35

• How to lay out data on disk
• Data Items
• Records
• Blocks
• Files
• Memory
• DBMS

36
Indexing

• Index sequential file
• Search key ( ? primary key)
• Primary index (on Sequencing field)
• Secondary index
• Dense index (all Search Key values in)
• Sparse index
• Multi-level index
• Insertion/deletion

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BTree n3

• Root

100
120 150 180
30
3 5 11
120 130
180 200
100 101 110
150 156 179
30 35
38
B tree rules

• (1) All leaves at same lowest level (balanced
  tree)
• (2) Pointers in leaves point to records except
  for sequence pointer
• Use at least
• Non-leaf ?(n1)/2? pointers
• Leaf ?(n1)/2? pointers to data

39
CS 541Review

• Undo/Redo Logging?Normalization?Multiple
  Granularity Locking?
• December 6, 2002

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undo/redo logging

• Update ? ltTi, Xid, New X val, Old X valgt
• page X
• Page X can be flushed before or after Ti commit
• Log record flushed before corresponding updated
  page (WAL)
• Flush at commit (log only)

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Non-quiesce checkpoint

• L
• O
• G
• for
• undo dirty buffer
• pool pages
• flushed

Start-ckpt active TR Ti,T2,...
end ckpt
...
...
...
...
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Examples what to do at recovery time?

• no T1 commit
• L
• O
• G

T1,- a
...
Ckpt T1
...
Ckpt end
...
T1- b
...
? Undo T1 (undo a,b)
43
Example

• L
• O
• G

...
T1 a
...
...
T1 b
...
...
T1 c
...
T1 cmt
...
ckpt- end
ckpt-s T1
? Redo T1 (redo b,c)
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Recovery process

• Backwards pass (end of log ? latest checkpoint
  start)
• construct set S of committed transactions
• undo actions of transactions not in S
• Undo pending transactions
• follow undo chains for transactions in
  (checkpoint active list) - S
• Forward pass (latest checkpoint start ? end of
  log)
• redo actions of S transactions

backward pass
start check- point
forward pass
45
Undo/Redo Logging,17.4.5 (c)Where could End CKPT
be written?

• ltStart Sgt
• ltS, A, 60, 61gt
• ltCommit Sgt
• ltStart Tgt
• ltT, A, 61, 62gt
• ltStart Ugt
• ltU, B, 20, 21gt
• ltstart checkpointgt
• ltT, C, 30, 31gt

• ltStart Vgt
• ltU, D, 40, 41gt
• ltV, F, 70, 71gt
• ltCommit Ugt
• ltT, E, 50, 51gt
• ltCommit Tgt
• ltV, B, 21, 22gt
• ltCommit Vgt

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Normalization (3.6.1 (e))

• R(A,B,C,D,E)
• FDs AB?C, C?D, D?B, D?E
• BCNF Violations
• BCNF
• 3NF

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Multiple Granularity Locking

• Comp Requestor
• IS IX S SIX X
• IS
• Holder IX
• S
• SIX
• X

T
T
T
T
F
F
F
F
T
T
F
F
T
F
T
F
F
F
F
T
F
F
F
F
F
48

• Parent Child can be
• locked in locked in
• IS
• IX
• S
• SIX
• X

P
IS, S IS, S, IX, X, SIX S, IS not necessary X,
IX, SIX none
C
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Rules

• (1) Follow multiple granularity comp function
• (2) Lock root of tree first, any mode
• (3) Node Q can be locked by Ti in S or IS only if
  
• parent(Q) locked by Ti in IX or IS
• (4) Node Q can be locked by Ti in X,SIX,IX only
• if parent(Q) locked by Ti in IX,SIX
• (5) Ti is two-phase
• (6) Ti can unlock node Q only if none of Qs
  
• children are locked by Ti

50
Exercise

• Can T2 access object f2.2 in X mode? What locks
  will T2 get?

T1(IX)
R1
t1
t4
t2
T1(IX)
t3
f2.1
f2.2
f3.1
f3.2
T1(X)
51
Exercise

• Can T2 access object f2.2 in X mode? What locks
  will T2 get?

T1(IX)
R1
t1
t4
t2
T1(X)
t3
f2.1
f2.2
f3.1
f3.2
52
Exercise

• Can T2 access object f3.1 in X mode? What locks
  will T2 get?

T1(IS)
R1
t1
t4
t2
T1(S)
t3
f2.1
f2.2
f3.1
f3.2
53
Exercise

• Can T2 access object f2.2 in S mode? What locks
  will T2 get?

T1(SIX)
R1
t1
t4
t2
T1(IX)
t3
f2.1
f2.2
f3.1
f3.2
T1(X)
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Exercise

• Can T2 access object f2.2 in X mode? What locks
  will T2 get?

T1(SIX)
R1
t1
t4
t2
T1(IX)
t3
f2.1
f2.2
f3.1
f3.2
T1(X)