review jun 5th, 2002. hw#5.2 tabletupletuple/pagepage r10000101000 s200010200 r r.a = s.b s...

Review

Jun 5th, 2002

HW#5.2

Table Tuple Tuple/page Page

R 10000 10 1000

S 2000 10 200

R R.a = S.b S (52buffers)

Page-Oriented Nested Loop Join For each page in the outer relation R,

we scan the entire inner relation S. – Cost: M + M * N

__________________

. . .

R & S

Input buffer for S

Output buffer . . .

Join ResultInput buffer for R

Nested Join v.s. Index Join Simple Nested Join

– Cost: M + ( PR*M ) * N

_______________________ Page-oriented Simple Nested Join

– Cost: M + M * N

_______________________ Index Join (Unclustered)

– Cost: M + ( PR*M ) * (1.2 + 1)

_______________________ When is Nested Join better than Index Join?

_______________________

Blocked Nested Loop Join For each matching tuple r in R-block, s in S-

page, add<r, s> to result. Then read next R-block, scan S, etc. – Cost: M + ( M / (B-2) ) * N

____________________

. . .

. . .

R & SInput buffer for R

( k < B-1 pages)

Input buffer for S Output buffer

. . .

Join Result

Hash-Join Partition both

relations using hash fn h1: R tuples in partition i will only match S tuples in partition i.

__________ Read in a

partition of R, hash it using h2 (<> h1). Scan matching partition of S, search for matches.

________

Partitionsof R & S

Input bufferfor Si

Hash table for partitionRi (k < B-1 pages)

B main memory buffersDisk

Output buffer

Disk

Join Result

hashfnh2

h2

B main memory buffers DiskDisk

Original Relation OUTPUT

2INPUT

1

hashfunction

h1 B-1

Partitions

1

2

B-1

. . .

Blocked Join v.s. Hash-Join Blocked Join

– Cost: M + ( M / (B-2) ) * N

___________________ Hash Join

– Cost: 3 * ( M + N )

___________________ When is Blocked Join better than Hash Join?

___________________

Sort-Join Sorting both

relations using Multi-way sort: ________

Read in each intermediate result of R and S, search for matches.

________

Partitionsof R & S

Disk Disk

Join Result

DiskDisk

Original Relation

Partitions(B-1) pages

1

2

M_B-1

. . .

B main memory buffers

INPUT

2 OUTPUT

1

Multisorting

B-1

B main memory buffers

INPUT

_ M_ B-1 OUTPUT

1

MergeJoin

_ N_ B-1

1

Sort-Merge Join v.s. Hash-Join

Sort-Merge needs more buffer space– Sort-Merge Join

• Cost: 3 * ( M + N )

• Buffer Size: ________________– Hash Join

• Cost: 3 * ( M + N )

• Buffer Size: ________________ Sort-Merge join is less sensitive to data skew Result of Sort-Merge join is sorted

HW#5.4 SQL TransformationSELECT DISTINCT F.FirstName, F.LastNameFROM GradStudents AS G, Faculty AS F, Advise AS AWHERE G.LoginID = A.Student AND F.LoginID = A.Advisor

AND G.Office = '224';

GradStudents: 157 tuples (20 distinct values for Office, uniform distribution)Faculty: 53 tuples Advise: 87 tuples

HW#5.4 SQL TransformationSELECT EntryYear, count(*) FROM GradStudentsWHERE FirstName = 'David'GROUP BY EntryYearHAVING EntryYear >= 1995ORDER BY EntryYear DESC

SELECT EntryYear, COUNT(*) FROM GradStudentsWHERE FirstName = 'David'GROUP BY EntryYearHAVING COUNT(*) >= 10ORDER BY EntryYear DESC

HW#5.4 SQL TransformationSELECT FirstNameFROM FacultyWHERE FirstName IN (

SELECT FirstNameFROM GradStudents)

SELECT FirstNameFROM FacultyWHERE FirstName NOT IN (

SELECT FirstNameFROM gradStudents)

HW#5.4 SQL TransformationSELECT LoginIDFROM UndergradStudentsWHERE EntryYear >= ANY (

SELECT EntryYearFROM GradStudents)

SELECT LoginIDFROM UndergradStudentsWHERE EntryYear >= ALL (

SELECT EntryYearFROM GradStudents)

HW#4.1 XML & XQuery<!ELEMENT products (product*)><!ELEMENT product (name, price, description, store*)><!ELEMENT store (name, phone, markup)>

Which products are sold at least in one store?

What are the product-store pairs whose markup is no lower than 15%?

Which stores sell some products with a price higher than 50?

Which products (except “gizmo”) are sold in some store that also sells the product “gizmo”?


Returns the names and prices of all products that are sold in all stores with a markup of 25%.

Returns the names and prices of all products that are sold at least at one store with a markup of 25%


<products>{

FOR $p IN documents(“database.xml”)//products/row

RETURN

<product pid = “{$p/pid/text()}”>

<name>{$p/name/text()}</name>

<price>{$p/price/text()}</price>

<description>{$p/description/text()}</description>

{FOR $x IN documents(“database.xml”)//sells/row[pid = $p/pid]

FOR $s IN documents(“database.xml”)//stores/row[sid = $x/sid]

RETURN

<store sid = “{$s/sid/text()}”>

<name>{$s/name/text()}</name>

<phone>{$s/phone/text()}</phone>

<markup>{$x/markup/text)()}</markup>

</store>

}</product>

}</products>

Midterm 1

Midterm 1

Company (DeptID, Name, Budget, CEOEmployID, CEOContratID, Since)

Work-in (EmployID, Lot, DeptID, Name, Budget, CEOEmployID, Since)

HW#5.1 B+ Tree

B+ Tree – Insert 70

B+ Tree – Delete 10

B+ Tree – Delete 8

review jun 5th, 2002. hw#5.2 tabletupletuple/pagepage r10000101000 s200010200 r r.a = s.b s...

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