B-Tree Structures over Flash Memory

Speaker: 吳晋賢 (Chin-Hsien Wu)Embedded Computing and Applications LabDepartment of Electronic EngineeringNational Taiwan University of Science and Technology, Taipei, Taiwan

Slide 1

B-Tree Structures over Flash Memory

Outline

Slide 2

IntroductionFlash Memory CharacteristicsEfficient B-Tree Index Structures over Flash MemoryConclusion

Introduction

Slide 3

Storage SystemsEmbedded Systems or General Operating SystemsFile Systems

An interface for information retrieval and access.Physical Devices

A persistent (non-volatile) storage.Benefits of Flash Memory as Storage Systems

Shock ResistantNo mechanical gadgets.

Non-VolatilePersistent across power-failures.

Power EconomicRelatively to hard-disks.

Flash Memory is a good storage device for storage systems!

Introduction

Slide 4

Small updates could deteriorate flash-memory storage systems.B-Tree index structures over flash memory.

We aim at resolving these issues over flash memory storage systems!

Outline

Slide 5


Organization of a Typical NAND Flash MemoryErase a block time (2ms) > Write a page time (200us) > Read a page time (50us)

Slide 6

……Block 0Block 0

Block 1Block 1

Block 2Block 2

Block 3Block 3 Erase Erase one one

blockblock

1 Page = 512B + 16B1 Page = 512B + 16B1 Block = 32 pages1 Block = 32 pages

……

Read/Read/Write one Write one

pagepage

Flash Memory Characteristics

512B

16BUser Area

Spare Area

Example 1: Out-place Update

Slide 7

Live pagesLive pages Free pagesFree pages

AA BB CC DD

Suppose that we want to update data A and B…Suppose that we want to update data A and B…



Slide 8

Dead pagesDead pages

AA BB CC DD AA BB

Example 1: Out-place Update

Example 2:Garbage Collection

Slide 9

A live pageA live page

A dead pageA dead pageA free pageA free page

This block is to be This block is to be recycled. recycled. (3 live pages and 5 dead (3 live pages and 5 dead pages)pages)

LL DD DD LL DD DD LL DD

LL LL DD LL LL LL FF DD

LL FF LL LL LL LL DD FF

FF LL LL FF LL LL FF DD



Slide 10

LL LL DD LL LL LL DD

LL FF LL LL LL LL DD

LL LL FF LL LL FF DD

LL

LL

DD DD DD DD



Live data are copied to Live data are copied to somewhere else.somewhere else.

LL

DD DDDDDD



Slide 11



The block is then erased.The block is then erased.

Overheads: Overheads: •live data copying live data copying •block eraseing.block eraseing.

LL LL DD LL LL LL DD

LL FF LL LL LL LL DD

LL LL FF LL LL FF DD

LL

LL

FF FF FF FF FF FF FF FF

LL



Slide 13

GarbageCollection

AddressTranslation

FTL Layer

File system (FAT, ext2......)

Device Driver

fwrite(file,data)

Block write(LBA,size)

Flash I/O Requests

Controlsignals

File Systems

process processprocess Applications

Flash-MemoryStorage System

Physical Devices(Flash Memory Banks)


Slide 14

Flash Translation Layer (FTL)

Userdata

.

.

.

Logical Address(array index)

Physical Address(block,page)

Physical Address(block,page)

Access LBA = 3

Address Translation Table(in main-memory) Flash memory

0,00,10,20,30,40,50,60,71,01,11,21,3

(0,3)(0,1)

(0,6)(0,4)(4,7)(1,0)(2,1)(1,2)(1,3)

01234567891011

.

.

.

Sparedata

Spare data

LBA=3;ECC=. . .;

Status=. . .;

GarbageCollection

AddressTranslation

FTL Layer

File system (FAT, ext2......)

Device Driver

fwrite(file,data)

Block write(LBA,size)

Flash I/O Requests

Controlsignals

File Systems

process processprocess Applications

Flash-MemoryStorage System

Physical Devices(Flash Memory Banks)

Outline

Slide 15


Why Research On Index Structures Over Flash Memory ?

Slide 16

Now, a 16G bit NAND flash-memory chip (SAMSUNG K9WAG08U1M flash memory chips) is available in the market. Flash memory could be considered as an alternative to

hard disks in many applications.

The implementation of index structures, which are very popular in the organization of data on disks, must be considered regarding flash memory.

Efficient B-Tree Index Structures over Flash Memory

Slide 17

B-TreeB-Tree is one of the most popular data structures

adopted by database applications or databases systems (such as IBM DB2, Informix, Microsoft SQL Server, Oracle 8, and Sybase ASE), or even many well-known journaling file systems (such as XFS, JFS, and ReiserFS *)

The implementation of B-Tree index structures, which provide efficient data access on disks, must be considered regarding flash memory.


Motivation

100

A

B C

D E F G H I J

20 45 85 130 185 250

30 60 95 150 200

10 40 70 120 180 22097

Slide 18

A B-Tree Example


Slide 19

MotivationFor disk storage systems:

A B-Tree node occupies a fixed number of sectors.Large chunks are fetched from/committed to disks.It is very efficient for disk storage systems to do this.

For flash-memory storage systems:Intensively byte-wise operations are needed for B-Tree.A page must be written even if few bytes are modified.Free space is consumed very quickly due to the adoption of out-place

updates.Garbage collection will be triggered frequently, and the lifetime of flash

memory is reduced severely.


Slide 20

Logical view of a B-TreeIndex Structure

A

B C

D E F G H I J

100

30 60 95 150 200

10 40 70 97 120 180 220


Flash Memory

BF

TL

ReservationBuffer

(in RAM)

A record

Primary keyContents

N20 25 85 180 185 250

20 25 85

I1 I2 I3

Index Unit

180 185 250

I4 I6I5

Sector 1Sector 1 Sector 2Sector 2

Efficient B-Tree Index Structures over Flash MemoryIndex Units vs. B-Tree

Nodes

Slide 21

Logical view of a B-TreeIndex Structure

A

B C

D E F G H I J

100

30 60 95 150 200

10 40 70 97 120 180 220

BF

TL

ReservationBuffer

(in RAM)

A record

Primary keyContents

N20 25 85 180 185 250


Flash Memory

20 25 85

I1

I2

I3

Index Unit

180 185 250

I4

I6

I5

Sector 1Sector 1

Sector 2Sector 2I1 . . .I2 I3 Ik

A B-Tree Node(in RAM)

I3I1

I2Ik

Flash Memory

data_ptrparent_node

identifierprimary_key

left_ptrright_ptrop_flag

An Index Unit


Slide 22

The Commit PolicyLogical view of a B-Tree

Index Structure

A

B C

D E F G H I J

100

30 60 95 150 200

10 40 70 97 120 180 220

BF

TL

ReservationBuffer

(in RAM)

A record

Primary keyContents

N20 25 85 180 185 250


Flash Memory

20 25 85

I1

I2

I3

Index Unit

180 185 250

I4

I6

I5

Sector 1Sector 1

Sector 2Sector 2

Suppose that a sector can store up to 3 index units

The technical issue is to minimize the number of sectors written to store the committed index units. The problem of packing index units into sectors that is reduced from the Bin-Packing problem is NP-Hard. A FIRST-FIT approximation algorithm was adopted in our experiments.

20 25 85

I1 I2 I3Index Unit: 180 185 250

I4 I6I5

Sector 1Sector 1 Sector 2Sector 2

D F H I JNode:

Sector:


Slide 23

The Node Translation Table

To construct node C, BFTL reads and parses sectors whose addresses’ are 23 and 100 To prevent the lists from being too long, the lists To prevent the lists from being too long, the lists should be compacted when needed.should be compacted when needed.

A

B

C

A

B

C

(a) The logical view of a B-tree (b) The node translation table

23

42 34 100 53

23 100

2 100 15

B

A

C

D E F G H II...


Slide 24

Performance EvaluationExperimental Setup

Flash-memory environmentsA 4MB NAND flash memory.The greedy block-recycling policy in garbage collection.

B-Tree environmentsThe fan-out of was 21.The size of a B-Tree node fitted in a sector (512 bytes).

Other parametersThe reservation buffer was configured to hold up to 60

records. The bound of the lengths of lists in the node translation

table was set as 4.


Slide 25

Experimental ResultsPerformance Metrics

Average response time.

Number of pages read and written.

Number of blocks erased.

Number of executions of the compact function


Slide 26

00.5

11.5

22.5

33.5

44.5

0 0.2 0.4 0.6 0.8 1

rs

Av

erag

e R

esp

on

se T

ime

(ms)

FTL BFTL

Average Response Time of Insertions after Inserting 30,000 Records

Rs: To control the distribution of the values of the inserted keys.

Rs 1Sequential

0Random


Slide 27

010000200003000040000

50000600007000080000

0 0.2 0.4 0.6 0.8 1

rs

Num

ber

of P

ages

Wri

tten

(Pag

es)

FTL BFTL

Number of Pages Written after Inserting 30,000 Records


Slide 28

0

50000

100000

150000

200000

250000

300000

0 0.2 0.4 0.6 0.8 1rs

Num

ber o

f Pag

es R

ead

(Pag

es)

FTL BFTL

Number of Pages Read after Inserting 30,000 Records


Slide 29

0

500

1000

1500

2000

0 0.2 0.4 0.6 0.8 1

rs

Num

ber

of E

rase

d B

lock

s

FTL BFTL

Number of Blocks Erased after Inserting 30,000 Records


Slide 30

01000

20003000

40005000

60007000

8000

0 0.2 0.4 0.6 0.8 1

rs

Num

ber

of E

xecu

tions

of

Com

pact

Fun

ctio

nBFTL

Number of Executions of Compact Function

after Inserting 30,000 Records

Conclusion

Slide 33

Index structures usually cause intensively find-grained updates which could damage the performance and the reliability of flash memory.

An Efficient B-Tree implementation is proposed to resolve the confliction between page-based operations and intensive byte-wise updates.

Performance and reliability of flash memory could be greatly improved.

Q & A

Slide 34

Thank YouQ & A

Documents

B-Tree Structures over Flash Memory