電子情報通信学会ワードテンプレート...

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DEIM Forum 2014 D3-3 305-0001 1-1-1 305-0001 1-1-1 E-mail: [email protected], [email protected] ( ) AIS 1. 1 [1 2 3 5 7] SASE[1 5] Cayuga[6] ZStream[2] RFID SASE SASE (Nondeterministic Finite Automaton NFA) NFA AIS(Active Instance Stack) NFA AIS NFA AIS PATTERN FROM WHERE WITHIN 4 PATTERN FROM SASE[1 5] [8] WHERE PATTERN WITHIN SEQ(A B) A B A B FROM PacketStream IP IP PacketStream IP WHERE dstport A.dstport = 80 AND B.dstport != 80 1 PATTERN <event pattern> FROM <input stream> WHERE <filtering conditions> WITHIN <window> PATTERN SEQ (A, B) FROM PacketStream WHERE A.dstport = 80 AND B.dstport != 80 WITHIN 500 events

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Page 1: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

DEIM Forum 2014 D3-3

305-0001 1-1-1

305-0001 1-1-1

E-mail: [email protected], [email protected]

( )

AIS

1.

1 [1 2 3

5 7]

SASE[1 5] Cayuga[6] ZStream[2]

RFID

SASE

SASE

(Nondeterministic Finite

Automaton NFA) NFA

AIS(Active Instance Stack)

NFA

AIS NFA

AIS

PATTERN FROM WHERE

WITHIN 4

PATTERN FROM

SASE[1 5]

[8]

WHERE PATTERN

WITHIN

SEQ(A B) A B

A B

FROM

PacketStream IP

IP

PacketStream

IP

WHERE

dstport

A.dstport = 80 AND B.dstport != 80 1

PATTERN <event pattern> FROM <input stream>

WHERE <filtering conditions> WITHIN <window>

PATTERN SEQ (A, B) FROM PacketStream

WHERE A.dstport = 80 AND B.dstport != 80 WITHIN 500 events

Page 2: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

80

80

WITHIN 500 events

[8] CQL [ROWS

500]

SASE 2

SASE

SASE

SASE [24]

FLA(Forward Link Aggregation)

FLA

FLA 4.1

PRC(Partial Result

Caching)

2

3

4

5

2.

[4] STREAM[8]

Aurora[11] Borealis[12] NiagaraCQ[10] TelegraphCQ[9]

GigaScope[14] AT T

XStream[13]

uCosminexus Stream Data Platform[19], Microsoft

SQL Server StreamInsight[15, 18] Oracle CEP[16]

EsperTech[17] System S[20]

SASE[1 5] Cayuga[6] ZStream[2]

[22]

[23]

[23] 2 SASE 2006

1 NFA

ZStream[2] NFA

SASE

3. FLA (Forward Link Aggregation)

[24]

FLA(Forward Link Aggregation)

FLA

SASE[1] 1

FLA

4 FLA

Page 3: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

3.1. 準備

9

SEQ(A B D) a1 d9

a1, c2, b3, a4, d5, b6, d7, a8, d9

1

2

c2 C

2

[1 5] skip till next match

1 <a1 b3 d5>

c2

FLA

3.2. FLA の手続き

3.2 FLA

3.1 4

STEP1 SEQ(A B D)

1 NFA 1 *

[1]

NFA

NFA

1: NFA

STEP2 NFA AIS(Active

Instance Stack) AIS

NFA

AIS FLA

1 AIS

RIS(the

most Recent Instance in the Subsequence stack)

FLA

AIS

2 a1 d9

2

a1 b3 b3

d5

2: RIS AIS

STEP3 FLA

1

2

STEP4

2

RIS

a1 b6

b6 d9

<a1 b3 d5> <a1 b3 d7> <a1 b6 d7>

<a4 b6 d7> <a1 b3 d9> <a1 b6 d9> <a4

b6 d9> 7

STEP5 FLA NFA AIS

d5 d7 d9

3

3: AIS

STEP6 a1

a1 a4

b3 RIS

b3 4

Page 4: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

4: a1 b3

FLA STEP6 STEP2 a4

AIS

d12

AIS 5 AIS d12

5: d12

4.

4.1. FLA の問題点

3 FLA

2

1 1 2

3.2 d11

2 STEP3 <a4 b6 d11>

<a4 b6

d7> <a4 b6 d11> <a4

b6>

(a4 b6)

2 FLA

FLA

4.2. 部分的パタンオカレンスのキャッシュ構築

4.1 PRC(Partial

Result Caching)

FLA

PRC

1

FLA

4.3. PRC の処理手順

SEQ(A B D)

9

PRC

a1, c2, b3, a4, d5, b6, d7, a8, d9, b10, d11, d12, b13

STEP1

AIS

PRC AIS

RIS RIS

RIS

1

AIS a1

d9 NFA

2

STEP2

STEP3 NFA AIS

2

STEP4-1

RIS RIS

RIS

3 STEP4

STEP4-2

Page 5: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

NFA

6

6 A

STEP4-1 STEP4-2

6:

STEP5 NFA AIS

NFA AIS

RIS 2 b3

b6 d5 d7 d9 a1

a4 RIS

7

7: NFA AIS

STEP6 NFA AIS

( a1 )

a1 <a1 b3>

<a1 b6> a1 AIS 8

9

8: a1 AIS

9: a1

STEP6 STEP1 a4

AIS

d12

AIS 10 d12

AIS

STEP2

10: d12

STEP2’

3 AIS

10 d11 d12

b6 2

<a4 b6 d11 > <a4 b6 d12 >

AIS

1

STEP3’ NFA AIS

10 a4 RIS a8 RIS

1

a4 a8

11

Page 6: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

11: a4 a8

STEP4-1’

4

< a8 b10 d11 > < a8 b10 d12 > < a4 b10 d11

> < a4 b10 d12 >

STEP4-2’

NFA

12

STEP4-1 STEP4-2

12:

STEP5’ NFA AIS

b10 d11 d12 a4

a8 RIS

STEP6’ NFA AIS

( a4 )

a4 <a4

b6> <a4 b10>

PRC STEP1 STEP6

FLA STEP2

11

PRC

5 FLA PRC

5.

SEQ

[1] Eugene Wu, Yanlei Diao, Shariq Rizvi,

“High-Performance Complex Event Processing over Streams”, Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, Illinois, USA, pp.407-418, June. 2006.

[2] Yuan Mei, Samuel Madden, “ZStream: A Cost -based Query Processor for Adaptively Detecting Composite Event”, Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, Rhode Island, USA, pp.193-206, June-July. 2009.

[3] Xin Li, Hideyuki Kawashima, Hiroyuki Kitagawa, “Complex Event Processing over Uncertain Data Streams”, The 70th National Convention of IPSJ, Ibaraki, Japan, March. 2010.

[4] H. Garcia-Molina, J.D. Ullman, and J. Widom, “Database Systems - The Complete Book Second edition”, Prentice Hall Press Upper Saddle River, USA, June. 2008.

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[9] Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M. J., Hellerstein, J. M., Hong, W., Krishnamurthy, S., Madden, S. R., Reiss, F., and Shah, M. A. 2003. “TelegraphCQ: Continuous Dataflow Processing”, Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diego, CA, pp.668-668, June. 2003.

[10] Chen, J., DeWitt, D. J., Tian, F., and Wang, Y. “NiagaraCQ: a Scalable Continuous Query System for Internet Databases”, Proceedings of the 2000 ACM SIGMOD international conference on Management of data, Dallas, TX, pp.379 -390, June. 2000.

[11] Balakrishnan, H., Balazinska, M., Carney, D., Çetintemel, U., Cherniack, M., Convey, C., Galvez, E., Salz, J., Stonebraker, M., Tatbul, N., Tibbetts, R., and Zdonik, S. 2004. “Retrospective on Aurora”. The VLDB Journal, vol.13, no.4, pp.370-383, December. 2004.

[12] Daniel J. Abadi, Yanif Ahmad, Magdalena Balazinska, Ugur Cetintemel, Mitch Cherniack, Jeong-Hyon Hwang, Wolfgang Lindner, Anurag S. Maskey, Alexander Rasin, Esther Ryvkina, Nesime Tatbul,

Page 7: 電子情報通信学会ワードテンプレート (タイトル)db-event.jpn.org/deim2014/final/proceedings/D3-3.pdf · SQL Server StreamInsight[15, 18] Oracle CEP[16] EsperTech[17]

Ying Xing, and Stan Zdonik, “The Design of the Borealis Stream Processing Engine” , Proceedings of Conference on Innovative Data Systems Research 2005, Asilomar, CA, pp.277-289, January. 2005.

[13] Girod, L., Mei, Y., Newton, R., Rost, S., Thiagarajan, A., Balakrishnan, H., and Madden, S. “XStream: a Signal-Oriented Data Stream Management System”, Proceedings of 24th IEEE International Conference on Data Engineering, Cancun, Mexico, pp.1180 -1189, April. 2008.

[14] Cranor, C., Johnson, T., Spataschek, O., and Shkapenyuk, V. “Gigascope: a Stream Database for Network Applications”, Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diego, CA, pp.647-651, June. 2003.

[15] Microsoft, “Microsoft SQL Server StreamInSight”, http://www.microsoft.com/sqlserver/2008/en/us/r2 -complex-event.aspx, accessed August. 2013.

[16] Oracle, “Oracle CEP”, http://www.oracle.com/us/technologies/soa/service -oriented-architecture-066455.html, accessed August. 2013.

[17] EsperTech Inc., “EsperTech”, http://www.espertech.com/, accessed August. 2013.

[18] Chandramouli, B., Goldstein, J., and Maier, D. “On-the-fly Progress Detection in Iterative Stream Queries”, Proceedings of VLDB Endowment, vol.2, no.1, pp.241-252, August. 2009.

[19] Hitachi,Ltd., “Real -Time Log Analysis Using Hitachi uCosminexus Stream Data Platform”, http://www.hitachi.com/products/it/software/prod/ cosminexus/index.html, accessed August. 2013.

[20] Gedik, B., Andrade, H., Wu, K., Yu, P. S., and Doo, M. 2008. “SPADE: The System S Declarative Stream Processing Engine”, Proceedings of the 2008 ACM SIGMOD international conference on Management of data, Vancouver, BC, pp.1123-1134, June. 2008.

[21] Barzan Mozafari, Kai Zeng, and Carlo Zaniolo, “High-performance Complex Event Processing over XML streams”, Proceedings of 2012 ACM SIGMOD International Conference on Management of Data, Arizona, USA, pp.253-264, May. 2012.

[22] Thanh T. L. Tran, Liping Peng, Yanlei Diao, Andrew McGregor, Anna Liu, “CLARO: Modeling and Processing Uncertain Data Streams”, The VLDB Journal, vol. 21, no. 5, pp. 651-676, October. 2012.

[23] Medhabi Ray , Elke A. Rundensteiner , Mo Liu , Chetan Gupta , Song Wang , Ismail Ari, “High-performance Complex Event Processing using Continuous Sliding Views”, Proceedings of 16th International Conference on Extending Database Technology, Genoa, Italy, pp. 525-536. March. 2013.

[24] Naotaka Nishimura, Hideyuki Kawashima,Accelerating CEP with Link Aggregation and Bulk

Evaluation , IPSJ Transaction on Database.(Conditional Acceptance)