Evaluation of Data Placement Method in Database Run-Time Processing Considering Energy Saving and...
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Evaluation of Data Placement Method in Database Run-Time Processing Considering Energy Saving and
Application Performance
Naho IIMURA† Norifumi NISHIKAWA‡ Miyuki NAKANO†† Masato OGUCHI†
†Ochanomizu University ‡ Hitachi, Ltd., Yokohama Research Laboratory
†† Shibaura Institute of Technology
NOVEMBER 3rd, 2014 IGCC14 GPCDP Workshop
OUTLINE
• Introduction• Previous Work• Our Proposed Method and Evaluation Plan
– Data Placement Control• Experimental• Evaluation Results and Discussion• Conclusion and Future Works
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Background(1/2)
• The amount of digital data is increased rapidly.• The scale of datacenters(DC) has become
larger.→ The management use cost of DC has
become larger.
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•Operating costs of machines•Amortization of buildings and cooling equipment•Electricity charge
Energy saving of DC is drawing attention NOW
Background(2/2)
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63%14%
13%
5%5%
Typical Data Center Energy Consumption Rate
Cooling
Servers
Storages
Network Hardware
Power Conversion
Reducing the power consumption of storage is an efficient way to save energy in datacenters
Research Objective
• Conventional Methods– Performance enhancement of cooling facilities– Performance enhancement of power efficiency and more...
• Our Proposed Method– The power saving of storage
by efficient management of data
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have been already addressed
Goal of Research
To achieve …• Analyze of Power Consumption and System
Performance of the TPC-H Runtime• Propose Storage Power Saving Method
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Reducing Energy Consumption of Storage while Minimizing the Deterioration
of Database Application Performance
TPC-H is one of the standard benchmark tool of database application
Previous Works
• Combine application level I/O and device level I/O• Extract Logical I/O pattern• Select appropriate power saving methods
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Runtime Power Saving Framework
Application level I/O Monitor
Buffer based Power Saving Methods
• Pre-load• Write Delay
Storage Device level I/O Monitor
Control MAID• Power ON/OFF
DB Buffer
DB EngineApplications
File System BufferDevice Driver
Storage Buffer
Storage Devices
Energy Efficient Storage Management Cooperated with Large Data Intensive Applications Nishikawa ,et al. (IEEE ICDE 2012)
Present Work Direction
• Experiment Environment– Large scale Unit → Single Unit
• For the storage power saving of TPC-H runtime– Calculate the Break-Even Time– Evaluate our proposed method focusing on the
Service Level Agreement (SLA)• Data Placement Control
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To analyze power saving more detail in
more small unit
Our Proposed Method
• Data Placement Control– Based on I/O frequency on Run-Time applications, Modify
the data placement
Change to the Standby-mode when disk is not being used Finally, power consumption can be reduced more
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Long I/O interval
*The using frequency of data
< <
Evaluation Plan
The number of used HDDs are 3 - 10
Evaluation Environment
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CPU 4 cores * 2
Memory 8GBytes
HDD 3TB *11
OS Cent OS 5.10 64bit
DBMS HITACHI HiRDBSingle ServerVersion 9
Benchmark
TPC-H (SF=10)
Power Meter
YOKOGAWADigital Power Meter
Local PC
Remote Server
Power Meter
PC to Control Power Meter
Ochanomizu Univ.
Univ. of Tokyo
Break-Even Time• Break-Even Time is the amount of time to continue the Standby state
that satisfies the following condition.• The amount of energy needed for the spinup or spindown of the disk
is equal to that of the energy saved by remaining in the Standby state during Break-Even Time.
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24 seconds
To reduce power consumption by using the Standby state, an I/O interval of approximately 24 seconds or more is needed.
The Investigation of I/O Frequency
• Investigate the I/O frequency of data, tables and indexes of during runtime processing of TPC-H queries.– Divide LINE ITEM Table and Indexes into 10 Buffers.– I/O interval is obtained every second.– The survey period is from the beginning to the end
of the query execution.– Focus on the actual number of times the READs
from the obtained data items.
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Classified Data From I/O Frequency
• Classified the data into two types:– the data that HAVE actual number of instances of
READ or NOT
• In next page, I/O frequency of partitioned data is focused
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I/O Frequency of Partitioned Data
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•Partitioned tables are used in a numerical order•A longer I/O intervals is obtainable by placing partitioned data with near numbers on the same disk
First ExperimentData placement control with table partitioning
• Divide LINE ITEM Table and Indexes into 10 buffers– To use more flexible arrangement of data– Use the Hash Partitioning
• Place all data on 3 HDDs– Design 2 patterns of placement about partitioned data.
• Compare 2 patterns of placement during runtime processing of TPC-H– Times of I/O Interval– Power Consumption and Response Time
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Two Patterns of Data Placement
A) Partitioned data is placed by round-robin placement
B) Partitioned data with near numbers are placed on the same HDDs
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1,4,7,10 2,5,8 3,6,9
1,2,34,5,6 7,8 9,10
Number and Times of I/O Intervals
• Pattern A get more times of short (less than the Break-Even Time) I/O interval.
• Placement of partitioned data by Near-Number Placement is efficient in this case.
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A) Round-Robin Placement B) Near-Number Placement
~ 24sec(Break-Even Time) 111 12
25 ~ 100sec 59 35
101 ~ 200sec 9 14
201sec ~ 8 14
Much More TimesGet longer I/O
intervals
First ExperimentResult
Power Consumption Response Time
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(1) (2)0
20,000
40,000
60,000
80,000
100,000
120,000 98,880 98,789
84,244 65,972
Without Standby stateWith Standby state[J]
(1) (2)0:00
24:00
48:00
72:00
96:00
120:00
82:58 85:13
105:5292:43
Without Standby stateWith Standby state
[mm:ss]
A B A B
•Reduce the Power Consumption more in B because I/O interval is longer than A.
•Delay rate of Response Time of B is smaller than A because the seek overhead is smaller.
The placement partitioned data by Near-Number Placement is efficient in this case.
A) Round-Robin Placement B) Near-Number Placement
Reduction Rate of Power Consumption 15% 33%
Delay Rate of Response Time 22% 8%
Second ExperimentData placement control with using 10 HDDs
• The number of HDD is 10• Compare during runtime processing of TPC-H
queries between With and Without Data Placement Control– Power Consumption and Response Time
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Second ExperimentData Placemet(1/2)
• Without Control– Placed all data such that the amount of data in each HDD to
be evenly.– The frequency of the data I/O is not considered in this case.
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HDD1
HDD7HDD6
HDD2 HDD3 HDD4 HDD5
HDD9HDD8 HDD10LINEITEM_1
LINEITEM_Index_1
21%
16%
12%8%7%
7%
7%
7%7%7%
HDD1 HDD2HDD3 HDD4HDD5 HDD6HDD7 HDD8HDD9 HDD10
Energy State of All Disks is
Idle or Active
the same partitioned number of data are placed on the same HDD
The amount of data in each HDD
Second ExperimentData Placemet(2/2)
• With Control– HDD1: Placed the data that have I/O– HDD2: Placed the data that have no I/O– HDD3-10: No data is placed
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HDD1
HDD7
HDD6HDD2 HDD3 HDD4 HDD5
HDD9HDD8 HDD10Have I/O No I/O
No data
Idle or Active
Standby
Biased
Second ExperimentResult
Power Consumption Response Time
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0:00
24:00
48:00
72:00
96:00
120:00
92:04 96:24
Without ControlWith Control
[mm:ss]
0
100,000
200,000
300,000
400,000 332,649
93,070
Without controlWith control
[J]
•Reduce the Power Consumption 72%•Delay of Response Time is 4%•This Result is reasonable because only one of HDD has the data that have I/O, and the power consumption state is Idle or Active.
Conclusion
• Proposed data placement control method in Database Run-Time Processing – Based on I/O frequency, modify the data placement– Consider energy saving and application performance
• Evaluate our proposed method with TPC-H– Found the data placement control method is
effective for energy saving during runtime application processing
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Future Works
• Examination of more detailed data placement
• Investigation the relation of Trade-off between power consumption and response time
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Acknowledgement
• Thank for the conscientious advice with this work– Institute of Industrial Science, the University of Tokyo
• Associate Prof. Daisaku Yokoyama
– Kogakuin University • Associate Prof. Saneyasu Yamaguchi
– Institute of Information Security• Prof. Atsuhiro Goto
– Shibaura Institute of Technology• Associate Prof. Midori Sugaya
• This work is partly supported by the Ministry of Education, Culture, Sports, Science and Technology
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END
Thank you for your kind attention.
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