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It Takes Two: Instrumenting the
Interaction between In-Memory
Databases and Solid-State Drives
Alberto Lerner1 Jaewook Kwak2 Sangjin Lee2 Kibin Park2
Yong Ho Song2,3 Philippe Cudré-Mauroux1
1 XI Lab – University of Fribourg, Switzerland
2 ENC Lab – Hanyang University, Korea
3 Samsung Electronics, Korea
CIDR – January 2020 - Amsterdam
Motivation
• Where is time going?
• CPU/cache utilization
-> HW performance counters
• Per-instruction cost
-> pprof, linux perf tool
• Operating System impact
-> systemtap, several others
• SSD performance
-> ?
2
Challenges in In-Memory Databases Durability
• Log needs to be written as fast as
possible
• Checkpoint competes with client
request for memory and disk
access
• Can we understand the
interference? Was the TX Log IO
pattern efficient to begin with?
¼
Users Txn’s CP workers
3
host
storage
Txn
Log
Check
point
Cosmos+ OpenSSD
• Idea: let’s instrument an actual
device!
• SSD rapid prototyping platform
• SoC-based
• Fully functional
• Open source firmware
• Next generation is on final stages
of development
4
Anatomy of an SSD
¼
¼
¼
¼
5
Lifetime of a Write
¼
¼
¼
¼
6
Lifetime of a Write
¼
¼
¼
¼
7
Instrumentation
• Timestamping (in red)
• Counters (in green)
• Pagemap
• Mechanisms
• Triggers
• Data extraction
commands
8
Performance Event Records (PEV)
• Currently four types of records
IO_TIMESTAMP Regular timestamp stations
GC_TIMESTAMP FTL timestamp stations
PERFORMANCE_INDEX Aggregated counter
PERFORMANCE_INDEX_PER_CH Per channel counters
9
Experimenting with Timestamps
• In-memory Databases Simulated
Workloads
• (1-1) WAL – IPP
• (1-N) WAL – CALC
• (M-N) SILOR / CPR ¼
...
10
Txn
Log
Check
point
Delay Examples
11
t0 t1
Interference Analysis
No interference
2.5x
12
Research Agenda I - Instrumentation
• Functionality Limitations
• Currently limited at 4 channels
• Further annotations to trace back
valid copies
• Contextual triggers
• Signal Generation
• Process instrumentation records
on-the-fly
• Identify scenarios where a
scheduling policy change is
beneficial
13
Research Agenda II – SSD as a Platform
• Adaptive Scheduling
• Respond instantaneously to
signals generated by changing
priorities
• In-Storage Checkpoint
”Derivation”
• Move the checkpoint process
partially or entirely into the device
14
Conclusion
• SSDs don’t have to be black boxes
• The Instrumented Cosmos+ allows designers of both Databases and FTLs to
analyze and understand interference in workloads
• Opportunities to
• Have SSDs interact with applications in richer ways
• Exploit new possibilities of Near-Data Computing for Databases
15
Q&A
Thank you!
16

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It Takes Two: Instrumenting the Interaction between In-Memory Databases and Solid-State Drives CIDR 2020 presentation

  • 1. It Takes Two: Instrumenting the Interaction between In-Memory Databases and Solid-State Drives Alberto Lerner1 Jaewook Kwak2 Sangjin Lee2 Kibin Park2 Yong Ho Song2,3 Philippe Cudré-Mauroux1 1 XI Lab – University of Fribourg, Switzerland 2 ENC Lab – Hanyang University, Korea 3 Samsung Electronics, Korea CIDR – January 2020 - Amsterdam
  • 2. Motivation • Where is time going? • CPU/cache utilization -> HW performance counters • Per-instruction cost -> pprof, linux perf tool • Operating System impact -> systemtap, several others • SSD performance -> ? 2
  • 3. Challenges in In-Memory Databases Durability • Log needs to be written as fast as possible • Checkpoint competes with client request for memory and disk access • Can we understand the interference? Was the TX Log IO pattern efficient to begin with? ¼ Users Txn’s CP workers 3 host storage Txn Log Check point
  • 4. Cosmos+ OpenSSD • Idea: let’s instrument an actual device! • SSD rapid prototyping platform • SoC-based • Fully functional • Open source firmware • Next generation is on final stages of development 4
  • 5. Anatomy of an SSD ¼ ¼ ¼ ¼ 5
  • 6. Lifetime of a Write ¼ ¼ ¼ ¼ 6
  • 7. Lifetime of a Write ¼ ¼ ¼ ¼ 7
  • 8. Instrumentation • Timestamping (in red) • Counters (in green) • Pagemap • Mechanisms • Triggers • Data extraction commands 8
  • 9. Performance Event Records (PEV) • Currently four types of records IO_TIMESTAMP Regular timestamp stations GC_TIMESTAMP FTL timestamp stations PERFORMANCE_INDEX Aggregated counter PERFORMANCE_INDEX_PER_CH Per channel counters 9
  • 10. Experimenting with Timestamps • In-memory Databases Simulated Workloads • (1-1) WAL – IPP • (1-N) WAL – CALC • (M-N) SILOR / CPR ¼ ... 10 Txn Log Check point
  • 13. Research Agenda I - Instrumentation • Functionality Limitations • Currently limited at 4 channels • Further annotations to trace back valid copies • Contextual triggers • Signal Generation • Process instrumentation records on-the-fly • Identify scenarios where a scheduling policy change is beneficial 13
  • 14. Research Agenda II – SSD as a Platform • Adaptive Scheduling • Respond instantaneously to signals generated by changing priorities • In-Storage Checkpoint ”Derivation” • Move the checkpoint process partially or entirely into the device 14
  • 15. Conclusion • SSDs don’t have to be black boxes • The Instrumented Cosmos+ allows designers of both Databases and FTLs to analyze and understand interference in workloads • Opportunities to • Have SSDs interact with applications in richer ways • Exploit new possibilities of Near-Data Computing for Databases 15