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Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
EventWave: Programming Model and Runtime Support
forTightly-Coupled Elastic Cloud Applications
Wei-Chiu Chuang, Bo Sang, Sunghwan Yoo, Rui Gu, Charles Killian, Milind Kulkarni
1
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Motivation
2
clients
server
world
building building
room
room
room
room
TimeResponse time
# clients
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Motivation
3
Scale up
TimeResponsetime
clients
server
# clients
Elasticity is hard
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Objectives
4
A programming model which supports:
Stateful computation
Simple sequential semantics
Transparent elasticity
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Related Work
5
Data Flow stateless
Live Migration
Live Migration of Virtual Machines[Clark et. al. NSDI ‘05]
Zephyr [Elmore et. al. SIGMOD ‘11]
Does not change scale:“split”/”merge” state
Scalable programming model
Orleans [Bykov et. al. SoCC ‘11]Transactional, reconcile conflicts
MapReduce [Dean et. al. OSDI ‘04]
Dryad [Isard et. al. EuroSys ‘07]
CIEL [Murray et. al. NSDI ‘11]
No Stateful Computation
No transparent elasticity
No simple sequential semantics
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Event Driven Systems
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123
Event 1 commitsEvent 2
commitsEvent 3
commits
Typical event driven systems are not scalable.
Event queueclient
server
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Context
8
world
building building
room
room
room
room
Scalability comes from parallelism Partition program state into `contexts` An event accesses one or more contexts Events accessing disjoint contexts can run in parallel
world
building
room
hallwayContexts enable implicit
parallelism
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
EventWave
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Event 1 commits
Event 2 commits
Event 3 commits
Event 2 finishes
Event 1 finishes
Event 3 finishes
Context 1
Context 2
Context 3
123
Enforce sequential orderingEvent 2 can not commit until Event
1 commits
Stateful
Sequential semantics
Parallelism
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Access Multiple Contexts
A player can move from one room to another
Remove it from source room
Insert it into destination room
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world
building building
room
room
room
room
Room 1 Room 2
Alice BobBob
Player list
An event may access multiple contexts
Bob
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Access Multiple Contexts
Must ensure
Sequential semantics
parallelism
Event 1 finishes
Event 2 commits12
10
To be scalable, events can not access contexts arbitrarily
Event 2 can’t start before event 1 finishes
Context 1
Context 2
Context 3
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Hierarchical Contexts
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Contexts are not completely independent
The world has many buildings
A building has many rooms
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Must access contexts from top to bottom
The hierarchical access enables parallelism
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Move a player from room 1 to room 2
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Allow the next event to access Building<1>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Enter Room<1>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Remove playerRelease
exclusive access
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
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world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Enter Room<2>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
19
world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Insert player
Event finishes, releasing all contexts
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
20
world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Wave of Events
21
world
Building<1> Building<2>
Room<1> Room<2> Room<1> Room<2>
Event commits, releasing snapshot
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Scale more by executing events across multiple nodes
Map contexts
Head node
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Distributed Execution
Head nodeworld
Building<1> Building<2>
Room<1>
Room<2>
Room<3>
Room<4>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13 23
Distributed Execution
Client Logical Node #1
Client Logical Node #2
Logical Node: a set of physical nodes
Server Logical Node
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13 24
Distributed Execution
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13 25
Elasticity
world
Building<1> Building<2>
Room<1>
Room<2>
Room<1>
Room<2>
Request nodes from cloud scheduler
Update context mapping
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13 26
Elasticity
world
Building<1> Building<2>
Room<1>
Room<2>
Room<1>
Room<2>
Transfer contexts to the new node
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Evaluation
Does it scale?
Microbechmarks
Scalability
What is the cost of migration?
Microbechmarks
Migration latency
Case study
Multi-player game server
28
In the paper
Key-value store
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Microbenchmark-Scalability
Setup
One logical node, fixed context mapping
EC2 Small Instances
1 vCPU, 1.7GB RAM, 160 GB local disk
Distribute 160 contexts to physical nodes
Measures
Throughput
29
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Microbenchmark-Scalability
30
Takeaway:Throughput grows
w.r.t. # of nodes
P: workload
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Microbenchmark-Migration Latency
31
Setup
2 x 8-core 2.0 GHz Xeon, 8GB RAM
1Gb Ethernet connection
Scale does not change
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Microbenchmark-Migration Latency
Measure
Throughput of events
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The migration event commits
Finished events must wait for migration event
Migrate a 100MB context
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Multi-player Game Server
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Setup
Server logical node
1 x Extra Large Instance (head)
64 x Small Instances
Client logical nodes
128 clients on 16 EC2 Small Instances
Measure
Latency
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Multi-player Game Server
34
Server contexts spread to 64 physical nodes
Synthetic workload
Server contexts merge to 1 physical nodes
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Conclusion
Elasticity is crucial for cloud applications.
Our programming model enables transparent elasticity for tightly-coupled applications
Case studies show EventWave is efficient
35
http://www.macesystems.org
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Backups
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Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Language Construct
37
state_variables{Hallway hw;vector<Room> rooms;
}
context Hallway{int x;
}context Room<int>{
int y;}
Declare implicit
parallelism
Mace [Killian et. al. PLDI ‘07]
HallwayRoom[0]Room[1]…
Hallway
Room<0>
Room<1>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Event Handler
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upcall deliver(Message m){
}
upcall [Room<m.roomID>] deliver(Message m){
}
AnnotationSpecify what context to access
Message(roomID = 2)
Context Room<2>
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Key-value store
39
Setup
2 x 8-core 2.0 GHz Xeon, 8GB RAM
1Gb Ethernet connection
Measure
Latency
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Key-value store
40
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13
Microbenchmark-Migration Latency
41
Setup
2 x 8-core 2.0 GHz Xeon, 8GB RAM
1Gb Ethernet connection
Scale does not change
Context
Chuang, Sang, Yoo, Gu, Killian and Kulkarni, “EventWave” SoCC ‘13 42
Context Migration
Head
Old node
New node
Copy context state
Replicate context state
Event 1 goes to the old node
Event 3 goes to the new node
1 M 3
Update context-node mapping
