Applying control theory to stream processing systems
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Applying Control Theory to Stream Processing Systems. Wei Xu ( [email protected] ) Bill Kramer ( [email protected] ) Joe Hellerstein ( [email protected] ). TCQ drops tuples silently if result queue is full. Description of the system. TCQ Complex internal structure. Data Source.

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Applying Control Theory to Stream Processing Systems

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Applying Control Theory to Stream Processing Systems

Wei Xu ([email protected])

Bill Kramer ([email protected])

Joe Hellerstein ( [email protected] )


TCQ drops tuples silently if result queue is full

Description of the system

TCQ

Complex internal structure

Data Source

Input Buffer


Why do we need control?

  • Data source does not provide accurate data rate


Why do we need control?

  • TCQ node drops tuples when result queue fill up

Source

Buffer

TCQ

Result Q


Control Problems

  • Providing an accurate data source

    • Get the actual data rate

  • Regulate queue length on TCQ node

    • Prevent dropping tuples

    • Maximize throughput (and adapts when disturbance happens)


2

Queue Length Monitor

System with Control

Controlled

Data Source

Output Rate

Controller


PI Controller

The Control Architecture

P Controller


Result – An accurate data source

P Controller with Pre-compensation

PI Controller


Result – regulating queue length

Source

Buffer

TCQ

Result Q


Result – Under CPU Contention

Source

Buffer

TCQ

Result Q


Why theory is useful?

  • One of my implementations .. What happened?

Source

Buffer

TCQ

Result Q


What is going on?

Controlled

Output Thread(Code Reuse)

Queue Length

Controller

Desired

Queue length

Data Rate to TCQ

Actual Queue Length


Output Y from simulation

Theory meets reality

Queue length

Time


Tricky part of parameter estimation

Model evaluation – Making the system operate in desired range

Data rate vs free space

Free Space

Non-Linear range

Easy for data source, but queue length ..


Settling Time and Overshoot matters

A lot of small disturbance in a Java program

Incremental garbage collection

P Controller

PI Controller


Conclusion

  • Advantages of feedback control

    • Make system more robust under disturbance

    • Treat complex systems as black boxes

      • Cope with the system characteristics instead of having to change it

    • Encourage reporting system statistics

    • Implementation is easy and has theoretical guarantees


Future Work

  • Load balancer

  • Smaller sample time to reduce disturbance caused by Java GC?

  • Controller on scheduling of system shared by multiple streams


Backup Slides


Outline

  • Problems and Motivation

  • Controller design

  • Result

  • Discussion


Description of the System

Tuples

TCQ Node

Tuple

Blocks

Routing

Logic

Input Buffer

Data

Source

TCQ Node

Load Splitter

Tuples

Queue length

  • Operation of Load Splitter

  • Arriving blocks wait in Input Buffer

  • Tuples are routed to balance TCQ queue lengths

  • Stop routing if queue length is too large to avoid tuple discards

Revised


Compare to Open Loop Control

We know

Y(k) , and we know what we want y(k+1) to be.. Use transfer function to solve for u(k)…

(Expected result – accuracy and disturbance ) -- do be done


Estimation of the transfer function

y(k+1)=ay(k)+bu(k)

Regression


Tricky part of parameter estimation

Model evaluation – A data rate that make it operate in linear range


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