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the potential dangersof causal consistencyand an explicit solutionPeter Bailis, Alan Fekete, Ali Ghodsi,Joseph M. Hellerstein, Ion Stoica
UC Berkeley SOCC 2012
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A Story
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A Story
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“Sally’s in a coma!”
A Story
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“Sally’s in a coma!”“Sally’s in a coma!”
A Story“Sally’s okay!”
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“Sally’s in a coma!”“Sally’s in a coma!”
A Story“Sally’s okay!”
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“Sally’s in a coma!”“Sally’s in a coma!”
A Story
“Great news!”
“Sally’s okay!”
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“Sally’s in a coma!”“Sally’s in a coma!”
A Story
“Great news!”
“Sally’s okay!”
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“Sally’s in a coma!”“Sally’s in a coma!”
“Great news!”
“Sally’s okay!”
The Wrong Story
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“Sally’s in a coma!”
“Great news!”
The Wrong Story
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“Sally’s in a coma!”
“Great news!”
The Wrong Story
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“Sally’s in a coma!”
“Great news!”
???The Wrong Story
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The Right Order
“Sally’s in a coma!”
“Great news!”
“Sally’s okay!”
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The Right Order
“Sally’s in a coma!”
“Great news!”
“Sally’s okay!”
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The Right Order
“Sally’s in a coma!”
“Great news!”
“Sally’s okay!”
![Page 16: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/16.jpg)
CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
![Page 20: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/20.jpg)
CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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1978“Time, Clocks, and the Ordering of Events
in a Distributed System” by Leslie Lamport
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1978“Time, Clocks, and the Ordering of Events
in a Distributed System” by Leslie Lamport
1994“Causal Memory” by Ahamad et al.
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1978“Time, Clocks, and the Ordering of Events
in a Distributed System” by Leslie Lamport
1994“Causal Memory” by Ahamad et al.
2011-12
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2011-12
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2011-12
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2011-12
IEEE CAP
There aremany hardtrade-offs,
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2011-12
IEEE CAP SOSP: COPS
There aremany hardtrade-offs,
butcausalconsistencycan workwell
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2011-12
IEEE CAP SOSP: COPS Texas: CAC
There aremany hardtrade-offs,
butcausalconsistencycan workwell
and it’sthe bestyou cando*!
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“Sally’s okay!”
![Page 33: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/33.jpg)
“Sally’s okay!”
![Page 34: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/34.jpg)
“Sally’s okay!”
![Page 35: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/35.jpg)
“Sally’s okay!”
![Page 36: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/36.jpg)
“Sally’s okay!”
![Page 37: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/37.jpg)
“Sally’s okay!”
![Page 38: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/38.jpg)
“Great news!”
“Sally’s okay!”
![Page 39: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/39.jpg)
“Great news!”
“Sally’s okay!”
![Page 40: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/40.jpg)
“Great news!”
“Sally’s okay!”
![Page 41: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/41.jpg)
“Great news!”
“Sally’s okay!”
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Deliver writesin the “right”order
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Deliver writesin the “right”order
“Great news!”
“Sally’s okay!”
“Sally’s in a coma!”
![Page 47: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/47.jpg)
Causal Consistencyreads obey partial ordercalled “happens-before”
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Write value
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Write valueHappens-beforemetadata
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Write valueHappens-beforemetadata
![Page 60: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/60.jpg)
Happens-beforemetadata
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Happens-before metadata
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per-DC vector clocksO(datacenters)
Happens-before metadata
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per-DC vector clocksO(datacenters)
Happens-before metadata
LESS PARALLELISM
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per-DC vector clocksO(datacenters)
per-key vector clock(dependency set)
O(keys)
Happens-before metadata
LESS PARALLELISM
![Page 65: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/65.jpg)
per-DC vector clocksO(datacenters)
per-key vector clock(dependency set)
O(keys)
Happens-before metadata
MORE PARALLELISM
LESS PARALLELISM
![Page 66: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/66.jpg)
per-DC vector clocksO(datacenters)
per-server vector clocksO(servers)
per-key vector clock(dependency set)
O(keys)
Happens-before metadata
MORE PARALLELISM
LESS PARALLELISM
![Page 67: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/67.jpg)
per-DC vector clocksO(datacenters)
per-server vector clocksO(servers)
per-key vector clock(dependency set)
O(keys)
Happens-before metadata
MORE PARALLELISM
LESS PARALLELISM
![Page 68: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/68.jpg)
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Have we seen alldependencies?
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Have we seen alldependencies?
![Page 73: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/73.jpg)
Have we seen alldependencies?
Y
![Page 74: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/74.jpg)
Have we seen alldependencies?
![Page 75: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/75.jpg)
Have we seen alldependencies?
Y
![Page 76: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/76.jpg)
Have we seen alldependencies?
Yes: apply write
![Page 77: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/77.jpg)
Have we seen alldependencies?
Yes: apply write
![Page 78: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/78.jpg)
Have we seen alldependencies?
No: waitYes: apply write
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Sounds great, right?
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CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
![Page 81: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/81.jpg)
Causal Consistencyreads obey partial ordercalled “happens-before”
![Page 82: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/82.jpg)
Causal Consistency
traditional happens-before:potential causality
reads obey partial ordercalled “happens-before”
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If you wish to make an apple pie from scratch,you must first inventthe universe.
-Carl Sagan
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“Great news!”
![Page 86: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/86.jpg)
“Great news!”
“Sally’s okay!”
![Page 87: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/87.jpg)
“Great news!”
“Sally’s okay!”
“Great picture!”
“Rad party!” “Lol!”
“Can’t waitfor SOCC!”
“Want to go skiing?”
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“Great news!”
“Sally’s okay!”
“Great picture!”
“Rad party!” “Lol!”
“Can’t waitfor SOCC!”
“Want to go skiing?”
“I hope my paper gets in.”
“Youwho?”
“I love Tahoe!”
“Coming tonight?
![Page 89: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/89.jpg)
“Great news!”
“Sally’s okay!”
“Great picture!”
“Rad party!” “Lol!”
“Can’t waitfor SOCC!”
“Want to go skiing?”
“Snow rocks!”
“I hear the PC is great!”
“You.”“Hello,
“I hope my paper gets in.”
“Youwho?”
“I love Tahoe!”
“Coming tonight?
![Page 90: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/90.jpg)
“Great news!”
“Sally’s okay!”
“Great picture!”
“Rad party!” “Lol!”
“Can’t waitfor SOCC!”
“Want to go skiing?”
“Snow rocks!”
“I hear the PC is great!”
“You.”“Hello,
“Who’s there?”
“Are you submitting?”
“Have you met Larry?”
“Great food here”
“I hope my paper gets in.”
“Youwho?”
“I love Tahoe!”
“Coming tonight?
![Page 91: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/91.jpg)
“Great news!”
“Sally’s okay!”
“Great picture!”
“Rad party!” “Lol!”
“Can’t waitfor SOCC!”
“Want to go skiing?”
“Snow rocks!”
“I hear the PC is great!”
“You.”“Hello,
“Who’s there?”
“Are you submitting?”
“Have you met Larry?”
“Great food here”
“Knock, knock.”
“I hope my paper gets in.”
“Youwho?”
“I love Tahoe!”
“Coming tonight?
![Page 92: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/92.jpg)
“Great news!”
“Sally’s okay!”
“Great picture!”
“Rad party!” “Lol!”
“Can’t waitfor SOCC!”
“Want to go skiing?”
“Snow rocks!”
“I hear the PC is great!”
“You.”“Hello,
“Who’s there?”
“Are you submitting?”
“Have you met Larry?”
“Great food here”
“Knock, knock.”
“I hope my paper gets in.”
“Youwho?”
“I love Tahoe!”
“Coming tonight?
![Page 93: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/93.jpg)
Twitter.com20 Tweetsat login
20 moreauto-scroll
600+ per min
![Page 94: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/94.jpg)
Twitter.comquicklyapproachesupper bound
![Page 95: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/95.jpg)
rec
ap
![Page 96: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/96.jpg)
potential dangerPotential causality graphs are huge,limiting local apply rates and throughput
rec
ap
![Page 97: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/97.jpg)
CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!
![Page 104: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/104.jpg)
DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!Unstable queue!
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!Unstable queue!
Sustained throughputlimited to slowest DC
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!Unstable queue!
Sustained throughputlimited to slowest DC
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!Sustained throughputlimited to slowest DC
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!
Adding DCs doesn’t helpslowest site
Sustained throughputlimited to slowest DC
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!
During partitions/failures,sustainable throughput iszero writes/szero
Sustained throughputlimited to slowest DC
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!During partitions/failures,sustainable throughput iszero writes/szero
![Page 111: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/111.jpg)
DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!During partitions/failures,sustainable throughput iszero writes/szero
![Page 112: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/112.jpg)
DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!During partitions/failures,sustainable throughput iszero writes/szero
Metadata garbage collectionstallsstalls
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!During partitions/failures,sustainable throughput iszero writes/szero
Metadata garbage collectionstallsstalls
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DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!DANGER!During partitions/failures,sustainable throughput iszero writes/szero
Metadata garbage collectionstallsstalls
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rec
ap
![Page 116: The Potential Dangers of Causal Consistency and an Explicit Solution - SOCC 2012](https://reader033.vdocument.in/reader033/viewer/2022060108/554f4e5cb4c905423f8b502c/html5/thumbnails/116.jpg)
rec
ap
potential dangerWrite throughput limited to slowest DCViolation ⇒ arbitrarily high visibility latencyAdding DCs does not increase throughput
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Potential dangers spell trouble for causality
bad news
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Potential dangers spell trouble for causality
to it?Are live without wedestined
bad news
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Potential dangers spell trouble for causality
to it?Are live withoutwe destined
bad news
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CAUSALITY: TL;DRMETADATA AND MODERN SERVICESTHE SITE SCALABILITY WALLSCALING WITH EXPLICIT CAUSALITY
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ObservationWhy track dependencies that don’t matter?
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ObservationWhy track dependencies that don’t matter?
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ObservationWhy track dependencies that don’t matter?
Need to know application semantics
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ObservationWhy track dependencies that don’t matter?
Need to know application semantics
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Explicit Causalityapp-defined “happens-before”
transitivity enforced
subset of potential causality
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Explicit Causalityapp-defined “happens-before”
transitivity enforced
subset of potential causality
not a new idea(e.g., Cheriton and Skeen SOSP 1993,
Ladin et al. PODC 1990)
but...
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Explicit Matters
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Explicit MattersTwitter28% of Tweets in conversations69% of convos are depth twoaverage depth is 10.7
[Ye and Wu SocInfo 2010, Ritter et al. HLT 2010]
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Explicit MattersTwitter28% of Tweets in conversations69% of convos are depth twoaverage depth is 10.7
[Ye and Wu SocInfo 2010, Ritter et al. HLT 2010]
reply-to degree and depth are limited
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Explicit MattersTwitter28% of Tweets in conversations69% of convos are depth twoaverage depth is 10.7
[Ye and Wu SocInfo 2010, Ritter et al. HLT 2010]
reply-to degree and depth are limited
109 smaller graph for a year of Tweets
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Explicit APIput(key, value)
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put_after(key, value, deps)
Explicit API
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put_after(key, value, deps)
Explicit API
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put_after(key, value, deps)
Explicit API
(possibly empty) set ofreferences to other writes
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put_after(key, value, deps)
Explicit API
track what matters
(possibly empty) set ofreferences to other writes
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put_after(key, value, deps)
Explicit API
track what mattersfrequently in data model already
(possibly empty) set ofreferences to other writes
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put_after(key, value, deps)
Explicit API
track what mattersfrequently in data model alreadycan simulate fencing
(possibly empty) set ofreferences to other writes
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put_after(key, value, deps)
Explicit API
track what mattersfrequently in data model alreadycan simulate fencing
(possibly empty) set ofreferences to other writes
won’t track non-explicit references
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Extra Note:
paper for more details
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can treat foreign key references in relational data model as explicit dependencies automatically!
can use schema to describe explicit deps...
Extra Note:
paper for more details
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NATURAL EXTENSIONNOT ROCKET SCIENCE
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NATURAL EXTENSIONNOT ROCKET SCIENCE
http://twitter.com/rbranson/status/256795094387142657
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potentialcausality
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A WORLD OFPHYSICAL
OPERATIONSMESSAGESREGISTERS
READSWRITES
MODEST SCALE
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A WORLD OF HUGE SCALE
MASSIVEINTERACTIVITYPLANET-WIDE
NETWORKSREAL-WORLD
INTERFACESUBICOMPBIG DATA
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potential
dangers
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potential
dangers
huge causality graphs
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potential
dangers
huge causality graphs
throughput scalability limited
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potential
dangers
huge causality graphs
throughput scalability limited
explicitcausalitysemantic context to the rescueconsider modern appshelps with #1, indirectly with #2