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Cloud Storage Consistency . … Explained through Baseball. Doug Terry Microsoft Research Silicon Valley. Data Replication in the Cloud. Question : What consistency choices should cloud storage systems offer applications?. Some Popular Systems. Amazon S3 – eventual consistency

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cloud storage consistency

Cloud Storage Consistency

… Explained through Baseball

Doug Terry

Microsoft Research Silicon Valley

data replication in the cloud
Data Replication in the Cloud

Question: What consistency choices should cloud storage systems offer applications?

some popular systems
Some Popular Systems
  • Amazon S3 – eventual consistency
  • Amazon Simple DB – eventual or strong
  • Google App Engine – strong or eventual
  • Yahoo! PNUTS – eventual or strong
  • Windows Azure Storage – strong (or eventual)
  • Cassandra – eventual or strong (if R+W > N)
  • ...
a spectrum of consistency
A Spectrum of Consistency

Strong

Consistency

Intermediate

Consistency

Eventual

Consistency

Lots of consistencies proposed in research community: probabilistic quorums, session guarantees, epsilon serializability, fork consistency, causal consistency, demarcation, continuous consistency, ...

comparing consistency
Comparing Consistency

strength

Strong

metric =

set of allowable read results

Prefix

Bounded

Monotonic

RMW

Eventual

consistency trade offs
Consistency Trade-offs

performance

consistency

availability

the game of baseball
The Game of Baseball

for inning = 1 .. 9

outs = 0;

while outs < 3

visiting player bats;

for each run scored

score = Read (“visitors”);

Write (“visitors”, score + 1);

outs = 0;

while outs < 3

home player bats;

for each run scored

score = Read (“home”);

Write (“home”, score + 1);

end game;

official scorekeeper
Official Scorekeeper

Desired consistency?

Strong

= Read My Writes!

score = Read (“visitors”);

Write (“visitors”, score + 1);

umpire
Umpire

Desired consistency?

Strong consistency

if middle of 9th inning then

vScore = Read (“visitors”);

hScore = Read (“home”);

if vScore < hScore

end game;

radio reporter
Radio Reporter

do {

BeginTx();

vScore = Read (“visitors”);

hScore = Read (“home”);

EndTx();

report vScore and hScore;

sleep (30 minutes);

}

Desired consistency?

Consistent Prefix

Monotonic Reads

or Bounded Staleness

sportswriter
Sportswriter

While not end of game {

drink beer;

smoke cigar;

}

go out to dinner;

vScore = Read (“visitors”);

hScore = Read (“home”);

write article;

Desired consistency?

Eventual?

Strong = Bounded Staleness

statistician
Statistician

Desired consistency?

Strong Consistency (1st read)

Read My Writes (2nd read)

Wait for end of game;

score = Read (“home”);

stat = Read (“season-runs”);

Write (“season-runs”, stat + score);

stat watcher
Stat Watcher

Desired consistency?

Eventual Consistency

do {

stat = Read (“season-runs”);

discuss stats with friends;

sleep (1 day);

}

slide15

Read My Writes

Official scorekeeper:

score = Read (“visitors”);

Write(“visitors”, score + 1);

Statistician:

Wait for end of game;

score = Read (“home”);

stat = Read (“season-runs”);

Write (“season-runs”, stat + score);

Umpire:

if middle of 9th inning then

vScore= Read (“visitors”);

hScore = Read (“home”);

if vScore < hScore

end game;

Radio reporter:

do {

vScore = Read (“visitors”);

hScore = Read (“home”);

report vScore and hScore;

sleep (30 minutes);

}

Sportswriter:

While not end of game {

drink beer;

smoke cigar;

}

go out to dinner;

vScore= Read (“visitors”);

hScore = Read (“home”);

write article;

Stat watcher:

stat = Read (“season-runs”);

discuss stats with friends;

Bounded Staleness

Strong Consistency

Strong Consistency

Read My Writes

Consistent Prefix

Monotonic Reads

Eventual Consistency

conclusions
Conclusions
  • Replication schemes involve tradeoffs between consistency, performance, and availability
  • Consistency choices can benefit applications
  • But we, the research community, must provide better definitions, analysis, and tools
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