January/February 2018 issue of acmqueue

The January/February issue of acmqueue is out now


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Originally published in Queue vol. 11, no. 3
see this item in the ACM Digital Library



Graham Cormode - Data Sketching
The approximate approach is often faster and more efficient.

Heinrich Hartmann - Statistics for Engineers
Applying statistical techniques to operations data

Pat Helland - Immutability Changes Everything
We need it, we can afford it, and the time is now.

R. V. Guha, Dan Brickley, Steve MacBeth - Schema.org: Evolution of Structured Data on the Web
Big data makes common schemas even more necessary.


(newest first)

David Collier-Brown | Wed, 10 Apr 2013 21:53:19 UTC

There is an interesting parallel here between the reasoning about the properties of causal consistency and the reasoning employed in safety-critical systems.

A classic example used to illustrate the latter is a train approaching a crossing-gate where a road crosses the tracks, (Example courtesy of Professor Jonathan Ostroff, https://wiki.cse.yorku.ca/user/jonathan/start, but all errors are mine)

When a train enters the block containing the gate and the gate is open, as it normally is, the state of the system changes from safe to dangerous.

Within time t1, the crossing gate most report itself as closed. if so, state returns to safe if not, then the train must stop in time t2 if so, state again returns to safe if not, the train runs through any cars crossing the track.

These systems can be statically sized and proved correct, based on - the maximum speed of the train, - the minimum deceleration rate of the train, and - the maximum time taken to close the gate

Logically, the guarantees available in variations on eventual consistency could be explored this way. For example, we might ask how long a system would take to regain consistency after repairing a partition, or explore when we should consider a possible partition to be a failure.

--dave --dave

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