Difference between revisions of "Ceilometer/AlarmEvaluatorJuno"
(Created page with "====Statistics over sliding windows==== Statistics where increments/decrements are possible: * count, * sum, * average, * stddev Statistics with special implementation: *...") |
(→Statistics over sliding windows) |
||
(4 intermediate revisions by the same user not shown) | |||
Line 1: | Line 1: | ||
− | + | ==Statistics over sliding windows== | |
+ | Two approaches to improve the alarm evaluator were discussed at the summit. | ||
+ | |||
+ | ===Map-reduce approach=== | ||
+ | [[File:EvaluatorMapReduce.png]] | ||
+ | <br/><br/><br/><br/> | ||
+ | |||
+ | ===Increment/decrement approach=== | ||
+ | [[File:EvaluatorIncDecrement.png]] | ||
+ | <br/> | ||
+ | |||
Statistics where increments/decrements are possible: | Statistics where increments/decrements are possible: | ||
* count, | * count, | ||
Line 5: | Line 15: | ||
* average, | * average, | ||
* stddev | * stddev | ||
+ | |||
Statistics with special implementation: | Statistics with special implementation: | ||
* min/max : needs O(log n) space (probably in DB), where n = window size | * min/max : needs O(log n) space (probably in DB), where n = window size | ||
* percentile : classical statistics query | * percentile : classical statistics query | ||
* cardinality : approximate algorithm, extremely efficient | * cardinality : approximate algorithm, extremely efficient | ||
+ | |||
+ | Map-reduce approach covers all these statistics. |
Latest revision as of 19:11, 16 May 2014
Statistics over sliding windows
Two approaches to improve the alarm evaluator were discussed at the summit.
Map-reduce approach
Increment/decrement approach
Statistics where increments/decrements are possible:
- count,
- sum,
- average,
- stddev
Statistics with special implementation:
- min/max : needs O(log n) space (probably in DB), where n = window size
- percentile : classical statistics query
- cardinality : approximate algorithm, extremely efficient
Map-reduce approach covers all these statistics.