- Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
- Models and Issues in Data Stream Systems
- Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
- Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
- [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
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ex() { | |
if [ -z "$1" ] ; then | |
echo >&2 'File not specified' | |
return 1 | |
fi | |
if [ ! -f "$1" ] ; then | |
echo >&2 "'$1' is not a valid file" | |
return 1 | |
fi |
- Measure time spend on index, flush, refresh, merge, query, etc. (TD - done)
- Take hot threads snapshots under read+write, read-only, write-only (TD - done)
- Adjust refresh time to 10s (from 1s) and see how load changes (TD)
- Measure time of a rolling restart doing
disable_flush
anddisable_recovery
(TD) - Specify routing on query -- make it choose same node for each shard each time (MD)
- GC new generation size (TD)
- Warmers
- measure before/after of client query time with and without warmers (MD)