chaotic-good

9 ms·

61.
by chaotic-good 11y ago
Even simple delta+RLE can squeeze increasing unix timestamps up to few bytes. I'm talking about floating point data compression. Even the specialized state of the art algorithms can't guarantee you 2.2 bytes per float in general.
62.
by chaotic-good 11y ago
It depends greatly on the shape of your data, but with regularly spaced timestamps at second level precision and float64s, we’ve seen compression reduce each point down to around 2.2 bytes per point. AFAIK you're using float64 compre
63.
by chaotic-good 11y ago
OpenTSDB is really nice but it has some drawbacks: 1. Limited timestamp precision (because of storage schema). 2. Dependency on HBase.
64.
by chaotic-good 11y ago
No, they didn't. This article is narrow minded and prejudiced. Of cause if we're talking about programming in general - static typing languages are often a better option. But programming doesn't ends there, there is technical
65.
How to scale graphite up to X times and reduce cpu consumption twice?(stableit.ru)
2 points by chaotic-good 11y ago|0 comments
66.
by chaotic-good 11y ago
If you can predict next value in the sequence you can achieve better compression (xor predicted value and actual, not previous and next - http://users.ices.utexas.edu/~burtscher/papers/dcc06.pdf ), but I don't
67.
by chaotic-good 11y ago
> It can still be pointing to the raw data. Yep. Each SAX word should be mapped to the list of seriesid:timestamp pairs. This list is often referred as postings list in information retrieval. The resulting data-structure is an inverted i
68.
by chaotic-good 11y ago
You can't retrieve original time-series data from SAX storage because of normalization. To query time-series data by content (approximate 1-NN, motif discovery, etc) you need inverted index.
69.
by chaotic-good 11y ago
Can't agree more. Time-series data analysis should be considered the most important, not storage. Storage is a solved problem. Let's imagine that we're getting ECG data from many patients. What most time-series databases is a
70.
by chaotic-good 11y ago
SAX requires different type of storage. You can store SAXified time series in ElasticSearch, or Solr but time-series database doesn't fit for this. Time-series databases should be able to generate SAX representation.
71.
by chaotic-good 11y ago
I'm building my own time-series database for some time. https://github.com/akumuli/Akumuli It's a standalone solution without dependencies on other services or databases. It can handle more than a million dat
72.
Some thoughts about numeric time-series databases(akumuli.org)
2 points by chaotic-good 11y ago|0 comments
73.
by chaotic-good 11y ago
SCADA systems usually handles small amount of data (because data comes from real sensors, this sensors is expensive and you simply can't have millions of them).
74.
by chaotic-good 11y ago
You can't compare this solution to InfluxDB or other time-series databases out there because you're loosing information here. You can't store timestamps with arbitrary precision, and all the data is resampled, there is no way
75.
by chaotic-good 11y ago
Are you considering remote candidates?
76.
Ask HN: What do you need from time-series database?
1 points by chaotic-good 11y ago|0 comments
77.
by chaotic-good 11y ago
We have used such systems in industrial control systems for decades. TSDB is integral part of any modern SCADA system. This patent is a nonsense.
78.
by chaotic-good 11y ago
iSAX was an improvement over simple SAX indexing scheme that was known since 2005 or so.
79.
iSAX 2.0: Indexing and Mining One Billion Time Series [pdf](cs.ucr.edu)
26 points by chaotic-good 11y ago|8 comments
80.
by chaotic-good 11y ago
In erlang old data structures can't reference new data. This simplifies GC a lot.
81.
by chaotic-good 11y ago
Can I read about this storage engine somewhere?
82.
by chaotic-good 11y ago
What is throughput of the system per node?
83.
by chaotic-good 12y ago
This technique usually called 'kernel bypass'. http://highscalability.com/blog/2013/5/13/the-secret-to-10-m... and http://lukego.github.io/blog/2013/01/04/ke
84.
Why text-based serialization is awesome(akumuli.org)
2 points by chaotic-good 12y ago|1 comments
85.
Time-series storage design – compression(akumuli.org)
2 points by chaotic-good 12y ago|0 comments
86.
TCPKali: Open-source load generator and performance testing tool(github.com)
8 points by chaotic-good 12y ago|0 comments
87.
Time-series storage design(akumuli.org)
2 points by chaotic-good 12y ago|0 comments
88.
by chaotic-good 12y ago
It has interfaces to write generic code. It doesn't allow you to write your own generic data structures but it's not an issue because it has built-in dynamic arrays and dictionaries. You supposed to use built in data structures mo
89.
by chaotic-good 12y ago
UI looks really cool though a little bit alien on ubuntu.
90.
by chaotic-good 12y ago
It is possible to search using address bar and separate search bar, why not to join them?

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