Re: Time-Series Forecasting

Thank you very much, really appreciate the information. Kindest regards, Mina On Sat, Sep 29, 2018 at 9:42 PM Peyman Mohajerian wrote: > Here's a blog on Flint: > https://databricks.com/blog/2018/09/11/introducing-flint-a-time-series-library-for-apache-spark.html > I don't have an opinion about

Re: Time-Series Forecasting

Here's a blog on Flint: https://databricks.com/blog/2018/09/11/introducing-flint-a-time-series-library-for-apache-spark.html I don't have an opinion about it, just that Flint was mentioned earlier. On Thu, Sep 20, 2018 at 2:12 AM, Gourav Sengupta wrote: > Hi, > > If you are following the time se

Re: Time-Series Forecasting

Hi, If you are following the time series forecasting with the mathematical rigour and tractability then I think that using R is the best option. I do think that people tend to claim quite a lot these days that SPARK ML and other Python libraries are better, but just pick up a classical text book o

Re: Time-Series Forecasting

We are using Yahoo Egads for our Anomaly Detection system on time series data. If has good forecasting and Anomaly Detection modules. https://github.com/yahoo/egads On Thu, Sep 20, 2018 at 5:22 AM Aakash Basu wrote: > Hey, > > Even though I'm more of a Data Engineer than Data Scientist, but st

Re: Time-Series Forecasting

Hey, Even though I'm more of a Data Engineer than Data Scientist, but still, I work closely with the DS guys extensively on Spark ML, it is something which they're still working on following the scikit-learn trend, but, I never saw Spark handling Time-Series problems. Talking about both Scala-Spar

Re: Time-Series Forecasting

Hi I work mostly in data engineering and trying to promote use of sparkR within the company I recently joined. Some of the users are working around forecasting a bunch of things and want to use SparklyR as they found time series implementation is better than SparkR. Does anyone have a point of vi

Re: Time-Series Forecasting

Hi, Thank you for your quick response, really appreciate it. I just started learning TimeSeries forecasting, and I may try different methods and observe their predictions/forecasting.However, my understanding is that below methods are needed: - Smoothing - Decomposing(e.g. remove/separate trend/

Re: Time-Series Forecasting

There’s also flint: https://github.com/twosigma/flint > On 19 Sep 2018, at 17:55, Jörn Franke wrote: > > What functionality do you need ? Ie which methods? > >> On 19. Sep 2018, at 18:01, Mina Aslani wrote: >> >> Hi, >> I have a question for you. Do we have any Time-Series Forecasting library

Re: Time-Series Forecasting

What functionality do you need ? Ie which methods? > On 19. Sep 2018, at 18:01, Mina Aslani wrote: > > Hi, > I have a question for you. Do we have any Time-Series Forecasting library in > Spark? > > Best regards, > Mina - To

Re: Time-Series Forecasting

Hi, I saw spark-ts , however, looks like it's not under active development any more. I really appreciate to get your insight. Kindest regards, Mina On Wed, Sep 19, 2018 at 12:01 PM Mina Aslani wrote: > Hi, > I have a question for you. Do we have any Ti

Re: Time series forecasting

Im interested in machine learning on time series. In our environment we have lot of metric data continuously coming from agents. Data are stored in Cassandra. Is it possible to set up spark that would use machine learning on previous data and new incoming data? -- View this message in conte

Re: Time series forecasting

i guess it is not a question of spark but a question on your dataset you need to Setup think about what you wonna model and how you can shape the data in such a way spark can use it akima is a technique i know a_{t+1} = C1 * a_{t} + C2* a_{t-1} + ... + C6 * a_{t-5} spark can finde the cofficien