hello Gianluca and all Regarding to thin client, in my architecture I avoided to use thin clients; I'm using thick clients; so if python is supported only in "thin client" mode, I'd prefer to avoid it
Regarding distributed computing, I didn't see it but it seems to be interesting but something is missing me. Let's suppose I want to use djl https://djl.ai/ and its timeseries support ( https://djl.ai/extensions/timeseries/) I can use the distributed computing; as far as I understood the distributed computing allows to me to distribute computations across all my cluster nodes. Now I'm using thick clients, this means my java application is remotely connected to the apache ignite "master nodes"; in distributed computing I should execute the computation on master nodes but if I use a custom dependency (e.g. djl) how can these master remote nodes execute the computation if they don't have the libraries? Am I missing anything? Thank you Angelo Il giorno ven 5 gen 2024 alle ore 14:24 Gianluca Bonetti < [email protected]> ha scritto: > Hello Jagat > > There are Ignite thin clients for a number of languages, including Python. > For a full list of functionalities and comparison, please always refer to > the official documentation. > > https://ignite.apache.org/docs/latest/thin-clients/getting-started-with-thin-clients > > All thin clients should perform around the same in tasks such as storing > and retrieving data as they use the Apache Ignite binary protocol. > As you know performance also varies case by case, because of different > setups, configurations, and versions of software/frameworks/libraries > being used, and of course the performance of the code that you will write > yourself. > > For my specific use cases, Apache Ignite always performed extremely well. > As I don't know anything about your project, there are far too many > possible variables to be able to reduce to a yes/no answer. > The advice is to run your own benchmarks on your infrastructure to get > some meaningful figures for your specific project and infrastructure. > > Cheers > Gianluca Bonetti > > On Fri, 5 Jan 2024 at 12:40, Jagat Singh <[email protected]> wrote: > >> Hi Gianluna, >> >> Does the Python client miss any functionality or performance compared to >> Java? >> >> Thanks >> >> On Fri, 5 Jan 2024 at 15:55, Gianluca Bonetti <[email protected]> >> wrote: >> >>> Hello Angelo >>> >>> It seems to be an interesting use case for Ignite. >>> >>> However, you should consider what Ignite is, and what is not. >>> Essentially, Ignite is a distributed in-memory >>> database/cache/grid/etc... >>> It also has some distributed computing API capabilities. >>> >>> You can store data easily in Ignite, and consume data by your code >>> written in Java. >>> You can also use Python since there is a Python Ignite Client available >>> if it makes your time series analysis easier. >>> You can also use the Ignite Computing API to execute code on your >>> cluster >>> https://ignite.apache.org/docs/latest/distributed-computing/distributed-computing >>> but in this case I think Python is not supported. >>> >>> Cheers >>> Gianluca Bonetti >>> >>> On Fri, 5 Jan 2024 at 08:52, Angelo Immediata <[email protected]> >>> wrote: >>> >>>> I'm pretty new to Apache Ignite >>>> >>>> >>>> I asked this also on stackoverflow ( >>>> https://stackoverflow.com/questions/77667648/apache-ignite-time-series-forecasting) >>>> but I received no answer >>>> >>>> I need to make some forecasting analysis >>>> >>>> Basically I can collect data in Ignite in real time. Ignite will store >>>> data in its own caches >>>> >>>> Now I need to make some forecasting showing me the distribution of data >>>> in the next X months/years by starting from observed and collected data. >>>> >>>> As far as I know, this kind of forecasting can be realized by time >>>> series forecasting. In Ignite I see no time series based algorithm. Am I >>>> right? >>>> >>>> If I'm correct I may use or tensor flow or Deep Java Library. But in >>>> this case what I don't understand is: where should I use these libraries? >>>> Inside my thick client microservice or should I write an Ignite plugin in >>>> order to use the scalability feature provided by Ignite? >>>> >>>> Thank you >>>> >>>> Angelo >>>> >>>
