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Posted to user@ignite.apache.org by David Williams <le...@gmail.com> on 2019/09/06 09:50:55 UTC
ML stable and performance
I am evaluating ML framework for Java platform. I knew Ignite has ML
package.
But I like to know its stability and performance for production. Can Ignite
ML code run in distribute way?
Except its own ML package, which ml packages are best options for Ignite?
Re: ML stable and performance
Posted by Alexey Zinoviev <za...@gmail.com>.
I've started the discussion here
http://apache-ignite-developers.2346864.n4.nabble.com/Proposed-Release-2-7-7-2-7-6-ML-extra-fixed-bugs-td43537.html
пт, 13 сент. 2019 г. в 22:12, Alexey Zinoviev <za...@gmail.com>:
> The reason was that the last year there is no significant releases of
> Ignite between 2.7 and 2.8, only minor releases with long story of renaming.
> I am and another ML guys are ready in 1-2 months prepare ML module for 2.8
> or for the minor release 2.7.7 = 2.7.6 + updated ML + new fixed bugs
>
> Let's discuss it in separate thread next week
>
>
>
> пт, 13 сент. 2019 г. в 21:55, Denis Magda <dm...@apache.org>:
>
>> Alexey, I'm wondering,
>>
>> Are there any dependencies on Ignite Core that make us put off the ML
>> changes release until 2.8? I know that you do not support the idea of ML
>> as
>> a separate Ignite module but this concept would allow us to release ML as
>> frequently as we want not being blocked by Ignite core releases.
>>
>>
>> -
>> Denis
>>
>>
>> On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <za...@gmail.com>
>> wrote:
>>
>> > I could answer as one of developers of ML module.
>> > Currently is available the ML in version 2.7.5, it supports a lot of
>> > algorithms and could be used in production, but the API is not stable
>> and
>> > will be changed in 2.8
>> >
>> > The ML module will be stable since next release 2.8, also we have no
>> > performance report to compare for example with Spark ML
>> > Based on my exploration the performance of in terms of Big O notation is
>> > the same like in Spark ML (real numbers says that Ignite ML is more
>> faster
>> > than Spark ML due to Ignite in-memory nature and so on)
>> >
>> > Since 2.8 it will have good integration with TensorFlow, Spark ML,
>> XGBoost
>> > via model inference.
>> >
>> > You as a user have no ability to run, for-example scikit-learn or R
>> > packages in distributed mode over Ignite, but you could run the
>> TensorFlow,
>> > using Ignite as a distributed back-end instead of Horovod.
>> >
>> > If you have any questions, please let me know
>> >
>> >
>> >
>> > пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
>> >
>> >> David,
>> >>
>> >> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
>> >> Please, could you share more details in regards to your performance
>> >> testing
>> >> and objectives for Ignite ML overall?
>> >>
>> >> The module is ready for production and we're ready to help solve any
>> >> cornerstones.
>> >>
>> >> -
>> >> Denis
>> >>
>> >>
>> >> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com>
>> >> wrote:
>> >>
>> >> > Python is 25 times slower than Java for ML at runtimes, which I found
>> >> out
>> >> > online. But I don't know that statement is true or not. I need
>> insiders'
>> >> > opinion. Which ml other packages are best options for Ignite?
>> >> >
>> >> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com>
>> >> wrote:
>> >> >
>> >> >> Hi!
>> >> >>
>> >> >> I have never used it myself but it's been there for long time and I
>> >> >> would expect it to be stable, and yes it will run distributed, I
>> can't
>> >> >> say anything about performance as I have never used it.
>> >> >>
>> >> >> You will find a lot of more information at:
>> >> >>
>> >> >> https://apacheignite.readme.io/docs/machine-learning
>> >> >>
>> >> >> Mikael
>> >> >>
>> >> >>
>> >> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
>> >> >> >
>> >> >> >
>> >> >> > I am evaluating ML framework for Java platform. I knew Ignite has
>> ML
>> >> >> > package.
>> >> >> > But I like to know its stability and performance for production.
>> Can
>> >> >> > Ignite
>> >> >> > ML code run in distribute way?
>> >> >> >
>> >> >> > Except its own ML package, which ml packages are best options for
>> >> >> Ignite?
>> >> >>
>> >> >
>> >>
>> >
>>
>
Re: ML stable and performance
Posted by Alexey Zinoviev <za...@gmail.com>.
I've started the discussion here
http://apache-ignite-developers.2346864.n4.nabble.com/Proposed-Release-2-7-7-2-7-6-ML-extra-fixed-bugs-td43537.html
пт, 13 сент. 2019 г. в 22:12, Alexey Zinoviev <za...@gmail.com>:
> The reason was that the last year there is no significant releases of
> Ignite between 2.7 and 2.8, only minor releases with long story of renaming.
> I am and another ML guys are ready in 1-2 months prepare ML module for 2.8
> or for the minor release 2.7.7 = 2.7.6 + updated ML + new fixed bugs
>
> Let's discuss it in separate thread next week
>
>
>
> пт, 13 сент. 2019 г. в 21:55, Denis Magda <dm...@apache.org>:
>
>> Alexey, I'm wondering,
>>
>> Are there any dependencies on Ignite Core that make us put off the ML
>> changes release until 2.8? I know that you do not support the idea of ML
>> as
>> a separate Ignite module but this concept would allow us to release ML as
>> frequently as we want not being blocked by Ignite core releases.
>>
>>
>> -
>> Denis
>>
>>
>> On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <za...@gmail.com>
>> wrote:
>>
>> > I could answer as one of developers of ML module.
>> > Currently is available the ML in version 2.7.5, it supports a lot of
>> > algorithms and could be used in production, but the API is not stable
>> and
>> > will be changed in 2.8
>> >
>> > The ML module will be stable since next release 2.8, also we have no
>> > performance report to compare for example with Spark ML
>> > Based on my exploration the performance of in terms of Big O notation is
>> > the same like in Spark ML (real numbers says that Ignite ML is more
>> faster
>> > than Spark ML due to Ignite in-memory nature and so on)
>> >
>> > Since 2.8 it will have good integration with TensorFlow, Spark ML,
>> XGBoost
>> > via model inference.
>> >
>> > You as a user have no ability to run, for-example scikit-learn or R
>> > packages in distributed mode over Ignite, but you could run the
>> TensorFlow,
>> > using Ignite as a distributed back-end instead of Horovod.
>> >
>> > If you have any questions, please let me know
>> >
>> >
>> >
>> > пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
>> >
>> >> David,
>> >>
>> >> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
>> >> Please, could you share more details in regards to your performance
>> >> testing
>> >> and objectives for Ignite ML overall?
>> >>
>> >> The module is ready for production and we're ready to help solve any
>> >> cornerstones.
>> >>
>> >> -
>> >> Denis
>> >>
>> >>
>> >> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com>
>> >> wrote:
>> >>
>> >> > Python is 25 times slower than Java for ML at runtimes, which I found
>> >> out
>> >> > online. But I don't know that statement is true or not. I need
>> insiders'
>> >> > opinion. Which ml other packages are best options for Ignite?
>> >> >
>> >> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com>
>> >> wrote:
>> >> >
>> >> >> Hi!
>> >> >>
>> >> >> I have never used it myself but it's been there for long time and I
>> >> >> would expect it to be stable, and yes it will run distributed, I
>> can't
>> >> >> say anything about performance as I have never used it.
>> >> >>
>> >> >> You will find a lot of more information at:
>> >> >>
>> >> >> https://apacheignite.readme.io/docs/machine-learning
>> >> >>
>> >> >> Mikael
>> >> >>
>> >> >>
>> >> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
>> >> >> >
>> >> >> >
>> >> >> > I am evaluating ML framework for Java platform. I knew Ignite has
>> ML
>> >> >> > package.
>> >> >> > But I like to know its stability and performance for production.
>> Can
>> >> >> > Ignite
>> >> >> > ML code run in distribute way?
>> >> >> >
>> >> >> > Except its own ML package, which ml packages are best options for
>> >> >> Ignite?
>> >> >>
>> >> >
>> >>
>> >
>>
>
Re: ML stable and performance
Posted by Alexey Zinoviev <za...@gmail.com>.
The reason was that the last year there is no significant releases of
Ignite between 2.7 and 2.8, only minor releases with long story of renaming.
I am and another ML guys are ready in 1-2 months prepare ML module for 2.8
or for the minor release 2.7.7 = 2.7.6 + updated ML + new fixed bugs
Let's discuss it in separate thread next week
пт, 13 сент. 2019 г. в 21:55, Denis Magda <dm...@apache.org>:
> Alexey, I'm wondering,
>
> Are there any dependencies on Ignite Core that make us put off the ML
> changes release until 2.8? I know that you do not support the idea of ML as
> a separate Ignite module but this concept would allow us to release ML as
> frequently as we want not being blocked by Ignite core releases.
>
>
> -
> Denis
>
>
> On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <za...@gmail.com>
> wrote:
>
> > I could answer as one of developers of ML module.
> > Currently is available the ML in version 2.7.5, it supports a lot of
> > algorithms and could be used in production, but the API is not stable and
> > will be changed in 2.8
> >
> > The ML module will be stable since next release 2.8, also we have no
> > performance report to compare for example with Spark ML
> > Based on my exploration the performance of in terms of Big O notation is
> > the same like in Spark ML (real numbers says that Ignite ML is more
> faster
> > than Spark ML due to Ignite in-memory nature and so on)
> >
> > Since 2.8 it will have good integration with TensorFlow, Spark ML,
> XGBoost
> > via model inference.
> >
> > You as a user have no ability to run, for-example scikit-learn or R
> > packages in distributed mode over Ignite, but you could run the
> TensorFlow,
> > using Ignite as a distributed back-end instead of Horovod.
> >
> > If you have any questions, please let me know
> >
> >
> >
> > пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
> >
> >> David,
> >>
> >> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
> >> Please, could you share more details in regards to your performance
> >> testing
> >> and objectives for Ignite ML overall?
> >>
> >> The module is ready for production and we're ready to help solve any
> >> cornerstones.
> >>
> >> -
> >> Denis
> >>
> >>
> >> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com>
> >> wrote:
> >>
> >> > Python is 25 times slower than Java for ML at runtimes, which I found
> >> out
> >> > online. But I don't know that statement is true or not. I need
> insiders'
> >> > opinion. Which ml other packages are best options for Ignite?
> >> >
> >> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com>
> >> wrote:
> >> >
> >> >> Hi!
> >> >>
> >> >> I have never used it myself but it's been there for long time and I
> >> >> would expect it to be stable, and yes it will run distributed, I
> can't
> >> >> say anything about performance as I have never used it.
> >> >>
> >> >> You will find a lot of more information at:
> >> >>
> >> >> https://apacheignite.readme.io/docs/machine-learning
> >> >>
> >> >> Mikael
> >> >>
> >> >>
> >> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
> >> >> >
> >> >> >
> >> >> > I am evaluating ML framework for Java platform. I knew Ignite has
> ML
> >> >> > package.
> >> >> > But I like to know its stability and performance for production.
> Can
> >> >> > Ignite
> >> >> > ML code run in distribute way?
> >> >> >
> >> >> > Except its own ML package, which ml packages are best options for
> >> >> Ignite?
> >> >>
> >> >
> >>
> >
>
Re: ML stable and performance
Posted by Alexey Zinoviev <za...@gmail.com>.
The reason was that the last year there is no significant releases of
Ignite between 2.7 and 2.8, only minor releases with long story of renaming.
I am and another ML guys are ready in 1-2 months prepare ML module for 2.8
or for the minor release 2.7.7 = 2.7.6 + updated ML + new fixed bugs
Let's discuss it in separate thread next week
пт, 13 сент. 2019 г. в 21:55, Denis Magda <dm...@apache.org>:
> Alexey, I'm wondering,
>
> Are there any dependencies on Ignite Core that make us put off the ML
> changes release until 2.8? I know that you do not support the idea of ML as
> a separate Ignite module but this concept would allow us to release ML as
> frequently as we want not being blocked by Ignite core releases.
>
>
> -
> Denis
>
>
> On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <za...@gmail.com>
> wrote:
>
> > I could answer as one of developers of ML module.
> > Currently is available the ML in version 2.7.5, it supports a lot of
> > algorithms and could be used in production, but the API is not stable and
> > will be changed in 2.8
> >
> > The ML module will be stable since next release 2.8, also we have no
> > performance report to compare for example with Spark ML
> > Based on my exploration the performance of in terms of Big O notation is
> > the same like in Spark ML (real numbers says that Ignite ML is more
> faster
> > than Spark ML due to Ignite in-memory nature and so on)
> >
> > Since 2.8 it will have good integration with TensorFlow, Spark ML,
> XGBoost
> > via model inference.
> >
> > You as a user have no ability to run, for-example scikit-learn or R
> > packages in distributed mode over Ignite, but you could run the
> TensorFlow,
> > using Ignite as a distributed back-end instead of Horovod.
> >
> > If you have any questions, please let me know
> >
> >
> >
> > пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
> >
> >> David,
> >>
> >> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
> >> Please, could you share more details in regards to your performance
> >> testing
> >> and objectives for Ignite ML overall?
> >>
> >> The module is ready for production and we're ready to help solve any
> >> cornerstones.
> >>
> >> -
> >> Denis
> >>
> >>
> >> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com>
> >> wrote:
> >>
> >> > Python is 25 times slower than Java for ML at runtimes, which I found
> >> out
> >> > online. But I don't know that statement is true or not. I need
> insiders'
> >> > opinion. Which ml other packages are best options for Ignite?
> >> >
> >> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com>
> >> wrote:
> >> >
> >> >> Hi!
> >> >>
> >> >> I have never used it myself but it's been there for long time and I
> >> >> would expect it to be stable, and yes it will run distributed, I
> can't
> >> >> say anything about performance as I have never used it.
> >> >>
> >> >> You will find a lot of more information at:
> >> >>
> >> >> https://apacheignite.readme.io/docs/machine-learning
> >> >>
> >> >> Mikael
> >> >>
> >> >>
> >> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
> >> >> >
> >> >> >
> >> >> > I am evaluating ML framework for Java platform. I knew Ignite has
> ML
> >> >> > package.
> >> >> > But I like to know its stability and performance for production.
> Can
> >> >> > Ignite
> >> >> > ML code run in distribute way?
> >> >> >
> >> >> > Except its own ML package, which ml packages are best options for
> >> >> Ignite?
> >> >>
> >> >
> >>
> >
>
Re: ML stable and performance
Posted by Denis Magda <dm...@apache.org>.
Alexey, I'm wondering,
Are there any dependencies on Ignite Core that make us put off the ML
changes release until 2.8? I know that you do not support the idea of ML as
a separate Ignite module but this concept would allow us to release ML as
frequently as we want not being blocked by Ignite core releases.
-
Denis
On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <za...@gmail.com>
wrote:
> I could answer as one of developers of ML module.
> Currently is available the ML in version 2.7.5, it supports a lot of
> algorithms and could be used in production, but the API is not stable and
> will be changed in 2.8
>
> The ML module will be stable since next release 2.8, also we have no
> performance report to compare for example with Spark ML
> Based on my exploration the performance of in terms of Big O notation is
> the same like in Spark ML (real numbers says that Ignite ML is more faster
> than Spark ML due to Ignite in-memory nature and so on)
>
> Since 2.8 it will have good integration with TensorFlow, Spark ML, XGBoost
> via model inference.
>
> You as a user have no ability to run, for-example scikit-learn or R
> packages in distributed mode over Ignite, but you could run the TensorFlow,
> using Ignite as a distributed back-end instead of Horovod.
>
> If you have any questions, please let me know
>
>
>
> пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
>
>> David,
>>
>> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
>> Please, could you share more details in regards to your performance
>> testing
>> and objectives for Ignite ML overall?
>>
>> The module is ready for production and we're ready to help solve any
>> cornerstones.
>>
>> -
>> Denis
>>
>>
>> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com>
>> wrote:
>>
>> > Python is 25 times slower than Java for ML at runtimes, which I found
>> out
>> > online. But I don't know that statement is true or not. I need insiders'
>> > opinion. Which ml other packages are best options for Ignite?
>> >
>> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com>
>> wrote:
>> >
>> >> Hi!
>> >>
>> >> I have never used it myself but it's been there for long time and I
>> >> would expect it to be stable, and yes it will run distributed, I can't
>> >> say anything about performance as I have never used it.
>> >>
>> >> You will find a lot of more information at:
>> >>
>> >> https://apacheignite.readme.io/docs/machine-learning
>> >>
>> >> Mikael
>> >>
>> >>
>> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
>> >> >
>> >> >
>> >> > I am evaluating ML framework for Java platform. I knew Ignite has ML
>> >> > package.
>> >> > But I like to know its stability and performance for production. Can
>> >> > Ignite
>> >> > ML code run in distribute way?
>> >> >
>> >> > Except its own ML package, which ml packages are best options for
>> >> Ignite?
>> >>
>> >
>>
>
Re: ML stable and performance
Posted by Denis Magda <dm...@apache.org>.
Alexey, I'm wondering,
Are there any dependencies on Ignite Core that make us put off the ML
changes release until 2.8? I know that you do not support the idea of ML as
a separate Ignite module but this concept would allow us to release ML as
frequently as we want not being blocked by Ignite core releases.
-
Denis
On Fri, Sep 13, 2019 at 11:45 AM Alexey Zinoviev <za...@gmail.com>
wrote:
> I could answer as one of developers of ML module.
> Currently is available the ML in version 2.7.5, it supports a lot of
> algorithms and could be used in production, but the API is not stable and
> will be changed in 2.8
>
> The ML module will be stable since next release 2.8, also we have no
> performance report to compare for example with Spark ML
> Based on my exploration the performance of in terms of Big O notation is
> the same like in Spark ML (real numbers says that Ignite ML is more faster
> than Spark ML due to Ignite in-memory nature and so on)
>
> Since 2.8 it will have good integration with TensorFlow, Spark ML, XGBoost
> via model inference.
>
> You as a user have no ability to run, for-example scikit-learn or R
> packages in distributed mode over Ignite, but you could run the TensorFlow,
> using Ignite as a distributed back-end instead of Horovod.
>
> If you have any questions, please let me know
>
>
>
> пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
>
>> David,
>>
>> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
>> Please, could you share more details in regards to your performance
>> testing
>> and objectives for Ignite ML overall?
>>
>> The module is ready for production and we're ready to help solve any
>> cornerstones.
>>
>> -
>> Denis
>>
>>
>> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com>
>> wrote:
>>
>> > Python is 25 times slower than Java for ML at runtimes, which I found
>> out
>> > online. But I don't know that statement is true or not. I need insiders'
>> > opinion. Which ml other packages are best options for Ignite?
>> >
>> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com>
>> wrote:
>> >
>> >> Hi!
>> >>
>> >> I have never used it myself but it's been there for long time and I
>> >> would expect it to be stable, and yes it will run distributed, I can't
>> >> say anything about performance as I have never used it.
>> >>
>> >> You will find a lot of more information at:
>> >>
>> >> https://apacheignite.readme.io/docs/machine-learning
>> >>
>> >> Mikael
>> >>
>> >>
>> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
>> >> >
>> >> >
>> >> > I am evaluating ML framework for Java platform. I knew Ignite has ML
>> >> > package.
>> >> > But I like to know its stability and performance for production. Can
>> >> > Ignite
>> >> > ML code run in distribute way?
>> >> >
>> >> > Except its own ML package, which ml packages are best options for
>> >> Ignite?
>> >>
>> >
>>
>
Re: ML stable and performance
Posted by Alexey Zinoviev <za...@gmail.com>.
I could answer as one of developers of ML module.
Currently is available the ML in version 2.7.5, it supports a lot of
algorithms and could be used in production, but the API is not stable and
will be changed in 2.8
The ML module will be stable since next release 2.8, also we have no
performance report to compare for example with Spark ML
Based on my exploration the performance of in terms of Big O notation is
the same like in Spark ML (real numbers says that Ignite ML is more faster
than Spark ML due to Ignite in-memory nature and so on)
Since 2.8 it will have good integration with TensorFlow, Spark ML, XGBoost
via model inference.
You as a user have no ability to run, for-example scikit-learn or R
packages in distributed mode over Ignite, but you could run the TensorFlow,
using Ignite as a distributed back-end instead of Horovod.
If you have any questions, please let me know
пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
> David,
>
> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
> Please, could you share more details in regards to your performance testing
> and objectives for Ignite ML overall?
>
> The module is ready for production and we're ready to help solve any
> cornerstones.
>
> -
> Denis
>
>
> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com> wrote:
>
> > Python is 25 times slower than Java for ML at runtimes, which I found out
> > online. But I don't know that statement is true or not. I need insiders'
> > opinion. Which ml other packages are best options for Ignite?
> >
> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com> wrote:
> >
> >> Hi!
> >>
> >> I have never used it myself but it's been there for long time and I
> >> would expect it to be stable, and yes it will run distributed, I can't
> >> say anything about performance as I have never used it.
> >>
> >> You will find a lot of more information at:
> >>
> >> https://apacheignite.readme.io/docs/machine-learning
> >>
> >> Mikael
> >>
> >>
> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
> >> >
> >> >
> >> > I am evaluating ML framework for Java platform. I knew Ignite has ML
> >> > package.
> >> > But I like to know its stability and performance for production. Can
> >> > Ignite
> >> > ML code run in distribute way?
> >> >
> >> > Except its own ML package, which ml packages are best options for
> >> Ignite?
> >>
> >
>
Re: ML stable and performance
Posted by Alexey Zinoviev <za...@gmail.com>.
I could answer as one of developers of ML module.
Currently is available the ML in version 2.7.5, it supports a lot of
algorithms and could be used in production, but the API is not stable and
will be changed in 2.8
The ML module will be stable since next release 2.8, also we have no
performance report to compare for example with Spark ML
Based on my exploration the performance of in terms of Big O notation is
the same like in Spark ML (real numbers says that Ignite ML is more faster
than Spark ML due to Ignite in-memory nature and so on)
Since 2.8 it will have good integration with TensorFlow, Spark ML, XGBoost
via model inference.
You as a user have no ability to run, for-example scikit-learn or R
packages in distributed mode over Ignite, but you could run the TensorFlow,
using Ignite as a distributed back-end instead of Horovod.
If you have any questions, please let me know
пт, 13 сент. 2019 г. в 21:28, Denis Magda <dm...@apache.org>:
> David,
>
> Let me loop in Ignite dev list that has Ignite ML experts subscribed.
> Please, could you share more details in regards to your performance testing
> and objectives for Ignite ML overall?
>
> The module is ready for production and we're ready to help solve any
> cornerstones.
>
> -
> Denis
>
>
> On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com> wrote:
>
> > Python is 25 times slower than Java for ML at runtimes, which I found out
> > online. But I don't know that statement is true or not. I need insiders'
> > opinion. Which ml other packages are best options for Ignite?
> >
> > On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com> wrote:
> >
> >> Hi!
> >>
> >> I have never used it myself but it's been there for long time and I
> >> would expect it to be stable, and yes it will run distributed, I can't
> >> say anything about performance as I have never used it.
> >>
> >> You will find a lot of more information at:
> >>
> >> https://apacheignite.readme.io/docs/machine-learning
> >>
> >> Mikael
> >>
> >>
> >> Den 2019-09-06 kl. 11:50, skrev David Williams:
> >> >
> >> >
> >> > I am evaluating ML framework for Java platform. I knew Ignite has ML
> >> > package.
> >> > But I like to know its stability and performance for production. Can
> >> > Ignite
> >> > ML code run in distribute way?
> >> >
> >> > Except its own ML package, which ml packages are best options for
> >> Ignite?
> >>
> >
>
Re: ML stable and performance
Posted by Denis Magda <dm...@apache.org>.
David,
Let me loop in Ignite dev list that has Ignite ML experts subscribed.
Please, could you share more details in regards to your performance testing
and objectives for Ignite ML overall?
The module is ready for production and we're ready to help solve any
cornerstones.
-
Denis
On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com> wrote:
> Python is 25 times slower than Java for ML at runtimes, which I found out
> online. But I don't know that statement is true or not. I need insiders'
> opinion. Which ml other packages are best options for Ignite?
>
> On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com> wrote:
>
>> Hi!
>>
>> I have never used it myself but it's been there for long time and I
>> would expect it to be stable, and yes it will run distributed, I can't
>> say anything about performance as I have never used it.
>>
>> You will find a lot of more information at:
>>
>> https://apacheignite.readme.io/docs/machine-learning
>>
>> Mikael
>>
>>
>> Den 2019-09-06 kl. 11:50, skrev David Williams:
>> >
>> >
>> > I am evaluating ML framework for Java platform. I knew Ignite has ML
>> > package.
>> > But I like to know its stability and performance for production. Can
>> > Ignite
>> > ML code run in distribute way?
>> >
>> > Except its own ML package, which ml packages are best options for
>> Ignite?
>>
>
Re: ML stable and performance
Posted by Denis Magda <dm...@apache.org>.
David,
Let me loop in Ignite dev list that has Ignite ML experts subscribed.
Please, could you share more details in regards to your performance testing
and objectives for Ignite ML overall?
The module is ready for production and we're ready to help solve any
cornerstones.
-
Denis
On Fri, Sep 6, 2019 at 4:50 AM David Williams <le...@gmail.com> wrote:
> Python is 25 times slower than Java for ML at runtimes, which I found out
> online. But I don't know that statement is true or not. I need insiders'
> opinion. Which ml other packages are best options for Ignite?
>
> On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com> wrote:
>
>> Hi!
>>
>> I have never used it myself but it's been there for long time and I
>> would expect it to be stable, and yes it will run distributed, I can't
>> say anything about performance as I have never used it.
>>
>> You will find a lot of more information at:
>>
>> https://apacheignite.readme.io/docs/machine-learning
>>
>> Mikael
>>
>>
>> Den 2019-09-06 kl. 11:50, skrev David Williams:
>> >
>> >
>> > I am evaluating ML framework for Java platform. I knew Ignite has ML
>> > package.
>> > But I like to know its stability and performance for production. Can
>> > Ignite
>> > ML code run in distribute way?
>> >
>> > Except its own ML package, which ml packages are best options for
>> Ignite?
>>
>
Re: ML stable and performance
Posted by David Williams <le...@gmail.com>.
Python is 25 times slower than Java for ML at runtimes, which I found out
online. But I don't know that statement is true or not. I need insiders'
opinion. Which ml other packages are best options for Ignite?
On Fri, Sep 6, 2019 at 7:28 PM Mikael <mi...@telia.com> wrote:
> Hi!
>
> I have never used it myself but it's been there for long time and I
> would expect it to be stable, and yes it will run distributed, I can't
> say anything about performance as I have never used it.
>
> You will find a lot of more information at:
>
> https://apacheignite.readme.io/docs/machine-learning
>
> Mikael
>
>
> Den 2019-09-06 kl. 11:50, skrev David Williams:
> >
> >
> > I am evaluating ML framework for Java platform. I knew Ignite has ML
> > package.
> > But I like to know its stability and performance for production. Can
> > Ignite
> > ML code run in distribute way?
> >
> > Except its own ML package, which ml packages are best options for Ignite?
>
Re: ML stable and performance
Posted by Mikael <mi...@telia.com>.
Hi!
I have never used it myself but it's been there for long time and I
would expect it to be stable, and yes it will run distributed, I can't
say anything about performance as I have never used it.
You will find a lot of more information at:
https://apacheignite.readme.io/docs/machine-learning
Mikael
Den 2019-09-06 kl. 11:50, skrev David Williams:
>
>
> I am evaluating ML framework for Java platform. I knew Ignite has ML
> package.
> But I like to know its stability and performance for production. Can
> Ignite
> ML code run in distribute way?
>
> Except its own ML package, which ml packages are best options for Ignite?