[IGNITE-5717] improvements of MemoryPolicy default size

[Sergey Chugunov]

Folks,

I would like to get back to the question about MemoryPolicy maxMemory
defaults.

Although MemoryPolicy may be configured with initial and maxMemory
settings, when persistence is used MemoryPolicy always allocates maxMemory
size for performance reasons.

As default size of maxMemory is 80% of physical memory it causes OOME
exceptions of 32 bit platforms (either on OS or JVM level) and hurts
performance in setups when multiple Ignite nodes are started on the same
physical server.

I suggest to rethink these defaults and switch to other options:

   - Check whether platform is 32 or 64 bits and adapt defaults. In this
   case we still need to address the issue with multiple nodes on one machine
   even on 64 bit systems.

   - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
   availableMemory, 1Gb).
   This option allows us to solve all issues with starting on 32 bit
   platforms and reduce instability with multiple nodes on the same machine.


Thoughts and/or other options?

Thanks,
Sergey.

[Vladimir Ozerov]

+1

80% of RAM is way too aggressive. With this value virtually every user will
have problems with OOME or excessive swapping during development. I would
set maxMemory to some relatively small value, may be even less that 1Gb to
let Ignite run smoothly on developer's laptops, and print a performance
suggestion to increase it in production.

On Tue, Aug 1, 2017 at 12:19 PM, Sergey Chugunov <[hidden email]>
wrote:

> Folks,
>
> I would like to get back to the question about MemoryPolicy maxMemory
> defaults.
>
> Although MemoryPolicy may be configured with initial and maxMemory
> settings, when persistence is used MemoryPolicy always allocates maxMemory
> size for performance reasons.
>
> As default size of maxMemory is 80% of physical memory it causes OOME
> exceptions of 32 bit platforms (either on OS or JVM level) and hurts
> performance in setups when multiple Ignite nodes are started on the same
> physical server.
>
> I suggest to rethink these defaults and switch to other options:
>
>    - Check whether platform is 32 or 64 bits and adapt defaults. In this
>    case we still need to address the issue with multiple nodes on one
> machine
>    even on 64 bit systems.
>
>    - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
>    availableMemory, 1Gb).
>    This option allows us to solve all issues with starting on 32 bit
>    platforms and reduce instability with multiple nodes on the same
> machine.
>
>
> Thoughts and/or other options?
>
> Thanks,
> Sergey.
>

[Dmitriy Pavlov]

+1 to Sergey,
I think OOME may confuse user and and may spoil the user's impression at
first check of Apache Ignite.

вт, 1 авг. 2017 г. в 12:36, Vladimir Ozerov <[hidden email]>:

> +1
>
> 80% of RAM is way too aggressive. With this value virtually every user will
> have problems with OOME or excessive swapping during development. I would
> set maxMemory to some relatively small value, may be even less that 1Gb to
> let Ignite run smoothly on developer's laptops, and print a performance
> suggestion to increase it in production.
>
> On Tue, Aug 1, 2017 at 12:19 PM, Sergey Chugunov <
> [hidden email]>
> wrote:
>
> > Folks,
> >
> > I would like to get back to the question about MemoryPolicy maxMemory
> > defaults.
> >
> > Although MemoryPolicy may be configured with initial and maxMemory
> > settings, when persistence is used MemoryPolicy always allocates
> maxMemory
> > size for performance reasons.
> >
> > As default size of maxMemory is 80% of physical memory it causes OOME
> > exceptions of 32 bit platforms (either on OS or JVM level) and hurts
> > performance in setups when multiple Ignite nodes are started on the same
> > physical server.
> >
> > I suggest to rethink these defaults and switch to other options:
> >
> >    - Check whether platform is 32 or 64 bits and adapt defaults. In this
> >    case we still need to address the issue with multiple nodes on one
> > machine
> >    even on 64 bit systems.
> >
> >    - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
> >    availableMemory, 1Gb).
> >    This option allows us to solve all issues with starting on 32 bit
> >    platforms and reduce instability with multiple nodes on the same
> > machine.
> >
> >
> > Thoughts and/or other options?
> >
> > Thanks,
> > Sergey.
> >
>

[dsetrakyan]

I prefer option #1.

⁣D.​

On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <[hidden email]> wrote:

>Folks,
>
>I would like to get back to the question about MemoryPolicy maxMemory
>defaults.
>
>Although MemoryPolicy may be configured with initial and maxMemory
>settings, when persistence is used MemoryPolicy always allocates
>maxMemory
>size for performance reasons.
>
>As default size of maxMemory is 80% of physical memory it causes OOME
>exceptions of 32 bit platforms (either on OS or JVM level) and hurts
>performance in setups when multiple Ignite nodes are started on the
>same
>physical server.
>
>I suggest to rethink these defaults and switch to other options:
>
>  - Check whether platform is 32 or 64 bits and adapt defaults. In this
>case we still need to address the issue with multiple nodes on one
>machine
>   even on 64 bit systems.
>
>   - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
>   availableMemory, 1Gb).
>   This option allows us to solve all issues with starting on 32 bit
>platforms and reduce instability with multiple nodes on the same
>machine.
>
>
>Thoughts and/or other options?
>
>Thanks,
>Sergey.

[dmagda]

My vote goes for option #1 too. I don’t think that 80% is too aggressive to bring it down.

IGNITE-5717 was created to fix the issue of the 80% RAM allocation on 64 bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of any other complaints in regards the default allocation size.

—
Denis
 

> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
>
> I prefer option #1.
>
> ⁣D.​
>
> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <[hidden email]> wrote:
>> Folks,
>>
>> I would like to get back to the question about MemoryPolicy maxMemory
>> defaults.
>>
>> Although MemoryPolicy may be configured with initial and maxMemory
>> settings, when persistence is used MemoryPolicy always allocates
>> maxMemory
>> size for performance reasons.
>>
>> As default size of maxMemory is 80% of physical memory it causes OOME
>> exceptions of 32 bit platforms (either on OS or JVM level) and hurts
>> performance in setups when multiple Ignite nodes are started on the
>> same
>> physical server.
>>
>> I suggest to rethink these defaults and switch to other options:
>>
>> - Check whether platform is 32 or 64 bits and adapt defaults. In this
>> case we still need to address the issue with multiple nodes on one
>> machine
>>  even on 64 bit systems.
>>
>>  - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
>>  availableMemory, 1Gb).
>>  This option allows us to solve all issues with starting on 32 bit
>> platforms and reduce instability with multiple nodes on the same
>> machine.
>>
>>
>> Thoughts and/or other options?
>>
>> Thanks,
>> Sergey.

[Vladimir Ozerov]

Denis,
No doubts you haven't heard about it - AI 2.1 with persistence, when 80% of
RAM is allocated right away, was released several days ago. How do you
think, how many users tried it already?

Guys,
Do you really think allocating 80% of available RAM is a normal thing? Take
your laptop and check how many available RAM you have right now. Do you fit
to remaining 20%? If not, then running AI with persistence with all
defaults will bring your machine down. This is insane. We shold allocate no
more than 1Gb, so that user can play with it without any problems.

On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]> wrote:

> My vote goes for option #1 too. I don’t think that 80% is too aggressive
> to bring it down.
>
> IGNITE-5717 was created to fix the issue of the 80% RAM allocation on 64
> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of any
> other complaints in regards the default allocation size.
>
> —
> Denis
>
> > On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> >
> > I prefer option #1.
> >
> > ⁣D.​
> >
> > On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> [hidden email]> wrote:
> >> Folks,
> >>
> >> I would like to get back to the question about MemoryPolicy maxMemory
> >> defaults.
> >>
> >> Although MemoryPolicy may be configured with initial and maxMemory
> >> settings, when persistence is used MemoryPolicy always allocates
> >> maxMemory
> >> size for performance reasons.
> >>
> >> As default size of maxMemory is 80% of physical memory it causes OOME
> >> exceptions of 32 bit platforms (either on OS or JVM level) and hurts
> >> performance in setups when multiple Ignite nodes are started on the
> >> same
> >> physical server.
> >>
> >> I suggest to rethink these defaults and switch to other options:
> >>
> >> - Check whether platform is 32 or 64 bits and adapt defaults. In this
> >> case we still need to address the issue with multiple nodes on one
> >> machine
> >>  even on 64 bit systems.
> >>
> >>  - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
> >>  availableMemory, 1Gb).
> >>  This option allows us to solve all issues with starting on 32 bit
> >> platforms and reduce instability with multiple nodes on the same
> >> machine.
> >>
> >>
> >> Thoughts and/or other options?
> >>
> >> Thanks,
> >> Sergey.
>
>

[dmagda]

Vladimir,

80% allocation approach was implemented in AI 2.0. I personally explained users on the forums its behavior.

Actually, dynamic vs static memory allocation scenarios were analyzed and discussed long time ago and eventually we decided to go for with the former:
http://apache-ignite-developers.2346864.n4.nabble.com/Page-Memory-behavior-with-default-memory-policy-td16716.html

I don’t see anything harmful with the dynamic allocation. Operating systems are sophisticated enough to leverage from swapping when there are to many processes running that complete for RAM. Never had any issue with this on my local laptop.

There will be even more benefits for production scenarios when a server has a plenty of RAM available and not that many applications running. If to stick to the static allocation approach it will require to set a specific value all the time depending on a hardware. This is what we wanted to avoid.

—
Denis

> On Aug 1, 2017, at 2:03 PM, Vladimir Ozerov <[hidden email]> wrote:
>
> Denis,
> No doubts you haven't heard about it - AI 2.1 with persistence, when 80% of
> RAM is allocated right away, was released several days ago. How do you
> think, how many users tried it already?
>
> Guys,
> Do you really think allocating 80% of available RAM is a normal thing? Take
> your laptop and check how many available RAM you have right now. Do you fit
> to remaining 20%? If not, then running AI with persistence with all
> defaults will bring your machine down. This is insane. We shold allocate no
> more than 1Gb, so that user can play with it without any problems.
>
> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]> wrote:
>
>> My vote goes for option #1 too. I don’t think that 80% is too aggressive
>> to bring it down.
>>
>> IGNITE-5717 was created to fix the issue of the 80% RAM allocation on 64
>> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of any
>> other complaints in regards the default allocation size.
>>
>> —
>> Denis
>>
>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
>>>
>>> I prefer option #1.
>>>
>>> ⁣D.​
>>>
>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
>> [hidden email]> wrote:
>>>> Folks,
>>>>
>>>> I would like to get back to the question about MemoryPolicy maxMemory
>>>> defaults.
>>>>
>>>> Although MemoryPolicy may be configured with initial and maxMemory
>>>> settings, when persistence is used MemoryPolicy always allocates
>>>> maxMemory
>>>> size for performance reasons.
>>>>
>>>> As default size of maxMemory is 80% of physical memory it causes OOME
>>>> exceptions of 32 bit platforms (either on OS or JVM level) and hurts
>>>> performance in setups when multiple Ignite nodes are started on the
>>>> same
>>>> physical server.
>>>>
>>>> I suggest to rethink these defaults and switch to other options:
>>>>
>>>> - Check whether platform is 32 or 64 bits and adapt defaults. In this
>>>> case we still need to address the issue with multiple nodes on one
>>>> machine
>>>> even on 64 bit systems.
>>>>
>>>> - Lower defaults for maxMemory and allocate, for instance, max(0.3 *
>>>> availableMemory, 1Gb).
>>>> This option allows us to solve all issues with starting on 32 bit
>>>> platforms and reduce instability with multiple nodes on the same
>>>> machine.
>>>>
>>>>
>>>> Thoughts and/or other options?
>>>>
>>>> Thanks,
>>>> Sergey.
>>
>>

[dsetrakyan]

Vova, 1GB seems a bit too small for me, and frankly i do not want t o guess. Why not allocate in increments automatically?

⁣D.​

On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <[hidden email]> wrote:

>Denis,
>No doubts you haven't heard about it - AI 2.1 with persistence, when
>80% of
>RAM is allocated right away, was released several days ago. How do you
>think, how many users tried it already?
>
>Guys,
>Do you really think allocating 80% of available RAM is a normal thing?
>Take
>your laptop and check how many available RAM you have right now. Do you
>fit
>to remaining 20%? If not, then running AI with persistence with all
>defaults will bring your machine down. This is insane. We shold
>allocate no
>more than 1Gb, so that user can play with it without any problems.
>
>On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]> wrote:
>
>> My vote goes for option #1 too. I don’t think that 80% is too
>aggressive
>> to bring it down.
>>
>> IGNITE-5717 was created to fix the issue of the 80% RAM allocation on
>64
>> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of
>any
>> other complaints in regards the default allocation size.
>>
>> —
>> Denis
>>
>> > On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
>> >
>> > I prefer option #1.
>> >
>> > ⁣D.​
>> >
>> > On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
>> [hidden email]> wrote:
>> >> Folks,
>> >>
>> >> I would like to get back to the question about MemoryPolicy
>maxMemory
>> >> defaults.
>> >>
>> >> Although MemoryPolicy may be configured with initial and maxMemory
>> >> settings, when persistence is used MemoryPolicy always allocates
>> >> maxMemory
>> >> size for performance reasons.
>> >>
>> >> As default size of maxMemory is 80% of physical memory it causes
>OOME
>> >> exceptions of 32 bit platforms (either on OS or JVM level) and
>hurts
>> >> performance in setups when multiple Ignite nodes are started on
>the
>> >> same
>> >> physical server.
>> >>
>> >> I suggest to rethink these defaults and switch to other options:
>> >>
>> >> - Check whether platform is 32 or 64 bits and adapt defaults. In
>this
>> >> case we still need to address the issue with multiple nodes on one
>> >> machine
>> >>  even on 64 bit systems.
>> >>
>> >>  - Lower defaults for maxMemory and allocate, for instance,
>max(0.3 *
>> >>  availableMemory, 1Gb).
>> >>  This option allows us to solve all issues with starting on 32 bit
>> >> platforms and reduce instability with multiple nodes on the same
>> >> machine.
>> >>
>> >>
>> >> Thoughts and/or other options?
>> >>
>> >> Thanks,
>> >> Sergey.
>>
>>

[dmagda]

> Why not allocate in increments automatically?

This is exactly how the allocation works right now. The memory will grow incrementally until the max size is reached (80% of RAM by default).

—
Denis

> On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
>
> Vova, 1GB seems a bit too small for me, and frankly i do not want t o guess. Why not allocate in increments automatically?
>
> ⁣D.​
>
> On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <[hidden email]> wrote:
>> Denis,
>> No doubts you haven't heard about it - AI 2.1 with persistence, when
>> 80% of
>> RAM is allocated right away, was released several days ago. How do you
>> think, how many users tried it already?
>>
>> Guys,
>> Do you really think allocating 80% of available RAM is a normal thing?
>> Take
>> your laptop and check how many available RAM you have right now. Do you
>> fit
>> to remaining 20%? If not, then running AI with persistence with all
>> defaults will bring your machine down. This is insane. We shold
>> allocate no
>> more than 1Gb, so that user can play with it without any problems.
>>
>> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]> wrote:
>>
>>> My vote goes for option #1 too. I don’t think that 80% is too
>> aggressive
>>> to bring it down.
>>>
>>> IGNITE-5717 was created to fix the issue of the 80% RAM allocation on
>> 64
>>> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of
>> any
>>> other complaints in regards the default allocation size.
>>>
>>> —
>>> Denis
>>>
>>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
>>>>
>>>> I prefer option #1.
>>>>
>>>> ⁣D.​
>>>>
>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
>>> [hidden email]> wrote:
>>>>> Folks,
>>>>>
>>>>> I would like to get back to the question about MemoryPolicy
>> maxMemory
>>>>> defaults.
>>>>>
>>>>> Although MemoryPolicy may be configured with initial and maxMemory
>>>>> settings, when persistence is used MemoryPolicy always allocates
>>>>> maxMemory
>>>>> size for performance reasons.
>>>>>
>>>>> As default size of maxMemory is 80% of physical memory it causes
>> OOME
>>>>> exceptions of 32 bit platforms (either on OS or JVM level) and
>> hurts
>>>>> performance in setups when multiple Ignite nodes are started on
>> the
>>>>> same
>>>>> physical server.
>>>>>
>>>>> I suggest to rethink these defaults and switch to other options:
>>>>>
>>>>> - Check whether platform is 32 or 64 bits and adapt defaults. In
>> this
>>>>> case we still need to address the issue with multiple nodes on one
>>>>> machine
>>>>> even on 64 bit systems.
>>>>>
>>>>> - Lower defaults for maxMemory and allocate, for instance,
>> max(0.3 *
>>>>> availableMemory, 1Gb).
>>>>> This option allows us to solve all issues with starting on 32 bit
>>>>> platforms and reduce instability with multiple nodes on the same
>>>>> machine.
>>>>>
>>>>>
>>>>> Thoughts and/or other options?
>>>>>
>>>>> Thanks,
>>>>> Sergey.
>>>
>>>

[Vladimir Ozerov]

Please see original Sergey's message - when persistence is enabled, memory
is not allocated incrementally, maxSize is used.

But this is a problem even for in-memory case. Consider that I wanted to
load several gigs of data as an experiment on my laptop - frequent
scenario. First several seconds it works fine. Then it starts swapping and
machine becomes unresponsive.

Default settings must allow for normal work on developer's environment.

ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:

> > Why not allocate in increments automatically?
>
> This is exactly how the allocation works right now. The memory will grow
> incrementally until the max size is reached (80% of RAM by default).
>
> —
> Denis
>
> > On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> >
> > Vova, 1GB seems a bit too small for me, and frankly i do not want t o
> guess. Why not allocate in increments automatically?
> >
> > ⁣D.​
> >
> > On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> [hidden email]> wrote:
> >> Denis,
> >> No doubts you haven't heard about it - AI 2.1 with persistence, when
> >> 80% of
> >> RAM is allocated right away, was released several days ago. How do you
> >> think, how many users tried it already?
> >>
> >> Guys,
> >> Do you really think allocating 80% of available RAM is a normal thing?
> >> Take
> >> your laptop and check how many available RAM you have right now. Do you
> >> fit
> >> to remaining 20%? If not, then running AI with persistence with all
> >> defaults will bring your machine down. This is insane. We shold
> >> allocate no
> >> more than 1Gb, so that user can play with it without any problems.
> >>
> >> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]> wrote:
> >>
> >>> My vote goes for option #1 too. I don’t think that 80% is too
> >> aggressive
> >>> to bring it down.
> >>>
> >>> IGNITE-5717 was created to fix the issue of the 80% RAM allocation on
> >> 64
> >>> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of
> >> any
> >>> other complaints in regards the default allocation size.
> >>>
> >>> —
> >>> Denis
> >>>
> >>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> >>>>
> >>>> I prefer option #1.
> >>>>
> >>>> ⁣D.​
> >>>>
> >>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> >>> [hidden email]> wrote:
> >>>>> Folks,
> >>>>>
> >>>>> I would like to get back to the question about MemoryPolicy
> >> maxMemory
> >>>>> defaults.
> >>>>>
> >>>>> Although MemoryPolicy may be configured with initial and maxMemory
> >>>>> settings, when persistence is used MemoryPolicy always allocates
> >>>>> maxMemory
> >>>>> size for performance reasons.
> >>>>>
> >>>>> As default size of maxMemory is 80% of physical memory it causes
> >> OOME
> >>>>> exceptions of 32 bit platforms (either on OS or JVM level) and
> >> hurts
> >>>>> performance in setups when multiple Ignite nodes are started on
> >> the
> >>>>> same
> >>>>> physical server.
> >>>>>
> >>>>> I suggest to rethink these defaults and switch to other options:
> >>>>>
> >>>>> - Check whether platform is 32 or 64 bits and adapt defaults. In
> >> this
> >>>>> case we still need to address the issue with multiple nodes on one
> >>>>> machine
> >>>>> even on 64 bit systems.
> >>>>>
> >>>>> - Lower defaults for maxMemory and allocate, for instance,
> >> max(0.3 *
> >>>>> availableMemory, 1Gb).
> >>>>> This option allows us to solve all issues with starting on 32 bit
> >>>>> platforms and reduce instability with multiple nodes on the same
> >>>>> machine.
> >>>>>
> >>>>>
> >>>>> Thoughts and/or other options?
> >>>>>
> >>>>> Thanks,
> >>>>> Sergey.
> >>>
> >>>
>
>

[dsetrakyan]

On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]>
wrote:

> Please see original Sergey's message - when persistence is enabled, memory
> is not allocated incrementally, maxSize is used.
>

Why?


> Default settings must allow for normal work on developer's environment.
>

Agree, but why not in increments?

>
> ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
>
> > > Why not allocate in increments automatically?
> >
> > This is exactly how the allocation works right now. The memory will grow
> > incrementally until the max size is reached (80% of RAM by default).
> >
> > —
> > Denis
> >
> > > On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> > >
> > > Vova, 1GB seems a bit too small for me, and frankly i do not want t o
> > guess. Why not allocate in increments automatically?
> > >
> > > ⁣D.​
> > >
> > > On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> > [hidden email]> wrote:
> > >> Denis,
> > >> No doubts you haven't heard about it - AI 2.1 with persistence, when
> > >> 80% of
> > >> RAM is allocated right away, was released several days ago. How do you
> > >> think, how many users tried it already?
> > >>
> > >> Guys,
> > >> Do you really think allocating 80% of available RAM is a normal thing?
> > >> Take
> > >> your laptop and check how many available RAM you have right now. Do
> you
> > >> fit
> > >> to remaining 20%? If not, then running AI with persistence with all
> > >> defaults will bring your machine down. This is insane. We shold
> > >> allocate no
> > >> more than 1Gb, so that user can play with it without any problems.
> > >>
> > >> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]>
> wrote:
> > >>
> > >>> My vote goes for option #1 too. I don’t think that 80% is too
> > >> aggressive
> > >>> to bring it down.
> > >>>
> > >>> IGNITE-5717 was created to fix the issue of the 80% RAM allocation on
> > >> 64
> > >>> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard of
> > >> any
> > >>> other complaints in regards the default allocation size.
> > >>>
> > >>> —
> > >>> Denis
> > >>>
> > >>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> > >>>>
> > >>>> I prefer option #1.
> > >>>>
> > >>>> ⁣D.​
> > >>>>
> > >>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> > >>> [hidden email]> wrote:
> > >>>>> Folks,
> > >>>>>
> > >>>>> I would like to get back to the question about MemoryPolicy
> > >> maxMemory
> > >>>>> defaults.
> > >>>>>
> > >>>>> Although MemoryPolicy may be configured with initial and maxMemory
> > >>>>> settings, when persistence is used MemoryPolicy always allocates
> > >>>>> maxMemory
> > >>>>> size for performance reasons.
> > >>>>>
> > >>>>> As default size of maxMemory is 80% of physical memory it causes
> > >> OOME
> > >>>>> exceptions of 32 bit platforms (either on OS or JVM level) and
> > >> hurts
> > >>>>> performance in setups when multiple Ignite nodes are started on
> > >> the
> > >>>>> same
> > >>>>> physical server.
> > >>>>>
> > >>>>> I suggest to rethink these defaults and switch to other options:
> > >>>>>
> > >>>>> - Check whether platform is 32 or 64 bits and adapt defaults. In
> > >> this
> > >>>>> case we still need to address the issue with multiple nodes on one
> > >>>>> machine
> > >>>>> even on 64 bit systems.
> > >>>>>
> > >>>>> - Lower defaults for maxMemory and allocate, for instance,
> > >> max(0.3 *
> > >>>>> availableMemory, 1Gb).
> > >>>>> This option allows us to solve all issues with starting on 32 bit
> > >>>>> platforms and reduce instability with multiple nodes on the same
> > >>>>> machine.
> > >>>>>
> > >>>>>
> > >>>>> Thoughts and/or other options?
> > >>>>>
> > >>>>> Thanks,
> > >>>>> Sergey.
> > >>>
> > >>>
> >
> >
>

[Vladimir Ozerov]

Dima,

Probably folks who worked closely with storage know why. However, even
increments will not help us. Most developers work on laptops. Common laptop
has 8-16 Gb RAM today. OS and working programs typically consume about a
half. So, for example, I have 8Gb total, 4Gb consumed, 4Gb free. And Ignite
will try to allocate up to 6.5Gb. Even if it is done incrementally, once I
tried to upload more than 4Gb of data, my laptop will hang silently, and
tomorrow I would tell my fellow engineers "Tried Ignite, it hanged, so I
have to reboot".

The very problem is that before being started once on production
environment, Ignite will typically be started hundred times on developer's
environment. I think that default should be ~10% of total RAM.

On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <[hidden email]>
wrote:

> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]>
> wrote:
>
> > Please see original Sergey's message - when persistence is enabled,
> memory
> > is not allocated incrementally, maxSize is used.
> >
>
> Why?
>
>
> > Default settings must allow for normal work on developer's environment.
> >
>
> Agree, but why not in increments?
>
>
> >
> > ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> >
> > > > Why not allocate in increments automatically?
> > >
> > > This is exactly how the allocation works right now. The memory will
> grow
> > > incrementally until the max size is reached (80% of RAM by default).
> > >
> > > —
> > > Denis
> > >
> > > > On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> > > >
> > > > Vova, 1GB seems a bit too small for me, and frankly i do not want t o
> > > guess. Why not allocate in increments automatically?
> > > >
> > > > ⁣D.​
> > > >
> > > > On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> > > [hidden email]> wrote:
> > > >> Denis,
> > > >> No doubts you haven't heard about it - AI 2.1 with persistence, when
> > > >> 80% of
> > > >> RAM is allocated right away, was released several days ago. How do
> you
> > > >> think, how many users tried it already?
> > > >>
> > > >> Guys,
> > > >> Do you really think allocating 80% of available RAM is a normal
> thing?
> > > >> Take
> > > >> your laptop and check how many available RAM you have right now. Do
> > you
> > > >> fit
> > > >> to remaining 20%? If not, then running AI with persistence with all
> > > >> defaults will bring your machine down. This is insane. We shold
> > > >> allocate no
> > > >> more than 1Gb, so that user can play with it without any problems.
> > > >>
> > > >> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]>
> > wrote:
> > > >>
> > > >>> My vote goes for option #1 too. I don’t think that 80% is too
> > > >> aggressive
> > > >>> to bring it down.
> > > >>>
> > > >>> IGNITE-5717 was created to fix the issue of the 80% RAM allocation
> on
> > > >> 64
> > > >>> bit systems when Ignite works on top of 32 bit JVM. I’ve not heard
> of
> > > >> any
> > > >>> other complaints in regards the default allocation size.
> > > >>>
> > > >>> —
> > > >>> Denis
> > > >>>
> > > >>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> > > >>>>
> > > >>>> I prefer option #1.
> > > >>>>
> > > >>>> ⁣D.​
> > > >>>>
> > > >>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> > > >>> [hidden email]> wrote:
> > > >>>>> Folks,
> > > >>>>>
> > > >>>>> I would like to get back to the question about MemoryPolicy
> > > >> maxMemory
> > > >>>>> defaults.
> > > >>>>>
> > > >>>>> Although MemoryPolicy may be configured with initial and
> maxMemory
> > > >>>>> settings, when persistence is used MemoryPolicy always allocates
> > > >>>>> maxMemory
> > > >>>>> size for performance reasons.
> > > >>>>>
> > > >>>>> As default size of maxMemory is 80% of physical memory it causes
> > > >> OOME
> > > >>>>> exceptions of 32 bit platforms (either on OS or JVM level) and
> > > >> hurts
> > > >>>>> performance in setups when multiple Ignite nodes are started on
> > > >> the
> > > >>>>> same
> > > >>>>> physical server.
> > > >>>>>
> > > >>>>> I suggest to rethink these defaults and switch to other options:
> > > >>>>>
> > > >>>>> - Check whether platform is 32 or 64 bits and adapt defaults. In
> > > >> this
> > > >>>>> case we still need to address the issue with multiple nodes on
> one
> > > >>>>> machine
> > > >>>>> even on 64 bit systems.
> > > >>>>>
> > > >>>>> - Lower defaults for maxMemory and allocate, for instance,
> > > >> max(0.3 *
> > > >>>>> availableMemory, 1Gb).
> > > >>>>> This option allows us to solve all issues with starting on 32 bit
> > > >>>>> platforms and reduce instability with multiple nodes on the same
> > > >>>>> machine.
> > > >>>>>
> > > >>>>>
> > > >>>>> Thoughts and/or other options?
> > > >>>>>
> > > >>>>> Thanks,
> > > >>>>> Sergey.
> > > >>>
> > > >>>
> > >
> > >
> >
>

[dsetrakyan]

On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]>
wrote:

> Dima,
>
> Probably folks who worked closely with storage know why.
>

Without knowing why, how can we make a decision?

Alexey Goncharuk, was it you who made the decision about not using
increments? Do know remember what was the reason?


>
> The very problem is that before being started once on production
> environment, Ignite will typically be started hundred times on developer's
> environment. I think that default should be ~10% of total RAM.
>

Why not 80% of *free *RAM?

>
> On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <[hidden email]>
> wrote:
>
> > On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]>
> > wrote:
> >
> > > Please see original Sergey's message - when persistence is enabled,
> > memory
> > > is not allocated incrementally, maxSize is used.
> > >
> >
> > Why?
> >
> >
> > > Default settings must allow for normal work on developer's environment.
> > >
> >
> > Agree, but why not in increments?
> >
> >
> > >
> > > ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> > >
> > > > > Why not allocate in increments automatically?
> > > >
> > > > This is exactly how the allocation works right now. The memory will
> > grow
> > > > incrementally until the max size is reached (80% of RAM by default).
> > > >
> > > > —
> > > > Denis
> > > >
> > > > > On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> > > > >
> > > > > Vova, 1GB seems a bit too small for me, and frankly i do not want
> t o
> > > > guess. Why not allocate in increments automatically?
> > > > >
> > > > > ⁣D.​
> > > > >
> > > > > On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> > > > [hidden email]> wrote:
> > > > >> Denis,
> > > > >> No doubts you haven't heard about it - AI 2.1 with persistence,
> when
> > > > >> 80% of
> > > > >> RAM is allocated right away, was released several days ago. How do
> > you
> > > > >> think, how many users tried it already?
> > > > >>
> > > > >> Guys,
> > > > >> Do you really think allocating 80% of available RAM is a normal
> > thing?
> > > > >> Take
> > > > >> your laptop and check how many available RAM you have right now.
> Do
> > > you
> > > > >> fit
> > > > >> to remaining 20%? If not, then running AI with persistence with
> all
> > > > >> defaults will bring your machine down. This is insane. We shold
> > > > >> allocate no
> > > > >> more than 1Gb, so that user can play with it without any problems.
> > > > >>
> > > > >> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]>
> > > wrote:
> > > > >>
> > > > >>> My vote goes for option #1 too. I don’t think that 80% is too
> > > > >> aggressive
> > > > >>> to bring it down.
> > > > >>>
> > > > >>> IGNITE-5717 was created to fix the issue of the 80% RAM
> allocation
> > on
> > > > >> 64
> > > > >>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
> heard
> > of
> > > > >> any
> > > > >>> other complaints in regards the default allocation size.
> > > > >>>
> > > > >>> —
> > > > >>> Denis
> > > > >>>
> > > > >>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> > > > >>>>
> > > > >>>> I prefer option #1.
> > > > >>>>
> > > > >>>> ⁣D.​
> > > > >>>>
> > > > >>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> > > > >>> [hidden email]> wrote:
> > > > >>>>> Folks,
> > > > >>>>>
> > > > >>>>> I would like to get back to the question about MemoryPolicy
> > > > >> maxMemory
> > > > >>>>> defaults.
> > > > >>>>>
> > > > >>>>> Although MemoryPolicy may be configured with initial and
> > maxMemory
> > > > >>>>> settings, when persistence is used MemoryPolicy always
> allocates
> > > > >>>>> maxMemory
> > > > >>>>> size for performance reasons.
> > > > >>>>>
> > > > >>>>> As default size of maxMemory is 80% of physical memory it
> causes
> > > > >> OOME
> > > > >>>>> exceptions of 32 bit platforms (either on OS or JVM level) and
> > > > >> hurts
> > > > >>>>> performance in setups when multiple Ignite nodes are started on
> > > > >> the
> > > > >>>>> same
> > > > >>>>> physical server.
> > > > >>>>>
> > > > >>>>> I suggest to rethink these defaults and switch to other
> options:
> > > > >>>>>
> > > > >>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
> In
> > > > >> this
> > > > >>>>> case we still need to address the issue with multiple nodes on
> > one
> > > > >>>>> machine
> > > > >>>>> even on 64 bit systems.
> > > > >>>>>
> > > > >>>>> - Lower defaults for maxMemory and allocate, for instance,
> > > > >> max(0.3 *
> > > > >>>>> availableMemory, 1Gb).
> > > > >>>>> This option allows us to solve all issues with starting on 32
> bit
> > > > >>>>> platforms and reduce instability with multiple nodes on the
> same
> > > > >>>>> machine.
> > > > >>>>>
> > > > >>>>>
> > > > >>>>> Thoughts and/or other options?
> > > > >>>>>
> > > > >>>>> Thanks,
> > > > >>>>> Sergey.
> > > > >>>
> > > > >>>
> > > >
> > > >
> > >
> >
>

[Alexey Goncharuk]

Dmitriy,

The reason behind this is the need to to be able to evict and load pages to
disk, thus we need to preserve a PageId->Pointer mapping in memory. In
order to do this in the most efficient way, we need to know in advance all
the address ranges we work with. We can add dynamic memory extension for
persistence-enabled config, but this will add yet another step of
indirection when resolving every page address, which adds a noticeable
performance penalty.

As far as allocating 80% of available RAM - I was against this even for
In-memory mode and still think that this is a wrong default. Looking at
free RAM is even worse because it gives you undefined behavior.

2017-08-02 10:37 GMT+03:00 Dmitriy Setrakyan <[hidden email]>:

> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]>
> wrote:
>
> > Dima,
> >
> > Probably folks who worked closely with storage know why.
> >
>
> Without knowing why, how can we make a decision?
>
> Alexey Goncharuk, was it you who made the decision about not using
> increments? Do know remember what was the reason?
>
>
> >
> > The very problem is that before being started once on production
> > environment, Ignite will typically be started hundred times on
> developer's
> > environment. I think that default should be ~10% of total RAM.
> >
>
> Why not 80% of *free *RAM?
>
>
> >
> > On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
> [hidden email]>
> > wrote:
> >
> > > On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]>
> > > wrote:
> > >
> > > > Please see original Sergey's message - when persistence is enabled,
> > > memory
> > > > is not allocated incrementally, maxSize is used.
> > > >
> > >
> > > Why?
> > >
> > >
> > > > Default settings must allow for normal work on developer's
> environment.
> > > >
> > >
> > > Agree, but why not in increments?
> > >
> > >
> > > >
> > > > ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> > > >
> > > > > > Why not allocate in increments automatically?
> > > > >
> > > > > This is exactly how the allocation works right now. The memory will
> > > grow
> > > > > incrementally until the max size is reached (80% of RAM by
> default).
> > > > >
> > > > > —
> > > > > Denis
> > > > >
> > > > > > On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> > > > > >
> > > > > > Vova, 1GB seems a bit too small for me, and frankly i do not want
> > t o
> > > > > guess. Why not allocate in increments automatically?
> > > > > >
> > > > > > ⁣D.​
> > > > > >
> > > > > > On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> > > > > [hidden email]> wrote:
> > > > > >> Denis,
> > > > > >> No doubts you haven't heard about it - AI 2.1 with persistence,
> > when
> > > > > >> 80% of
> > > > > >> RAM is allocated right away, was released several days ago. How
> do
> > > you
> > > > > >> think, how many users tried it already?
> > > > > >>
> > > > > >> Guys,
> > > > > >> Do you really think allocating 80% of available RAM is a normal
> > > thing?
> > > > > >> Take
> > > > > >> your laptop and check how many available RAM you have right now.
> > Do
> > > > you
> > > > > >> fit
> > > > > >> to remaining 20%? If not, then running AI with persistence with
> > all
> > > > > >> defaults will bring your machine down. This is insane. We shold
> > > > > >> allocate no
> > > > > >> more than 1Gb, so that user can play with it without any
> problems.
> > > > > >>
> > > > > >> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
> >
> > > > wrote:
> > > > > >>
> > > > > >>> My vote goes for option #1 too. I don’t think that 80% is too
> > > > > >> aggressive
> > > > > >>> to bring it down.
> > > > > >>>
> > > > > >>> IGNITE-5717 was created to fix the issue of the 80% RAM
> > allocation
> > > on
> > > > > >> 64
> > > > > >>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
> > heard
> > > of
> > > > > >> any
> > > > > >>> other complaints in regards the default allocation size.
> > > > > >>>
> > > > > >>> —
> > > > > >>> Denis
> > > > > >>>
> > > > > >>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> > > > > >>>>
> > > > > >>>> I prefer option #1.
> > > > > >>>>
> > > > > >>>> ⁣D.​
> > > > > >>>>
> > > > > >>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> > > > > >>> [hidden email]> wrote:
> > > > > >>>>> Folks,
> > > > > >>>>>
> > > > > >>>>> I would like to get back to the question about MemoryPolicy
> > > > > >> maxMemory
> > > > > >>>>> defaults.
> > > > > >>>>>
> > > > > >>>>> Although MemoryPolicy may be configured with initial and
> > > maxMemory
> > > > > >>>>> settings, when persistence is used MemoryPolicy always
> > allocates
> > > > > >>>>> maxMemory
> > > > > >>>>> size for performance reasons.
> > > > > >>>>>
> > > > > >>>>> As default size of maxMemory is 80% of physical memory it
> > causes
> > > > > >> OOME
> > > > > >>>>> exceptions of 32 bit platforms (either on OS or JVM level)
> and
> > > > > >> hurts
> > > > > >>>>> performance in setups when multiple Ignite nodes are started
> on
> > > > > >> the
> > > > > >>>>> same
> > > > > >>>>> physical server.
> > > > > >>>>>
> > > > > >>>>> I suggest to rethink these defaults and switch to other
> > options:
> > > > > >>>>>
> > > > > >>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
> > In
> > > > > >> this
> > > > > >>>>> case we still need to address the issue with multiple nodes
> on
> > > one
> > > > > >>>>> machine
> > > > > >>>>> even on 64 bit systems.
> > > > > >>>>>
> > > > > >>>>> - Lower defaults for maxMemory and allocate, for instance,
> > > > > >> max(0.3 *
> > > > > >>>>> availableMemory, 1Gb).
> > > > > >>>>> This option allows us to solve all issues with starting on 32
> > bit
> > > > > >>>>> platforms and reduce instability with multiple nodes on the
> > same
> > > > > >>>>> machine.
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>> Thoughts and/or other options?
> > > > > >>>>>
> > > > > >>>>> Thanks,
> > > > > >>>>> Sergey.
> > > > > >>>
> > > > > >>>
> > > > >
> > > > >
> > > >
> > >
> >
>

[Vladimir Ozerov]

Free RAM is variable. For example, I can start Ignite before IDE (Eclipse,
or so), or after IDE. In the first case it will hang, in the send it won't.
Unstable.

To be clear - I propose to have "maxMemory" set to 10%, not
"initialMemory". It doesn't matter how exactly we reach it - in one hop, or
in several hops. What do matter, is that I do not bring user's PC down with
default settings.

On Wed, Aug 2, 2017 at 10:37 AM, Dmitriy Setrakyan <[hidden email]>
wrote:

> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]>
> wrote:
>
> > Dima,
> >
> > Probably folks who worked closely with storage know why.
> >
>
> Without knowing why, how can we make a decision?
>
> Alexey Goncharuk, was it you who made the decision about not using
> increments? Do know remember what was the reason?
>
>
> >
> > The very problem is that before being started once on production
> > environment, Ignite will typically be started hundred times on
> developer's
> > environment. I think that default should be ~10% of total RAM.
> >
>
> Why not 80% of *free *RAM?
>
>
> >
> > On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
> [hidden email]>
> > wrote:
> >
> > > On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]>
> > > wrote:
> > >
> > > > Please see original Sergey's message - when persistence is enabled,
> > > memory
> > > > is not allocated incrementally, maxSize is used.
> > > >
> > >
> > > Why?
> > >
> > >
> > > > Default settings must allow for normal work on developer's
> environment.
> > > >
> > >
> > > Agree, but why not in increments?
> > >
> > >
> > > >
> > > > ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> > > >
> > > > > > Why not allocate in increments automatically?
> > > > >
> > > > > This is exactly how the allocation works right now. The memory will
> > > grow
> > > > > incrementally until the max size is reached (80% of RAM by
> default).
> > > > >
> > > > > —
> > > > > Denis
> > > > >
> > > > > > On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> > > > > >
> > > > > > Vova, 1GB seems a bit too small for me, and frankly i do not want
> > t o
> > > > > guess. Why not allocate in increments automatically?
> > > > > >
> > > > > > ⁣D.​
> > > > > >
> > > > > > On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> > > > > [hidden email]> wrote:
> > > > > >> Denis,
> > > > > >> No doubts you haven't heard about it - AI 2.1 with persistence,
> > when
> > > > > >> 80% of
> > > > > >> RAM is allocated right away, was released several days ago. How
> do
> > > you
> > > > > >> think, how many users tried it already?
> > > > > >>
> > > > > >> Guys,
> > > > > >> Do you really think allocating 80% of available RAM is a normal
> > > thing?
> > > > > >> Take
> > > > > >> your laptop and check how many available RAM you have right now.
> > Do
> > > > you
> > > > > >> fit
> > > > > >> to remaining 20%? If not, then running AI with persistence with
> > all
> > > > > >> defaults will bring your machine down. This is insane. We shold
> > > > > >> allocate no
> > > > > >> more than 1Gb, so that user can play with it without any
> problems.
> > > > > >>
> > > > > >> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
> >
> > > > wrote:
> > > > > >>
> > > > > >>> My vote goes for option #1 too. I don’t think that 80% is too
> > > > > >> aggressive
> > > > > >>> to bring it down.
> > > > > >>>
> > > > > >>> IGNITE-5717 was created to fix the issue of the 80% RAM
> > allocation
> > > on
> > > > > >> 64
> > > > > >>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
> > heard
> > > of
> > > > > >> any
> > > > > >>> other complaints in regards the default allocation size.
> > > > > >>>
> > > > > >>> —
> > > > > >>> Denis
> > > > > >>>
> > > > > >>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> > > > > >>>>
> > > > > >>>> I prefer option #1.
> > > > > >>>>
> > > > > >>>> ⁣D.​
> > > > > >>>>
> > > > > >>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> > > > > >>> [hidden email]> wrote:
> > > > > >>>>> Folks,
> > > > > >>>>>
> > > > > >>>>> I would like to get back to the question about MemoryPolicy
> > > > > >> maxMemory
> > > > > >>>>> defaults.
> > > > > >>>>>
> > > > > >>>>> Although MemoryPolicy may be configured with initial and
> > > maxMemory
> > > > > >>>>> settings, when persistence is used MemoryPolicy always
> > allocates
> > > > > >>>>> maxMemory
> > > > > >>>>> size for performance reasons.
> > > > > >>>>>
> > > > > >>>>> As default size of maxMemory is 80% of physical memory it
> > causes
> > > > > >> OOME
> > > > > >>>>> exceptions of 32 bit platforms (either on OS or JVM level)
> and
> > > > > >> hurts
> > > > > >>>>> performance in setups when multiple Ignite nodes are started
> on
> > > > > >> the
> > > > > >>>>> same
> > > > > >>>>> physical server.
> > > > > >>>>>
> > > > > >>>>> I suggest to rethink these defaults and switch to other
> > options:
> > > > > >>>>>
> > > > > >>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
> > In
> > > > > >> this
> > > > > >>>>> case we still need to address the issue with multiple nodes
> on
> > > one
> > > > > >>>>> machine
> > > > > >>>>> even on 64 bit systems.
> > > > > >>>>>
> > > > > >>>>> - Lower defaults for maxMemory and allocate, for instance,
> > > > > >> max(0.3 *
> > > > > >>>>> availableMemory, 1Gb).
> > > > > >>>>> This option allows us to solve all issues with starting on 32
> > bit
> > > > > >>>>> platforms and reduce instability with multiple nodes on the
> > same
> > > > > >>>>> machine.
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>> Thoughts and/or other options?
> > > > > >>>>>
> > > > > >>>>> Thanks,
> > > > > >>>>> Sergey.
> > > > > >>>
> > > > > >>>
> > > > >
> > > > >
> > > >
> > >
> >
>

[dmagda]

> As far as allocating 80% of available RAM - I was against this even for
> In-memory mode and still think that this is a wrong default. Looking at
> free RAM is even worse because it gives you undefined behavior.

Guys, I can not understand how this dynamic memory allocation's high-level behavior (with the persistence DISABLED) is different from the legacy off-heap memory we had in 1.x. Both off-heap memories allocate the space on demand, the current just does this more aggressively requesting big chunks.

Next, the legacy one was unlimited by default and the user can start as many nodes as he wanted on a laptop and preload as much data as he needed. Sure he could bring down the laptop if too many entries were injected into the local cluster. But that’s about too massive preloading and not caused by the ability of the legacy off-heap memory to grow infinitely. The same preloading would cause a hang if the Java heap memory mode is used.

The upshot is that the massive preloading of data on the local laptop should not fixed with repealing of the dynamic memory allocation.
Is there any other reason why we have to use the static memory allocation for the case when the persistence is disabled? I think the case with the persistence should be reviewed separately.

—
Denis

> On Aug 2, 2017, at 12:45 AM, Alexey Goncharuk <[hidden email]> wrote:
>
> Dmitriy,
>
> The reason behind this is the need to to be able to evict and load pages to
> disk, thus we need to preserve a PageId->Pointer mapping in memory. In
> order to do this in the most efficient way, we need to know in advance all
> the address ranges we work with. We can add dynamic memory extension for
> persistence-enabled config, but this will add yet another step of
> indirection when resolving every page address, which adds a noticeable
> performance penalty.
>
>
>
> 2017-08-02 10:37 GMT+03:00 Dmitriy Setrakyan <[hidden email]>:
>
>> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]>
>> wrote:
>>
>>> Dima,
>>>
>>> Probably folks who worked closely with storage know why.
>>>
>>
>> Without knowing why, how can we make a decision?
>>
>> Alexey Goncharuk, was it you who made the decision about not using
>> increments? Do know remember what was the reason?
>>
>>
>>>
>>> The very problem is that before being started once on production
>>> environment, Ignite will typically be started hundred times on
>> developer's
>>> environment. I think that default should be ~10% of total RAM.
>>>
>>
>> Why not 80% of *free *RAM?
>>
>>
>>>
>>> On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
>> [hidden email]>
>>> wrote:
>>>
>>>> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]>
>>>> wrote:
>>>>
>>>>> Please see original Sergey's message - when persistence is enabled,
>>>> memory
>>>>> is not allocated incrementally, maxSize is used.
>>>>>
>>>>
>>>> Why?
>>>>
>>>>
>>>>> Default settings must allow for normal work on developer's
>> environment.
>>>>>
>>>>
>>>> Agree, but why not in increments?
>>>>
>>>>
>>>>>
>>>>> ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
>>>>>
>>>>>>> Why not allocate in increments automatically?
>>>>>>
>>>>>> This is exactly how the allocation works right now. The memory will
>>>> grow
>>>>>> incrementally until the max size is reached (80% of RAM by
>> default).
>>>>>>
>>>>>> —
>>>>>> Denis
>>>>>>
>>>>>>> On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
>>>>>>>
>>>>>>> Vova, 1GB seems a bit too small for me, and frankly i do not want
>>> t o
>>>>>> guess. Why not allocate in increments automatically?
>>>>>>>
>>>>>>> ⁣D.​
>>>>>>>
>>>>>>> On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
>>>>>> [hidden email]> wrote:
>>>>>>>> Denis,
>>>>>>>> No doubts you haven't heard about it - AI 2.1 with persistence,
>>> when
>>>>>>>> 80% of
>>>>>>>> RAM is allocated right away, was released several days ago. How
>> do
>>>> you
>>>>>>>> think, how many users tried it already?
>>>>>>>>
>>>>>>>> Guys,
>>>>>>>> Do you really think allocating 80% of available RAM is a normal
>>>> thing?
>>>>>>>> Take
>>>>>>>> your laptop and check how many available RAM you have right now.
>>> Do
>>>>> you
>>>>>>>> fit
>>>>>>>> to remaining 20%? If not, then running AI with persistence with
>>> all
>>>>>>>> defaults will bring your machine down. This is insane. We shold
>>>>>>>> allocate no
>>>>>>>> more than 1Gb, so that user can play with it without any
>> problems.
>>>>>>>>
>>>>>>>> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
>>>
>>>>> wrote:
>>>>>>>>
>>>>>>>>> My vote goes for option #1 too. I don’t think that 80% is too
>>>>>>>> aggressive
>>>>>>>>> to bring it down.
>>>>>>>>>
>>>>>>>>> IGNITE-5717 was created to fix the issue of the 80% RAM
>>> allocation
>>>> on
>>>>>>>> 64
>>>>>>>>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
>>> heard
>>>> of
>>>>>>>> any
>>>>>>>>> other complaints in regards the default allocation size.
>>>>>>>>>
>>>>>>>>> —
>>>>>>>>> Denis
>>>>>>>>>
>>>>>>>>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
>>>>>>>>>>
>>>>>>>>>> I prefer option #1.
>>>>>>>>>>
>>>>>>>>>> ⁣D.​
>>>>>>>>>>
>>>>>>>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
>>>>>>>>> [hidden email]> wrote:
>>>>>>>>>>> Folks,
>>>>>>>>>>>
>>>>>>>>>>> I would like to get back to the question about MemoryPolicy
>>>>>>>> maxMemory
>>>>>>>>>>> defaults.
>>>>>>>>>>>
>>>>>>>>>>> Although MemoryPolicy may be configured with initial and
>>>> maxMemory
>>>>>>>>>>> settings, when persistence is used MemoryPolicy always
>>> allocates
>>>>>>>>>>> maxMemory
>>>>>>>>>>> size for performance reasons.
>>>>>>>>>>>
>>>>>>>>>>> As default size of maxMemory is 80% of physical memory it
>>> causes
>>>>>>>> OOME
>>>>>>>>>>> exceptions of 32 bit platforms (either on OS or JVM level)
>> and
>>>>>>>> hurts
>>>>>>>>>>> performance in setups when multiple Ignite nodes are started
>> on
>>>>>>>> the
>>>>>>>>>>> same
>>>>>>>>>>> physical server.
>>>>>>>>>>>
>>>>>>>>>>> I suggest to rethink these defaults and switch to other
>>> options:
>>>>>>>>>>>
>>>>>>>>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
>>> In
>>>>>>>> this
>>>>>>>>>>> case we still need to address the issue with multiple nodes
>> on
>>>> one
>>>>>>>>>>> machine
>>>>>>>>>>> even on 64 bit systems.
>>>>>>>>>>>
>>>>>>>>>>> - Lower defaults for maxMemory and allocate, for instance,
>>>>>>>> max(0.3 *
>>>>>>>>>>> availableMemory, 1Gb).
>>>>>>>>>>> This option allows us to solve all issues with starting on 32
>>> bit
>>>>>>>>>>> platforms and reduce instability with multiple nodes on the
>>> same
>>>>>>>>>>> machine.
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Thoughts and/or other options?
>>>>>>>>>>>
>>>>>>>>>>> Thanks,
>>>>>>>>>>> Sergey.
>>>>>>>>>
>>>>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>

[Sergey Chugunov]

Denis,

Just a simple example from our own codebase: I tried to execute
PersistentStoreExample with default settings and two server nodes and
client node got frozen even on initial load of data into the grid.
Although with one server node the example finishes pretty quickly.

And my laptop isn't the weakest one and has 16 gigs of memory, but it
cannot deal with it.


On Wed, Aug 2, 2017 at 4:58 PM, Denis Magda <[hidden email]> wrote:

> > As far as allocating 80% of available RAM - I was against this even for
> > In-memory mode and still think that this is a wrong default. Looking at
> > free RAM is even worse because it gives you undefined behavior.
>
> Guys, I can not understand how this dynamic memory allocation's high-level
> behavior (with the persistence DISABLED) is different from the legacy
> off-heap memory we had in 1.x. Both off-heap memories allocate the space on
> demand, the current just does this more aggressively requesting big chunks.
>
> Next, the legacy one was unlimited by default and the user can start as
> many nodes as he wanted on a laptop and preload as much data as he needed.
> Sure he could bring down the laptop if too many entries were injected into
> the local cluster. But that’s about too massive preloading and not caused
> by the ability of the legacy off-heap memory to grow infinitely. The same
> preloading would cause a hang if the Java heap memory mode is used.
>
> The upshot is that the massive preloading of data on the local laptop
> should not fixed with repealing of the dynamic memory allocation.
> Is there any other reason why we have to use the static memory allocation
> for the case when the persistence is disabled? I think the case with the
> persistence should be reviewed separately.
>
> —
> Denis
>
> > On Aug 2, 2017, at 12:45 AM, Alexey Goncharuk <
> [hidden email]> wrote:
> >
> > Dmitriy,
> >
> > The reason behind this is the need to to be able to evict and load pages
> to
> > disk, thus we need to preserve a PageId->Pointer mapping in memory. In
> > order to do this in the most efficient way, we need to know in advance
> all
> > the address ranges we work with. We can add dynamic memory extension for
> > persistence-enabled config, but this will add yet another step of
> > indirection when resolving every page address, which adds a noticeable
> > performance penalty.
> >
> >
> >
> > 2017-08-02 10:37 GMT+03:00 Dmitriy Setrakyan <[hidden email]>:
> >
> >> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]>
> >> wrote:
> >>
> >>> Dima,
> >>>
> >>> Probably folks who worked closely with storage know why.
> >>>
> >>
> >> Without knowing why, how can we make a decision?
> >>
> >> Alexey Goncharuk, was it you who made the decision about not using
> >> increments? Do know remember what was the reason?
> >>
> >>
> >>>
> >>> The very problem is that before being started once on production
> >>> environment, Ignite will typically be started hundred times on
> >> developer's
> >>> environment. I think that default should be ~10% of total RAM.
> >>>
> >>
> >> Why not 80% of *free *RAM?
> >>
> >>
> >>>
> >>> On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
> >> [hidden email]>
> >>> wrote:
> >>>
> >>>> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]
> >
> >>>> wrote:
> >>>>
> >>>>> Please see original Sergey's message - when persistence is enabled,
> >>>> memory
> >>>>> is not allocated incrementally, maxSize is used.
> >>>>>
> >>>>
> >>>> Why?
> >>>>
> >>>>
> >>>>> Default settings must allow for normal work on developer's
> >> environment.
> >>>>>
> >>>>
> >>>> Agree, but why not in increments?
> >>>>
> >>>>
> >>>>>
> >>>>> ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> >>>>>
> >>>>>>> Why not allocate in increments automatically?
> >>>>>>
> >>>>>> This is exactly how the allocation works right now. The memory will
> >>>> grow
> >>>>>> incrementally until the max size is reached (80% of RAM by
> >> default).
> >>>>>>
> >>>>>> —
> >>>>>> Denis
> >>>>>>
> >>>>>>> On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> >>>>>>>
> >>>>>>> Vova, 1GB seems a bit too small for me, and frankly i do not want
> >>> t o
> >>>>>> guess. Why not allocate in increments automatically?
> >>>>>>>
> >>>>>>> ⁣D.​
> >>>>>>>
> >>>>>>> On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> >>>>>> [hidden email]> wrote:
> >>>>>>>> Denis,
> >>>>>>>> No doubts you haven't heard about it - AI 2.1 with persistence,
> >>> when
> >>>>>>>> 80% of
> >>>>>>>> RAM is allocated right away, was released several days ago. How
> >> do
> >>>> you
> >>>>>>>> think, how many users tried it already?
> >>>>>>>>
> >>>>>>>> Guys,
> >>>>>>>> Do you really think allocating 80% of available RAM is a normal
> >>>> thing?
> >>>>>>>> Take
> >>>>>>>> your laptop and check how many available RAM you have right now.
> >>> Do
> >>>>> you
> >>>>>>>> fit
> >>>>>>>> to remaining 20%? If not, then running AI with persistence with
> >>> all
> >>>>>>>> defaults will bring your machine down. This is insane. We shold
> >>>>>>>> allocate no
> >>>>>>>> more than 1Gb, so that user can play with it without any
> >> problems.
> >>>>>>>>
> >>>>>>>> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
> >>>
> >>>>> wrote:
> >>>>>>>>
> >>>>>>>>> My vote goes for option #1 too. I don’t think that 80% is too
> >>>>>>>> aggressive
> >>>>>>>>> to bring it down.
> >>>>>>>>>
> >>>>>>>>> IGNITE-5717 was created to fix the issue of the 80% RAM
> >>> allocation
> >>>> on
> >>>>>>>> 64
> >>>>>>>>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
> >>> heard
> >>>> of
> >>>>>>>> any
> >>>>>>>>> other complaints in regards the default allocation size.
> >>>>>>>>>
> >>>>>>>>> —
> >>>>>>>>> Denis
> >>>>>>>>>
> >>>>>>>>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> >>>>>>>>>>
> >>>>>>>>>> I prefer option #1.
> >>>>>>>>>>
> >>>>>>>>>> ⁣D.​
> >>>>>>>>>>
> >>>>>>>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> >>>>>>>>> [hidden email]> wrote:
> >>>>>>>>>>> Folks,
> >>>>>>>>>>>
> >>>>>>>>>>> I would like to get back to the question about MemoryPolicy
> >>>>>>>> maxMemory
> >>>>>>>>>>> defaults.
> >>>>>>>>>>>
> >>>>>>>>>>> Although MemoryPolicy may be configured with initial and
> >>>> maxMemory
> >>>>>>>>>>> settings, when persistence is used MemoryPolicy always
> >>> allocates
> >>>>>>>>>>> maxMemory
> >>>>>>>>>>> size for performance reasons.
> >>>>>>>>>>>
> >>>>>>>>>>> As default size of maxMemory is 80% of physical memory it
> >>> causes
> >>>>>>>> OOME
> >>>>>>>>>>> exceptions of 32 bit platforms (either on OS or JVM level)
> >> and
> >>>>>>>> hurts
> >>>>>>>>>>> performance in setups when multiple Ignite nodes are started
> >> on
> >>>>>>>> the
> >>>>>>>>>>> same
> >>>>>>>>>>> physical server.
> >>>>>>>>>>>
> >>>>>>>>>>> I suggest to rethink these defaults and switch to other
> >>> options:
> >>>>>>>>>>>
> >>>>>>>>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
> >>> In
> >>>>>>>> this
> >>>>>>>>>>> case we still need to address the issue with multiple nodes
> >> on
> >>>> one
> >>>>>>>>>>> machine
> >>>>>>>>>>> even on 64 bit systems.
> >>>>>>>>>>>
> >>>>>>>>>>> - Lower defaults for maxMemory and allocate, for instance,
> >>>>>>>> max(0.3 *
> >>>>>>>>>>> availableMemory, 1Gb).
> >>>>>>>>>>> This option allows us to solve all issues with starting on 32
> >>> bit
> >>>>>>>>>>> platforms and reduce instability with multiple nodes on the
> >>> same
> >>>>>>>>>>> machine.
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>> Thoughts and/or other options?
> >>>>>>>>>>>
> >>>>>>>>>>> Thanks,
> >>>>>>>>>>> Sergey.
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>
> >>>>>>
> >>>>>
> >>>>
> >>>
> >>
>
>

[dmagda]

Sergey,

That’s expectable because as we revealed from this discussion the allocation works different depending on whether the persistence is used or not:

1) In-memory mode (the persistence is disabled) - the space will be allocated incrementally until the max threshold is reached. Good!

2) The persistence mode - the whole space (limited by the max threshold) is allocated right away. It’s not surprising that your laptop starts choking.

So, in my previous response I tried to explain that I can’t find any reason why we should adjust 1). Any reasons except for the massive preloading?

As for 2), that was a big surprise to reveal this after 2.1 release. Definitely we have to fix this somehow.

—
Denis

> On Aug 2, 2017, at 6:59 AM, Sergey Chugunov <[hidden email]> wrote:
>
> Denis,
>
> Just a simple example from our own codebase: I tried to execute
> PersistentStoreExample with default settings and two server nodes and
> client node got frozen even on initial load of data into the grid.
> Although with one server node the example finishes pretty quickly.
>
> And my laptop isn't the weakest one and has 16 gigs of memory, but it
> cannot deal with it.
>
>
> On Wed, Aug 2, 2017 at 4:58 PM, Denis Magda <[hidden email]> wrote:
>
>>> As far as allocating 80% of available RAM - I was against this even for
>>> In-memory mode and still think that this is a wrong default. Looking at
>>> free RAM is even worse because it gives you undefined behavior.
>>
>> Guys, I can not understand how this dynamic memory allocation's high-level
>> behavior (with the persistence DISABLED) is different from the legacy
>> off-heap memory we had in 1.x. Both off-heap memories allocate the space on
>> demand, the current just does this more aggressively requesting big chunks.
>>
>> Next, the legacy one was unlimited by default and the user can start as
>> many nodes as he wanted on a laptop and preload as much data as he needed.
>> Sure he could bring down the laptop if too many entries were injected into
>> the local cluster. But that’s about too massive preloading and not caused
>> by the ability of the legacy off-heap memory to grow infinitely. The same
>> preloading would cause a hang if the Java heap memory mode is used.
>>
>> The upshot is that the massive preloading of data on the local laptop
>> should not fixed with repealing of the dynamic memory allocation.
>> Is there any other reason why we have to use the static memory allocation
>> for the case when the persistence is disabled? I think the case with the
>> persistence should be reviewed separately.
>>
>> —
>> Denis
>>
>>> On Aug 2, 2017, at 12:45 AM, Alexey Goncharuk <
>> [hidden email]> wrote:
>>>
>>> Dmitriy,
>>>
>>> The reason behind this is the need to to be able to evict and load pages
>> to
>>> disk, thus we need to preserve a PageId->Pointer mapping in memory. In
>>> order to do this in the most efficient way, we need to know in advance
>> all
>>> the address ranges we work with. We can add dynamic memory extension for
>>> persistence-enabled config, but this will add yet another step of
>>> indirection when resolving every page address, which adds a noticeable
>>> performance penalty.
>>>
>>>
>>>
>>> 2017-08-02 10:37 GMT+03:00 Dmitriy Setrakyan <[hidden email]>:
>>>
>>>> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]>
>>>> wrote:
>>>>
>>>>> Dima,
>>>>>
>>>>> Probably folks who worked closely with storage know why.
>>>>>
>>>>
>>>> Without knowing why, how can we make a decision?
>>>>
>>>> Alexey Goncharuk, was it you who made the decision about not using
>>>> increments? Do know remember what was the reason?
>>>>
>>>>
>>>>>
>>>>> The very problem is that before being started once on production
>>>>> environment, Ignite will typically be started hundred times on
>>>> developer's
>>>>> environment. I think that default should be ~10% of total RAM.
>>>>>
>>>>
>>>> Why not 80% of *free *RAM?
>>>>
>>>>
>>>>>
>>>>> On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
>>>> [hidden email]>
>>>>> wrote:
>>>>>
>>>>>> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <[hidden email]
>>>
>>>>>> wrote:
>>>>>>
>>>>>>> Please see original Sergey's message - when persistence is enabled,
>>>>>> memory
>>>>>>> is not allocated incrementally, maxSize is used.
>>>>>>>
>>>>>>
>>>>>> Why?
>>>>>>
>>>>>>
>>>>>>> Default settings must allow for normal work on developer's
>>>> environment.
>>>>>>>
>>>>>>
>>>>>> Agree, but why not in increments?
>>>>>>
>>>>>>
>>>>>>>
>>>>>>> ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
>>>>>>>
>>>>>>>>> Why not allocate in increments automatically?
>>>>>>>>
>>>>>>>> This is exactly how the allocation works right now. The memory will
>>>>>> grow
>>>>>>>> incrementally until the max size is reached (80% of RAM by
>>>> default).
>>>>>>>>
>>>>>>>> —
>>>>>>>> Denis
>>>>>>>>
>>>>>>>>> On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
>>>>>>>>>
>>>>>>>>> Vova, 1GB seems a bit too small for me, and frankly i do not want
>>>>> t o
>>>>>>>> guess. Why not allocate in increments automatically?
>>>>>>>>>
>>>>>>>>> ⁣D.​
>>>>>>>>>
>>>>>>>>> On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
>>>>>>>> [hidden email]> wrote:
>>>>>>>>>> Denis,
>>>>>>>>>> No doubts you haven't heard about it - AI 2.1 with persistence,
>>>>> when
>>>>>>>>>> 80% of
>>>>>>>>>> RAM is allocated right away, was released several days ago. How
>>>> do
>>>>>> you
>>>>>>>>>> think, how many users tried it already?
>>>>>>>>>>
>>>>>>>>>> Guys,
>>>>>>>>>> Do you really think allocating 80% of available RAM is a normal
>>>>>> thing?
>>>>>>>>>> Take
>>>>>>>>>> your laptop and check how many available RAM you have right now.
>>>>> Do
>>>>>>> you
>>>>>>>>>> fit
>>>>>>>>>> to remaining 20%? If not, then running AI with persistence with
>>>>> all
>>>>>>>>>> defaults will bring your machine down. This is insane. We shold
>>>>>>>>>> allocate no
>>>>>>>>>> more than 1Gb, so that user can play with it without any
>>>> problems.
>>>>>>>>>>
>>>>>>>>>> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
>>>>>
>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>> My vote goes for option #1 too. I don’t think that 80% is too
>>>>>>>>>> aggressive
>>>>>>>>>>> to bring it down.
>>>>>>>>>>>
>>>>>>>>>>> IGNITE-5717 was created to fix the issue of the 80% RAM
>>>>> allocation
>>>>>> on
>>>>>>>>>> 64
>>>>>>>>>>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
>>>>> heard
>>>>>> of
>>>>>>>>>> any
>>>>>>>>>>> other complaints in regards the default allocation size.
>>>>>>>>>>>
>>>>>>>>>>> —
>>>>>>>>>>> Denis
>>>>>>>>>>>
>>>>>>>>>>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
>>>>>>>>>>>>
>>>>>>>>>>>> I prefer option #1.
>>>>>>>>>>>>
>>>>>>>>>>>> ⁣D.​
>>>>>>>>>>>>
>>>>>>>>>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
>>>>>>>>>>> [hidden email]> wrote:
>>>>>>>>>>>>> Folks,
>>>>>>>>>>>>>
>>>>>>>>>>>>> I would like to get back to the question about MemoryPolicy
>>>>>>>>>> maxMemory
>>>>>>>>>>>>> defaults.
>>>>>>>>>>>>>
>>>>>>>>>>>>> Although MemoryPolicy may be configured with initial and
>>>>>> maxMemory
>>>>>>>>>>>>> settings, when persistence is used MemoryPolicy always
>>>>> allocates
>>>>>>>>>>>>> maxMemory
>>>>>>>>>>>>> size for performance reasons.
>>>>>>>>>>>>>
>>>>>>>>>>>>> As default size of maxMemory is 80% of physical memory it
>>>>> causes
>>>>>>>>>> OOME
>>>>>>>>>>>>> exceptions of 32 bit platforms (either on OS or JVM level)
>>>> and
>>>>>>>>>> hurts
>>>>>>>>>>>>> performance in setups when multiple Ignite nodes are started
>>>> on
>>>>>>>>>> the
>>>>>>>>>>>>> same
>>>>>>>>>>>>> physical server.
>>>>>>>>>>>>>
>>>>>>>>>>>>> I suggest to rethink these defaults and switch to other
>>>>> options:
>>>>>>>>>>>>>
>>>>>>>>>>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
>>>>> In
>>>>>>>>>> this
>>>>>>>>>>>>> case we still need to address the issue with multiple nodes
>>>> on
>>>>>> one
>>>>>>>>>>>>> machine
>>>>>>>>>>>>> even on 64 bit systems.
>>>>>>>>>>>>>
>>>>>>>>>>>>> - Lower defaults for maxMemory and allocate, for instance,
>>>>>>>>>> max(0.3 *
>>>>>>>>>>>>> availableMemory, 1Gb).
>>>>>>>>>>>>> This option allows us to solve all issues with starting on 32
>>>>> bit
>>>>>>>>>>>>> platforms and reduce instability with multiple nodes on the
>>>>> same
>>>>>>>>>>>>> machine.
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> Thoughts and/or other options?
>>>>>>>>>>>>>
>>>>>>>>>>>>> Thanks,
>>>>>>>>>>>>> Sergey.
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>
>>

[Dmitriy Pavlov]

Hi Igniters,

When I was Ignite user before installing product on production server I’ve
always used this page
https://apacheignite.readme.io/docs/jvm-and-system-tuning for selecting
appropriate parameters.

But before go live, I’ve used Ignition.start() 20 times per day to check if
my changes in business code work correctly. Most of runs I’ve used 2-5
nodes on one laptop (plus application server, plus emulators, plus browser).


I think defaults should be targeted to developers (Ignite users). But for
powerful production servers should be performance hints added and
highlighted in doc (like
https://apacheignite.readme.io/docs/memory-configuration )

Sincerely,

Dmitriy Pavlov.


ср, 2 авг. 2017 г. в 17:08, Denis Magda <[hidden email]>:

> Sergey,
>
> That’s expectable because as we revealed from this discussion the
> allocation works different depending on whether the persistence is used or
> not:
>
> 1) In-memory mode (the persistence is disabled) - the space will be
> allocated incrementally until the max threshold is reached. Good!
>
> 2) The persistence mode - the whole space (limited by the max threshold)
> is allocated right away. It’s not surprising that your laptop starts
> choking.
>
> So, in my previous response I tried to explain that I can’t find any
> reason why we should adjust 1). Any reasons except for the massive
> preloading?
>
> As for 2), that was a big surprise to reveal this after 2.1 release.
> Definitely we have to fix this somehow.
>
> —
> Denis
>
> > On Aug 2, 2017, at 6:59 AM, Sergey Chugunov <[hidden email]>
> wrote:
> >
> > Denis,
> >
> > Just a simple example from our own codebase: I tried to execute
> > PersistentStoreExample with default settings and two server nodes and
> > client node got frozen even on initial load of data into the grid.
> > Although with one server node the example finishes pretty quickly.
> >
> > And my laptop isn't the weakest one and has 16 gigs of memory, but it
> > cannot deal with it.
> >
> >
> > On Wed, Aug 2, 2017 at 4:58 PM, Denis Magda <[hidden email]> wrote:
> >
> >>> As far as allocating 80% of available RAM - I was against this even for
> >>> In-memory mode and still think that this is a wrong default. Looking at
> >>> free RAM is even worse because it gives you undefined behavior.
> >>
> >> Guys, I can not understand how this dynamic memory allocation's
> high-level
> >> behavior (with the persistence DISABLED) is different from the legacy
> >> off-heap memory we had in 1.x. Both off-heap memories allocate the
> space on
> >> demand, the current just does this more aggressively requesting big
> chunks.
> >>
> >> Next, the legacy one was unlimited by default and the user can start as
> >> many nodes as he wanted on a laptop and preload as much data as he
> needed.
> >> Sure he could bring down the laptop if too many entries were injected
> into
> >> the local cluster. But that’s about too massive preloading and not
> caused
> >> by the ability of the legacy off-heap memory to grow infinitely. The
> same
> >> preloading would cause a hang if the Java heap memory mode is used.
> >>
> >> The upshot is that the massive preloading of data on the local laptop
> >> should not fixed with repealing of the dynamic memory allocation.
> >> Is there any other reason why we have to use the static memory
> allocation
> >> for the case when the persistence is disabled? I think the case with the
> >> persistence should be reviewed separately.
> >>
> >> —
> >> Denis
> >>
> >>> On Aug 2, 2017, at 12:45 AM, Alexey Goncharuk <
> >> [hidden email]> wrote:
> >>>
> >>> Dmitriy,
> >>>
> >>> The reason behind this is the need to to be able to evict and load
> pages
> >> to
> >>> disk, thus we need to preserve a PageId->Pointer mapping in memory. In
> >>> order to do this in the most efficient way, we need to know in advance
> >> all
> >>> the address ranges we work with. We can add dynamic memory extension
> for
> >>> persistence-enabled config, but this will add yet another step of
> >>> indirection when resolving every page address, which adds a noticeable
> >>> performance penalty.
> >>>
> >>>
> >>>
> >>> 2017-08-02 10:37 GMT+03:00 Dmitriy Setrakyan <[hidden email]>:
> >>>
> >>>> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]
> >
> >>>> wrote:
> >>>>
> >>>>> Dima,
> >>>>>
> >>>>> Probably folks who worked closely with storage know why.
> >>>>>
> >>>>
> >>>> Without knowing why, how can we make a decision?
> >>>>
> >>>> Alexey Goncharuk, was it you who made the decision about not using
> >>>> increments? Do know remember what was the reason?
> >>>>
> >>>>
> >>>>>
> >>>>> The very problem is that before being started once on production
> >>>>> environment, Ignite will typically be started hundred times on
> >>>> developer's
> >>>>> environment. I think that default should be ~10% of total RAM.
> >>>>>
> >>>>
> >>>> Why not 80% of *free *RAM?
> >>>>
> >>>>
> >>>>>
> >>>>> On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
> >>>> [hidden email]>
> >>>>> wrote:
> >>>>>
> >>>>>> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <
> [hidden email]
> >>>
> >>>>>> wrote:
> >>>>>>
> >>>>>>> Please see original Sergey's message - when persistence is enabled,
> >>>>>> memory
> >>>>>>> is not allocated incrementally, maxSize is used.
> >>>>>>>
> >>>>>>
> >>>>>> Why?
> >>>>>>
> >>>>>>
> >>>>>>> Default settings must allow for normal work on developer's
> >>>> environment.
> >>>>>>>
> >>>>>>
> >>>>>> Agree, but why not in increments?
> >>>>>>
> >>>>>>
> >>>>>>>
> >>>>>>> ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> >>>>>>>
> >>>>>>>>> Why not allocate in increments automatically?
> >>>>>>>>
> >>>>>>>> This is exactly how the allocation works right now. The memory
> will
> >>>>>> grow
> >>>>>>>> incrementally until the max size is reached (80% of RAM by
> >>>> default).
> >>>>>>>>
> >>>>>>>> —
> >>>>>>>> Denis
> >>>>>>>>
> >>>>>>>>> On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> >>>>>>>>>
> >>>>>>>>> Vova, 1GB seems a bit too small for me, and frankly i do not want
> >>>>> t o
> >>>>>>>> guess. Why not allocate in increments automatically?
> >>>>>>>>>
> >>>>>>>>> ⁣D.​
> >>>>>>>>>
> >>>>>>>>> On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> >>>>>>>> [hidden email]> wrote:
> >>>>>>>>>> Denis,
> >>>>>>>>>> No doubts you haven't heard about it - AI 2.1 with persistence,
> >>>>> when
> >>>>>>>>>> 80% of
> >>>>>>>>>> RAM is allocated right away, was released several days ago. How
> >>>> do
> >>>>>> you
> >>>>>>>>>> think, how many users tried it already?
> >>>>>>>>>>
> >>>>>>>>>> Guys,
> >>>>>>>>>> Do you really think allocating 80% of available RAM is a normal
> >>>>>> thing?
> >>>>>>>>>> Take
> >>>>>>>>>> your laptop and check how many available RAM you have right now.
> >>>>> Do
> >>>>>>> you
> >>>>>>>>>> fit
> >>>>>>>>>> to remaining 20%? If not, then running AI with persistence with
> >>>>> all
> >>>>>>>>>> defaults will bring your machine down. This is insane. We shold
> >>>>>>>>>> allocate no
> >>>>>>>>>> more than 1Gb, so that user can play with it without any
> >>>> problems.
> >>>>>>>>>>
> >>>>>>>>>> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
> >>>>>
> >>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>> My vote goes for option #1 too. I don’t think that 80% is too
> >>>>>>>>>> aggressive
> >>>>>>>>>>> to bring it down.
> >>>>>>>>>>>
> >>>>>>>>>>> IGNITE-5717 was created to fix the issue of the 80% RAM
> >>>>> allocation
> >>>>>> on
> >>>>>>>>>> 64
> >>>>>>>>>>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
> >>>>> heard
> >>>>>> of
> >>>>>>>>>> any
> >>>>>>>>>>> other complaints in regards the default allocation size.
> >>>>>>>>>>>
> >>>>>>>>>>> —
> >>>>>>>>>>> Denis
> >>>>>>>>>>>
> >>>>>>>>>>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> >>>>>>>>>>>>
> >>>>>>>>>>>> I prefer option #1.
> >>>>>>>>>>>>
> >>>>>>>>>>>> ⁣D.​
> >>>>>>>>>>>>
> >>>>>>>>>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> >>>>>>>>>>> [hidden email]> wrote:
> >>>>>>>>>>>>> Folks,
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> I would like to get back to the question about MemoryPolicy
> >>>>>>>>>> maxMemory
> >>>>>>>>>>>>> defaults.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> Although MemoryPolicy may be configured with initial and
> >>>>>> maxMemory
> >>>>>>>>>>>>> settings, when persistence is used MemoryPolicy always
> >>>>> allocates
> >>>>>>>>>>>>> maxMemory
> >>>>>>>>>>>>> size for performance reasons.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> As default size of maxMemory is 80% of physical memory it
> >>>>> causes
> >>>>>>>>>> OOME
> >>>>>>>>>>>>> exceptions of 32 bit platforms (either on OS or JVM level)
> >>>> and
> >>>>>>>>>> hurts
> >>>>>>>>>>>>> performance in setups when multiple Ignite nodes are started
> >>>> on
> >>>>>>>>>> the
> >>>>>>>>>>>>> same
> >>>>>>>>>>>>> physical server.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> I suggest to rethink these defaults and switch to other
> >>>>> options:
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
> >>>>> In
> >>>>>>>>>> this
> >>>>>>>>>>>>> case we still need to address the issue with multiple nodes
> >>>> on
> >>>>>> one
> >>>>>>>>>>>>> machine
> >>>>>>>>>>>>> even on 64 bit systems.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> - Lower defaults for maxMemory and allocate, for instance,
> >>>>>>>>>> max(0.3 *
> >>>>>>>>>>>>> availableMemory, 1Gb).
> >>>>>>>>>>>>> This option allows us to solve all issues with starting on 32
> >>>>> bit
> >>>>>>>>>>>>> platforms and reduce instability with multiple nodes on the
> >>>>> same
> >>>>>>>>>>>>> machine.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> Thoughts and/or other options?
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> Thanks,
> >>>>>>>>>>>>> Sergey.
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>>
> >>>>
> >>
> >>
>
>

[Vladimir Ozerov]

Denis,

The reason is that product should not hang user's computer. How else this
could be explained? I am developer. I start Ignite, 1 node, 2 nodes, X
nodes, observe how they join topology. Add one key, 10 keys, 1M keys. Then
I do a bug in example and load 100M keys accidentally - restart the
computer. Correct behavior is to have small "maxMemory" by default to avoid
that. User should get exception instead of hang. E.g. Java's "-Xmx" is
typically 25% of RAM - more adequate value, comparing to Ignite.

It doesn't matter whether you use persistence or not. Persistent case just
makes this flaw more obvious - you have virtually unlimited disk, and yet
you end up with swapping and hang when using Ignite with default
configuration. As already explained, the problem is not about allocating
"maxMemory" right away, but about the value of "maxMemory" - it is too big.

"We had this behavior before" is never an argument. Previous offheap
implementation had a lot of flaws, so let's just forget about it.

On Wed, Aug 2, 2017 at 5:08 PM, Denis Magda <[hidden email]> wrote:

> Sergey,
>
> That’s expectable because as we revealed from this discussion the
> allocation works different depending on whether the persistence is used or
> not:
>
> 1) In-memory mode (the persistence is disabled) - the space will be
> allocated incrementally until the max threshold is reached. Good!
>
> 2) The persistence mode - the whole space (limited by the max threshold)
> is allocated right away. It’s not surprising that your laptop starts
> choking.
>
> So, in my previous response I tried to explain that I can’t find any
> reason why we should adjust 1). Any reasons except for the massive
> preloading?
>
> As for 2), that was a big surprise to reveal this after 2.1 release.
> Definitely we have to fix this somehow.
>
> —
> Denis
>
> > On Aug 2, 2017, at 6:59 AM, Sergey Chugunov <[hidden email]>
> wrote:
> >
> > Denis,
> >
> > Just a simple example from our own codebase: I tried to execute
> > PersistentStoreExample with default settings and two server nodes and
> > client node got frozen even on initial load of data into the grid.
> > Although with one server node the example finishes pretty quickly.
> >
> > And my laptop isn't the weakest one and has 16 gigs of memory, but it
> > cannot deal with it.
> >
> >
> > On Wed, Aug 2, 2017 at 4:58 PM, Denis Magda <[hidden email]> wrote:
> >
> >>> As far as allocating 80% of available RAM - I was against this even for
> >>> In-memory mode and still think that this is a wrong default. Looking at
> >>> free RAM is even worse because it gives you undefined behavior.
> >>
> >> Guys, I can not understand how this dynamic memory allocation's
> high-level
> >> behavior (with the persistence DISABLED) is different from the legacy
> >> off-heap memory we had in 1.x. Both off-heap memories allocate the
> space on
> >> demand, the current just does this more aggressively requesting big
> chunks.
> >>
> >> Next, the legacy one was unlimited by default and the user can start as
> >> many nodes as he wanted on a laptop and preload as much data as he
> needed.
> >> Sure he could bring down the laptop if too many entries were injected
> into
> >> the local cluster. But that’s about too massive preloading and not
> caused
> >> by the ability of the legacy off-heap memory to grow infinitely. The
> same
> >> preloading would cause a hang if the Java heap memory mode is used.
> >>
> >> The upshot is that the massive preloading of data on the local laptop
> >> should not fixed with repealing of the dynamic memory allocation.
> >> Is there any other reason why we have to use the static memory
> allocation
> >> for the case when the persistence is disabled? I think the case with the
> >> persistence should be reviewed separately.
> >>
> >> —
> >> Denis
> >>
> >>> On Aug 2, 2017, at 12:45 AM, Alexey Goncharuk <
> >> [hidden email]> wrote:
> >>>
> >>> Dmitriy,
> >>>
> >>> The reason behind this is the need to to be able to evict and load
> pages
> >> to
> >>> disk, thus we need to preserve a PageId->Pointer mapping in memory. In
> >>> order to do this in the most efficient way, we need to know in advance
> >> all
> >>> the address ranges we work with. We can add dynamic memory extension
> for
> >>> persistence-enabled config, but this will add yet another step of
> >>> indirection when resolving every page address, which adds a noticeable
> >>> performance penalty.
> >>>
> >>>
> >>>
> >>> 2017-08-02 10:37 GMT+03:00 Dmitriy Setrakyan <[hidden email]>:
> >>>
> >>>> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <[hidden email]
> >
> >>>> wrote:
> >>>>
> >>>>> Dima,
> >>>>>
> >>>>> Probably folks who worked closely with storage know why.
> >>>>>
> >>>>
> >>>> Without knowing why, how can we make a decision?
> >>>>
> >>>> Alexey Goncharuk, was it you who made the decision about not using
> >>>> increments? Do know remember what was the reason?
> >>>>
> >>>>
> >>>>>
> >>>>> The very problem is that before being started once on production
> >>>>> environment, Ignite will typically be started hundred times on
> >>>> developer's
> >>>>> environment. I think that default should be ~10% of total RAM.
> >>>>>
> >>>>
> >>>> Why not 80% of *free *RAM?
> >>>>
> >>>>
> >>>>>
> >>>>> On Wed, Aug 2, 2017 at 10:21 AM, Dmitriy Setrakyan <
> >>>> [hidden email]>
> >>>>> wrote:
> >>>>>
> >>>>>> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <
> [hidden email]
> >>>
> >>>>>> wrote:
> >>>>>>
> >>>>>>> Please see original Sergey's message - when persistence is enabled,
> >>>>>> memory
> >>>>>>> is not allocated incrementally, maxSize is used.
> >>>>>>>
> >>>>>>
> >>>>>> Why?
> >>>>>>
> >>>>>>
> >>>>>>> Default settings must allow for normal work on developer's
> >>>> environment.
> >>>>>>>
> >>>>>>
> >>>>>> Agree, but why not in increments?
> >>>>>>
> >>>>>>
> >>>>>>>
> >>>>>>> ср, 2 авг. 2017 г. в 1:10, Denis Magda <[hidden email]>:
> >>>>>>>
> >>>>>>>>> Why not allocate in increments automatically?
> >>>>>>>>
> >>>>>>>> This is exactly how the allocation works right now. The memory
> will
> >>>>>> grow
> >>>>>>>> incrementally until the max size is reached (80% of RAM by
> >>>> default).
> >>>>>>>>
> >>>>>>>> —
> >>>>>>>> Denis
> >>>>>>>>
> >>>>>>>>> On Aug 1, 2017, at 3:03 PM, [hidden email] wrote:
> >>>>>>>>>
> >>>>>>>>> Vova, 1GB seems a bit too small for me, and frankly i do not want
> >>>>> t o
> >>>>>>>> guess. Why not allocate in increments automatically?
> >>>>>>>>>
> >>>>>>>>> ⁣D.​
> >>>>>>>>>
> >>>>>>>>> On Aug 1, 2017, 11:03 PM, at 11:03 PM, Vladimir Ozerov <
> >>>>>>>> [hidden email]> wrote:
> >>>>>>>>>> Denis,
> >>>>>>>>>> No doubts you haven't heard about it - AI 2.1 with persistence,
> >>>>> when
> >>>>>>>>>> 80% of
> >>>>>>>>>> RAM is allocated right away, was released several days ago. How
> >>>> do
> >>>>>> you
> >>>>>>>>>> think, how many users tried it already?
> >>>>>>>>>>
> >>>>>>>>>> Guys,
> >>>>>>>>>> Do you really think allocating 80% of available RAM is a normal
> >>>>>> thing?
> >>>>>>>>>> Take
> >>>>>>>>>> your laptop and check how many available RAM you have right now.
> >>>>> Do
> >>>>>>> you
> >>>>>>>>>> fit
> >>>>>>>>>> to remaining 20%? If not, then running AI with persistence with
> >>>>> all
> >>>>>>>>>> defaults will bring your machine down. This is insane. We shold
> >>>>>>>>>> allocate no
> >>>>>>>>>> more than 1Gb, so that user can play with it without any
> >>>> problems.
> >>>>>>>>>>
> >>>>>>>>>> On Tue, Aug 1, 2017 at 10:26 PM, Denis Magda <[hidden email]
> >>>>>
> >>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>> My vote goes for option #1 too. I don’t think that 80% is too
> >>>>>>>>>> aggressive
> >>>>>>>>>>> to bring it down.
> >>>>>>>>>>>
> >>>>>>>>>>> IGNITE-5717 was created to fix the issue of the 80% RAM
> >>>>> allocation
> >>>>>> on
> >>>>>>>>>> 64
> >>>>>>>>>>> bit systems when Ignite works on top of 32 bit JVM. I’ve not
> >>>>> heard
> >>>>>> of
> >>>>>>>>>> any
> >>>>>>>>>>> other complaints in regards the default allocation size.
> >>>>>>>>>>>
> >>>>>>>>>>> —
> >>>>>>>>>>> Denis
> >>>>>>>>>>>
> >>>>>>>>>>>> On Aug 1, 2017, at 10:58 AM, [hidden email] wrote:
> >>>>>>>>>>>>
> >>>>>>>>>>>> I prefer option #1.
> >>>>>>>>>>>>
> >>>>>>>>>>>> ⁣D.​
> >>>>>>>>>>>>
> >>>>>>>>>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov <
> >>>>>>>>>>> [hidden email]> wrote:
> >>>>>>>>>>>>> Folks,
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> I would like to get back to the question about MemoryPolicy
> >>>>>>>>>> maxMemory
> >>>>>>>>>>>>> defaults.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> Although MemoryPolicy may be configured with initial and
> >>>>>> maxMemory
> >>>>>>>>>>>>> settings, when persistence is used MemoryPolicy always
> >>>>> allocates
> >>>>>>>>>>>>> maxMemory
> >>>>>>>>>>>>> size for performance reasons.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> As default size of maxMemory is 80% of physical memory it
> >>>>> causes
> >>>>>>>>>> OOME
> >>>>>>>>>>>>> exceptions of 32 bit platforms (either on OS or JVM level)
> >>>> and
> >>>>>>>>>> hurts
> >>>>>>>>>>>>> performance in setups when multiple Ignite nodes are started
> >>>> on
> >>>>>>>>>> the
> >>>>>>>>>>>>> same
> >>>>>>>>>>>>> physical server.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> I suggest to rethink these defaults and switch to other
> >>>>> options:
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> - Check whether platform is 32 or 64 bits and adapt defaults.
> >>>>> In
> >>>>>>>>>> this
> >>>>>>>>>>>>> case we still need to address the issue with multiple nodes
> >>>> on
> >>>>>> one
> >>>>>>>>>>>>> machine
> >>>>>>>>>>>>> even on 64 bit systems.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> - Lower defaults for maxMemory and allocate, for instance,
> >>>>>>>>>> max(0.3 *
> >>>>>>>>>>>>> availableMemory, 1Gb).
> >>>>>>>>>>>>> This option allows us to solve all issues with starting on 32
> >>>>> bit
> >>>>>>>>>>>>> platforms and reduce instability with multiple nodes on the
> >>>>> same
> >>>>>>>>>>>>> machine.
> >>>>>>>>>>>>>
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> Thoughts and/or other options?
> >>>>>>>>>>>>>
> >>>>>>>>>>>>> Thanks,
> >>>>>>>>>>>>> Sergey.
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>>
> >>>>
> >>
> >>
>
>