> 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 <alexey.goncha...@gmail.com> > 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 <dsetrak...@apache.org>: > >> On Wed, Aug 2, 2017 at 9:33 AM, Vladimir Ozerov <voze...@gridgain.com> >> 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 < >> dsetrak...@apache.org> >>> wrote: >>> >>>> On Wed, Aug 2, 2017 at 7:27 AM, Vladimir Ozerov <voze...@gridgain.com> >>>> 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 <dma...@apache.org>: >>>>> >>>>>>> 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, dsetrak...@apache.org 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 < >>>>>> voze...@gridgain.com> 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 <dma...@apache.org >>> >>>>> 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, dsetrak...@apache.org wrote: >>>>>>>>>> >>>>>>>>>> I prefer option #1. >>>>>>>>>> >>>>>>>>>> D. >>>>>>>>>> >>>>>>>>>> On Aug 1, 2017, 11:20 AM, at 11:20 AM, Sergey Chugunov < >>>>>>>>> sergey.chugu...@gmail.com> 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. >>>>>>>>> >>>>>>>>> >>>>>> >>>>>> >>>>> >>>> >>> >>
