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From Dmitriy Setrakyan <dsetrak...@apache.org>
Subject Re: Data compression design proposal
Date Tue, 27 Mar 2018 00:03:00 GMT
AG,

I would also ask about the compression itself. How and where do we store
the compression meta information? We cannot be compressing every page
separately, it will not be effective. However, if we try to store the
compression metadata, how do we make other nodes aware of it? Has this been
discussed?

D.

On Mon, Mar 26, 2018 at 8:53 AM, Alexey Goncharuk <
alexey.goncharuk@gmail.com> wrote:

> Guys,
>
> How does this fit the PageMemory concept? Currently it assumes that the
> size of the page in memory and the size of the page on disk is the same, so
> only per-entry level compression within a page makes sense.
>
> If you compress a whole page, how do you calculate the page offset in the
> target data file?
>
> --AG
>
> 2018-03-26 17:39 GMT+03:00 Vladimir Ozerov <vozerov@gridgain.com>:
>
> > Gents,
> >
> > If I understood the idea correctly, the proposal is to compress pages on
> > eviction and decompress them on read from disk. Is it correct?
> >
> > On Mon, Mar 26, 2018 at 5:13 PM, Anton Vinogradov <av@apache.org> wrote:
> >
> > > + 1 to Taras's vision.
> > >
> > > Compression on eviction is a good case to store more.
> > > Pages at memory always hot a real system, so complession in memory will
> > > definetely slowdown the system, I think.
> > >
> > > Anyway, we can split issue to "on eviction compression" and to
> "in-memory
> > > compression".
> > >
> > >
> > > 2018-03-06 12:14 GMT+03:00 Taras Ledkov <tledkov@gridgain.com>:
> > >
> > > > Hi,
> > > >
> > > > I guess page level compression make sense on page loading / eviction.
> > > > In this case we can decrease I/O operation and performance boost can
> be
> > > > reached.
> > > > What is goal for in-memory compression? Holds about 2-5x data in
> memory
> > > > with performance drop?
> > > >
> > > > Also please clarify the case with compression/decompression for hot
> and
> > > > cold pages.
> > > > Is it right for your approach:
> > > > 1. Hot pages are always decompressed in memory because many
> read/write
> > > > operations touch ones.
> > > > 2. So we can compress only cold pages.
> > > >
> > > > So the way is suitable when the hot data size << available RAM size.
> > > >
> > > > Thoughts?
> > > >
> > > >
> > > > On 05.03.2018 20:18, Vyacheslav Daradur wrote:
> > > >
> > > >> Hi Igniters!
> > > >>
> > > >> I’d like to do next step in our data compression discussion [1].
> > > >>
> > > >> Most Igniters vote for per-data-page compression.
> > > >>
> > > >> I’d like to accumulate  main theses to start implementation:
> > > >> - page will be compressed with the dictionary-based approach
> (e.g.LZV)
> > > >> - page will be compressed in batch mode (not on every change)
> > > >> - page compression should been initiated by an event, for example,
a
> > > >> page’s free space drops below 20%
> > > >> - compression process will be under page write lock
> > > >>
> > > >> Vladimir Ozerov has written:
> > > >>
> > > >>> What we do not understand yet:
> > > >>>> 1) Granularity of compression algorithm.
> > > >>>> 1.1) It could be per-entry - i.e. we compress the whole entry
> > content,
> > > >>>> but
> > > >>>> respect boundaries between entries. E.g.: before -
> > [ENTRY_1][ENTRY_2],
> > > >>>> after - [COMPRESSED_ENTRY_1][COMPRESSED_ENTRY_2] (as opposed
to
> > > >>>> [COMPRESSED ENTRY_1 and ENTRY_2]).
> > > >>>> v1.2) Or it could be per-field - i.e. we compress fields,
but
> > respect
> > > >>>> binary
> > > >>>> object layout. First approach is simple, straightforward,
and will
> > > give
> > > >>>> acceptable compression rate, but we will have to compress
the
> whole
> > > >>>> binary
> > > >>>> object on every field access, what may ruin our SQL performance.
> > > Second
> > > >>>> approach is more complex, we are not sure about it's compression
> > rate,
> > > >>>> but
> > > >>>> as BinaryObject structure is preserved, we will still have
fast
> > > >>>> constant-time per-field access.
> > > >>>>
> > > >>> I think there are advantages in both approaches and we will be
able
> > to
> > > >> compare different approaches and algorithms after prototype
> > > >> implementation.
> > > >>
> > > >> Main approach in brief:
> > > >> 1) When page’s free space drops below 20% will be triggered
> > compression
> > > >> event
> > > >> 2) Page will be locked by write lock
> > > >> 3) Page will be passed to page’s compressor implementation
> > > >> 4) Page will be replaced by compressed page
> > > >>
> > > >> Whole object or a field reading:
> > > >> 1) If page marked as compressed then the page will be handled by
> > > >> page’s compressor implementation, otherwise, it will be handled
as
> > > >> usual.
> > > >>
> > > >> Thoughts?
> > > >>
> > > >> Should we create new IEP and register tickets to start
> implementation?
> > > >> This will allow us to watch for the feature progress and related
> > > >> tasks.
> > > >>
> > > >>
> > > >> [1] http://apache-ignite-developers.2346864.n4.nabble.com/Data-
> > > >> compression-in-Ignite-tc20679.html
> > > >>
> > > >>
> > > >>
> > > > --
> > > > Taras Ledkov
> > > > Mail-To: tledkov@gridgain.com
> > > >
> > > >
> > >
> >
>

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