RE: bluestore onode encoding efficiency

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> -----Original Message-----
> From: Sage Weil [mailto:sage@xxxxxxxxxxxx]
> Sent: Thursday, June 16, 2016 9:47 AM
> To: Allen Samuels <Allen.Samuels@xxxxxxxxxxx>
> Cc: Mark Nelson <mnelson@xxxxxxxxxx>; Evgeniy Firsov
> <Evgeniy.Firsov@xxxxxxxxxxx>; Jianjian Huo <jianjian.huo@xxxxxxxxxxx>;
> Somnath Roy <Somnath.Roy@xxxxxxxxxxx>; Igor Fedotov
> <ifedotov@xxxxxxxxxxxx>; Manavalan Krishnan
> <Manavalan.Krishnan@xxxxxxxxxxx>; Varada Kari
> <Varada.Kari@xxxxxxxxxxx>; Ramesh Chander
> <Ramesh.Chander@xxxxxxxxxxx>; ceph-devel@xxxxxxxxxxxxxxx
> Subject: Re: bluestore onode encoding efficiency
> 
> Based on some of Allen's comments I've updated my branch with (so far)
> three different encoders:
> 
> 1) varint - general purpose small integers (lops off high and low zero
> bits)
> 
>   first byte:
>     low 2 bits = how many low nibbles of zeros
>     5 bits = data
>     1 high bit = another byte follows
>   subsequent bytes:
>     7 bits = data
>     1 high bit = another byte follows
> 
> 2) delta varint
> 
>   first byte:
>     1 low bit = sign (0 = positive, 1 = negative)
>     low 2 bits = how many low nibbles of zeros
>     4 bits = data
>     1 high bit = another byte follows
>   subsequent bytes:
>     7 bits = data
>     1 high bit = another byte follows
> 
> 3) raw lba:
> 
>   first 3 bytes:
>     low 2 bits = how many low bits of zeros
>       00 = none
>       01 = 12 (4k alignment)
>       10 = 16 (64k alignment)
>       11 = 20 (256k alignment)
>     21 bits = data
>     1 high bit = another byte follows
>   subsequent bytes:
>     7 bits = data
>     1 high bit = another byte follows

Let's do some math here :)

Let's say I want to optimize for 4, 8, 16 and 32 TB devices going forward.

That's 2^42, 43, 44 and 45 respectively.

If assume a 4K blocksize/alignment, then we need 30, 31, 32 and 33 significant bits after downshifting for encoding.

That means for 30 bits I'll have 21 + 7 + 2 encoded bits which requires 5 bytes for a 4TB device. However, 1/2 of the addresses only need 29 bits (and 1/4 need 28, etc.)
So the approximate blended size is about 4.75 Bytes for a 4TB (1/4 of the addresses can save a byte) 
And about 4.875 Bytes for 8TB (1/8 of the addresses can save a byte).
We won't need another byte until we operate on 128TB devices.

If we switch to 64K alignment (reasonable for many HDD use-cases), then the #'s change to be 26, 27, 28  and 29 respectively,

That's 21 + 5 for 4TB which gets encoded in 4 bytes. 8 and 16TB also take 4Bytes, you need 32TB before you need 5Bytes.

If we change the encoding above so that the first chunk is 4 bytes (easier to deal with :)) and leave everything alone, then we have 39 bits of mantissa
Now for a 4KB align / 4TB device you only need 4.5 Bytes which is a savings of .25 Bytes, which will could easily be significant when you have up to 1K phys addrs / oNode.

I could argue for a skew on the format encoding, i.e., 0x for 4K, 110 for 16K, 111 for byte align, ,etc. and gain another bit picking up a further .5 bytes on a 4TB device.

The 16-bit alignment case isn't materially affected by this.

In conclusion. I think -- at a minimum -- you should switch to a first 4 bytes (rather than a first 3 bytes) for this use case. It doesn't seem to have any negative and there are significant positives.

A weaker case would be to switch the two bit encoding to something that favored 4K (the likely most prevalent) alignment, picking up another bit before a multi-byte encoding is needed.

> 
> 4) lba delta (distance between two lba's, e.g., when encoding a list of
> extents)
> 
>   first byte:
>     1 low bit = sign (0 = positive, 1 = negative)
>     2 bits = how many low bits of zeros
>       00 = none
>       01 = 12 (4k alignment)
>       10 = 16 (64k alignment)
>       11 = 20 (256k alignment)
>     4 bits = data
>     1 bit = another byte follows
>   subsequent bytes:
>     7 bits = data
>     1 bit = another byte follows
> 
>   Notably on this one we have 4 bits of data *and* when we roll over to
>   the next value you'll get 4 trailing 0's and we ask for one
>   more nibble of trailing 0's... still in one encoded byte.
> 
> 
> I think this'll be a decent set of building blocks to encoding the existing
> structures efficiently (and still in a generic way) before getting specific with
> common patterns.
> 
> 	https://github.com/ceph/ceph/pull/9728/files
> 
> sage
> 
> 
> On Wed, 15 Jun 2016, Sage Weil wrote:
> >
> > If we have those, I'm not sure #1 will be worth it--the zeroed offset
> > fields will encode with one byte.
> >
> > > (3) re-jiggering of blob/extents when possible. Much of the
> > > two-level blob/extent map exists to support compression. When you're
> > > not compressed you can collapse this into a single blob and avoid
> > > the encoding overhead for it.
> >
> > Hmm, good idea.  As long as the csum parameters match we can do this.
> > The existing function
> >
> > int bluestore_onode_t::compress_extent_map()
> >
> > currently just combines consecutive lextent's that point to contiguous
> > regions in the same blob.  We could extend this to combine blobs that
> > are combinable.
> >
> > > There are other potential optimizations too that are artifacts of
> > > the current code. For example, we support different checksum
> > > algorithms/values on a per-blob basis. Clearly moving this to a
> > > per-oNode basis is acceptable and would simplify and shrink the
> > > encoding even more.
> >
> > The latest csum branch
> >
> >         https://github.com/ceph/ceph/pull/9526
> >
> > varies csum_order on a per-blob basis (for example, larger csum chunks
> > for compressed blobs and small csum chunks for uncompressed blobs with
> > 4k overwrites).  The alg is probably consistent across the onode, but
> > the will uglify the code a bit to pass it into the blob_t csum
> > methods.  I'd prefer to hold off on this.  With the varint encoding
> > above it'll only be one byte per blob at least.
> >
> > sage
> >
> > --
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