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From Andrew Stitcher <astitc...@redhat.com>
Subject Initial results from reducing proton-c coding effort
Date Fri, 02 Mar 2018 16:06:18 GMT
I've now checked in my work to reduce some of the known coding overhead
in proton-c.

There were 3 parts to this:

1. Stop generating nulls at the end of described lists - if they are
not there the decoder must assume they are null - defualt values.

2. Generate nulls instead of default values everywhere possible - I may
have missed a few places, but have hit the commonly used frames -
transfers, flows and dispositions.

3. Generate LIST0 types instead of LIST8/LIST32 for zero length lists.
This is an optimisation then seems specifically to help frame
generation in a few places.

There are some known improvements that still need to happen to make
coding as efficient as I know about - these are in PROTON-1779 [1] and
PROTON-1780 [2]. These are omitting HEADER and PROPERTIES sections from
message payloads when they are all default; and generating LIST8/MAP8
types instead of LIST32/MAP32 where we can.

I performed 2 simple benchmarks agains 0.21 (which itself has some
simple improvements too):

1. The size of a minimum message payload:

Using this simple python:

from proton import *
m = Message()
d = m.encode()
print len(d)

The reduction is from 43 bytes in 0.21 to 8 bytes in 0.22.

If I'd measured the transfer frame I might have got a bigger reduction
as the transfer frame itself should be a bit smaller too. This leads

2. Bytes transferred using simple_send
[My measurement methodology is a little bit suspect, but should only be
10-30 bytes out for each measurement]

In this case I just ran simple_send.cpp with default settings (100
messages of around 20 bytes payload) against broker.cpp and recorded
the raw bytes from both ends using PN_TRACE_RAW=1.

In this case the reduction is from ~12100 for 0.21 to ~9000 for 0.22.
This is ~31 byte reduction per message overall including all changes -
I think this test had flows/dispositions every 10 messages.

Naturally, this reduction is going to be most noticeable when using
smaller message sizes.


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