So we could modify my #2 proposal to be sensitive to rle and compression 
chunks. If at the end of the row group, we wait until the rle and compression 
chunks close and interleave the streams. That means that for a column with 
three streams and two row groups, we could something like:


I think you mean #1 proposal, right? This modification will increase the 
complexity of implementation, and I am not sure how much we will gain by not 
closing compression and rle chunks. You probably have some data when you 
firstly designed row group and index.

Regarding double encoding, we actually have the 3rd option, which is to use 
what we already have today - PlainV2. According to Xu Cheng’s test, plainV2 is 
on par with Split in terms of the size when zStd is used as compressor. Flip is 
fast, but size has been a concern. At this point, I don’t see a clear winner.


On Mar 28, 2018, at 4:32 AM, Owen O'Malley 
<owen.omal...@gmail.com<mailto:owen.omal...@gmail.com>> wrote:

Going back to the point of double split encoding, it would make sense to try a 
variant where we combine the sign and the mantissa. That should remove the sign 
stream at a relatively little cost of making the mantissa stream signed.

Thinking more about the layout options...

Another consideration is that we'd be better off not splitting the compression 
chunks between ranges and yet I'm worried about the overhead of closing all of 
the compression chunks and rle runs early.

So we could modify my #2 proposal to be sensitive to rle and compression 
chunks. If at the end of the row group, we wait until the rle and compression 
chunks close and interleave the streams. That means that for a column with 
three streams and two row groups, we could something like:

stream1.1, stream2.1, stream3.1, stream1.2, stream2.2, stream3.2

stream x.y contains a whole number of compression chunks and the majority of 
the data for row group X is in the stream *.X. This significantly improves the 
current state of affairs because now we know that if we read stream *.1, we'll 
have the entire first row group and can start decompression and processing 
while we read the other "stripelets".

By not forcing the closure of the rle and compression, we have preserved the 
compression and yet gained the ability to have async io in the reader.

.. Owen


On Sun, Mar 25, 2018 at 11:47 PM, Gopal Vijayaraghavan 
<gop...@apache.org<mailto:gop...@apache.org>> wrote:

>    2. Under seek or predicate pushdown scenario, there’s no need to load the 
> entire stream.

Yes, that is a valid scenario where the reader reads partial-streams & causes 
random IO.

The current double encoding is actually 2 streams today & will continue to use 
2 streams for the FLIP implementation.

The SPLIT implementation will go from the current 2 streams to 4 streams (i.e 
1+1->1+3 streams) & the total data IO will drop by ~2x or so. More so if one of 
the streams can be suppressed (like in my IoT data-set, where the sign-bit is 
always +ve for my electric meter data).

The trade-offs seem to be working out on regular HDDs with locality & for LLAP 
SSD caches - if your use-cases are different, I'd like to hear more about it.

The only significant random IO delays expected seem to be entirely within the 
HDFS API network hops (which offers 0% locality when data is erasure coded or 
for cloud-storage), which I hope to fix in the Hadoop-3.x branch with a new API.

Cheers,
Gopal




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