subject:"RE\: GHC Performance \/ Replacement for R\?"

Re: GHC Performance / Replacement for R?

2016-08-31 Thread Dominic Steinitz


Hi Iavor,

Thank you very much for this. It's nice to know that we have the ability 
in Haskell to be as frugal (or profligate) with memory as R when working 
with data frames. I should say this number of fields is quite low in the 
data science world. Data sets with 500 columns are not uncommon and I 
did have one with 10,000 columns!


I know other folks have worked on producing something like data frames 
e.g. https://github.com/acowley/Frames and 
http://stla.github.io/stlapblog/posts/HaskellFrames.html for example but 
I wanted to remain in the world of relatively simple types and I haven't 
looked at its performance in terms of memory. On the plus side it did 
manage to read in the 10,000 column data set although ghc took about 5 
minutes to do the typechecking (I should say within ghci).


Just to mention that R is not the only language that has nice facilities 
for data exploration; python has a package called pandas: 
http://pandas.pydata.org.


I feel we still have a way to go to make Haskell provide as easy an 
environment for data exploration as R or Python but I shall continue on 
my crusade.


Many thanks once again, Dominic.


On 30/08/2016 22:05, Iavor Diatchki wrote:

Hello,

when you parse the CSV fully, you end up creating a lot of small 
bytestring objects, and each of these adds some overhead.   The 
vectors themselves add up some additional overhead.  All of this adds 
up when you have as many fields as you do.   An alternative would be 
to use a different representation for the data, which recomputes 
things when needed.   While this might be a bit slower in some cases, 
it could have significant saving in terms of memory use.   I wrote up 
a small example to illustrate what I have in mind, which should be 
attached to this e-mail.


Basically, instead of parsing the CSV file fully, I just indexed where 
the lines are (ref. the "rows" field of "CSV"). This allows me to 
access each row quickly, and the when I need to get a specific field, 
I simply parse the bytes of the row.
One could play all kinds of games like that, and I imagine R does 
something similar, although I have never looked at how it works.   To 
test the approach I generated ~200Mb of sample data (generator is also 
in the attached file), and I was able to filter it using ~240Mb, which 
is comparable to what you reported about R.  One could probably 
package all this up in library that supports "R like" operations.


These are the stats I get from -s:

   4,137,632,432 bytes allocated in the heap
 925,200 bytes copied during GC
 200,104,224 bytes maximum residency (2 sample(s))
   6,217,864 bytes maximum slop
 246 MB total memory in use (1 MB lost due to fragmentation)

 Tot time (elapsed)  Avg pause 
 Max pause
  Gen  0  7564 colls, 0 par0.024s   0.011s   0.s   
 0.0001s
  Gen  1 2 colls, 0 par0.000s   0.001s   0.0003s   
 0.0006s


  INITtime0.000s  (  0.000s elapsed)
  MUT time0.364s  (  0.451s elapsed)
  GC  time0.024s  (  0.011s elapsed)
  EXITtime0.000s  (  0.001s elapsed)
  Total   time0.388s  (  0.463s elapsed)

  %GC time   6.2%  (2.5% elapsed)

  Alloc rate11,367,122,065 bytes per MUT second

  Productivity  93.8% of total user, 78.6% of total elapsed

-Iavor




On Thu, Aug 25, 2016 at 3:31 AM, Simon Peyton Jones via 
Glasgow-haskell-users > wrote:


Sounds bad.  But it'll need someone with bytestring expertise to
debug.  Maybe there's a GHC problem underlying; or maybe it's
shortcoming of bytestring.

Simon

|  -Original Message-
|  From: Glasgow-haskell-users [mailto:glasgow-haskell-users-

| boun...@haskell.org ] On Behalf Of
Dominic Steinitz
|  Sent: 25 August 2016 10:11
|  To: GHC users >
|  Subject: GHC Performance / Replacement for R?
|
|  I am trying to use Haskell as a replacement for R but running
into two
|  problems which I describe below. Are there any plans to address the
|  performance issues I have encountered?
|
|   1. I seem to have to jump through a lot of hoops just to be
able to
|  select the data I am interested in.
|
|  {-# LANGUAGE ScopedTypeVariables #-}
|
|  {-# OPTIONS_GHC -Wall #-}
|
|  import Data.Csv hiding ( decodeByName )
|  import qualified Data.Vector as V
|
|  import Data.ByteString ( ByteString )
|  import qualified Data.ByteString.Char8 as B
|
|  import qualified Pipes.Prelude as P
|  import qualified Pipes.ByteString as Bytes import Pipes import
|  qualified Pipes.Csv as Csv import System.IO
|
|  import qualified Control.Foldl as L
|
|  main :: IO

Re: GHC Performance / Replacement for R?

2016-08-30 Thread Iavor Diatchki

Hello,

when you parse the CSV fully, you end up creating a lot of small bytestring
objects, and each of these adds some overhead.   The vectors themselves add
up some additional overhead.  All of this adds up when you have as many
fields as you do.   An alternative would be to use a different
representation for the data, which recomputes things when needed.   While
this might be a bit slower in some cases, it could have significant saving
in terms of memory use.   I wrote up a small example to illustrate what I
have in mind, which should be attached to this e-mail.

Basically, instead of parsing the CSV file fully, I just indexed where the
lines are (ref. the "rows" field of "CSV").  This allows me to access each
row quickly, and the when I need to get a specific field, I simply parse
the bytes of the row.
One could play all kinds of games like that, and I imagine R does something
similar, although I have never looked at how it works.   To test the
approach I generated ~200Mb of sample data (generator is also in the
attached file), and I was able to filter it using ~240Mb, which is
comparable to what you reported about R.  One could probably package all
this up in library that supports "R like" operations.

These are the stats I get from -s:

   4,137,632,432 bytes allocated in the heap
 925,200 bytes copied during GC
 200,104,224 bytes maximum residency (2 sample(s))
   6,217,864 bytes maximum slop
 246 MB total memory in use (1 MB lost due to fragmentation)

 Tot time (elapsed)  Avg pause  Max
pause
  Gen  0  7564 colls, 0 par0.024s   0.011s 0.s
 0.0001s
  Gen  1 2 colls, 0 par0.000s   0.001s 0.0003s
 0.0006s

  INITtime0.000s  (  0.000s elapsed)
  MUT time0.364s  (  0.451s elapsed)
  GC  time0.024s  (  0.011s elapsed)
  EXITtime0.000s  (  0.001s elapsed)
  Total   time0.388s  (  0.463s elapsed)

  %GC time   6.2%  (2.5% elapsed)

  Alloc rate11,367,122,065 bytes per MUT second

  Productivity  93.8% of total user, 78.6% of total elapsed

-Iavor




On Thu, Aug 25, 2016 at 3:31 AM, Simon Peyton Jones via
Glasgow-haskell-users  wrote:

> Sounds bad.  But it'll need someone with bytestring expertise to debug.
> Maybe there's a GHC problem underlying; or maybe it's shortcoming of
> bytestring.
>
> Simon
>
> |  -Original Message-
> |  From: Glasgow-haskell-users [mailto:glasgow-haskell-users-
> |  boun...@haskell.org] On Behalf Of Dominic Steinitz
> |  Sent: 25 August 2016 10:11
> |  To: GHC users 
> |  Subject: GHC Performance / Replacement for R?
> |
> |  I am trying to use Haskell as a replacement for R but running into two
> |  problems which I describe below. Are there any plans to address the
> |  performance issues I have encountered?
> |
> |   1. I seem to have to jump through a lot of hoops just to be able to
> |  select the data I am interested in.
> |
> |  {-# LANGUAGE ScopedTypeVariables #-}
> |
> |  {-# OPTIONS_GHC -Wall #-}
> |
> |  import Data.Csv hiding ( decodeByName )
> |  import qualified Data.Vector as V
> |
> |  import Data.ByteString ( ByteString )
> |  import qualified Data.ByteString.Char8 as B
> |
> |  import qualified Pipes.Prelude as P
> |  import qualified Pipes.ByteString as Bytes import Pipes import
> |  qualified Pipes.Csv as Csv import System.IO
> |
> |  import qualified Control.Foldl as L
> |
> |  main :: IO ()
> |  main = withFile "examples/787338586_T_ONTIME.csv" ReadMode $ \h -> do
> |let csvs :: Producer (V.Vector ByteString) IO ()
> |csvs = Csv.decode HasHeader (Bytes.fromHandle h) >-> P.concat
> |uvectors :: Producer (V.Vector ByteString) IO ()
> |uvectors = csvs  >-> P.map (V.foldr V.cons V.empty)
> |vec_vec <- L.impurely P.foldM  L.vector uvectors
> |print $ (vec_vec :: V.Vector (V.Vector ByteString)) V.! 17
> |print $ V.length vec_vec
> |let rockspring = V.filter (\x -> x V.! 8 == B.pack "RKS") vec_vec
> |print $ V.length rockspring
> |
> |  Here's the equivalent R:
> |
> |  df <- read.csv("787338586_T_ONTIME.csv")
> |  rockspring <- df[df$ORIGIN == "RKS",]
> |
> |   2. Now I think I could improve the above to make an environment that
> |  is more similar to the one my colleagues are used to in R but more
> |  problematical is the memory usage.
> |
> |   * 112.5M file
> |   * Just loading the source into ghci takes 142.7M
> |   * > foo <- readFile "examples/787338586_T_ONTIME.csv" > length foo
> | takes me up to 4.75G. But we probably don't want to do this!
> |   * Let's try again.
> |   * > :set -XScopedTypeVariables
> |   * > h <- openFile "examples/787338586_T_ONTIME.csv" ReadMode
> |   * > let csvs :: Producer (V.Vector ByteString) IO () = Csv.decode
> |  HasHeader (Bytes.fromHandle h) >-> P.concat
> |   * > let uvectors :: Producer (V.Vector ByteString) IO () = csvs  >->

RE: GHC Performance / Replacement for R?

2016-08-25 Thread Simon Peyton Jones via Glasgow-haskell-users

Sounds bad.  But it'll need someone with bytestring expertise to debug.  Maybe 
there's a GHC problem underlying; or maybe it's shortcoming of bytestring.  

Simon

|  -Original Message-
|  From: Glasgow-haskell-users [mailto:glasgow-haskell-users-
|  boun...@haskell.org] On Behalf Of Dominic Steinitz
|  Sent: 25 August 2016 10:11
|  To: GHC users 
|  Subject: GHC Performance / Replacement for R?
|  
|  I am trying to use Haskell as a replacement for R but running into two
|  problems which I describe below. Are there any plans to address the
|  performance issues I have encountered?
|  
|   1. I seem to have to jump through a lot of hoops just to be able to
|  select the data I am interested in.
|  
|  {-# LANGUAGE ScopedTypeVariables #-}
|  
|  {-# OPTIONS_GHC -Wall #-}
|  
|  import Data.Csv hiding ( decodeByName )
|  import qualified Data.Vector as V
|  
|  import Data.ByteString ( ByteString )
|  import qualified Data.ByteString.Char8 as B
|  
|  import qualified Pipes.Prelude as P
|  import qualified Pipes.ByteString as Bytes import Pipes import
|  qualified Pipes.Csv as Csv import System.IO
|  
|  import qualified Control.Foldl as L
|  
|  main :: IO ()
|  main = withFile "examples/787338586_T_ONTIME.csv" ReadMode $ \h -> do
|let csvs :: Producer (V.Vector ByteString) IO ()
|csvs = Csv.decode HasHeader (Bytes.fromHandle h) >-> P.concat
|uvectors :: Producer (V.Vector ByteString) IO ()
|uvectors = csvs  >-> P.map (V.foldr V.cons V.empty)
|vec_vec <- L.impurely P.foldM  L.vector uvectors
|print $ (vec_vec :: V.Vector (V.Vector ByteString)) V.! 17
|print $ V.length vec_vec
|let rockspring = V.filter (\x -> x V.! 8 == B.pack "RKS") vec_vec
|print $ V.length rockspring
|  
|  Here's the equivalent R:
|  
|  df <- read.csv("787338586_T_ONTIME.csv")
|  rockspring <- df[df$ORIGIN == "RKS",]
|  
|   2. Now I think I could improve the above to make an environment that
|  is more similar to the one my colleagues are used to in R but more
|  problematical is the memory usage.
|  
|   * 112.5M file
|   * Just loading the source into ghci takes 142.7M
|   * > foo <- readFile "examples/787338586_T_ONTIME.csv" > length foo
| takes me up to 4.75G. But we probably don't want to do this!
|   * Let's try again.
|   * > :set -XScopedTypeVariables
|   * > h <- openFile "examples/787338586_T_ONTIME.csv" ReadMode
|   * > let csvs :: Producer (V.Vector ByteString) IO () = Csv.decode
|  HasHeader (Bytes.fromHandle h) >-> P.concat
|   * > let uvectors :: Producer (V.Vector ByteString) IO () = csvs  >->
|  P.map (V.map id) >-> P.map (V.foldr V.cons V.empty)
|   * > vec_vec :: V.Vector (V.Vector ByteString) <- L.impurely P.foldM
|  L.vector uvectors
|   * Now I am up at 3.17G. In R I am under 221.3M.
|   * > V.length rockspring takes a long time to return 155 and now I am
| at 3.5G!!! In R > rockspring <- df[df$ORIGIN == "RKS",] seems
| instantaneous and now uses only 379.5M.
|   * > length(rockspring) 37 > length(df$ORIGIN) 471949 i.e. there are
| 37 columns and 471,949 rows.
|  
|  Running this as an executable gives
|  
|  ~/Dropbox/Private/labels $ ./examples/BugReport +RTS -s ["2014-01-
|  01","EV","20366","N904EV","2512","10747","1074702","30747",
|   "BRO","Brownsville, TX","Texas","11298","1129803","30194",
|"DFW","Dallas/Fort Worth, TX","Texas","0720","0718",
|"-2.00","8.00","0726","0837","7.00","0855","0844","-11.00","0.00",
|"","0.00","482.00","","","","","",""]
|  471949
|  155
|14,179,764,240 bytes allocated in the heap
| 3,378,342,072 bytes copied during GC
|   786,333,512 bytes maximum residency (13 sample(s))
|36,933,976 bytes maximum slop
|  1434 MB total memory in use (0 MB lost due to
|  fragmentation)
|  
|   Tot time (elapsed)  Avg pause
|  Max pause
|Gen  0 26989 colls, 0 par1.423s   1.483s 0.0001s
|  0.0039s
|Gen  113 colls, 0 par1.005s   1.499s 0.1153s
|  0.6730s
|  
|INITtime0.000s  (  0.003s elapsed)
|MUT time3.195s  (  3.193s elapsed)
|GC  time2.428s  (  2.982s elapsed)
|EXITtime0.016s  (  0.138s elapsed)
|Total   time5.642s  (  6.315s elapsed)
|  
|%GC time  43.0%  (47.2% elapsed)
|  
|Alloc rate4,437,740,019 bytes per MUT second
|  
|Productivity  57.0% of total user, 50.9% of total elapsed
|  
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Re: GHC Performance / Replacement for R?

Re: GHC Performance / Replacement for R?

RE: GHC Performance / Replacement for R?

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