Richard,
Am 07.01.21 um 07:15 schrieb Richard O'Keefe:
You aren't sure what point I was making?
exactly, the thread you answered was about a possible bug in NeoCSV
parser. Your post was about your doubts about the claim of efficiency on
the parser's web site. So you threw in some completely unrelated topic
and started by sounding more or less destructive (maybe this is a word
too harsh, but I am not a native english speaker... maybe "challenging"
is a better word?).
I cannot comment on the efficiency of NeoCSV, other than it is fast
enough for my use case and it gives me the option of combining reading
CSV and producing objects in one run, even if some checks,
backpointering, whatever has to be done after the parsing. It has a nice
API and is supported quite well. The thread and Sven's reaction
underline this last statement quite impressively: my bug was fixed
within hours.
How about the one I actually wrote down:
What test data was NeoCSV benchmarked with
and can I get my hands on it?
That is a valid question. It is off-topic in the thread, however. And
maybe your tone was a bit less kind than it should be. Nevertheless, the
discussion itself is worth its own thread. If the raw speed of reading
lots of CSV data is of concern in a use case, we should look for and at
alternatives. You are of course free to ask about alternatives, present
your measurements or alternative implementation and ask for comments,
ideas, all kinds of input. That's what yields progress.
THAT is the point. The data points I showed (and
many others I have not) are not satisfactory to me.
Fine and absolutely worth discussing. Maybe in its own discussion thread
and started with a friendly invitation for discussion. Your post was
more like "Oh, and, by the way, NeoCSV sucks". Maybe unintended, but
that is what I read.
I have been searching for CSV test collections.
One site offered 6 files of which only one downloaded.
I found a "benchmark suite" for CSV containing no
actual CSV files.
So where *else* should I look for benchmark data than
associated with a parser people in this community are
generally happy with that is described as "efficient"?
So you would like the developers of NeoCSV to provide test data that
allows for benchmarking and comparison? A valid point.
Is it so unreasonable to suspect that my results might
be a fluke? Is it bad manners to assume that something
described as efficient has tests showing that?
Well, no. It is absolutely okay to ask if a claim like "efficient" can
be proven. You are free to present better choices and discuss your
definition of efficiency.
For me personally, your post sounded a bit like some earlier ones of
yours which seemed to have no other point than "I have something better,
but I won't show you". Hence my reaction. I may have read something into
your post that you haven't written into it. Sorry for that.
Joachim
On Wed, 6 Jan 2021 at 22:23, jtuc...@objektfabrik.de
<mailto:jtuc...@objektfabrik.de> <jtuc...@objektfabrik.de
<mailto:jtuc...@objektfabrik.de>> wrote:
Richard,
I am not sure what point you are trying to make here.
You have something cooler and faster? Great, how about sharing?
You could make a faster one when it doesn't convert numbers and
stuff? Great. I guess the time will be spent after parsing in 95%
of the use cases. It depends. And that is exactly what you are
saying. The word efficient means nothing without context. How is
that related to this thread?
I think this thread mostly shows the strength of a community,
especially when there are members who are active, friendly and
highly motivated. My problem git solved in blazing speed without
me paying anything for it. Just because Sven thought my problem
could be other people's problem as well.
I am happy with NeoCSV's speed, even if there may be more
lightweigt and faster solutions. Tbh, my main concern with NeoCSV
is not speed, but how well I can understand problems and fix them.
I care about data types on parsing. A non-configurable csv parser
gives me a bunch of dictionaries and Strings. That could be a
waste of cycles and memory once you need the data as objects.
My use case is not importing trillions of records all day, and for
a few hundred or maybe sometimes thousands, it is good/fast enough.
Joachim
Am 06.01.21 um 05:10 schrieb Richard O'Keefe:
NeoCSVReader is described as efficient. What is that
in comparison to? What benchmark data are used?
Here are benchmark results measured today.
(5,000 data line file, 9,145,009 characters).
method time(ms)
Just read characters 410
CSVDecoder>>next 3415 astc's CSV reader (defaults). 1.26
x CSVParser
NeoCSVReader>>next 4798 NeoCSVReader (default state). 1.78
x CSVParser
CSVParser>>next 2701 pared-to-the-bone CSV reader. 1.00
reference.
(10,000 data line file, 1,544,836 characters).
method time(ms)
Just read characters 93
CSVDecoder>>next 530 astc's CSV reader (defaults). 1.26
x CSVParser
NeoCSVReader>>next 737 NeoCSVReader (default state). 1.75
x CSVParser
CSVParser>>next 421 pared-to-the-bone CSV reader. 1.00
reference.
CSVParser is just 78 lines and is not customisable. It really is
stripped to pretty much an absolute minimum. All of the parsers
were configured (if that made sense) to return an Array of Strings.
Many of the CSV files I've worked with use short records instead
of ending a line with a lot of commas. Some of them also have
the occasional stray comment off to the right, not mentioned in
the header.
I've also found it necessary to skip multiple lines at the beginning
and/or end. (Really, some government agencies seem to have NO idea
that anyone might want to do more with a CSV file than eyeball it in
Excel.)
If there is a benchmark suite I can use to improve CSVDecoder,
I would like to try it out.
On Tue, 5 Jan 2021 at 02:36, jtuc...@objektfabrik.de
<mailto:jtuc...@objektfabrik.de> <jtuc...@objektfabrik.de
<mailto:jtuc...@objektfabrik.de>> wrote:
Happy new year to all of you! May 2021 be an increasingly
less crazy
year than 2020...
I have a question that sounds a bit strange, but we have two
effects
with NeoCSVReader related to wrong definitions of the reader.
One effect is that reading a Stream #upToEnd leads to an
endless loop,
the other is that the Reader produces twice as many objects
as there are
lines in the file that is being read.
In both scenarios, the reason is that the CSV Reader has a
wrong number
of column definitions.
Of course that is my fault: why do I feed a "malformed" CSV
file to poor
NeoCSVReader?
Let me explain: we have a few import interfaces which end
users can
define using a more or less nice assistant in our
Application. The CSV
files they upload to our App come from third parties like
payment
providers, banks and other sources. These change their file
structures
whenever they feel like it and never tell anybody. So a CSV
import that
may have been working for years may one day tear a whole web
server
image down because of a wrong number of fieldAccessors. This
is bad on
many levels.
You can easily try the doubling effect at home: define a
working CSV
Reader and comment out one of the addField: commands before
you use the
NeoCSVReader to parse a CSV file. Say your CSV file has 3
lines with 4
columns each. If you remove one of the fieldAccessors, an
#upToEnd will
yoield an Array of 6 objects rather than 3.
I haven't found the reason for the cases where this leads to
an endless
loop, but at least this one is clear...
I *guess* this is due to the way #readEndOfLine is
implemented. It seems
to not peek forward to the end of the line. I have the gut
feeling
#peekChar should peek instead of reading the #next character
form the
input Stream, but #peekChar has too many senders to just go
ahead and
mess with it ;-)
So I wonder if there are any tried approaches to this problem.
One thing I might do is not use #upToEnd, but read each line
using
PositionableStream>>#nextLine and first check each line if
the number of
separators matches the number of fieldAccessors minus 1 (and
go through
the hoops of handling separators in quoted fields and
such...). Only if
that test succeeds, I would then hand a Stream with the whole
line to
the reader and do a #next.
This will, however, mean a lot of extra cycles for large
files. Of
course I could do this only for some lines, maybe just the
first one.
Whatever.
But somehow I have the feeling I should get an exception
telling me the
line is not compatible to the Reader's definition or such. Or
#readAtEndOrEndOfLine should just walk the line to the end
and ignore
the rest of the line, returnong an incomplete object....
Maybe I am just missing the right setting or switch? What
best practices
did you guys come up with for such problems?
Thanks in advance,
Joachim
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Objektfabrik Joachim Tuchel mailto:jtuc...@objektfabrik.de
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Telefon: +49 7141 56 10 86 0 Fax: +49 7141 56 10 86 1