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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