Sphinx indexer «No error» error - mysql

I have 25GB TSV file and trying to import it with command:
D:\sphinx\bin>indexer.exe -c D:\sphinx\sphinx.conf products --rotate
It works some time, but then shows error
ERROR: index 'products': source 'products_tsv': read error 'No error' (line=4595827, pos=908, docid=4595827).
But record at line 4595827 have no problems.
I have two questions:
What's usually causes this problem?
Does indexer have any flags for ignoring errors?


Lost a lot of time on checking datafile and found a lot of hidden symbols such as SYM (\U001A), NULL (\0000) and a more of them, which turns Sphinx crazy.
Simply(if «simply» can be said about 25GB file) replaced all SYM to ' and removed others.
We moved forward and faced another issue, but this is another question.


Try to add extra line break after the last line in your .tsv data source, so the last line is empty. In my case it helped. Thanks to #stefobark and his repository stefobark/index_tsv

Related

Admin import - Group not found

I am trying to load multiple csv files into a new db using the neo4j-admin import tool on a machine running Debian 11. To try to ensure there's no collisions in the ID fields, I've given every one of my node and relationship files.
However, I'm getting this error:
org.neo4j.internal.batchimport.input.HeaderException: Group 'INVS' not found. Available groups are: [CUST]
This is super frustrating, as I know that the INV group definitely exists. I've checked every file that uses that ID Space and they all include it.Another strange thing is that there are more ID spaces than just the CUST and INV ones. It feels like it's trying to load in relationships before it finishes loading in all of the nodes for some reason.
Here is what I'm seeing when I search through my input files
$ grep -r -h "(INV" ./import | sort | uniq
:ID(INVS),total,:LABEL
:START_ID(INVS),:END_ID(CUST),:TYPE
:START_ID(INVS),:END_ID(ITEM),:TYPE
The top one is from my $NEO4J_HOME/import/nodes folder, the other two are in my $NEO4J_HOME/import/relationships folder.
Is there a nice solution to this? Or have I just stumbled upon a bug here?
Edit: here's the command I've been using from within my $NEO4J_HOME directory:
neo4j-admin import --force=true --high-io=true --skip-duplicate-nodes --nodes=import/nodes/\.* --relationships=import/relationships/\.*

Indeed, such a thing would be great, but i don't think it's possible at the moment.
Anyway it doesn't seems a bug.
I suppose it may be a wanted behavior and / or a feature not yet foreseen.
In fact, on the documentation regarding the regular expression it says:
Assume that you want to include a header and then multiple files that matches a pattern, e.g. containing numbers.
In this case a regular expression can be used
while on the description of --nodes command:
Node CSV header and data. Multiple files will be
logically seen as one big file from the
perspective of the importer. The first line must
contain the header. Multiple data sources like
these can be specified in one import, where each
data source has its own header.
So, it appears that the neo4j-admin import considers the --nodes=import/nodes/\.* as a single .csv with the first header found, hence the error.
Contrariwise with more --nodes there are no problems.

What is causing a csv load error in weka?

Im receiving the following error when trying to open a CSV file in Weka version 3.8.5
File not recognized as an 'CSV data files' file Reason: wrong number
of values. Read 2, expected 12, read Token [EOL], Line 2 Problem
encountered on Line:2
I have read solutions to similar errors on this site and can't seem to find what is wrong with my particular file. However, as a very newbie weka user, it may just be my misunderstanding of the issue. Can someone take a look at the sample csv data below and let me know if you see what I am not understnding or missing?
LossMonth,LossYear,ClaimNumber,PolicyNumber,ClaimBranch,Agency,LocationCounty,CATCode,CauseCode,IncurredLoss,CurrentReserves,"
City",State,ZIPCODE,"
COLLISIONTYPECD","
CLOSEDDT",DaystoCLose,"
FATALITYCNT","
FATALITYIND","
FAULTRATINGIND","
AUTOGLASSIND","
DEERLOSSIND","
WEATHERRELATEDIND","
POLICYTIERCD",ClaimStatus,AgencyHandled,VEHICLEYEAR,DRIVERRELATIONTOINSUREDDESC,TOTALLOSSIND,INSURANCESCORE,Age
10,2016,4125858,20169200,4,113,73,1,comp,2525,0,PADUCAH,KY,42001,x,42692,18,0,0,0,0,0,1,70,1,0,2004,Other third party,0,703,73
1,2018,4265645,20137828,13,106,37,1,hail,3164,0,BAGDAD,KY,40003,x,43214,88,0,0,0,0,0,0,50,1,0,2010,Named Insured,1,799,63
12,2016,4136759,20322058,5,105,105,1,hail,2547,0,GEORGETOWN,KY,40324,x,42713,2,0,0,0,0,0,0,10,1,0,2010,Named Insured,0,999,68
1,2016,4033032,20175699,13,106,106,1,comp,15327,0,SIMPSONVILLE,KY,40067,x,42469,73,0,0,0,0,0,1,80,1,0,2000,Named Insured,1,999,34
9,2016,4116782,20133146,2,115,115,1,wind,7529,0,SPRINGFIELD,KY,40069,x,42649,8,0,0,0,0,0,0,10,1,0,2003,Named Insured,0,783,47
2,2016,4038442,20170355,7,148,10,1,hail,3631,0,ASHLAND,KY,41101,x,42417,1,0,0,0,0,0,0,50,1,0,2010,Named Insured,0,778,42
2,2016,4039439,20218265,7,45,10,1,hail,3579,0,FLATWOODS,KY,41139,x,42444,25,0,0,0,0,0,0,40,1,0,2013,Named Insured,0,820,52
2,2016,4039440,20218265,7,45,10,1,hail,570,0,FLATWOODS,KY,41139,x,42422,3,0,0,0,0,0,0,40,1,0,2012,Named Insured,0,820,52
3,2018,4275810,20126522,15,40,40,1,hail,3747,0,LANCASTER,KY,40444,x,43216,55,0,0,0,0,0,0,10,1,0,2009,Named Insured,1,999,74
5,2016,4071936,20461965,15,40,40,1,hail,525,0,LANCASTER,KY,40444,x,42521,7,0,0,0,0,0,0,50,1,0,2006,Named Insured,0,999,68
3,2016,4046685,20226270,7,35,35,1,hail,3558,0,FLEMINGSBURG,KY,41041,x,42447,2,0,0,0,0,0,0,80,1,0,2012,Named Insured,0,842,69
4,2016,4055942,20439287,7,35,35,1,hail,2551,0,EWING,KY,41039,x,42475,1,0,0,0,0,0,0,70,1,0,2006,Named Insured,0,867,48
1,2016,4026514,20394097,7,148,10,1,hail,1350,0,ASHLAND,KY,41101,x,42376,3,0,0,0,0,0,0,40,1,0,2007,Named Insured,0,637,65
3,2016,4047152,20212062,15,141,76,1,hail,1739,0,BEREA,KY,40403,x,42473,27,0,0,0,0,0,0,80,1,0,2008,Named Insured,0,777,77
2,2016,4035512,20103029,15,40,40,1,hail,2008,0,LANCASTER,KY,40444,x,42405,1,0,0,0,0,0,0,0,1,0,2000,Named Insured,1,885,72
1,2016,4030456,20385643,15,120,40,1,hail,1497,0,LANCASTER,KY,40444,x,42450,62,0,0,0,0,0,0,20,1,0,2013,Named Insured,0,839,65
4,2016,4053299,20251610,5,69,11,1,hail,1535,0,DANVILLE,KY,40422,x,42514,48,0,0,0,0,0,0,100,1,0,2013,Insured,0,999,64
6,2016,4076264,20337992,17,140,1,1,hail,1799,0,MILLTOWN,KY,42728,x,42529,2,0,0,0,0,0,0,50,1,0,2002,Named Insured,0,999,84
8,2017,4217498,20596983,8,86,86,1,hail,660,0,TOMPKINSVILLE,KY,42167,x,42954,0,0,0,0,0,0,0,100,1,0,2012,Named Insured,0,999,45
1,2016,4026053,20511114,4,113,113,1,hail,1310,0,STURGIS,KY,42459,x,42376,3,0,0,0,0,0,0,100,1,0,2003,Named Insured,0,694,44
1,2016,4026766,20656586,4,113,113,1,hail,2360,0,MORGANFIELD,KY,42437,x,42383,9,0,0,0,0,0,0,20,1,0,2010,Named Insured,0,999,89
1,2016,4027473,20085251,6,42,42,1,hail,1699,0,MAYFIELD,KY,42066,x,42381,5,0,0,0,0,0,0,90,1,0,2008,Named Insured,0,747,50
1,2016,4029284,20167051,17,109,109,1,wind,3133,0,CAMPBELLSVILLE,KY,42718,x,42387,5,0,0,0,0,0,0,10,1,0,1993,Named Insured,0,886,78
1,2016,4031937,20326278,3,81,12,1,comp,3385,0,FOSTER,KY,41043,x,42402,8,0,0,0,0,0,1,40,1,0,2003,Named Insured,0,723,79
1,2016,4027931,20339366,8,107,107,1,wind,5858,0,FRANKLIN,KY,42134,x,42447,70,0,0,0,0,0,0,20,1,0,2014,Named Insured,0,940,80
1,2016,4028456,20453076,15,87,87,1,comp,2056,0,JEFFERSONVILLE,KY,40337,x,42387,7,0,0,0,0,0,1,100,1,0,2013,Named Insured,0,999,51
1,2016,4028597,20051661,4,113,113,1,hail,5320,0,WAVERLY,KY,42462,x,42712,332,0,0,0,0,0,0,20,1,0,2014,Named Insured,0,717,58
3,2016,4046687,20018268,6,42,42,1,hail,2736,0,MAYFIELD,KY,42066,x,42450,5,0,0,0,0,0,0,110,1,0,2012,Named Insured,0,735,73
9,2016,4116499,20128172,3,96,59,1,glss,320,0,TAYLOR MILL,KY,41015,x,42660,20,0,0,0,0,0,1,0,1,0,1997,Spouse,0,923,81
1,2016,4026247,20086164,4,113,113,1,hail,1611,0,MORGANFIELD,KY,42437,x,42376,3,0,0,0,0,0,0,10,1,0,2013,Named Insured,0,902,61
1,2016,4027222,20033936,6,79,79,1,glss,105,0,CALVERT CITY,KY,42029,x,42389,14,0,0,0,0,0,1,110,1,0,2001,Named Insured,0,772,57
1,2016,4028311,20059964,4,75,75,1,comp,1040,0,SACRAMENTO,KY,42372,x,42382,2,0,0,0,0,0,1,10,1,0,1996,Named Insured,0,999,64
1,2016,4029164,20541039,6,42,42,1,wind,1495,0,SEDALIA,KY,42079,x,42382,0,0,0,0,0,0,0,0,1,0,2008,Named Insured,0,756,67
1,2016,4027475,20085251,6,42,42,1,hail,940,0,MAYFIELD,KY,42066,x,42381,5,0,0,0,0,0,0,90,1,0,2013,Named Insured,0,747,50
1,2016,4030356,20007300,4,117,117,1,hail,6550,0,DIXON,KY,42409,x,42436,49,0,0,0,0,0,0,40,1,0,2009,Named Insured,0,864,34

Weka's CSVLoader cannot handle rows that span multiple lines (despite quoting). Once all your rows (header and data) are one per line, you should be fine.
The common-csv (unofficial) Weka package should be able to handle rows spanning multiple lines.

Error in a line on big CSV imported to BigQuery

I'm trying to import a big CSV file to BigQuery (2.2 GB+). This is the error I get:
"Error while reading data, error message: CSV table references column position 33, but line starting at position:254025076 contains only 26 columns."
There are more errors on that file – and on that file only, out of one per state. Usually I would skip the faulty lines, but then I would lose a lot of data.
What can be a good way to check and correct the errors in a file that big?
EDIT: This is what seems to happen in the file. It's one single line and it breaks between "Instituto" and "Butantan". As a result, BigQuery parses it as one line with 26 columns and another with nine columns. That repeats a lot.
As far as I've seen, it's just with Butantan, but sometimes the first word is described differently (I caught "Instituto" and "Fundação"). Can I correct that maybe with grep on the command line? If so, what syntax?

Actually 2.2GB is quite manageble size. It can be quickly pre-processed with command line tools or simple python script on any +/- modern laptop/desktop or on a small VM in GCP.
You can start from looking at the problematic row:
head -n 254025076 your_file.csv | tail -n 1
If problematic rows just have missing values for last columns - you can use "--allow_jagged_rows" loading CSV option.
Otherwise I'm usually using simple python script like this:
import fileinput
def process_line(line):
# your logic to fix line
return line
if __name__ == '__main__':
for line in fileinput.input():
print(process_line(line))
and run it with:
cat your_file.csv | python3 preprocess.py > new_file.csv
UPDATE:
For newline characters in value - try BigQuery "Allow quoted newlines" option.

powerline jason messed up after trying to restart using "powerline-daemon --replace"

I tried installing powerline for bash linux. It was working fine with all the changes for git etc..
By mistake I typed powerline-daemon --replace and from then I started getting this error,
Expecting ',' delimiter: line 13 column 6 (char 147).
Any clue what could be the issue. I did check all the json files for the , delimiters, wherever I added the git related codes but unable to find any the reason. I tried doing the below command but the results are same.
powerline-daemon k and then powerline-damen q
Any help/suggestion would be really helpful.

Got it resolved.
Missed , while adding new segments.
Also used // for comments and looks like its not possible in the json.

Premature end of line Weka error

I'm new to Weka and I have to use it for a University project. So, I created a .csv file and when I try to upload it to Weka, it says: "not recognised as a CSV data file. Reason: 1 problem encountered on line 2".
Then, if I open the .csv file with Notepad and then save as .arff file, when I try to open it again with Weka, in this case I get another error message: "not recognised as an arff data file. Reason: premature end of line, read Token[EOL], line 8".
Please help, I don't know much about working with Weka and really don't know what could be the problem, even though I did a lot of research about this problem.
This is the file: https://app.box.com/s/adfpf1zatgpl5mo20u5hdd1gnqihnq40
#Relation "PIB_Rata inflatiei"
#Attribute "PIB" NUMERIC
#Attribute "Rata_inflatiei" NUMERIC
#Data
30624.3,20780.9,27980.4,31920.3,37657.0,37168.3,35838.9,41978.0,36183.4,37439.0,40717.1,46174.0,59867.6,76217.6,99699.2,123533.7,171540.2,208185.1,167421.6,167998.1,185362.3,171664.6,191548.1,199325.9,177956.0
128.0,211.2,255.2,136.8,32.2,38.8,154.8,59.1,45.8,45.7,34.5,22.5,15.3,11.3,9.0,6.6,4.8,7.8,5.6,6.1,5.8,3.3,4.0,1.1,-0.6

In the ARFF format (as well as CSV) instances are rows, and attributes are columns.
Your file thus has too many columns, ever row must have exactly.two values.