I'm facing a challenge for one of my first projects as a junior dev. I'm using Talend to open some metadata files that have a series of "key=value" pairs within the files. I eventually need to transform the metadata and write it as a new row in an Excel file.
The metadata file looks something like this:
DOCTYPE=some_data
DOCNBR=some_data
DOCREV=some_data
DOCBASE=some_data
DOCNAME=some_data
RELEASE=some_data
DWG=TYPE=2;NAME=some_data;SIZE=some_data
DESCRIPTION=some_data
Line 7 of the example above (DWG=TYPE=2;NAME=some_data;SIZE=some_data) is what I'm stuck on when I'm attempting to create a new delimited metadata file, using "=" as the field separator and "\n" as the row separator.
Is there a way to have multiple row separators to include ";" so that I could have the other items on line 7 on their own rows?
Yes you can.
Write a regex which include \n and ; both and give it to the field delimiter field
Related
I am using a data flow in Synapse, the sink is Delimited text. I have to provide the output to a system that expects CR/LF (\r\n) as the row terminator.
Default (\r,\n, or \r\n)
returns \n (LF) only as the row terminator in all of my tests. Has anyone had this requirement and found a work around?
In DataFlow mapping for separating rows in Delimited text format there are certain default values:
To Read from file: "\r\n", "\r," or "\n"
To Write in file: "\n"
To workaround try by manually adding in dataflow script and running the pipeline.
rowDelimiter: '\r\n'
[pratiklad] (https://stackoverflow.com/users/18043699/pratiklad) has it right. As odd as it sounds CR/LF is not supported in data flow in sink. Seems the best I can do, if I am using a data flow, is to out to my storage account, then use copy activity to open the file and re-write it adding the CR/LF (\r\n).
You can concat a '\r' on the last column of your dataset and then it will read \r\n on the text or csv files.
The file format I have is sort of like csv and looks like this (abinitio .dat file of some sort):
1,apple,10.00,\n
2,banana,12.35,\n
3,orange,9.23,\n
The commas are actually "Start of Header" 0x01 byte characters, but I will use commas for simplicity. I can easily read the above sample by reading the file as a string RDD with a custom line split ,\n and then passing that into spark.read.csv. I am currently splitting lines by ,\n because there may be newlines in the data and I thought that those two characters were unique for each record. However a problem occurs when there are newline characters at the start of text fields. For example:
1,one \n apple,10.00,\n
2,two banana,12.35,\n
3,\n three orange,9.23,\n
My current code is able to ignore the newline in record 1 but picks up the ,\n after the 3 and splits the 3 lines into 4. How can I reliably read in this format?
My current ideas are:
Check that there are the right number of , column delimiters before allowing a split. I am not sure how to implement this, is it possible to do a regex look-back when spark sees a ,\n and check for the correct number of delimiters?
Try to coerce the file into some other format besides CSV
Make my own InputFormatClass, although I am not sure what this entails.
When exporting a column header from web menu to CSV in Robot framework, the language is polish the text identifies unknown charcters. How to encode it?
I don't think the problem you are seeing above is to do with encoding. The result from
Get column headers from CSV file isn't a list which is what your error is pointing too.
List Should Contain Sub List is expecting 2 lists as args
I am using Scala to parse CSV files. Some of these files have fields which are non-textual data like images or octet-streams. I would like to use Apache Spark's textFile() method to split up the CSV into rows, and
split(",[ ]*(?=([^\"]*\"[^\"]*\")*[^\"]*$)")
to split the row into fields. Unfortunatly this does not work with files that have these mentioned binary fields. There are two problems: 1) The octet-streams can contain newlines which make textFile() split rows which should be one, and 2) The octet-streams contain commas and/or double quotes which are not escaped and mess up my schema.
The files are usually big, couple of MBs up to couple of 100MBs. I have to take the CSV's as they are, although I could preprocess them.
All I want to achieve is a working split function so I can ignore the field with the octet-stream. Nevertheless, a great bonus would be to extract the textual information in the octet-stream.
So how would I go forward to solve my problems?
Edit: A typical record obtained with cat, the newlines are from the file, not for cosmetic purposes (shortened):
7,url,user,02/24/2015 02:29:00 AM,03/22/2015 03:12:36 PM,octet-stream,27156,"MSCF^#^#^#^#�,^#^#^#^#^#^#D^#^#^#^#^#^#^#^C^A^A^#^C^#^D^#^#^#^#^#^T^#^#^#^#^#^P^#�,^#^#^X=^#^#^#^#^#^#^#^#^#^#�^#^#^#^E^#^A^#��^A^#^#^#^#^#^#^#WF6�!^#Info.txt^#=^B^#^#��^A^#^#^#WF7�^#^#List.xml^#^�^#^#��^A^#^#^#WF:�^#^#Filename.txt^#��>��
^#�CK�]�r��^Q��T�^O�^#�-�j�]��FI�Ky��Ei�Je^K""!�^Qx #�*^U^?�^_�;��ħ�^LI^#$(�^Q���b��\N����t�����+������ȷgvM�^L̽�LǴL�^L��^ER��w^Ui^M��^X�Kޓ�^QJȧ��^N~��&�x�bB��D]1�^B|^G���g^SyG�����:����^_P�^T�^_�����U�|B�gH=��%Z^NY���,^U�^VI{��^S�^U�!�^Lpw�T���+�a�z�l������b����w^K��or��pH� ��ܞ�l��z�^\i=�z�:^C�^S!_ESCW��ESC""��g^NY2��s�� u���X^?�^R^R+��b^]^Ro�r���^AR�h�^D��^X^M�^]ޫ���ܰ�^]���0^?��^]�92^GhCx�DN^?
mY<{��L^Zk�^\���M�^V^HE���-Ե�$f�f����^D�e�^R:�u����� ^E^A�Ȑ�^B�^E�sZ���Yo��8Eސ�}��&JY���^A9^P������^P����~Jʭy��`�^9«�""�U� �:�}3���6�Hߧ�v���A7^Xi^L^]�sA�^Q�7�5d�^Xo˛�tY
Bp��4�Y���7DkV_���\^_q~�w�|�a�s̆���#�g�ӳu�^�!W}�n��Rgż_2�]�p�2}��b�G9�M^Q
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=r/X2�^O�����r^M�Rȕ�goG^X-����}���P+˥Qf�#��^C�Բ�z1�I�j����6�^Np���ܯ^P�[�^Tzԏ���^F2�e��\�E�6c�%���$�:E�*�*©t�y�J�,�S�2U�S�^X}ME�]��]�i��G�su�""��!�-��!r'ܷe_et Y^K^?0���l^A��^^�m�1/q����|�_r�5$�%�([x��W^E�G^^y���#����Z2^?ڠ�^_��^AҶ�OO��^]�vq%:j�^?�jX��\�]����^S�^^n�^C��>.^CY^O-� �_�\K����:p�<7Sֺnj���-Yk�r���^Q^M�n�J^B��^Z0^?�(^C��^W³!�g�Z�~R�A^M�^O^^�%;��Ԗ�p^S�w���*m^S���jڒ|�����<�^S�;Z^^Fc�1���^O�G_o����8��CS���w��^?��n�2~��m���G;��rx4�(�]�'��^E���eƧ�x��.�w�9WO�^^�י3��0,�y��H�Y�.H�x�""'���h}灢^T�Gm;^XE�̼�J��c�^^;�^A�qZ1ׁBZ^Q�^A^FB�^QbQ�_�3|ƺ�EvZ���^S�w���^P���9^MT��ǩY[+�+�9�Ԩ�^O�^Q���Fy(+�9p�^^Mj�2��Y^?��ڞ��^Ķb�^Z�ψMр}�ڣ�^^S�^?��^U�^Wڻ����z�^#��uk��k^^�>^O�^W�ݤO�h�^G�����Kˇ�.�R|�)-��e^G�^]�/J����U�ϴ�a���i5HO�^L�ESCg�R'���.����d���+~�}��ڝ^Y5]l�3jg54M�������2t�5^Y}�q)��^O;�X\�q^Ox~Vۗ�t�^\f� >k;^G�K5��,��X�t/�ǧ^G""5��4^MiΟ�n��^B^]�|�����V��ߌ֗Q~�H���8��t��5��ܗ�
�Z�^c�6N�ESCG����^_��>��t^L^R�^:�x���^]v�{^#+KM��qԎ�.^S�%&��=^W-�=�^S�����^CI���&^]_�s�˞�y�z�Jc^W�kڠ�^\��^]j�����^O��;�oY^^�^V59;�c��^B��T�nb����^C��^N��s�x�<{�9-�F�T�^N�5�^Se-���^T�Y[���`^ZsL��v�բ<C�+�~�^ۚ��""�Yκ2^_�^VxT�>��/ݳ^U�m�^#���3^Ge�n^Vc�V�^#�NVn�,�q��^^^]gy�R�S��Ȃ$���>A�d����xg�^GB3�M�J�^QJ^]�^\�{.�D��碎�^W�8a����qޠl?,'^R�^X�Cgy�P[����mڞ��H�Z�s�SD&蠤�s�E��nu�O#O<��3wj`C-%w�W�J�^WP^T�^]r^NT�TC�Lq�Z�f�!�;�l�Y��Gb��>�ud�hx�Ԭ^N)9�^N!k�҉s�35v������.�""^]��~4������۴�Z^]u�^Ti^^�i:�)K��P᳕!�#�^?�>��EE^VE-u�^SgV^L��<��^D�O<�+�J.�c�Z#>�.l����^S�
ESC��(��E�j�π쬖���2{^U&b\��P^S�`^O^XdL�^ 6bu��FD��^#^#^#^#","field_x, data",field_y,field_z
Expected output would be an array
("7","url","user","02/24/2015 02:29:00 AM","03/22/2015 03:12:36 PM","octet-stream","27156","field_x, data",field_y",field_z")
Or, but this is probably another question, such an array (like running strings on the octet-stream field):
("7","url","user","02/24/2015 02:29:00 AM","03/22/2015 03:12:36 PM","octet-stream","27156","Info.txt List.xml Filename.txt","field_x, data",field_y",field_z")
Edit 2: Every file that has a binary field also contains a length field for it. So instead of splitting directly I can walk left to right through my record and extract the fields. This is certainly a great improvement of my current situation but problem 1) still persists. How can I split those files reliably?
I took a closer look at the files and a header looks like this:
RecordId, Field_A, Content_Type, Content_Length, Content, Field_B
(Where Content_Type can be "octet-stream", Content_Length the number of bytes in the Content field, and Content obviously the data). And good for me, the value of Field_B is predictable, let's assume for a certain file it's always "Hello World".
So instead of using Spark's default behaviour splitting on newlines, how can I achieve that Spark is only splitting on newlines following "Hello World"? (I also edited the question title since the focus of the question changed)
As answered in Spark: Reading files using different delimiter than new line, I used textinputformat.record.delimiter to split on "Hello World\n" because I am a bit lucky that the last column always contains the same value. After that I simply walk left to right through the record and when I reach the length field I skip the next n bytes. Everything works now. Thanks for pointing me in the right direction.
There are two problems: 1) The octet-streams can contain newlines
which make textFile() split rows which should be one, and 2) The
octet-streams contain commas and/or double quotes which are not
escaped and mess up my schema.
Well, actually that csv file is properly escaped:
the multiline field is enclosed in double quotes: "MSCF^# .. ^#^#" (which also handles possible separators inside the field)
double quotes inside the field are escaped with another double quote as it should be: Je^K""!
Of course a simple split will not work in this case (and should never be used on csv data), but any csv reader able to handle multiline fields should parse that data correctly.
Also keep in mind that the double quotes inside the octet-stream have to be unescaped, or that data won't be valid (another reason not to use split, but a csv reader that handles this).
i've a large text file around 43GB in .ttl contains triples in the form :
<http://www.wikidata.org/entity/Q1001> <http://www.w3.org/2002/07/owl#sameAs> <http://la.dbpedia.org/resource/Mahatma_Gandhi> .
<http://www.wikidata.org/entity/Q1001> <http://www.w3.org/2002/07/owl#sameAs> <http://lad.dbpedia.org/resource/Mohandas_Gandhi> .
and i want to find the fastest way to update a specific line inside the file without rewriting all next text. either by updating it or deleting it and appending it to the end of the file
to access the specific line i use this code :
val lines = io.Source.fromFile("text.txt").getLines
val seventhLine = lines drop(10000000) next
If you want to use text files, consider a fixed length/record size for each line/record.
This way you can use a RandomAccessFile to seek to the exact position of each line by number: You just seek to line * LineSize, and then update it.
It will not really help, if you have to insert a new line. Other limitations are: The file size will grow (because of the fixed record length), and there will always be one record which is too big.
As for the initial conversion:
Get the maximum line length of the current file, then add 10% for example.
Now you have to convert the file once: Read a line from the text file, and convert it into a fixed-size record.
You could use a special character like | to separate the fields. If possible, use somthing like ;, so you get a .csv file
I suggest padding the remaining space it with spaces, so it still looks like a text file which you can parse with shell utilities.
You could use a \n to terminate the record.
For example
http://x.com|http://x.com|http://x.com|...\n
or
http://x.com;http://x.com;http://x.com;...\n
where each . at the end represents a space character. So it's still somehow compatible with a "normal" text file.
On the other hand, looking at your data, consider using a key-value data store like Redis: You could use the line number or the 1st URL as the key.