I have a multiselect list parameter and two of the options have commas in them, well SSRS passes parameters with commas in it so its not registering the right value for it. how do i go around this?
multi list parameter examples-
option1, this is option one.
option2, this is option two, 2.
option three.
option four.
right now i have my code set up where i have WHEN Field in (#Param split string function that splits on commas).
i added this where clause and it helped show results from the parameter value with the commas,
Where ([Param]) collate database_default IN(SELECT Value FROM dbo.FnSplit(#Param,';'))
but now i cannot select more than one parameter at a time because i get an error message
An Error Occurred During Local Report Processing.
An Error has occurred during report porcessing.
Cannot Read the next data row for the dataset Dataset1.
String or binary data would be truncated.
Any clues as to whats my next step?
You shouldn't need to use a string split. Just use:
WHERE Value IN (#Param)
SQL Server will handle the commas automatically.
Related
I have some data in a text file in the following format:
1079,40,011,1,301 17,310 4,668 6,680 1,682 1,400 7,590 2,591 139,592 332,565 23,568 2,569 2,595 1,471 1,470 10,481 12,540 117,510 1,522 187,492 9,533 41,558 15,555 12,556 9,558 27,546 1,446 1,523 4000,534 2000,364 1,999/
1083,40,021,1,301 4,310 2,680 1,442 1,400 2,590 2,591 90,592 139,595 11,565 6,470 2,540 66,522 4,492 1,533 19,546 3,505 1,523 3000,534 500,999/
These examples represent what would be two rows in a spreadsheet. The first four values (in the first example, "1079,40,011,1") each go into their own column. The rest of the data are in a paired format, first listing a name of a column, designated by a number, then a space followed by the value that should appear in that column. So again, example: 301 17,310 4,668 6: in this row, column 301 has a value of 17, column 310 has value of 4, column 668 has value of 6, etc. Then 999/ indicates an end to that row.
Any suggestions on how I can transform this text file format into a usable spreadsheet would be greatly appreciated. There are thousands of "rows" and so can't just manually convert them and I don't possess the coding skills to execute such a transformation myself.
This is messy but since there is a pattern it should be doable. What software are you using?
My first idea would be to identify when the delimeter changes from comma to space. Is it based on a fixed width, like always after 14 characters? Or is it based on the delimiter, like it is always after the 4th comma?
Once you've done that, you could make two passes at the data. The first pass imports the first four values from the beginning of the line which are separated by comma. The second pass imports the remaining values which are separated by space.
If you include a row number when importing you can then use it to join first and second passes at importing.
So I have a dataset which I want to export to csv with pipe as separator and no escape character.
That dataset contains in fact 4 source columns, 3 regular ones (just text) and one variable one.
That last column holds another subset of values that are also separated with a pipe.
Purpose is that the export looks like this, where the values are coming from my 4th field.
COL1|COL2|COL3|VAL1|VAL2|VAL3|....
The number of values can be different for each record but.
When I set the csv export separator to ";", I get this result which is expected
COL1;COL2;COL3;VAL1|VAL2|VAL3|....
However setting it to "|", it throws the error DF-CSVWriter-InvalidEscapeSetting.
Most likely because it detected the separator character in my 4th field and then enforces that an escape character needs to be set.
Which is a logical thing in most case but in my case I would like him to ignore this and just export as-is.
Any way how I can work around this, perhaps with a different approach or some additional settings?
Split & flatten produces extra rows but that's not what I want.
Regards,
Sven Peeters
As you have the same characters in the column value same as your delimiter character, with no escape character in your dataset will throw an error.
You have to change the delimiter character to a different character or add a Quote character and Escape character to Double quote(").
Downloaded file:
I'm trying to change the value of nulls to something else that can be used to filter. This data comes from a QVD file. The field that contains nulls, contains nulls due to no action taken on those items ( they will eventually change to something else once an action has been taken). I found this link which was very informative but i tried multiple solutions from the document to no avail.
What i don't quite understand is that whenever i make a new field (in the script or as an expression) the formula does not propagate in the records that are null, it shows " - ". For instance, the expression isNull(ActionTaken) will return false in a field that that not null, but only " - " in fields that are null. If i export the table to Excel, the " - " is exported, i copy this cell to a text analyzer i the UTF-8 encoded is \x2D\x0A\x0A, i'm not sure if that's an artifact of the export process.
I also tried using the NullAsValue statement but no luck. Using a combination of Len & Trim = 0 will return the same result as above. This is only one table, no other tables are involved.
Thanks in advance.
I had a similar case few years ago where the field looked empty but actually it was filled with a character which just looked empty. Trimming the field also didnt worked as expected in this case, because the character code was different
What I can suggest you is to check if the character number, returned for the empty value, is actually an empty string. You can use the ord to check the character number for the empty values. Once you have the number then you can use this number to replace it with whatever you want (for example empty string)
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�$f�f����^D�e�^R:�u����� ^E^A�Ȑ�^B�^E�sZ���Yo��8Eސ�}��&JY���^A9^P������^P����~Jʭy��`�^9«�""�U� �:�}3���6�Hߧ�v���A7^Xi^L^]�sA�^Q�7�5d�^Xo˛�tY
Bp��4�Y���7DkV_���\^_q~�w�|�a�s̆���#�g�ӳu�^�!W}�n��Rgż_2�]�p�2}��b�G9�M^Q
�����:�X����bR[ԳZV!^G����^U�tq�&�Y6b��GR���s#mn6Z=^ZH^]�b��R^G�C�0R��{r1��4�#�
=r/X2�^O�����r^M�Rȕ�goG^X-����}���P+˥Qf�#��^C�Բ�z1�I�j����6�^Np���ܯ^P�[�^Tzԏ���^F2�e��\�E�6c�%���$�: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'm trying to do a simple mail merge in Word 2010 but when I insert an excel field that's supposed to represent a zip code from Connecticut (ie. 06880) I am having 2 problems:
the leading zero gets suppressed such as 06880 becoming 6880 instead. I know that I can at least toggle field code to make it so it works as {MERGEFIELD ZipCode # 00000} and that at least works.
but here's the real problem I can't seem to figure out:
A zip+4 field such as 06470-5530 gets treated like an arithmetic expression. 6470 - 5530 = 940 so by using above formula instead it becomes 00940 which is wrong.
Perhaps is there something in my excel spreadsheet or an option in Word that I need to set to make this properly work? Please advise, thanks.
See macropod's post in this conversation
As long as the ZIP codes are reaching Word (with or without "-" signs in the 5+4 format ZIPs, his field code should sort things out. However, if you are mixing text and numeric formats in your Excel column, there is a danger that the OLE DB provider or ODBC driver - if that is what you are using to get the data - will treat the column as numeric and return all the text values as 0.
Yes, Word sometimes treats text strings as numeric expressions as you have noticed. It will do that when you try to apply a numeric format, or when you try to do a calculation in an { = } field, when you sum table cell contents in an { = } field, or when Word decides to do a numeric comparison in (say) an { IF } field - in the latter case you can get Word to treat the expression as a string by surrounding the comparands by double-quotes.
in Excel, to force the string data type when entering data that looks like a number, a date, a fraction etc. but is not numeric (zip, phone number, etc.) simply type an apostrophe before the data.
=06470 will be interpreted as a the number 6470 but ='06470 will be the string "06470"
The simplest fix I've found is to save the Excel file as CSV. Word takes it all at face value then.