I'm trying to extract data from an Oracle table. I'm using utl file for that and I'm receiving the error ORA-29285: file write error. The weird here is if I try extract the data directly from the table return the error, if I extract the data using a simple view the error is returned as well, BUT if I extract the data using a view with an ORDER BY the extraction is well succeed. I can't understand where the error is, I already look for the length of lines and nothing. Any suggestion from which can be?
I extract a lot of other data through the utl_file and I'm well succed. This data in specific is at the first time uploaded to Oracle table directly from a csv file with ANSI encoding. However I have other data uploaded by the same way and then I can export correctly. I checked the encoding too in order to reduce the possible mistakes and I found nothing.
Many thanks,
Priscila Ferreira
Related
I am currently trying to convert a simple table into a PDF file using an existing .rdf file.
My first approach was to look for a new program that can do so because I want to replace the current 'Oracle Reports' program.
Is there any other program that would support converting SQL data into an PDF using an .rdf File?
I tried writing a Python 3 script to do just that, but I would not know where to start.
Oracle APEX 21.2 (latest at the current time) has a package named APEX_DATA_EXPORT that can take a SELECT statement and export it into various formats, one of them being PDF. The example in the documentation shows how to generate a PDF from a simple query. After calling apex_data_export.export, you can use the BLOB that is returned by the function and do whatever you need with the PDF.
There are not very many options for styling and formatting the table, but Oracle does plan on adding additional printing capabilities for PDFs in the future.
I am using AbInitio and attempting to have my results from my query in my Input Table populated into hdfs. I am wanting the format in parquet. I tried using the dml to hive text but the following is my results and I am not sure what this means.
$ dml-to-hive text $AI_DML/myprojectdml.dml
Usage: dml-to-avro <record_format> <output_file>
or: dml-to-avro help
<record-format> is one of:
<filename> Read record format from file
-string <string> Read record format from string
<output_file> is one of:
<filename> Output Avro schema to file
- Output Avro schema to standard output
I also tried using the Write Hive Table component but I receive the following error:
[B276]
The internal charset "XXcharset_NONE" was encountered when a valid character set data
structure was expected. One possible cause of this error is that you specified a
character set to the Co>Operating System that is misspelled or otherwise incorrect.
If you cannot resolve the error please contact Customer Support.
Any help would be great, I am trying to have my output to hdfs in parquet.
Thanks,
Chris Richardson
I know this is a late reply, but if you're still working on this or somebody else stumbles onto this like I did, I think I've found a solution.
I used dml-to-hive to create a DML for parquet format and write it to a file.
dml-to-hive parquet current.dml > parquet.dml
Once this dml is created, you can use it on the in port of the "Write HDFS" component. Double click the component, go to Port tab, click Radio button "Use File" and then point it to parquet.dml
Then, just set the WRITE_FORMAT choice to parquet and give it a whirl. I was able to create parquet, orc, and avro files using the above process.
I would like to use GET DATA to open my data. Then read a string from a text file. The string would be a date (eg. "2017-09-02 13:24") which I would use in filtering the data set before saving as .sav.
Is this possible? Or any other suggestion on how to import external information to use while processing the data set?
With ADD FilE I know its possible to open up two different data sets. However, I have to use GET DATA.
The .sps-file is run from spss job-file.
I am using clickhouse to store data, and I'm getting the following error while querying the column cid from the click table.
Checksum doesn't match: corrupted data.
I don't have any replicate for now, any suggestions for recovery?
The error comes down to the fact the checksum of the CityHash128 and the compressed data doesn't match and throws this exception in the readCompressedData function.
You can try to disable this check using the disable_checksum via the disableChecksumming method.
It could work, but a corrupted most probably means that something is wrong with your raw data and there is small chances for recovery unless you did backups.
Usually, you will get data part name and column name in exception message.
You could locate specific data part, remove files related to that single column, and restart the server. You will lose (already corrupted) data for one column in one data part (it will be filled with default values on read), but all other data will remain.
I'm trying to import data from a csv file which, unfortunately, contains multiple data tables. Actually, it's not really a pure csv file.
It contains a header field with some metadata and then the actual csv data parts are separated by:
//-------------
Table <table_nr>;;;;
An example file looks as follows:
Summary;;
Reporting Date;29/05/2013;12:36:18
Report Name;xyz
Reporting Period From;20/05/2013;00:00:00
Reporting Period To;26/05/2013;23:59:59
//-------------
Table 1;;;;
header1;header2;header3;header4;header5
string_aw;0;0;0;0
string_ax;1;1;1;0
string_ay;1;2;0;1
string_az;0;0;0;0
TOTAL;2;3;1;1
//-------------
Table 2;;;
header1;header2;header3;header4
string_bv;2;2;2
string_bw;3;2;3
string_bx;1;1;1
string_by;1;1;1
string_bz;0;0;0
What would be the best way to process load such data using kettle?
Is there a way to split this file into the header and csv data parts and then process each of them as separate inputs?
Thanks in advance for any hints and tips.
Best,
Haes.
I don't think there are any steps that will really help you with data in such a format. You probably need to do some preprocessing before bringing your data into a CSV step. You could still do this in your job, though, by calling out to the shell and executing a command there first, like maybe an awk script to split up the file into its component files and then load those files via the normal Kettle pattern.