Hey guys I work as a DB Consultant, I am new to the DataStage software and have been running into some issues. I need to load .xls files to .txt files and then upload them, but I am running into issues with the special characters below. I am not sure what DataType or syntax I could use to upload the data to the DB as the job crashes every time it encounters anything other than
Á,',’,Ç,Í,`,É, * etc
What attempts have we made?
**Convert(Convert('ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789 ','', Column_Name1),'',Column_Name1)
What issues persist?
Á,',’,Ç,Í,`,É and Spanish tildes
Question?
Is there not a way to bring in the data as is? I do not want the Convert statement because that only works on special chars but when accents and German Umlauts are involved that is a letter, and I don't want to replace with a space or remove it altogether, how do I handle this error?
Check out the unstructured data stage
The Knowledge Center provides a lot of nformation how to design a job with an Excel as data source.
In addition to that there are blogs and vidoes out there as well.
Once you understood the design / interface of the stage it is not difficult to do.
Related
We are working towards migrating data from MongoDB to Teradata (DW).
We feel that transformations on the data will be necessary.
Could you please help me answer the below questions which will guide us on developing a solution for migration :
Which would be the best and efficient format to export data from MongoDB to load into Teradata(DW) considering transformations involved ? (CSV/JSON/Others)
Transformations could include omission of line(s) from the exported file, omission of fields, aggregation(sum/count) across fields etc.
If developing a framework for ETL, will Java be a good choice ?
We noticed that ‘\n’ [newline character] is also part of some records. Hence, in the csv we are seeing some blank lines in between.
Do we need to be concerned of the right line delimiter ? Or can the export format help us in this regard ?
We are seeing some records getting truncated because the length of the record exceeds 1024 characters.
We get the ‘Line too long’ message in VI editor. We don’t have an alternate editor in our system. Is there a way around to handle line truncation ?
CSV is not particularly well-specified - there are several variants of it in the wild with slightly different escaping behaviors. I almost always prefer anything-but-csv.
JSON
Yes
This is not a question, but ok.
Don't edit the data with vi, this is purely a limitation of the editor and not the export format. Do transformations programmatically
I was given the task to decide whether our stack of technologies is adequate to complete the project we have at hand or should we change it (and to which technologies exactly).
The problem is that I'm just a SQL Server DBA and I have a few days to come up with a solution...
This is what our client wants:
They want a web application to centralize pharmaceutical researches separated into topics, or projects, in their jargon. These researches are sent as csv files and they are somewhat structured as follows:
Project (just a name for the project)
Segment (could be behavioral, toxicology, etc. There is a finite set of about 10 segments. Each csv file holds a segment)
Mandatory fixed fields (a small set of fields that are always present, like Date, subjects IDs, etc. These will be the PKs).
Dynamic fields (could be anything here, but always as a key/pair value and shouldn't be more than 200 fields)
Whatever files (images, PDFs, etc.) that are associated with the project.
At the moment, they just want to store these files and retrieve them through a simple search mechanism.
They don't want to crunch the numbers at this point.
98% of the files have a couple of thousand lines, but there's a 2% with a couple of million rows (and around 200 fields).
This is what we are developing so far:
The back-end is SQL 2008R2. I've designed EAVs for each segment (before anything please keep in mind that this is not our first EAV design. It worked well before with less data.) and the mid-tier/front-end is PHP 5.3 and Laravel 4 framework with Bootstrap.
The issue we are experiencing is that PHP chokes up with the big files. It can't insert into SQL in a timely fashion when there's more than 100k rows and that's because there's a lot of pivoting involved and, on top of that, PHP needs to get back all the fields IDs first to start inserting. I'll explain: this is necessary because the client wants some sort of control on the fields names. We created a repository for all the possible fields to try and minimize ambiguity problems; fields, for instance, named as "Blood Pressure", "BP", "BloodPressure" or "Blood-Pressure" should all be stored under the same name in the database. So, to minimize the issue, the user has to actually insert his csv fields into another table first, we called it properties table. This action won't completely solve the problem, but as he's inserting the fields, he's seeing possible matches already inserted. When the user types in blood, there's a panel showing all the fields already used with the word blood. If the user thinks it's the same thing, he has to change the csv header to the field. Anyway, all this is to explain that's not a simple EAV structure and there's a lot of back and forth of IDs.
This issue is giving us second thoughts about our technologies stack choice, but we have limitations on our possible choices: I only have worked with relational DBs so far, only SQL Server actually and the other guys know only PHP. I guess a MS full stack is out of the question.
It seems to me that a non-SQL approach would be the best. I read a lot about MongoDB but honestly, I think it would be a super steep learning curve for us and if they want to start crunching the numbers or even to have some reporting capabilities,
I guess Mongo wouldn't be up to that. I'm reading about PostgreSQL which is relational and it's famous HStore type. So here is where my questions start:
Would you guys think that Postgres would be a better fit than SQL Server for this project?
Would we be able to convert the csv files into JSON objects or whatever to be stored into HStore fields and be somewhat queryable?
Is there any issues with Postgres sitting in a windows box? I don't think our client has Linux admins. Nor have we for that matter...
Is it's licensing free for commercial applications?
Or should we stick with what we have and try to sort the problem out with staging tables or bulk-insert or other technique that relies on the back-end to do the heavy lifting?
Sorry for the long post and thanks for your input guys, I appreciate all answers as I'm pulling my hair out here :)
Does anyone know how to export a CSV file from a SQLite3 database in an iPhone app?
There are several iOS CSV libraries that can be used to export the data from the phone. This is a trivial data transformation task - you read the information line-by-line from the SQLite result set, and send it out into the CSV file. If you do not need to process the file after the complete read-in, then you should be able to stream the data as quickly as it is read.
Writing CSV files is mostly trivial - and can be implemented by someone without much effort. I'm certain there are libraries for iOS specifically, but I've used the python CSV export routines regularly, and they have been read by excel without much effort. You just have to be careful, as excel has the habit of interpreting the results once they are in there, making some accuracy calculations impossible.
the .csv file format is trivial, and I've implemented it several times in several languages. if you have numeric requirements, though, you will be spending a lot of time making sure that the program that you feed it into is accepting the numbers properly - and you will have to deal with 'I imported it into excel, saved it and the data is wrong now' bugs...
I am working on a web development project using flask and sqlalchemy orm. My post is related to use of unicode in developing this app.
What I have understood till now about unicode :
If I want my webapp to handle data in languages other than English I need to use unicode data type for my variables. Because string variables can't handle unicode data.
I use some database which stores unicode data or take responsibility to convert unicode to raw while saving and vice versa while retrieving. Sqlalchemy gives me option to set automatic conversion both ways, so that I dont have to worry about them.
I am using python2.7 so I have to be aware of processing unicode data properly. Normal string operations on unicode data maybe buggy.
Correct me if any of the above assumption is wrong.
Now my doubts or questions :
If I dont use unicodes now then will I have some problems if I or flask people decide to port to python3?
I dont want to hassle with the thought of my webapp catering to different languages right now. I just want to concentrate on first creating the app. Can I do that later without using unicode right now?
If I use unicode now then how it affects my code. Do I replace every string input and output with unicode or what?
Conversion of unicode when saving to database, Can it be source of performance problems?
Basically I am asking whether to use unicode or not with explaining my needs and requirement out of the project.
No, but make sure you separate binary data from text data. That makes it easier to port.
It's easier to use Unicode from the start, but of course you can postpone it. But it's really not very difficult.
You replace everything that should be text data with Unicode, yes.
Only of you make loads of conversions of really massive amounts of text.
I'm guessing this won't apply to 99.99% of anyone that sees this. I've been doing some Sawtooth survey programming at work and I've been needing to create a webpage that shows some aggregate data from the completed surveys. I was just wondering if anyone else has done this using the flat files that Sawtooth generates and how you went about doing it. I only know very basic Perl and the server I use does not have PHP so I'm somewhat at a loss for solutions. Anything you've got would be helpful.
Edit: The problem with offering example files is that it's more complicated. It's not a single file and it occasionally gets moved to a different file with a different format. The complexities added in there are why I ask this question.
Doesn't Sawtooth export into CSV format? There are many Perl parsers for CSV files. Just about every language has a CSV parser or two (or twelve), and MS Excel can open them directly, and they're still plaintext so you can look at them in any text editor.
I know our version of Sawtooth at work (which is admittedly very old) exports Sawtooth data into SPSS format, which can then be exported into various spreadsheet formats including CSV, if all else fails.
If you have a flat (fixed-width field) file, you can easily parse it in Perl using regular expressions or just taking substrings of each line one at a time, assuming you know the width of the fields. Your question is too general to give much better advice, sorry.
Matching the values up from a plaintext file with meta-data (variable names and labels, value labels etc.) is more complicated unless you already have the meta-data in some script-readable format. Making all of that stuff available on a web page is more complicated still. I've done it and it can be a bit of a lengthy project to roll your own. There are packages you can buy, like SDA, which will help you build a website where people can browse and download your survey data and view your codebooks.
Honestly though the easiest thing to do if you're posting statistical data on a website is get the data into SPSS or SAS or another statistics package format and post those files for download directly. Then you don't have to worry about it.