In my case, I need to process input data in Excel (xls and xlsx) format. I need to do a file level validation of the Excel file for the order and number of columns, before processing the row level data. If this file level validation is failed, then exclude this file and inform the concerned through mail.
Please guide me, with some sample or example, how to validate the excel files for metadata? I thought of placing a variable in kettle.properties with semicolon separated header fields and compare this with the source excel file. But not getting a way to extract only the header row from file as I want.
Please guide me.
Are column names on Row 1 of your file (or any other row reasonably close to row 1) and you know how many fields are in each, at most? If so, maybe you can get away with that.
Step 1: You need to understand how many rows may there be, what they may be called, what data types, etc.
Step 2: Read the first N rows of the file(s) ensuring the header row will be read; Filter everything that is not the header (how to? depends on the specific structure). Because you don't know what are the field names, just name them field0, ... field999 or whatever.
Step3: Work some magic on the headers; filtering based on position of certain fields, mapping field names to data types, etc.
Step4: Metadata injection. Using the information you already have from before, you create a template transformation that is generic in the sense that field names are not set up in the excel input step. The metadata injection allows you to set up that step in run time, depending on the entire logic you just applied on the headers.
This page has a couple example videos: http://wiki.pentaho.com/display/EAI/ETL+Metadata+Injection
I had to build something like that (only it was CSV files and not XLS) a while back and metadata injection allowed me to load every single file in one go with 100% mapping accuracy. Of course, the magic happens before, when you parse the header row.
Thanks nsousa for your answer.
I got to the required solution with the help of my colleague. Here what I did
(1) Read only the 1st row of the source Excel file as normal data (no header, limit 1) where the field names will be called as F1, F2 etc
(2) concat the fields (data) to get a pattern
(3) Match this pattern with acual metadata pattern, if they are matching, then excel file is passed
Good trick. Thanks.
Related
I'm new to PDI and Kettle, and what I thought was a simple experiment to teach myself some basics has turned into a lot of frustration.
I want to check a database to see if a particular record exists (i.e. vendor). I would like to get the name of the vendor from reading a flat file (.CSV).
My first hurdle selecting only the vendor name from 8 fields in the CSV
The second hurdle is how to use that vendor name as a variable in a database query.
My third issue is what type of step to use for the database lookup.
I tried a dynamic SQL query, but I couldn't determine how to build the query using a variable, then how to pass the desired value to the variable.
The database table (VendorRatings) has 30 fields, one of which is vendor. The CSV also has 8 fields, one of which is also vendor.
My best effort was to use a dynamic query using:
SELECT * FROM VENDORRATINGS WHERE VENDOR = ?
How do I programmatically assign the desired value to "?" in the query? Specifically, how do I link the output of a specific field from Text File Input to the "vendor = ?" SQL query?
The best practice is a Stream lookup. For each record in the main flow (VendorRating) lookup in the reference file (the CSV) for the vendor details (lookup fields), based on its identifier (possibly its number or name or firstname+lastname).
First "hurdle" : Once the path of the csv file defined, press the Get field button.
It will take the first line as header to know the field names and explore the first 100 (customizable) record to determine the field types.
If the name is not on the first line, uncheck the Header row present, press the Get field button, and then change the name on the panel.
If there is more than one header row or other complexities, use the Text file input.
The same is valid for the lookup step: use the Get lookup field button and delete the fields you do not need.
Due to the fact that
There is at most one vendorrating per vendor.
You have to do something if there is no match.
I suggest the following flow:
Read the CSV and for each row look up in the table (i.e.: the lookup table is the SQL table rather that the CSV file). And put default upon not matching. I suggest something really visible like "--- NO MATCH ---".
Then, in case of no match, the filter redirect the flow to the alternative action (here: insert into the SQL table). Then the two flows and merged into the downstream flow.
I’m new to Pentaho and I’m currently having an issue with mapping specific row values to an ID.
I have a data file with around 30 columns, one of which is for currencies (USD, GBP, AUD, etc).
The main objective is to have the user select up to 8 (minimum of 1) currencies and map them to a corresponding ID 1-8. All other currencies not in the specified 8 will be mapped with an ID of 9.
The final step is to then output the original data set, along with the IDs.
I’m pretty sure I’m making this way harder than it should, but here is what I have at the moment.
I have created a job where the first step is to set the variables for my 8 currencies, selectionOne -> AUD, selectionTwo -> GBP, …, selectionEight -> JPY.
I then have a transformation to read the data from the file and use the copy rows to result step.
Following that I have a second job called for-each which is my loop for checking the current currency in the row.
Within this job I have two transformations, one called set-current, one called map-currencies.
set-current simply uses the get rows from result step (to grab the data from the first transformation). I then use the set variable step to set the current currency to the value in currency field. This works fine, as each pass through in the loop changes the current variable to the correct value.
Map-currencies is where I’m having the most issues.
The goal is to use the filter row step to compare the current currency against the original 8 selected currencies, and then using the value mapper step to map it to an ID, before outputting the csv file.
The main issue here, is that I can’t use my original variables in the filter or value mapper.
So, what I’ve done here is use the get variables step to retrieve the variables and named them: one, two, three, …, eight. This allows me to bypass the filtering issue, but they don’t seem to work for the value mapper, which is the all important step.
The second issue is that when the file is output it only outputs one value (because of the loop), selecting the append option works, but this could be a problem if the job is run more than once.
However, the priority here is the mapping issue.
I understand that this is rather long, and perhaps a tad confusing, but I will greatly appreciate any help on this, even if it’s an entirely new approach 😊.
Like I said, I’m probably making it harder than it should be.
Thanks for your time.
Edit for AlainD
Input example
Output example
This should be doable in a single transformation using the Stream Lookup step.
Text File Input is your main file, Property input reads your property file into Key and Value columns. You could use a normal text file with two columns instead of the property input.
Below are the settings of the Stream lookup. Note the default value "9" for records that are not found in the lookup stream.
Is the following transformation looping through each of the rows in the applications field?
Also is there a way to loop through and output each individual row to it's own txt or excel file (preferably txt).
At the moment it outputs all rows to the one text file. I want to do this without creating multiple text file transformations.
Unsure if a switch case would be a loop.
Transformations by their very nature apply the steps to all the rows in them. It's probably a good idea to familiarize yourself a bit more with the flow-based concept, then you can answer the switch/case question for yourself.
Regarding one file per row, you can use the option "Accept filename from field" in the Text File Output step and then put your Applications field there. You will need to add the destination path in a prior step, since PDI expects the full path and filename in that field.
I am new in Pentaho project. Need to know about some validation rules whether these can be handled by PDI or not.
My input data is CSV format and target is ORACLE table. Suppose total number of column is 50.
Validation Rules :
if any less number of columns coming from input file (like 48) we
should inform via email
if any more number of columns coming from input file (like 54) we
should inform via email
if there are any duplicate columns coming in input file we should
inform via email
if there a missing order in input file with respect to target table
layout we should inform via email
if there any columns started with a number we should inform via email
if there any columns more than 30 characters in length we should
inform via email
Any help is appreciated.
If anything required from me kindly reply.
After lots of R&D it can be done by adding "Metadata Structure" under Utility in Transformation and load all column list into a text file.
Then create a Job and compare this text file with lookup text file (containing all target column list) by "File Compare" under File Management. Make a check option if true then invoke the final Transformation or if False send email notification.
Yes. There are steps that will allow you to identify all of these things.
More generally, if you want to do something in Kettle and don't see a step available that makes it easy to do, you can always write custom steps or steps with custom Java or JavaScript code in them to do it.
We get weekly data files (flat files) from our vendor to import into SQL, and at times the column names change or new columns are added.
What we have currently is an SSIS package to import columns that have been defined. Since we've assigned the mapping, SSIS only throws up an error when a column is absent. However when a new column is added (apart from the existing ones), it doesn't get imported at all, as it is not named. This is a concern for us.
What we'd like is to get the list of all the columns present in the flat file so that we can check whether any new columns are present before we import the file.
I am relatively new to SSIS, so a detailed help would be much appreciated.
Thanks!
Exactly how to code this will depend on the rules for the flat file layout, but I would approach this by writing a script task that reads the flat file using the file system object and a StreamReader object, and looks at the columns, which are hopefully named in the first line of the file.
However, about all you can do if the columns have changed is send an alert. I know of no way to dynamically change your data transformation task to accomodate new columns. It will have to be edited to handle them. And frankly, if all you're going to do is send an alert, you might as well just use the error handler to do it, and save yourself the trouble of pre-reading the column list.
I agree with the answer provided by #TabAlleman. SSIS can't natively handle dynamic columns (and niether can your SQL destination).
May I propose an alternative? You can detect a change in headers without using a C# Script Tasks. One way to do this would be to create a flafile connection that reads the entire row as a single column. Use a Conditional Split to discard anything other than the header row. Save that row to a RecordSet object. Any change? Send Email.
The "Get Header Row" DataFlow would look like this. Row Number if needed.
The Control Flow level would look like this. Use a ForEach ADO RecordSet object to assign the header row value to an SSIS variable CurrentHeader..
Above, the precedent constraints (fx icons ) of
[#ExpectedHeader] == [#CurrentHeader]
[#ExpectedHeader] != [#CurrentHeader]
determine whether you load data or send email.
Hope this helps!
i have worked for banking clients. And for banks to randomly add columns to a db is not possible due to fed requirements and rules. That said I get your not fed regulated bizz. So here are some steps
This is not a code issue but more of soft skills and working with other teams(yours and your vendors).
Steps you can take are:
(1) reach a solid columns structure that you always require. Because for newer columns older data rows will carry NULL.
(2) if a new column is going to be sent by the vendor. You or your team needs to make the DDL/DML changes to the table were data will be inserted. Ofcouse of correct data type.
(3) document this change in data dictanary as over time you or another member will do analysis on this data and would like to know what is the use of each attribute or column.
(4) long-term you do not wish to keep changing table structure monthly because one of your many vendors decided to change the style the send you data. Some clients push back very aggresively other not so much.
If a third-party tool is an option for you, check out CozyRoc's Data Flow Task Plus. It handles variable columns in sources.
SSIS cannot make the columns dynamic,
one thing, i always do, is use a script task to read the first and last lines of a file.
if it is not an expected list of csv columns i mark file as errored and continue/fail as required.
Headers are obviously important, but so are footers. Files can through any unknown issue be partially built. Requesting the header be placed at the rear of the file it is a double check.
I also do not know if SSIS can do this dynamically, but it never ceases to amaze me how people add/change order of columns and assume things will still work.
1-SSIS Does not provide dynamic source and destination mapping.But some third party component such as Data flow task plus , supporting this feature
2-We can achieve this using ssis script task.
3-If the Header is correct process further for migration else fail the package before DFT execute.
4-Read the line from the header using script task and store in array or list object
5-Then compare those array values to user defined variables declare earlier contained default value as column name.
6-If values are matching exactly then progress further else fail it.