I am reading a fixed-width file in mapping Data Flow and loading it to the table. I want to validate the fields, datatype, lengths of the field that I am extracting in the Derived column using substring.
How to Achieve this in ADF
Use a Conditional Split and add a condition for each property of the field that you wish to test for. For data type checking, we literally just landed new isInteger(), isString() ... functions today. The docs are still in the printing press, but you'll find them in the expression builder. For length use length().
Related
I am currently using Azure Datafactory in that I am creating a Derived column and since the field will always will be blank, so I want the value to be NULL
currently Derived Column I am doing this for adding the expression e.g. toString("null") and toString(null()) but this is appearing as string. I only want null to appear without quotes in Json document
I have reproduced the above and got below results.
I tried to give null() to a column and it gave the error like below.
So, in ADF Dataflow, there should be any wrap over null() with the functions like toInteger() or toString()
When I give toString(null()) when id is 4 in derived column of dataflow and the sink is a JSON, it gave me the below output.
You can see the row with id==4 skipped the null valued key in JSON. If you give toString(null()) same key in every row will be skipped.
You can go through this link by #ShaikMaheer-MSFT to understand more about this.
AFAIK, The workaround for this can be to store the null as 'null' string to get that key in JSON like this and later use this as per your requirement.
I have below column in my table
I need an output as below
I am using Dataflow in the Azure data factory and unable to get the above output. I used derived column but no success. I used replace function, but it's not coming correct. Can anyone advise how to format this in dataflow?
Source is taken in data flow with data as in below image.
Derived column transformation is added next to source.
New column is added and the expression is given as
iif(left(id,1)=='-', replace(replace(id,"USD",""),"-","-$"), concat("$", replace(id,"USD","")))
Output of Derived Column activity
I have a scenario for creating spectrum table in redshift using matillion.
my CSV file data is like this:-
column1,column2,column3
abc,"qwety,pqr",xyz
but in spectrum table i am seeing data
as
column1 column2 column3
abc qwerty pqr
Matillion is not taking quotes value as one.
can you please suggest how to achieve this using matillion's EXTERNAL TABLE component.
Basically you would like to specify a quote parameter for your CSV data.
Redshift has 2 ways of specifying external tables (see Redshift Docs for reference):
using the default built-in SerDes and properties like ROW FORMAT DELIMITED, FIELDS TERMINATED BY
explicitly specifying a SerDe with ROW FORMAT SERDE, WITH SERDEPROPERTIES
I don't think it's possible to specify a quote parameter using the built-in SerDes.
It is possible to specify them using org.apache.hadoop.hive.serde2.OpenCSVSerde (look here for details on it's properties), but beware that there are know problems with it, as one described in this SO question.
Now for Metillion:
I have never used Matillion, but looking at their Redshift External Table documentation page, looks like it's only possible to specify the FORMAT and the FIELD TERMINATOR, but not to specify a SerDe and it's properties, hence it's not possible to specify the quote parameters for the external table - unless there are some undocumented means to specify a custom SerDe.
Personal note:
We have experienced many problems with ingesting data stored as CSV, and we basically try to avoid it. There's no standard for CSV, each tool implements it's own version of support for it, and it's very difficult convince all your tools to see data the same way.
I have this simple flow in Talend DI 6 (simplified for posting on SO):
The last step crashes with a NullPointerException, because missing XML attributes are returned as null.
Is there a way to get empty string values instead of nulls?
For now I'm using a tReplace step to remove nulls as a work-around, but it's tedious and adds to the cost of maintenance by creating one more place where the list of attributes needs to be maintained.
In Talend DI 5.6.2 it is possible to add default data values to the schema. The column in the schema is called "Default". If you expect strings, you can set an empty string, which is set if the column value is null:
Talend schema view with Default column
Works also for other data types. Talend DI 6 should still be able to do this, although the field might be renamed.
I have this kind of data:
I need to transpose this data into something like this using Talend:
Help would be much appreciated.
dbh's suggestion should work indeed, but I did not try it.
However, I have another solution which doesn't require to change input format and is not too complicated to implement. Indeed the job has only 2 transformation components (tDenormalize and tMap).
The job looks like the following:
Explanation :
Your input is read from a CSV file (could be a database or any other kind of input)
tDenormalize component will Denormalize your column value (column 2), based on value on id column (column 1), separating fields with a specific delimiter (";" in my case), resulting as shown in 2 rows.
tMap : split the aggregated column into multiple columns, by using java's String.split() method and spreading the resulting array into multiple columns. The tMap should like like this:
Since Talend doesn't accept to store Array objects, make sure to store the splitted String in Object format. Then, cast that object into Array on the right side of the Map.
That approach should give you the expected result.
IMPORTANT:
tNormalize might shuffle the rows, meaning for bigger input, you might encounter unsorted output. Make sure to sort it if needed or use tDenormalizeSortedRow instead.
tNormalize is similar to an aggregation component meaning it scans the whole input before processing, which results into possible performance issues with particularly big inputs (tens of millions of records).
Your input is probably wrong (you have 5 entries with 1 as id, and 6 entries with 2 as id). 6 columns are expected meaning you should always have 6 lines per id. If not, then you should implement dbh's solution, and you probably HAVE TO add a column with a key.
You can use Talend's tPivotToColumnsDelimited component to achieve this. You will most likely need an additional column in your data to represent the field name.
Like "Identifier, field name, value "
Then you can use this component to pivot the data and write a file as output. If you need to process the data further, read the resulting file with tFileInoutDelimited .
See docs and an example at
https://help.talend.com/display/TalendOpenStudioComponentsReferenceGuide521EN/13.43+tPivotToColumnsDelimited