I've created a dataflow task in azure data factory and used derived column transformation. One of the source derived column value is '678396' which is extracted through Substring function and datatype "String" by default. I want to convert it into "Integer" because my target column datatype is "Integer".
I've to converted the column in this expression:
ToInteger(Substring(Column_1,1,8))
Please help me with correct expression.
Kind regards,
Rakesh
You don't need to build the expression. If you column data are all like int string "678396", or the output of Substring(Column_1,1,8) are int String
Data Factory can convert the int string to integer data type directly from source to sink. We don't need convert again.
Make sure you set column mapping correctly in sink settings. All things would works well.
Update:
This my csv dataset:
You can choose the Quote character to singe quote, then could solve the problem. See the source data preview in Copy active and Data Flow:
Copy active source:
Data Flow overview:
In data flow, we will get the alert like you said comment, we could ignore it and debug the data flow directly:
HTH.
you don't even need to substruct quotes '', as ToInteger function can convert numbers as string type
Related
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 simple pipeline that loads data from a csv file to an Azure SQL db.
I have added a data flow where I have ensured all schema matches the SQL table. I have a specific field which contains numbers with leading zeros. The data type in the source - projection is set to string. The field is mapped to the SQL sink showing as string data-type. The field in SQL has nvarchar(50) data-type.
Once the pipeline is run, all the leading zeros are lost and the field appears to be treated as decimal:
Original data: 0012345
Inserted data: 12345.0
The CSV data shown in the data preview is showing correctly, however for some reason it loses its formatting during insert.
Any ideas how I can get it to insert correctly?
I had repro’d in my lab and was able to load as expected. Please see the below repro details.
Source file (CSV file):
Sink table (SQL table):
ADF:
Connect the data flow source to the CSV source file. As my file is in text format, all the source columns in the projection are in a string.
Source data preview:
Connect sink to Azure SQL database to load the data to the destination table.
Data in Azure SQL database table.
Note: You can all add derived columns before sink to convert the value to string as the sink data type is a string.
Thank you very much for your response.
As per your post the DF dataflow appears to be working correctly. I have finally discovered an issue with the transformation - I have an Azure batch service which runs a python script, which does a basic transformation and saves the output to a csv file.
Interestingly, when I preview the data in the dataflow, it looks as expected. However, the values stored in SQL are not.
For the sake of others having a similar issue, my existing python script used to convert a 'float' datatype column to string-type. Upon conversion, it used to retain 1 decimal number but as all of my numbers are integers, they were ending up with .0.
The solution was to convert values to integer and then to string:
df['col_name'] = df['col_name'].astype('Int64').astype('str')
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().
In ADF i have a copy task that copies data from JSON to Delimited text, i get the result as
A | B | C
"name"|False|"description"
Json record is like
{"A":"name","B":"false","C":"description"}
Excepted result is as below
A | B | C
"name"|false|"description"
The bool value have to be in lowercase in the resulting Delimited text file, what am i missing?
I can reproduce this. The reason is you are converting the string to the ADF dataytpe "Boolean" which for some reason renders the values in Proper case.
Do you really have a receiving process which is case-sensitive? If you need to maintain the case of the source value simply remove the mapping, ie
If you do need some kind of custom mapping, then simply change the mapping data type to String and not Boolean.
UPDATE after new JSON provided
OK, so your first json sample has the "false" value in quotes so is treated as a string. In your second example, your json "true" is not in quotes so is a genuine json boolean value. ADF is auto-detecting this at run time and it seems like it can not be over-ridden as far as I can tell. Happy to be corrected. As an alternative, consider altering your original json to a string, as per you original example OR copying the file to Blob Store or Azure Data Lake, runniing some transform on it (eg Databricks) and then outputting the file. Alternately consider Mapping Data Flows.
I want to use Data Factory to migrate data in the storage account, but data in the original table is a many type ex: some data in column int, String, DateTime.
When I use Data Factory I need to specify the data type, so how I can definite dynamic type and copy column. Because all data migrate parsed to String type, so how can I keep value type of column?
This my data in the original table
enter image description here
Thanks for your help
According my experience in Data factory, Data Factory can not help you keep value type of column in source table. You must specify the data type in sink dataset.
Copy Data:
As you have tried, if you didn't set the sink data type, the column type will passed String in default.
I have an idea is that cope the data twice, each time copy the different entity column. The sink dataset support 'Merge' and 'Replace'.
Hope this helps.
Not sure if I am understanding the question , but let me first put forward my understanding , you want to copy a table lets say sourceT1 to SinkT1 , if that's the case you can always use the copy activity and then map the columns . When you map the columns it does set the data type also .