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 .
Related
I need to store/map one or more data flow parameters to my Sink (Azure SQL Table).
I can fetch other data from a REST Api and is able to map these to my Sink columns (see below). I also need to generate some UUID's as key fields and add these to the same table.
I would like my EmployeeId column to contain my Data Flow Input parameter, e.g. named param_test. In addition to this I need to insert UUID's to other columns which are not part of my REST input fields.
How to I acccomplish that?
You need to use a derived column transformation, and there edit the expression to include the parameters.
derived column transformation
expression builder
Adding to #Chen Hirsh, use the same derived column to get uuid values to the columns after REST API Source.
They will come into sink mapping:
Output:
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
my source is SQLDB
SINK :BLOB
SQL table have columns
in target file which i have creating blob initially no Header right. so customer given some Predefined Names so that data from sql column sholud be mapped those fileds.
in copy activity at mapping i need to map WITH proper data type and name which customer given
defaut its coming but i need ti map as i stated
HoW will i resolve it can some one help me
You can simply edit the sink header names, since its a TSV anyways
For addressing DataType mapping,
See, Data type mapping
Currently such data type conversion is supported when copying between
tabular data. Hierarchical sources/sinks are not supported, which
means there is no system-defined data type conversion between source
and sink interim types.
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
We are using Azure Data Factory Mapping data flow to read from Common Data Model (model.json).
We use dynamic pattern – where Entity is parameterised and we do not project any columns and we have selected Allow schema drift.
Problem: We are having issue with “Source” in mapping data flow (Source Type is Common Data Model). All the datetime/timestamp columns are read as null in source activity.
We also tried in projection tab Infer drifted column types where we provide a format for timestamp columns, However, it satisfies only certain timestamp columns - since in the source each datetime column has different timestamp format.
11/20/2020 12:45:01 PM
2020-11-20T03:18:45Z
2018-01-03T07:24:20.0000000+00:00
Question: How to prevent datetime columns becoming null? Ideally, we do not want Mapping Data Flow to typecast any columns - is there a way to just read all columns as string?
Some screenshots
In Projection tab - we do not specify schema - to allow schema drift and to dynamically load more than 1 entities.
In Data Preview tab
ModifiedOn, SinkCreatedOn, SinkModifiedOn - all these are system columns and will definitely have values in it.
This is now resolved on a separate conversation with Azure Data Factory team.
Firstly there is no way to 'stringfy' all the columns in Source, because CDM connector gets its metadata from model.json (if needed this file can be manipulated, however not ideal for my scenario).
To solve datetime/timestamp columns becoming null - under Projection tab we need to select Infer drifted column types and then you can add "multiple" time formats that you expect to come from CDM. You can either select from dropdown - if your particular datetime format is not listed in the dropdown (which was my case) then you can edit the code behind the data flow (i.e. data flow script), to add your format (see second screenshot).