I am building transformations that send data to Azure Table Storage. When the attribute value is missing there is a blank string inserted into the table. Due to the nature of the feature, there will only be one row of data but different columns may have missing or null values. These values we do not want written to the table. I have tried using Python and NullAttributeMappers, but these still leave the <missing> value which is causing issues. Is there a way to dynamically remove these columns? The reason for wanting to remove the attribute columns before the Azure Table Storage writer is that "Automatic" Attribute definition appears to be required in order to dynamically pass different columns to Azure.
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How do you dynamically remove attributes of missing columns?
Best answer by markatsafe
@svteshipley If an attribute is flagged as <missing> then the SchemaScanner will ignore it. So if you start with this:
_creation_instance 0
attr1 a
attr2 b
attr3 <null>
and pass it through NullAttributeMapper and set <null> to <missing> then the SchemaScanner will give you this:
attribute{0}.fme_data_type fme_varchar(2)
attribute{0}.name attr1
attribute{1}.fme_data_type fme_varchar(2)
attribute{1}.name attr2
attribute{2}.fme_data_type fme_uint8
attribute{2}.name _creation_instance
Note the absence of attr3 in the schema list
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