No, Timestream doesn't support user-defined functions (UDFs) at this time.
If your function is simple enough, you might be able to accomplish your goal with a
reduce function, which really lets you apply two inline functions (an input and output function) to transform your data. Here's a link to the docs,
Otherwise, you could write an AWS Lambda that consumes you table and writes back to either the same table or a different table. Timestream will support sparse columns, so you can have a lambda that is back-filling a column in a multi-measure row that initially doesn't exist for all records. You would need to read out the row, enrich it, and then write back the same data for the other columns with a higher version number.
Finally, scheduled queries are another way to automatically enrich your data. You could have a scheduled query that computes your "function" (separate query) result and pushes the record back to the same table or to a different table, in a different format. The nice thing is that the scheduled query engine will bump the version number for you. Here are the docs on scheduled queries:
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