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From "John, Vishal (Agoda)" <>
Subject Cases when to clear the checkpoint directories.
Date Sat, 07 Oct 2017 18:53:36 GMT

Hello TD,

You had replied to one of the questions about checkpointing –

This is an unfortunate design on my part when I was building DStreams :)

Fortunately, we learnt from our mistakes and built Structured Streaming the correct way. Checkpointing
in Structured Streaming stores only the progress information (offsets, etc.), and the user
can change their application code (within certain constraints, of course) and still restart
from checkpoints (unlike DStreams). If you are just building out your streaming applications,
then I highly recommend you to try out Structured Streaming instead of DStreams (which is
effectively in maintenance mode).

Can you please elaborate on what you mean by application code change in DStream applications?

If I add a couple of println statements in my application code will that become an application
code change? or do you mean, changing method signatures or adding new methods etc.
Could you please point to relevant source code in Spark, which does this type of code validation/de-serialisation
in case of DStreams?

We are using mapWithState in our application and it builds its state from checkpointed RDDs.
 I would like understand the cases where we can avoid clearing the checkpoint directories.

thanks in advance,

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