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, Vishal ________________________________ This message is confidential and is for the sole use of the intended recipient(s). It may also be privileged or otherwise protected by copyright or other legal rules. If you have received it by mistake please let us know by reply email and delete it from your system. It is prohibited to copy this message or disclose its content to anyone. Any confidentiality or privilege is not waived or lost by any mistaken delivery or unauthorized disclosure of the message. All messages sent to and from Agoda may be monitored to ensure compliance with company policies, to protect the company's interests and to remove potential malware. Electronic messages may be intercepted, amended, lost or deleted, or contain viruses.