Hi there, I wanted to know how re-partitioning of keys per operator instance would happen when the current operator instances are scaled up or down and we are restarting our job from a previous savepoint which had a different number of parallel instances of the same operator.
My main concern is whether the re-distribution would lead to mapping of same keys to same operator instances as was done earlier but if this happens then there would be no added advantage of adding new task slots for the same operator because they would remain less used or not used at all if all possible key values have been seen earlier and if we go by the other way around of evenly distributing out keys (based on the hash function) to the new parallel slots as well, won't this cause issues in terms of processing consistent results based on the state of operator as was provided by previous savepoint of application. Is there a guarantee given by the hash function as in attached snippet, that same keys which landed earlier on an operator instance will land back again to the same operator instance once the job is restarted with new set of parallelism configuration? Thanks, Vikash CONFIDENTIALITY NOTICE This message and any included attachments are from Cerner Corporation and are intended only for the addressee. The information contained in this message is confidential and may constitute inside or non-public information under international, federal, or state securities laws. Unauthorized forwarding, printing, copying, distribution, or use of such information is strictly prohibited and may be unlawful. If you are not the addressee, please promptly delete this message and notify the sender of the delivery error by e-mail or you may call Cerner's corporate offices in Kansas City, Missouri, U.S.A at (+1) (816)221-1024.
