I think that we are going to have to change the Sink API as part of SPARK-20928 <https://issues-test.apache.org/jira/browse/SPARK-20928>, which is why I linked these tickets together. I'm still targeting an initial version for Spark 2.3 which should happen sometime towards the end of the year.
There are some misconceptions in that stack overflow answer that I can correct. Until we improve the Source API, You should still be able to get exactly once processing by using the batchId that is passed to the Sink. We guarantee that the offsets present at any given batch ID will be the same across retries by recording this information in the checkpoint's WAL. The checkpoint does not use java serialization (like DStreams does) and can be used even after upgrading Spark. On Tue, Sep 12, 2017 at 12:45 AM, Dmitry Naumenko <dm.naume...@gmail.com> wrote: > Thanks, Cody > > Unfortunately, it seems to be there is no active development right now. > Maybe I can step in and help with it somehow? > > Dmitry > > 2017-09-11 21:01 GMT+03:00 Cody Koeninger <c...@koeninger.org>: > >> https://issues-test.apache.org/jira/browse/SPARK-18258 >> >> On Mon, Sep 11, 2017 at 7:15 AM, Dmitry Naumenko <dm.naume...@gmail.com> >> wrote: >> > Hi all, >> > >> > It started as a discussion in >> > https://stackoverflow.com/questions/46153105/how-to-get-kafk >> a-offsets-with-spark-structured-streaming-api. >> > >> > So the problem that there is no support in Public API to obtain the >> Kafka >> > (or Kineses) offsets. For example, if you want to save offsets in >> external >> > storage in Custom Sink, you should : >> > 1) preserve topic, partition and offset across all transform operations >> of >> > Dataset (based on hard-coded Kafka schema) >> > 2) make a manual group by partition/offset with aggregate max offset >> > >> > Structured Streaming doc says "Every streaming source is assumed to have >> > offsets", so why it's not a part of Public API? What do you think about >> > supporting it? >> > >> > Dmitry >> > >
