Hi Jeff & Till! Thanks for the feedback, this is exactly the discussion I was looking for. The JobListener looks very promising if we can expose the JobGraph somehow (correct me if I am wrong but it is not accessible at the moment).
I did not know about this feature that's why I added my JobSubmission hook which was pretty similar but only exposing the JobGraph. In general I like the listener better and I would not like to add anything extra if we can avoid it. Actually the bigger part of the integration work that will need more changes in Flink will be regarding the accessibility of sources/sinks from the JobGraph and their specific properties. For instance at the moment the Kafka sources and sinks do not expose anything publicly such as topics, kafka configs, etc. Same goes for other data connectors that we need to integrate in the long run. I guess there will be a separate thread on this once we iron out the initial integration points :) I will try to play around with the JobListener interface tomorrow and see if I can extend it to meet our needs. Cheers, Gyula On Thu, Feb 6, 2020 at 4:08 PM Jeff Zhang <zjf...@gmail.com> wrote: > Hi Gyula, > > Flink 1.10 introduced JobListener which is invoked after job submission and > finished. May we can add api on JobClient to get what info you needed for > altas integration. > > > https://github.com/apache/flink/blob/master/flink-core/src/main/java/org/apache/flink/core/execution/JobListener.java#L46 > > > Gyula Fóra <gyf...@apache.org> 于2020年2月5日周三 下午7:48写道： > > > Hi all! > > > > We have started some preliminary work on the Flink - Atlas integration at > > Cloudera. It seems that the integration will require some new hook > > interfaces at the jobgraph generation and submission phases, so I > figured I > > will open a discussion thread with my initial ideas to get some early > > feedback. > > > > *Minimal background* > > Very simply put Apache Atlas is a data governance framework that stores > > metadata for our data and processing logic to track ownership, lineage > etc. > > It is already integrated with systems like HDFS, Kafka, Hive and many > > others. > > > > Adding Flink integration would mean that we can track the input output > data > > of our Flink jobs, their owners and how different Flink jobs are > connected > > to each other through the data they produce (lineage). This seems to be a > > very big deal for a lot of companies :) > > > > *Flink - Atlas integration in a nutshell* > > In order to integrate with Atlas we basically need 2 things. > > - Flink entity definitions > > - Flink Atlas hook > > > > The entity definition is the easy part. It is a json that contains the > > objects (entities) that we want to store for any give Flink job. As a > > starter we could have a single FlinkApplication entity that has a set of > > inputs and outputs. These inputs/outputs are other Atlas entities that > are > > already defines such as Kafka topic or Hbase table. > > > > The Flink atlas hook will be the logic that creates the entity instance > and > > uploads it to Atlas when we start a new Flink job. This is the part where > > we implement the core logic. > > > > *Job submission hook* > > In order to implement the Atlas hook we need a place where we can inspect > > the pipeline, create and send the metadata when the job starts. When we > > create the FlinkApplication entity we need to be able to easily determine > > the sources and sinks (and their properties) of the pipeline. > > > > Unfortunately there is no JobSubmission hook in Flink that could execute > > this logic and even if there was one there is a mismatch of abstraction > > levels needed to implement the integration. > > We could imagine a JobSubmission hook executed in the JobManager runner > as > > this: > > > > void onSuccessfulSubmission(JobGraph jobGraph, Configuration > > configuration); > > > > This is nice but the JobGraph makes it super difficult to extract sources > > and UDFs to create the metadata entity. The atlas entity however could be > > easily created from the StreamGraph object (used to represent the logical > > flow) before the JobGraph is generated. To go around this limitation we > > could add a JobGraphGeneratorHook interface: > > > > void preProcess(StreamGraph streamGraph); void postProcess(JobGraph > > jobGraph); > > > > We could then generate the atlas entity in the preprocess step and add a > > jobmission hook in the postprocess step that will simply send the already > > baked in entity. > > > > *This kinda works but...* > > The approach outlined above seems to work and we have built a POC using > it. > > Unfortunately it is far from nice as it exposes non-public APIs such as > the > > StreamGraph. Also it feels a bit weird to have 2 hooks instead of one. > > > > It would be much nicer if we could somehow go back from JobGraph to > > StreamGraph or at least have an easy way to access source/sink UDFS. > > > > What do you think? > > > > Cheers, > > Gyula > > > > > -- > Best Regards > > Jeff Zhang >
