Hi all, We have a spark streaming job which reads from two kafka topics with 10 partitions each. And we are running the streaming job with 3 concurrent microbatches. (So total 20 partitions and 3 concurrency)
We have following question: In our processing DAG, we do a rdd.persist() at one stage, after which we fork out the DAG into two. Each of the forks has an action (forEach) at the end. In this case, we are observing that the number of executors is not exceeding the number of input kafka partitions. Job is not spawning more than 60 executors (2*10*3). And we see that the tasks from the two actions and the 3 concurrent microbatches are competing with each other for resources. So even though the max processing time of a task is 'x', the overall processing time of the stage is much greater than 'x'. Is there a way by which we can ensure that the two forks of the DAG get processed in parallel by spawning more number of executors? (We have not put any cap of maxExecutors) Following are the job configurations: spark.dynamicAllocation.enabled: true spark.dynamicAllocation.minExecutors: NOT_SET Please let us know if you have any ideas that can be useful here. Thanks, -Vibhor -- *-----------------------------------------------------------------------------------------* *This email and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom they are addressed. If you have received this email in error, please notify the system manager. This message contains confidential information and is intended only for the individual named. If you are not the named addressee, you should not disseminate, distribute or copy this email. Please notify the sender immediately by email if you have received this email by mistake and delete this email from your system. If you are not the intended recipient, you are notified that disclosing, copying, distributing or taking any action in reliance on the contents of this information is strictly prohibited.***** **** *Any views or opinions presented in this email are solely those of the author and do not necessarily represent those of the organization. Any information on shares, debentures or similar instruments, recommended product pricing, valuations and the like are for information purposes only. It is not meant to be an instruction or recommendation, as the case may be, to buy or to sell securities, products, services nor an offer to buy or sell securities, products or services unless specifically stated to be so on behalf of the Flipkart group. Employees of the Flipkart group of companies are expressly required not to make defamatory statements and not to infringe or authorise any infringement of copyright or any other legal right by email communications. Any such communication is contrary to organizational policy and outside the scope of the employment of the individual concerned. The organization will not accept any liability in respect of such communication, and the employee responsible will be personally liable for any damages or other liability arising.***** **** *Our organization accepts no liability for the content of this email, or for the consequences of any actions taken on the basis of the information *provided,* unless that information is subsequently confirmed in writing. If you are not the intended recipient, you are notified that disclosing, copying, distributing or taking any action in reliance on the contents of this information is strictly prohibited.* _-----------------------------------------------------------------------------------------_
