Re: Spark streaming multi-tasking during I/O
If you set concurrentJobs flag to 2, then it lets you run two jobs parallel. It will be a bit hard for you predict the application behavior with this flag thus debugging would be a headache. Thanks Best Regards On Sun, Aug 23, 2015 at 10:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi Akhil, Think of the scenario as running a piece of code in normal Java with multiple threads. Lets say there are 4 threads spawned by a Java process to handle reading from database, some processing and storing to database. In this process, while a thread is performing a database I/O, the CPU could allow another thread to perform the processing, thus efficiently using the resources. Incase of Spark, while a node executor is running the same read from DB = process data = store to DB, during the read from DB and store to DB phase, the CPU is not given to other requests in queue, since the executor will allocate the resources completely to the current ongoing request. Does not flag spark.streaming.concurrentJobs enable this kind of scenario or is there any other way to achieve what I am looking for Thanks, Sateesh On Sat, Aug 22, 2015 at 7:26 PM, Akhil Das ak...@sigmoidanalytics.com wrote: Hmm for a singl core VM you will have to run it in local mode(specifying master= local[4]). The flag is available in all the versions of spark i guess. On Aug 22, 2015 5:04 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Thanks Akhil. Does this mean that the executor running in the VM can spawn two concurrent jobs on the same core? If this is the case, this is what we are looking for. Also, which version of Spark is this flag in? Thanks, Sateesh On Sat, Aug 22, 2015 at 1:44 AM, Akhil Das ak...@sigmoidanalytics.com wrote: You can look at the spark.streaming.concurrentJobs by default it runs a single job. If set it to 2 then it can run 2 jobs parallely. Its an experimental flag, but go ahead and give it a try. On Aug 21, 2015 3:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
Re: Spark streaming multi-tasking during I/O
Hmm for a singl core VM you will have to run it in local mode(specifying master= local[4]). The flag is available in all the versions of spark i guess. On Aug 22, 2015 5:04 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Thanks Akhil. Does this mean that the executor running in the VM can spawn two concurrent jobs on the same core? If this is the case, this is what we are looking for. Also, which version of Spark is this flag in? Thanks, Sateesh On Sat, Aug 22, 2015 at 1:44 AM, Akhil Das ak...@sigmoidanalytics.com wrote: You can look at the spark.streaming.concurrentJobs by default it runs a single job. If set it to 2 then it can run 2 jobs parallely. Its an experimental flag, but go ahead and give it a try. On Aug 21, 2015 3:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
Re: Spark streaming multi-tasking during I/O
Hi Rishitesh, We are not using any RDD's to parallelize the processing and all of the algorithm runs on a single core (and in a single thread). The parallelism is done at the user level The disk can be started in a separate IO, but then the executor will not be able to take up more jobs, since thats how I believe Spark is designed by default On Sat, Aug 22, 2015 at 12:51 AM, Rishitesh Mishra rishi80.mis...@gmail.com wrote: Hi Sateesh, It is interesting to know , how did you determine that the Dstream runs on a single core. Did you mean receivers? Coming back to your question, could you not start disk io in a separate thread, so that the sceduler can go ahead and assign other tasks ? On 21 Aug 2015 16:06, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
Re: Spark streaming multi-tasking during I/O
Hi Akhil, Think of the scenario as running a piece of code in normal Java with multiple threads. Lets say there are 4 threads spawned by a Java process to handle reading from database, some processing and storing to database. In this process, while a thread is performing a database I/O, the CPU could allow another thread to perform the processing, thus efficiently using the resources. Incase of Spark, while a node executor is running the same read from DB = process data = store to DB, during the read from DB and store to DB phase, the CPU is not given to other requests in queue, since the executor will allocate the resources completely to the current ongoing request. Does not flag spark.streaming.concurrentJobs enable this kind of scenario or is there any other way to achieve what I am looking for Thanks, Sateesh On Sat, Aug 22, 2015 at 7:26 PM, Akhil Das ak...@sigmoidanalytics.com wrote: Hmm for a singl core VM you will have to run it in local mode(specifying master= local[4]). The flag is available in all the versions of spark i guess. On Aug 22, 2015 5:04 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Thanks Akhil. Does this mean that the executor running in the VM can spawn two concurrent jobs on the same core? If this is the case, this is what we are looking for. Also, which version of Spark is this flag in? Thanks, Sateesh On Sat, Aug 22, 2015 at 1:44 AM, Akhil Das ak...@sigmoidanalytics.com wrote: You can look at the spark.streaming.concurrentJobs by default it runs a single job. If set it to 2 then it can run 2 jobs parallely. Its an experimental flag, but go ahead and give it a try. On Aug 21, 2015 3:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
Re: Spark streaming multi-tasking during I/O
Thanks Akhil. Does this mean that the executor running in the VM can spawn two concurrent jobs on the same core? If this is the case, this is what we are looking for. Also, which version of Spark is this flag in? Thanks, Sateesh On Sat, Aug 22, 2015 at 1:44 AM, Akhil Das ak...@sigmoidanalytics.com wrote: You can look at the spark.streaming.concurrentJobs by default it runs a single job. If set it to 2 then it can run 2 jobs parallely. Its an experimental flag, but go ahead and give it a try. On Aug 21, 2015 3:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
Re: Spark streaming multi-tasking during I/O
Hi Sateesh, It is interesting to know , how did you determine that the Dstream runs on a single core. Did you mean receivers? Coming back to your question, could you not start disk io in a separate thread, so that the sceduler can go ahead and assign other tasks ? On 21 Aug 2015 16:06, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
Re: Spark streaming multi-tasking during I/O
You can look at the spark.streaming.concurrentJobs by default it runs a single job. If set it to 2 then it can run 2 jobs parallely. Its an experimental flag, but go ahead and give it a try. On Aug 21, 2015 3:36 AM, Sateesh Kavuri sateesh.kav...@gmail.com wrote: Hi, My scenario goes like this: I have an algorithm running in Spark streaming mode on a 4 core virtual machine. Majority of the time, the algorithm does disk I/O and database I/O. Question is, during the I/O, where the CPU is not considerably loaded, is it possible to run any other task/thread so as to efficiently utilize the CPU? Note that one DStream of the algorithm runs completely on a single CPU Thank you, Sateesh
