Re: OutOfMemoryException: unable to create native thread
Right now, I would go with the extra field. The roadmap has pending features that improve the scheduling for plans like yours (with many data sources), but it is not yet in the code. On Fri, Jul 17, 2015 at 11:24 AM, chan fentes chanfen...@gmail.com wrote: I am testing my regex file input format, but because I have a workflow that depends on the filename (each filename contains a number that I need), I need to add another field to each of my tuples. What is the best way to avoid this additional field, which I only need for grouping and one multiplication (in a MapFunction) late in my workflow? An easy way would be to do the multiplication in the input format, however I need the value also for grouping. If I were able to use many data sources (one for each file), I could avoid the additional field (no grouping per file required) and possibly decrease the runtime of the plan(s). Thanks in advance for your help. 2015-07-01 10:20 GMT+02:00 Stephan Ewen se...@apache.org: How about allowing also a varArg of multiple file names for the input format? We'd then have the option of - File or directory - List of files or directories - Base directory + regex that matches contained file paths On Wed, Jul 1, 2015 at 10:13 AM, Flavio Pompermaier pomperma...@okkam.it wrote: +1 :) On Wed, Jul 1, 2015 at 10:08 AM, chan fentes chanfen...@gmail.com wrote: Thank you all for your help and for pointing out different possibilities. It would be nice to have an input format that takes a directory and a regex pattern (for file names) to create one data source instead of 1500. This would have helped me to avoid the problem. Maybe this can be included in one of the future releases. ;) 2015-06-30 19:02 GMT+02:00 Stephan Ewen se...@apache.org: I agree with Aljoscha and Ufuk. As said, it will be hard for the system (currently) to handle 1500 sources, but handling a parallel source with 1500 files will be very efficient. This is possible, if all sources (files) deliver the same data type and would be unioned. If that is true, you can - Specify the input as a directory. - If you cannot do that, because there is no common parent directory, you can union the files into one data source with a simple trick, as described here: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
Re: OutOfMemoryException: unable to create native thread
I am testing my regex file input format, but because I have a workflow that depends on the filename (each filename contains a number that I need), I need to add another field to each of my tuples. What is the best way to avoid this additional field, which I only need for grouping and one multiplication (in a MapFunction) late in my workflow? An easy way would be to do the multiplication in the input format, however I need the value also for grouping. If I were able to use many data sources (one for each file), I could avoid the additional field (no grouping per file required) and possibly decrease the runtime of the plan(s). Thanks in advance for your help. 2015-07-01 10:20 GMT+02:00 Stephan Ewen se...@apache.org: How about allowing also a varArg of multiple file names for the input format? We'd then have the option of - File or directory - List of files or directories - Base directory + regex that matches contained file paths On Wed, Jul 1, 2015 at 10:13 AM, Flavio Pompermaier pomperma...@okkam.it wrote: +1 :) On Wed, Jul 1, 2015 at 10:08 AM, chan fentes chanfen...@gmail.com wrote: Thank you all for your help and for pointing out different possibilities. It would be nice to have an input format that takes a directory and a regex pattern (for file names) to create one data source instead of 1500. This would have helped me to avoid the problem. Maybe this can be included in one of the future releases. ;) 2015-06-30 19:02 GMT+02:00 Stephan Ewen se...@apache.org: I agree with Aljoscha and Ufuk. As said, it will be hard for the system (currently) to handle 1500 sources, but handling a parallel source with 1500 files will be very efficient. This is possible, if all sources (files) deliver the same data type and would be unioned. If that is true, you can - Specify the input as a directory. - If you cannot do that, because there is no common parent directory, you can union the files into one data source with a simple trick, as described here: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
Re: OutOfMemoryException: unable to create native thread
Hi Chan, if you feel up to implementing such an input format, then you can also contribute it. You simply have to open a JIRA issue and take ownership of it. Cheers, Till On Wed, Jul 1, 2015 at 10:08 AM, chan fentes chanfen...@gmail.com wrote: Thank you all for your help and for pointing out different possibilities. It would be nice to have an input format that takes a directory and a regex pattern (for file names) to create one data source instead of 1500. This would have helped me to avoid the problem. Maybe this can be included in one of the future releases. ;) 2015-06-30 19:02 GMT+02:00 Stephan Ewen se...@apache.org: I agree with Aljoscha and Ufuk. As said, it will be hard for the system (currently) to handle 1500 sources, but handling a parallel source with 1500 files will be very efficient. This is possible, if all sources (files) deliver the same data type and would be unioned. If that is true, you can - Specify the input as a directory. - If you cannot do that, because there is no common parent directory, you can union the files into one data source with a simple trick, as described here: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
Re: OutOfMemoryException: unable to create native thread
How about allowing also a varArg of multiple file names for the input format? We'd then have the option of - File or directory - List of files or directories - Base directory + regex that matches contained file paths On Wed, Jul 1, 2015 at 10:13 AM, Flavio Pompermaier pomperma...@okkam.it wrote: +1 :) On Wed, Jul 1, 2015 at 10:08 AM, chan fentes chanfen...@gmail.com wrote: Thank you all for your help and for pointing out different possibilities. It would be nice to have an input format that takes a directory and a regex pattern (for file names) to create one data source instead of 1500. This would have helped me to avoid the problem. Maybe this can be included in one of the future releases. ;) 2015-06-30 19:02 GMT+02:00 Stephan Ewen se...@apache.org: I agree with Aljoscha and Ufuk. As said, it will be hard for the system (currently) to handle 1500 sources, but handling a parallel source with 1500 files will be very efficient. This is possible, if all sources (files) deliver the same data type and would be unioned. If that is true, you can - Specify the input as a directory. - If you cannot do that, because there is no common parent directory, you can union the files into one data source with a simple trick, as described here: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
Re: OutOfMemoryException: unable to create native thread
Thank you all for your help and for pointing out different possibilities. It would be nice to have an input format that takes a directory and a regex pattern (for file names) to create one data source instead of 1500. This would have helped me to avoid the problem. Maybe this can be included in one of the future releases. ;) 2015-06-30 19:02 GMT+02:00 Stephan Ewen se...@apache.org: I agree with Aljoscha and Ufuk. As said, it will be hard for the system (currently) to handle 1500 sources, but handling a parallel source with 1500 files will be very efficient. This is possible, if all sources (files) deliver the same data type and would be unioned. If that is true, you can - Specify the input as a directory. - If you cannot do that, because there is no common parent directory, you can union the files into one data source with a simple trick, as described here: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
Re: OutOfMemoryException: unable to create native thread
Hey Chan, the problem is that all sources are scheduled at once for pipelined execution mode (default). There is work in progress to support your workload better in batch execution mode, e.g. run each source one after the other and materialize intermediate results. This will hopefully be in the next 0.10 release. At the moment the best thing you can do is as Aljoscha suggested. Does this work for you or does each file need different processing? – Ufuk On 30 Jun 2015, at 17:36, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
Re: OutOfMemoryException: unable to create native thread
I agree with Aljoscha and Ufuk. As said, it will be hard for the system (currently) to handle 1500 sources, but handling a parallel source with 1500 files will be very efficient. This is possible, if all sources (files) deliver the same data type and would be unioned. If that is true, you can - Specify the input as a directory. - If you cannot do that, because there is no common parent directory, you can union the files into one data source with a simple trick, as described here: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek aljos...@apache.org wrote: Hi Chan, Flink sources support giving a directory as an input path in a source. If you do this it will read each of the files in that directory. They way you do it leads to a very big plan, because the plan will be replicated 1500 times, this could lead to the OutOfMemoryException. Is there a specific reason why you create 1500 separate sources? Regards, Aljoscha On Tue, 30 Jun 2015 at 17:17 chan fentes chanfen...@gmail.com wrote: Hello, how many data sources can I use in one Flink plan? Is there any limit? I get an java.lang.OutOfMemoryException: unable to create native thread when having approx. 1500 files. What I basically do is the following: DataSource -Map - Map - GroupBy - GroupReduce per file and then Union - GroupBy - Sum in a tree-like reduction. I have checked the workflow. It runs on a cluster without any problem, if I only use few files. Does Flink use a thread per operator? It seems as if I am limited in the amount of threads I can use. How can I avoid the exception mentioned above? Best regards Chan
