2) if you want to use the result for a computation in the cluster use broadcast sets as described above.1) if you want to fetch the result into your client program use DataSet.collect(). This immediately triggers an execution and fetches the result from the cluster.Broadcasted DataSets are stored on the JVM heap of each task manager (but shared among multiple slots on the same TM), hence the size restriction.There are two ways to retrieve a DataSet (such as the result of a reduce).2016-02-16 21:54 GMT+01:00 Saliya Ekanayake <[hidden email]>:Thank you, yes, this makes sense. The broadcasted data in my case would a large array of 3D coordinates,On a side note, how can I take the output from a reduce function? I can see methods to write it to a given output, but is it possible to retrieve the reduced result back to the program - like a double value representing the average in the previous example.On Tue, Feb 16, 2016 at 3:47 PM, Fabian Hueske <[hidden email]> wrote:FabianIn your case it might be even better to read the data twice instead of reading, writing, and reading it.You can use so-called BroadcastSets to send any sufficiently small DataSet (such as a computed average) to any other function and use it there.However, in your case you'll end up with a data flow that branches (at the source) and merges again (when the average is send to the second map).
Such patterns can cause deadlocks and can therefore not be pipelined which means that the data before the branch is written to disk and read again.2016-02-16 21:15 GMT+01:00 Saliya Ekanayake <[hidden email]>:I looked at the samples and I think what you meant is clear, but I didn't find a solution for my need. In my case, I want to use the result from first map operation before I can apply the second map on the same data set. For simplicity, let's say I've a bunch of short values represented as my data set. Then I need to find their average, so I use a map and reduce. Then I want to map these short values with another function, but it needs that average computed in the beginning to work correctly.Is this possible without doing multiple reads of the input data to create the same dataset?Thank you,saliyaOn Tue, Feb 16, 2016 at 12:03 PM, Fabian Hueske <[hidden email]> wrote:Yes, if you implement both maps in a single job, data is read once.2016-02-16 15:53 GMT+01:00 Saliya Ekanayake <[hidden email]>:Fabian,I've a quick follow-up question on what you suggested. When streaming the same data through different maps, were you implying that everything goes as single job in Flink, so data read happens only once?Thanks,SaliyaOn Mon, Feb 15, 2016 at 3:58 PM, Fabian Hueske <[hidden email]> wrote:It is not possible to "pin" data sets in memory, yet.However, you can stream the same data set through two different mappers at the same time.For instance you can have a job like:/---> Map 1 --> SInk1Source --<
\---> Map 2 --> SInk2and execute it at once.For that you define you data flow and call execute once after all sinks have been created.Best, Fabian2016-02-15 21:32 GMT+01:00 Saliya Ekanayake <[hidden email]>:Fabian,count() was just an example. What I would like to do is say run two map operations on the dataset (ds). Each map will have it's own reduction, so is there a way to avoid creating two jobs for such scenario?The reason is, reading these binary matrices are expensive. In our current MPI implementation, I am using memory maps for faster loading and reuse.Thank you,SaliyaOn Mon, Feb 15, 2016 at 3:15 PM, Fabian Hueske <[hidden email]> wrote:Hi,
it looks like you are executing two distinct Flink jobs.
DataSet.count() triggers the execution of a new job. If you have an execute() call in your program, this will lead to two Flink jobs being executed.It is not possible to share state among these jobs.Maybe you should add a custom count implementation (using a ReduceFunction) which is executed in the same program as the other ReduceFunction.Best, Fabian2016-02-15 21:05 GMT+01:00 Saliya Ekanayake <[hidden email]>:Hi,I see that an InputFormat's open() and nextRecord() methods get called for each terminal operation on a given dataset using that particular InputFormat. Is it possible to avoid this - possibly using some caching technique in Flink?For example, I've some code like below and I see for both the last two statements (reduce() and count()) the above methods in the input format get called. Btw. this is a custom input format I wrote to represent a binary matrix stored as Short values.ShortMatrixInputFormat smif = new ShortMatrixInputFormat();DataSet<Short[]> ds = env.createInput(smif, BasicArrayTypeInfo.SHORT_ARRAY_TYPE_INFO);
MapOperator<Short[], DoubleStatistics> op = ds.map(...)op.reduce(...)op.count(...)Thank you,Saliya--Saliya EkanayakePh.D. Candidate | Research AssistantSchool of Informatics and Computing | Digital Science CenterIndiana University, Bloomington
Cell <a href="tel:812-391-4914" value="+18123914914" target="_blank">812-391-4914
http://saliya.org--Saliya EkanayakePh.D. Candidate | Research AssistantSchool of Informatics and Computing | Digital Science CenterIndiana University, Bloomington
Cell <a href="tel:812-391-4914" value="+18123914914" target="_blank">812-391-4914
http://saliya.org--Saliya EkanayakePh.D. Candidate | Research AssistantSchool of Informatics and Computing | Digital Science CenterIndiana University, Bloomington
Cell <a href="tel:812-391-4914" value="+18123914914" target="_blank">812-391-4914
http://saliya.org--Saliya EkanayakePh.D. Candidate | Research AssistantSchool of Informatics and Computing | Digital Science CenterIndiana University, Bloomington
Cell <a href="tel:812-391-4914" value="+18123914914" target="_blank">812-391-4914
http://saliya.org--Saliya EkanayakePh.D. Candidate | Research AssistantSchool of Informatics and Computing | Digital Science CenterIndiana University, Bloomington
Cell <a href="tel:812-391-4914" value="+18123914914" target="_blank">812-391-4914
http://saliya.org
Free forum by Nabble | Edit this page |