Hey, thanks! Those are just seeds, the files aren't large.
The scale out data is the transactions. The seed data needs to be the same, shipped to ALL nodes, and then the nodes generate transactions. On Wed, Sep 2, 2015 at 9:21 AM, Robert Metzger <rmetz...@apache.org> wrote: > I'm starting a new discussion thread for the bigpetstore-flink integration > ... > > > I took a closer look into the code you've posted. > It seems to me that you are generating a lot of data locally on the > client, before you actually submit a job to Flink. (Both "customers" and > "stores" are generated locally) > Is that only some "seed" data? > > I would actually try to generate as much data as possible in the cluster, > making the generator very scalable. > > I don't think that you need to register a Kryo serializer for the Product > and Transaction type. > I was able to run the code without the serializer registration. > > > ---------- Forwarded message ---------- > From: jay vyas <jayunit100.apa...@gmail.com> > Date: Wed, Sep 2, 2015 at 2:56 PM > Subject: Re: Hardware requirements and learning resources > To: user@flink.apache.org > > > We're also working on a bigpetstore implementation of flink which will > help onboard spark/mapreduce folks. > > I have prototypical code here that runs a simple job in memory, > contributions welcome, > > right now there is a serialization error > https://github.com/bigpetstore/bigpetstore-flink . > > On Wed, Sep 2, 2015 at 8:50 AM, Robert Metzger <rmetz...@apache.org> > wrote: > >> Hi Juan, >> >> I think the recommendations in the Spark guide are quite good, and are >> similar to what I would recommend for Flink as well. >> Depending on the workloads you are interested to run, you can certainly >> use Flink with less than 8 GB per machine. I think you can start Flink >> TaskManagers with 500 MB of heap space and they'll still be able to process >> some GB of data. >> >> Everything above 2 GB is probably good enough for some initial >> experimentation (again depending on your workloads, network, disk speed >> etc.) >> >> >> >> >> On Wed, Sep 2, 2015 at 2:30 PM, Kostas Tzoumas <ktzou...@apache.org> >> wrote: >> >>> Hi Juan, >>> >>> Flink is quite nimble with hardware requirements; people have run it in >>> old-ish laptops and also the largest instances available in cloud >>> providers. I will let others chime in with more details. >>> >>> I am not aware of something along the lines of a cheatsheet that you >>> mention. If you actually try to do this, I would love to see it, and it >>> might be useful to others as well. Both use similar abstractions at the API >>> level (i.e., parallel collections), so if you stay true to the functional >>> paradigm and not try to "abuse" the system by exploiting knowledge of its >>> internals things should be straightforward. These apply to the batch APIs; >>> the streaming API in Flink follows a true streaming paradigm, where you get >>> an unbounded stream of records and operators on these streams. >>> >>> Funny that you ask about a video for the DataStream slides. There is a >>> Flink training happening as we speak, and a video is being recorded right >>> now :-) Hopefully it will be made available soon. >>> >>> Best, >>> Kostas >>> >>> >>> On Wed, Sep 2, 2015 at 1:13 PM, Juan Rodríguez Hortalá < >>> juan.rodriguez.hort...@gmail.com> wrote: >>> >>>> Answering to myself, I have found some nice training material at >>>> http://dataartisans.github.io/flink-training. There are even videos at >>>> youtube for some of the slides >>>> >>>> - http://dataartisans.github.io/flink-training/overview/intro.html >>>> https://www.youtube.com/watch?v=XgC6c4Wiqvs >>>> >>>> - >>>> http://dataartisans.github.io/flink-training/dataSetBasics/intro.html >>>> https://www.youtube.com/watch?v=0EARqW15dDk >>>> >>>> The third lecture >>>> http://dataartisans.github.io/flink-training/dataSetAdvanced/intro.html >>>> more or less corresponds to https://www.youtube.com/watch?v=1yWKZ26NQeU >>>> but not exactly, and there are more lessons at >>>> http://dataartisans.github.io/flink-training, for stream processing >>>> and the table API for which I haven't found a video. Does anyone have >>>> pointers to the missing videos? >>>> >>>> Greetings, >>>> >>>> Juan >>>> >>>> 2015-09-02 12:50 GMT+02:00 Juan Rodríguez Hortalá < >>>> juan.rodriguez.hort...@gmail.com>: >>>> >>>>> Hi list, >>>>> >>>>> I'm new to Flink, and I find this project very interesting. I have >>>>> experience with Apache Spark, and for I've seen so far I find that Flink >>>>> provides an API at a similar abstraction level but based on single record >>>>> processing instead of batch processing. I've read in Quora that Flink >>>>> extends stream processing to batch processing, while Spark extends batch >>>>> processing to streaming. Therefore I find Flink specially attractive for >>>>> low latency stream processing. Anyway, I would appreciate if someone could >>>>> give some indication about where I could find a list of hardware >>>>> requirements for the slave nodes in a Flink cluster. Something along the >>>>> lines of >>>>> https://spark.apache.org/docs/latest/hardware-provisioning.html. >>>>> Spark is known for having quite high minimal memory requirements (8GB RAM >>>>> and 8 cores minimum), and I was wondering if it is also the case for >>>>> Flink. >>>>> Lower memory requirements would be very interesting for building small >>>>> Flink clusters for educational purposes, or for small projects. >>>>> >>>>> Apart from that, I wonder if there is some blog post by the comunity >>>>> about transitioning from Spark to Flink. I think it could be interesting, >>>>> as there are some similarities in the APIs, but also deep differences in >>>>> the underlying approaches. I was thinking in something like Breeze's >>>>> cheatsheet comparing its matrix operatations with those available in >>>>> Matlab >>>>> and Numpy >>>>> https://github.com/scalanlp/breeze/wiki/Linear-Algebra-Cheat-Sheet, >>>>> or like http://rosettacode.org/wiki/Factorial. Just an idea anyway. >>>>> Also, any pointer to some online course, book or training for Flink >>>>> besides >>>>> the official programming guides would be much appreciated >>>>> >>>>> Thanks in advance for help >>>>> >>>>> Greetings, >>>>> >>>>> Juan >>>>> >>>>> >>>> >>> >> > > > -- > jay vyas > > -- jay vyas
