I am just a beginner in Hazelcast. I am still learning the basics of it. How is batch processing being done in Hazelcast? Is there any related architecture for it?
See hazelcast ExecutorService component:
http://www.hazelcast.com/docs/2.5/manual/single_html/#ExecutorService
Related
TensorFlow Model Server has a command-line option '--rest_api_timeout_in_ms' that controls the timeout for its rest api. I believe by default this is 30 seconds. I am serving a (slow) TF model with sagemaker-tensorflow-container (https://github.com/aws/sagemaker-tensorflow-serving-container) and getting timeouts from the underlying tensorflow model server process (which is started by the sagemaker container, see here: https://github.com/aws/sagemaker-tensorflow-serving-container/blob/3952606048615297e5629b2b27dfa6557616b986/docker/build_artifacts/sagemaker/serve.py#L178
Looking at the sagemaker-tensorflow-container source I do not see a way to supply this '--rest_api_timeout_in_ms' option :-(.
If anyone faced this or similar problem, I would really appreciate any hints or possible workarounds. Thanks!
I would like to implement Dominant Resource Fairness (DRF) or other scheduling algorithms in apache yarn. Does anybody know how to implement it? Is there any source?
Cheers
Yes, you can refer to DominantResourceFairnessPolicy.java in the fair scheduler for more information.
I was exploring redisson and decided to use for the ease of its simplicity when compared to Jedis, and few other good reviews i found over internet.
The environment on which i will be using redisson is Storm topologies.
It's not a good idea to create threads by application level code in a
Storm Topology
I dig deeper to some extent of redisson code which internally translates the commands to async and command executor and promise.
just want to confirm . Is redisson internally spawning threads to achieve this.
A follow up. Is Jedis also doing the same in its internal implementation.
Please consider pipeline implementation also in your answers
Redisson mentions in some perf documentation I found somewhere that Redisson v.x supports on the order 30k threads/sec. I read this as concurrent requests.
I imagine at least two of those are in separate threads
Not sure what you are asking, but perhaps this gives some insight
https://github.com/redisson/redisson/wiki/11.-Redis-commands-mapping
Hi I am finding it difficult comparing mapreduce with hama, I understand that hama uses this bulk synchronous parallel model and that the worker nodes can communicate with one another whereas in apache's hadoop the worker nodes only communicate to the namenode correct? If so I don't understand the benefits hama would have over a standard mapreduce in hadoop thanks!
Can you go through this PDF link
This explains the difference between MapReduce and BSP(Apache Hama offers Bulk Synchronous Parallel computing engine).
MapReduceframework has been used to solve a number of non-trivial problems in academia. Putting MapReduce on strong theoretical foundations is crucial in understanding its capabilities. T
whileHamause BSP model of computation, underlining the relevance of BSP to modern parallel algorithm design and defining a subclass of BSP algorithms that can be efficiently implemented in MapReduce.
I was searching about process model of Erlang over internet and found out some graphs slides 3-4 in one of the talk given by Joe Armstrong. They shows a lot of difference between process creation and message passing time between Erlang , java and C#. Can anybody tell me the reason behind such big difference?
In Erlang, processes are not real processes. They are light structures handled by the language. Message passing is also handled by the language, using shared memory when possible.
In the other hand, other languages are using real threads / processes since they don't have built-in light structures like this. Therefore, these structure are a bit heavier, are using thread primitives to communicate (slower).
I don't know about your graph, but I guess it shows that Erlang's processes are better. It's done comparing things that are inherently different, however it show that Erlang rocks to model standalone objects communicating using messages (things you cannot really do in other languages).
Erlang processes are very light weight. An implementation does not even need to allocate an OS thread to an Erlang process. This has to do with the functional nature of Erlang.