I am looking for spark scala function to find normal distribution value like norm.dist in Excel. Cannot find in spark library.
Could you please help me with the function or alternate approach to achieve the same in spark? Please advise. Thank you very much.
After searching and compare calculation in excel.
We can use NormalDistribution function to in commons.math3.distribution as followed.
Thanks for the comment.
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I’m new in Kapacitor. Trying to understand how Barrier Node is working. Could you please try to explain it to me in simple words?
Thanks in advace
I'm working on a script to convert a Simulink library to a plain model, meaning it can be simulated, it does not auto-lock etc.
Is there a way to do this with code aside from basically copy-pasting every single block into a new model? And if it isn't, what is the most efficient way to do the "copy-paste".
I was not able to find any clues as how to approach this problem here, or on Google, or on the official documentation or on the MathWorks forum so I'm at a loss on how to proceed.
Thank you in advance!
I don't think it's possible to convert a library to a model, but you can programmatically add library blocks to models like so:
sys = 'testModel';
new_system(sys);
open_system(sys);
add_block('Simulink/Sources/Sine Wave', [sys, '/MySineWave']);
save_system(sys);
close_system(sys);
sim(sys);
You could even use the find_system command to list all the blocks in a library and then loop through them all and create a new model for each using the above code.
I want to run evolutionary algorithms like GA,PSO using pyspark on spark.How to do this using MLLib using Deap python library.Is there any other library available to perform same task.
Have a look at my answer on how to use DEAP with Spark and see if it works for you.
Here is an example of how to configure the DEAP toolbox to replace the map function by a custom one using Spark.
from pyspark import SparkContext
sc = SparkContext(appName="DEAP")
def sparkMap(algorithm, population):
return sc.parallelize(population).map(algorithm)
toolbox.register("map", sparkMap)
In https://github.com/DEAP/deap/issues/268 they show how to do this in the DEAP package. However this is an issue. but they mention there is a pull request (https://github.com/DEAP/deap/pull/76), and is seems the fixed code/branch is from a forked repo.
It sounds like if you rebuild the package with that code it should resolve the issue.
Another resource I found, haven't tried it, is https://apacheignite.readme.io/docs/genetic-algorithms.
Also came across this https://github.com/paduraru2009/genetic-algorithm-with-Spark-for-test-generation
Can anyone provide a function which can be Bacon.combineTemplate alternative written in RxJS?
You can find the solution in the following repo:
https://github.com/ahomu/rx.observable.combinetemplate
How can I create or associate a super column to a column in Perl using Net::Cassandra?
I just chatted with the module author and he doesn't understand the question. Then he guessed you want batch_insert which can take a supercolumn.
If that doesn't help, perhaps you step back, try to explain what you want to achieve and rephrase the question.
Best way, IMHO, is to submit a request to add information about super columns into documentation into Net::Cassandra bug tracker.
batch_insert is one way like daxim says; another way is to just use normal insert but specify super_column in the ColumnPath as well as the column_family.
It looks like Net::Cassandra stays pretty close to the thrift api, so this should be useful: http://wiki.apache.org/cassandra/API