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Different random variable for same HTTP request when load in distributed mode


Different random variable for same HTTP request when load in distributed mode

By : user2185125
Date : November 20 2020, 04:01 AM
Hope that helps Keep Random Variable's Random Seed empty and set Per Thread(User)? to True
code :


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How do I most effectively prevent my normally-distributed random variable from being zero?

How do I most effectively prevent my normally-distributed random variable from being zero?


By : user3202642
Date : March 29 2020, 07:55 AM
it helps some times I'm writing a Monte Carlo algorithm, in which at one point I need to divide by a random variable. More precisely: the random variable is used as a step width for a difference quotient, so I actually first multiply something by the variable and then again divide it out of some locally linear function of this expression. Like , your way seems elegant enough, maybe a little different:
code :
do {
    h = r();
} while (h == 0.0);
Empty HTTP POST request or GET request to generate a random value through an HTTP API

Empty HTTP POST request or GET request to generate a random value through an HTTP API


By : Maxime Champesme
Date : March 29 2020, 07:55 AM
Hope this helps Safe => whether call results in a change of state on the server. Idempotent => whether multiple calls result in the same change on the server.
So the question is not the data that is returned. Rather it is the server state: so if you are storing this value on the server this results in a change in the state, then it is not fit for GET. Otherwise if it is the data that is returned, it is fine. Call to http://stackoverflow.com returns different data if called 10 minutes apart.
storm cluster mode, distributed bolt/worker load sharing

storm cluster mode, distributed bolt/worker load sharing


By : user3572686
Date : March 29 2020, 07:55 AM
around this issue You've already done it, unless something has gone wrong.
When you submit a topology to Storm, the Nimbus service looks at the load on the cluster via the Supervisor processes spread throughout the cluster. Nimbus then provides some quantity of resources for the topology to run. Those resources are oftentimes spread throughout the various Supervisor nodes in the cluster, and they will process tuples in parallel. Nimbus occasionally revisits these decisions and changes which nodes process what in an attempt to keep load in the cluster balanced. As a user you should never notice that process.
How to make a regression line in R using a normally distributed error and a uniformly distributed random variable

How to make a regression line in R using a normally distributed error and a uniformly distributed random variable


By : user3261295
Date : March 29 2020, 07:55 AM
wish of those help Arithmetic operators in R work on vectors, so you don't need the loops at all:
code :
y <- 5 + 3 * xvals + evals
xvals <- runif(n = 100, min = -1, max = 1)
evals <- rnorm(n = 100, mean = 0, sd = 1)
y <- 5 + 3 * xvals + evals

print(y)
plot(xvals, y)
y <- append(y, 5 + 3*x + e)
Request timed out Message while starting Kafka connect in distributed mode

Request timed out Message while starting Kafka connect in distributed mode


By : user3645921
Date : March 29 2020, 07:55 AM
Does that help
all three topic is created by kafka connect connect-offsets connect-configs connect-status
code :
offset.storage.topic=connect-offsets
offset.storage.replication.factor=1

config.storage.topic=connect-configs
config.storage.replication.factor=1

status.storage.topic=connect-status
status.storage.replication.factor=1
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