I did run the bench marking successfully without aggregator, and I did run the aggregator alone.
Can I run the bench marking and obtain the aggregator gui simultaneously?
Yes, it's possible, just write a main() that does both in sequence:
PlannerBenchmarkFactory plannerBenchmarkFactory = PlannerBenchmarkFactory.createFromXmlResource(
"org/optaplanner/examples/nqueens/benchmark/nqueensBenchmarkConfig.xml");
PlannerBenchmark plannerBenchmark = benchmarkFactory.buildPlannerBenchmark();
plannerBenchmark.benchmark();
PlannerBenchmarkFactory plannerBenchmarkFactory2 = PlannerBenchmarkFactory.createFromXmlResource(
"org/optaplanner/examples/nqueens/benchmark/nqueensBenchmarkConfig.xml");
BenchmarkAggregatorFrame.createAndDisplay(plannerBenchmarkFactory2);
Related
I am using APScheduler in decorator way to run jobs at certain intervals. The problem is that when below code is deployed in two EC2 instances then same job runs twice at same with difference in milliseconds.
My question is : How to avoid running same job by two EC2 instances at same time or Do I need to follow different code design pattern in this case. I want to run this job only once either by one of the severs.
from datetime import datetime
from apscheduler.schedulers.blocking import BlockingScheduler
sched = BlockingScheduler()
sched.start()
#sched.scheduled_job('interval', id='my_job_id', hours=2)
def job_function():
print("Hello World")
If you can share any locking mechanism examples it would be appreciable
You can use AWS-SDK/AWS-CLI by using AWS-SDK/AWS-CLI you can set
If instance_id = "your instance id"
Write your code here
Now your cron will get execute on each instances you have and your code will be executed from that specific instance.
So far I'm able to run cucumber-jvm tests in parallel by using multiple runner classes but as my project increasing and new features are adding up each time so it's getting really difficult to optimise execution time
So my question is what is the best approach to optimise execution time
Is it by adding new runner class for each feature/limiting to certain threads and updating runner class with new tags to execute
So far I'm using thread count 8 and I've runner classes are also 8
Using this approach is fine until now, but one of the feature has got more scenarios added recently and it's taking longer time to finish :( so how is it possible to optimise execution time here...
Any help much appreciated!!
This worked for me:
Courgette-JVM
It has added capabilities to run cucumber tests in parallel on a feature level or on a scenario level.
It also provides an option to automatically re-run failed scenarios.
Usage
#RunWith(Courgette.class)
#CourgetteOptions(
threads = 10,
runLevel = CourgetteRunLevel.SCENARIO,
rerunFailedScenarios = true,
showTestOutput = true,
cucumberOptions = #CucumberOptions(
features = "src/test/resources/features",
glue = "steps",
tags = {"#regression"},
plugin = {
"pretty",
"json:target/courgette-report/courgette.json",
"html:target/courgette-report/courgette.html"}
))
public class RegressionTestSuite {
}
I've got a large Groovy application with a lot of JUnit integration tests (256), most of which use 'com.github.tlrx.elasticsearch-test', version: '1.2.1' to run elasticsearch locally.
part way through running all of the test classes all the test that use elasticsearch start throwing a 'ElasticsearchIllegalStateException' with message 'Failed to obtain node lock, is the following location writable?: [./target/elasticsearch-test/data/cluster-test-kiml42s-MacBook-Pro.local]'.
If I run any of these classes alone, it works fine.
This is my initialising code run in all #Befores:
esSetup = new EsSetup();
CreateIndex createIndex = createIndex(index)
for(int i = 0; i < types.size(); i++){
createIndex.withMapping(types[i], fromClassPath(mappings[i]))
}
esSetup.execute(deleteAll(), createIndex)
client = esSetup.client()
And this if my teardown code run in the #Afters:
client.admin().indices().prepareDelete(index).get()
This problem doesn't seem to happen on our build server, so it's only annoying and inconvinient, not a serious problem, but any help would be most appreciated. Thanks.
This problem seems to have been cause by leaving the test nodes active while jUnit ran through all the tests - eventually it stopped being able to create new nodes. The solution is to use esSetup.terminate() in the after to destroy the nodes at the end of each test.
Here's an example of it being used correctly: https://gist.github.com/tlrx/4117854
I am trying to understand, how pipe lining in redis works? According to one blog I read, For this code
Pipeline pipeline = jedis.pipelined();
long start = System.currentTimeMillis();
for (int i = 0; i < 100000; i++) {
pipeline.set("" + i, "" + i);
}
List<Object> results = pipeline.execute();
Every call to pipeline.set() effectively sends the SET command to Redis (you can easily see this by setting a breakpoint inside the loop and querying Redis with redis-cli). The call to pipeline.execute() is when the reading of all the pending responses happens.
So basically, when we use pipe-lining, when we execute any command like set above, the command gets executed on the server but we don't collect the response until we executed, pipeline.execute().
However, according to the documentation of pyredis,
Pipelines are a subclass of the base Redis class that provide support for buffering multiple commands to the server in a single request.
I think, this implies that, we use pipelining, all the commands are buffered and are sent to the server, when we execute pipe.execute(), so this behaviour is different from the behaviour described above.
Could someone please tell me what is the right behaviour when using pyreids?
This is not just a redis-py thing. In Redis, pipelining always means buffering a set of commands and then sending them to the server all at once. The main point of pipelining is to avoid extraneous network back-and-forths-- frequently the bottleneck when running commands against Redis. If each command were sent to Redis before the pipeline was run, this would not be the case.
You can test this in practice. Open up python and:
import redis
r = redis.Redis()
p = r.pipeline()
p.set('blah', 'foo') # this buffers the command. it is not yet run.
r.get('blah') # pipeline hasn't been run, so this returns nothing.
p.execute()
r.get('blah') # now that we've run the pipeline, this returns "foo".
I did run the test that you described from the blog, and I could not reproduce the behaviour.
Setting breakpoints in the for loop, and running
redis-cli info | grep keys
does not show the size increasing after every set command.
Speaking of which, the code you pasted seems to be Java using Jedis (which I also used).
And in the test I ran, and according to the documentation, there is no method execute() in jedis but an exec() and sync() one.
I did see the values being set in redis after the sync() command.
Besides, this question seems to go with the pyredis documentation.
Finally, the redis documentation itself focuses on networking optimization (Quoting the example)
This time we are not paying the cost of RTT for every call, but just one time for the three commands.
P.S. Could you get the link to the blog you read?
How does one use the flag options for benchmarks with the gocheck testing framework? In the link that I provided it seems to be that the only example they provide is by running go test -check.b, however, they do not provide additional comments on how it works so its hard to use it. I could not even find the -check in the go documentation when I did go help test nor when I did go help testflag. In particular I want to know how to use the benchmark testing framework better and control how long it runs for or for how many iterations it runs for etc etc. For example in the example they provide:
func (s *MySuite) BenchmarkLogic(c *C) {
for i := 0; i < c.N; i++ {
// Logic to benchmark
}
}
There is the variable c.N. How does one specify that variable? Is it through the actual program itself or is it through go test and its flags or the command line?
On the side note, the documentation from go help testflag did talk about -bench regex, benchmem and benchtime t options, however, it does not talk about the -check.b option. However I did try to run these options as described there but it didn't really do anything I could notice. Does gocheck work with the original options for go test?
The main problem I see is that there is no clear documentation for how to use the gocheck tool or its commands. I accidentally gave it a wrong flag and it threw me a error message suggesting useful commands that I need (which limited description):
-check.b=false: Run benchmarks
-check.btime=1s: approximate run time for each benchmark
-check.f="": Regular expression selecting which tests and/or suites to run
-check.list=false: List the names of all tests that will be run
-check.v=false: Verbose mode
-check.vv=false: Super verbose mode (disables output caching)
-check.work=false: Display and do not remove the test working directory
-gocheck.b=false: Run benchmarks
-gocheck.btime=1s: approximate run time for each benchmark
-gocheck.f="": Regular expression selecting which tests and/or suites to run
-gocheck.list=false: List the names of all tests that will be run
-gocheck.v=false: Verbose mode
-gocheck.vv=false: Super verbose mode (disables output caching)
-gocheck.work=false: Display and do not remove the test working directory
-test.bench="": regular expression to select benchmarks to run
-test.benchmem=false: print memory allocations for benchmarks
-test.benchtime=1s: approximate run time for each benchmark
-test.blockprofile="": write a goroutine blocking profile to the named file after execution
-test.blockprofilerate=1: if >= 0, calls runtime.SetBlockProfileRate()
-test.coverprofile="": write a coverage profile to the named file after execution
-test.cpu="": comma-separated list of number of CPUs to use for each test
-test.cpuprofile="": write a cpu profile to the named file during execution
-test.memprofile="": write a memory profile to the named file after execution
-test.memprofilerate=0: if >=0, sets runtime.MemProfileRate
-test.outputdir="": directory in which to write profiles
-test.parallel=1: maximum test parallelism
-test.run="": regular expression to select tests and examples to run
-test.short=false: run smaller test suite to save time
-test.timeout=0: if positive, sets an aggregate time limit for all tests
-test.v=false: verbose: print additional output
is writing wrong commands the only way to get some help with this tool? it doesn't have a help flag or something?
I'm 5 years late, but to specify how many N times to run. Use the option -benchtime Nx.
Example:
go test -bench=. -benchtime 100x
BenchmarkTest 100 ... ns/op
Please read more about all go testing flags here.
see the Description_of_testing_flags:
-bench regexp
Run benchmarks matching the regular expression.
By default, no benchmarks run. To run all benchmarks,
use '-bench .' or '-bench=.'.
-check.b works the same way as -test.bench.
E.g. to run all benchmarks:
go test -check.b=.
to run a specific benchmark:
go test -check.b=BenchmarkLogic
more information about testing in Go can be found here