I need to set variables in root scope in one job to be used in a different job. The first job has a Javascript job entry, with the statements:
parent_job.setVariable("customers_full_path", "C:\\customers22.csv", "r");
true;
But the compilation fails with:
Couldn't compile javascript:
org.mozilla.javascript.EvaluatorException: Can't find method
org.pentaho.di.job.Job.setVariable(string,string,string). (#2)
How to set a variable at root level in a Javascript job entry?
Sorry for the passive agressive but:
I don't know if you are new to Pentaho but, the most common mistake for new users, with previous knowledge of programming, is to be sort of 'addicted' to know methods, as such you are using JavaScript for a functionality that is built in the tool. Both Transformations(KTR) and JOBs(KJB) have a similar step, you can better manipulate this in a KTR.
JavaScript steps slow down the flow considerably, so try to stay away from those as much as possible.
EDIT:
Reading This article, seems the only thing you're doing wrong is the actual syntax of the command..
Correct usage :
parent_job.setVariable("Desired Value", [name_of_variable]);
The command you described has 3 parameters, when it should be 2. If you have more than 1 variable you need to set, use 3 times the command. Try it out see if it works.
Related
Is there a way to make the logged user (on superset) to make the queries on impala?
I tried to enable the "Impersonate the logged on user" option on Databases but with no success because all the queries run on impala with superset user.
I'm trying to achieve the same! This will not completely answer this question since it does not still work but I want to share my research in order to maybe help another soul that is trying to use this instrument outside very basic use cases.
I went deep in the code and I found out that impersonation is not implemented for Impala. So you cannot achieve this from the UI. I found out this PR https://github.com/apache/superset/pull/4699 that for whatever reason was never merged into the codebase and tried to copy&paste code in my Superset version (1.1.0) but it didn't work. Adding some logs I can see that the configuration with the impersonation is updated, but then the actual Impala query is with the user I used to start the process.
As you can imagine, I am a complete noob at this. However I found out that the impersonation thing happens when you create a cursor and there is a constructor parameter in which you can pass the impersonation configuration.
I managed to correctly (at least to my understanding) implement impersonation for the SQL lab part.
In the sql_lab.py class you have to add in the execute_sql_statements method the following lines
with closing(engine.raw_connection()) as conn:
# closing the connection closes the cursor as well
cursor = conn.cursor(**database.cursor_kwargs)
where cursor_kwargs is defined in db_engine_specs/impala.py as the following
#classmethod
def get_configuration_for_impersonation(cls, uri, impersonate_user, username):
logger.info(
'Passing Impala execution_options.cursor_configuration for impersonation')
return {'execution_options': {
'cursor_configuration': {'impala.doas.user': username}}}
#classmethod
def get_cursor_configuration_for_impersonation(cls, uri, impersonate_user,
username):
logger.debug('Passing Impala cursor configuration for impersonation')
return {'configuration': {'impala.doas.user': username}}
Finally, in models/core.py you have to add the following bit in the get_sqla_engine def
params = extra.get("engine_params", {}) # that was already there just for you to find out the line
self.cursor_kwargs = self.db_engine_spec.get_cursor_configuration_for_impersonation(
str(url), self.impersonate_user, effective_username) # this is the line I added
...
params.update(self.get_encrypted_extra()) # already there
#new stuff
configuration = {}
configuration.update(
self.db_engine_spec.get_configuration_for_impersonation(
str(url),
self.impersonate_user,
effective_username))
if configuration:
params.update(configuration)
As you can see I just shamelessy pasted the code from the PR. However this kind of works only for the SQL lab as I already said. For the dashboards there is an entirely different way of querying Impala that I did not still find out.
This means that queries for the dashboards are handled in a different way and there isn't something like this
with closing(engine.raw_connection()) as conn:
# closing the connection closes the cursor as well
cursor = conn.cursor(**database.cursor_kwargs)
My gut (and debugging) feeling is that you need to first understand the sqlalchemy part and extend a new ImpalaEngine class that uses a custom cursor with the impersonation conf. Or something like that, however it is not simple (if we want to call this simple) as the sql_lab part. So, the trick is to find out where the query is executed and create a cursor with the impersonation configuration. Easy, isnt'it ?
I hope that this could shed some light to you and the others that have this issue. Let me know if you did find out another way to solve this issue, or if this comment was useful.
Update: something really useful
A colleague of mine succesfully implemented impersonation with impala without touching any superset related, but instead working directly with the impyla lib. A PR was open with the code to change. You can apply the patch directly in the impyla src used by superset. You have to edit both dbapi.py and hiveserver2.py.
As a reminder: we are still testing this and we do not know if it works with different accounts using the same superset instance.
In package development, each example requires <5s. However, the pair of stan_model() and rstan::sampling() take long times more than 5s as follows:
Examples with CPU or elapsed time > 5s
user system elapsed
fit 1.25 0.11 32.47
So I put \donttest{} for each rstan::sampling() in roxygen comments #'#examples
In examples#'#examples, we should not run sampling() or is there any treatment ?
I had tried to create my package based on the code rstan_package_skeleton(path = 'BayesianAAA') when I was taught from you (Thank you !!) but, I do not understand many things about it.
Previously, rstan_package_skeleton(path = 'BayesianAAA') launched the errors in my computer ( but now the error does not occur).
So, I made my package without the rstan_package_skeleton(), say BayesianAAA, and in my original making, I put the Model_A.stan,Model_B.stan,Model_C.stan,.... in the inst/extdata and I refer my stan files as follows;
scr <- system.file("extdata", "Model_A.stan", package="BayesianAAA")
scr <- rstan::stan_model(scr)
I have many questions about the code rstan_package_skeleton(path = 'BayesianAAA').
1) The first question is How to include my existing stan files and how to refer my .stan files for the rstan::stan_model() ?
According to the page following page, it said that
If we had existing .stan files to include with the package we could use the optional stan_files argument to rstan_package_skeleton to include them.
So, I think I should execute, I am not sure but the following like manner is required;
`rstan_package_skeleton(path = 'BayesianAAA', stan_files = "Model_A.stan" )`.
But I do not know how to write the code for several stan files, say Model_A.stan,Model_B.stan,Model_C.stan in my existing package made without the rstan_package_skeleton(). I do not understand , but the following code is correct ? Since I do not where the files described in the variable stan_files is reflected in the new project created by the rstan_package_skeleton().
`rstan_package_skeleton(path = 'BayesianAAA', stan_files = c("Model_A.stan",`Model_B.stan`,`Model_C.stan` )`.
Here, the another question arise, that is,
2) The second question: Where I execute the code rstan_package_skeleton(path = 'BayesianAAA', stan_files = "Model_A.stan" ) ? I execute it form the R studio console in my existing package project. Is it correct ? And then, the new project arise and it is contained the old existing project. What should I do ?
https://cran.r-project.org/web/packages/rstantools/vignettes/minimal-rstan-package.html
3) I do not quite know about the packages "rstanarm" , but I try to imitate it for my package, but I can not fined any .stan file in it, I am wrong ?
I am sorry for my poor English, and Lack of study about these things.
I would be grateful if you could tell me.
You generally should not be writing a package that calls stan_model at runtime, unless like brms or tmbstan you are generating a Stan program at runtime as opposed to writing it statically. There are dozens of packages on CRAN that provide compiled Stan programs basically by following the build process developed for rstanarm, which is facilitated by the rstantools::rstan_package.skeleton function, the step-by-step guide, and the developer guidelines which directly address your question
CRAN policy permits long installation times but imposes restrictions on the time consumed by examples and unit tests that are much shorter than the time that it takes to compile even a simple Stan program. Thus, it is only possible to adequately test your package if it has pre-compiled Stan programs.
Even then, it can be difficult to sample from a posterior distribution (adequately) in five seconds, so you often have to use small datasets, one chain, a small number of iterations, etc.
It is best to pass the names of your Stan programs (which should end in a .stan extension, not use a period otherwise, and only have ASCII letters, numbers, and the underscore in their names) to rstantools::rstan_package_skeleton(). If doing so from RStudio, I would call it while not in an existing project. Then
During installation, all Stan programs will be compiled and saved in the list stanmodels that can then be used by R function in the package. The rule is that the Stan program compiled from the model code in src/stan_files/foo.stan is stored as list element stanmodels$foo.
There are dozens of R packages that have Stan programs in their src/stan_files directory (although the locations of the Stan programs are going to move to inst/stan for the next rstantools release) that for the most part just followed the vignettes and did not have to do any additional steps except write more R functions.
I'm new to flowable and I'm trying to start a process instance with variables. params here is the Map of <String,Object> that I'm using to start the process. It all goes well, but if I try to get my variables back it tells me
"execution 22f42f67-5f88-11e9-9df0-d46d6dbfea92 doesn't exist"
But if I search for it in my process instances list, is there. This is what I do:
pi = runtimeService.startProcessInstanceById(processDefinitionId, params);
runtimeService.getVariables(pi.getId());
I'm stuck with this problem and I do not understand why it keeps doing this. What am I missing?
Flowable has the concept of RuntimeService and HistoryService. The first one contains only the runtime data (what is currently active) and the second one has all the data. The runtime data is a subset of the history data.
The reason why you can’t find the variables via the RuntimeService is due to the fact that the process is completed.
If you use the HistoryService then it would work as expected.
I have alot of Bamboo variables defined due the fact that i have a system with alot of legacy and config at places where it does not belong. Getting rid of all this will take a bit longer on the roadmap so i need to find a way to auto replace all these values.
The number im talking about is that there are 8 customer config files with each about 100 variables. Indeed, there was a maniac who added all of those in Bamboo because as you might thought most of them are variable for each environment.
At this moment i want to automate the deployment process and all is going fine exact the fact that i need to replace 100 variables and i dont want to maintain it in my script itself all the time.
I am looking for a way to retrieve all the variables in an array so i can just iterate through all the keys and try to replace them at the config files.
echo "${bamboo.application.myvalue}" will replace the value as expected. The only problem is, how can i get all the keys under bamboo.*
I tried it with the following functions but all without success:
printenv
env
declare
All above without success. How can i retrieve a list of all those variables as inline script in Bamboo.
Thanks alot
I think it is not possible to change the value of the variables on the fly. Instead, you can use the "Inject Bamboo variables" task in order to be able to change the variable value.
This task reads a file to create the variables. So, all you have to do is to create this file with the values you need, and then use this variables.
E.g.: Creating a file from a powershell script:
$path = 'bambooVariaveis.properties'
$connectionstringX = 'connectionstring="Data Source=XXXX;"'
$Utf8NoBomEncoding = New-Object System.Text.UTF8Encoding($False)
[System.IO.File]::WriteAllLines($path, $connectionstringX, $Utf8NoBomEncoding)
E.g: Inject Bamboo Variables config
Using it (in a subsequent script task):
echo ${bamboo.inject.connectionstring}
I'm very new at JMeter issues.
In a test script i have a BeanShell PreProcessor element that updates some variables previously defined at a "User Defined Variables" element.
Latter those variables are used in "Http Requests". However, the value that is used in the http request is the default one.
The scripts seems to be working due to some debug print();
My question is if it's necessary to delay the script to be sure that the BeanShell finishes?
Thanks a lot for your attention
There is no need to put any delay to Beanshell Pre-Processor as it's being executed before request. I'd recommend to check your jmeter.log file to see if there are any scripting issues as Beanshell Pre-Processor does not report errors anywhere including View Results Tree listener.
There are at least 2 ways to assure that everything is fine with your Beanshell script:
Put your debug print code after variables replace logic to see if it fires
Use JMeter __Beahshell function right in your HTTP request. If it's ok - View Results Tree will demonstrate beanshell-generated value. If not - the field will be blank and relevant error will be displayed in the log.
Example test case:
Given following Test Plan structure:
Thread Group with 1 user and 1 loop
HTTP GET Request to google.com with path of / and parameter q
If you provide as parameter "q" following beanshell function:
${__BeanShell(System.currentTimeMillis())}
and look into View Results Tree "Request" tab you should see something like:
GET http://www.google.com/?q=1385206045832
and if you change function to something incorrect like:
${__BeanShell(Something.incorrect())}
you'll see a blank request.
The correct way of changing existing variable (or creating new if variable doesn't exist) looks like
vars.put("variablename", "variablevalue");
*Important: * JMeter Variables are Java Strings, if you're trying to set something else (date, integer, whatever) to JMeter Variable you need to cast it to String somehow.
Example:
int i = 5;
vars.put("int_i", String.valueOf(i));
Hope this helps.
You can update the vale of a "user defined variable".
You have to create a bean shell sampler
vars.put("user_defined_variable", "newvalue");
#theINtoy got it right.
http://www.blazemeter.com/blog/queen-jmeters-built-componentshow-use-beanshell
I'm new to jmeter too but as I know variables defined in "User defined variables" are constants, so you can't change them. I recommend to use "User Parameters" in preprocessors or CSV Data Set Config.