Workflow | Debuggable script language for interoperation with C++ using reflection | Reflection library
kandi X-RAY | Workflow Summary
kandi X-RAY | Workflow Summary
Debuggable script language for interoperation with C++ using reflection.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Workflow
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Trending Discussions on Workflow
QUESTION
Turns out you can't have comments in JSON files, and it's a bit awkward to have people refer to some documentation telling them what line to copy/paste in and where in order to achieve this.
I think I can make a python script to copy/paste in one of two package.json files depending on what flags they pass in, but that feels overcomplicated.
I think I can include both dependencies (under different names) but that would create a requirement for both to be available, which is not good either.
Looking for ideas/thoughts on a good way to accomplish this. I have a release and dev version of the same dependency and I often need to swap between the two. Would like to improve the workflow beyond just having a notepad on the side with the two lines pasted in it...
...ANSWER
Answered 2021-Jun-15 at 21:43yarn
and npm
already do this job, why not use them?
Tag the dev versions when you release them
QUESTION
I have a following class that reads csv data into Spark's Dataset
. Everything works fine if I just simply read and return the data
.
However, if I apply a MapFunction
to the data
before returning from function, I get
Exception in thread "main" org.apache.spark.SparkException: Task not serializable
Caused by: java.io.NotSerializableException: com.Workflow
.
I know Spark's working and its need to serialize objects for distributed processing, however, I'm NOT using any reference to Workflow
class in my mapping logic. I'm not calling any Workflow
class function in my mapping logic. So why is Spark trying to serialize Workflow
class? Any help will be appreciated.
ANSWER
Answered 2021-Feb-17 at 08:21you could make Workflow implement Serializeble and SparkSession as @transient
QUESTION
I have a workflow which creates a new branch with a name that I save as an env variable. the reason is I need the workflow to run on a new clean branch.
1 Job after that I want to check out the branch. the problem is I cant seem to use env variables on the "ref" in order to check it out.
is there a way to do this ? or does github not support this yet.
example code:
...ANSWER
Answered 2021-Jun-13 at 10:33This question asked the same thing.
What you want to use here are not env variables
but outputs
.
You can specify a set of outputs that you want to pass to subsequent jobs and then access those values from your needs context.
See documentation:
QUESTION
Base.html
...ANSWER
Answered 2021-Jun-15 at 04:11Typo.
In the base.html, you've named the block "content". In index.html, you've called it "contend".
It would be nice if Django threw an error when this sort of thing happens - but I think the main reason it doesn't is for adaptability. At a glance it seem you're doing everything else correctly though.
QUESTION
I am trying to follow this tutorial here - https://juliasilge.com/blog/xgboost-tune-volleyball/
I am using it on the most recent Tidy Tuesday dataset about great lakes fishing - trying to predict agency based on many other values.
ALL of the code below works except the final row where I get the following error:
...ANSWER
Answered 2021-Jun-15 at 04:08If we look at the documentation of last_fit() We see that split
must be
An rsplit object created from `rsample::initial_split().
You accidentally passed the cross-validation folds object stock_folds
into split
but you should have passed rsplit
object stock_split
instead
QUESTION
I have a Python Apache Beam streaming pipeline running in Dataflow. It's reading from PubSub and writing to GCS. Sometimes I get errors like "Error in _start_upload while inserting file ...", which comes from:
...ANSWER
Answered 2021-Jun-14 at 18:49In a streaming pipeline, Dataflow retries work items running into errors indefinitely.
The code itself does not need to have retry logic.
QUESTION
I have recently decided to try out Laravel Sail instead of my usual setup with Vagrant/Homestead. Everything seems to be beautifully and easily laid out but I cannot seem to find a workaround for changing domain names in the local environment.
I tried serving the application on say port 89 with the APP_PORT=89 sail up
command which works fine using localhost:89 however it seems cumbersome to try and remember what port was which project before starting it up.
I am looking for a way to change the default port so that I don't have to specify what port to serve every time I want to sail up. Then I can use an alias like laravel.test
for localhost:89
so I don't have to remember ports anymore I can just type the project names.
I tried changing the etc/hosts file but found out it doesn't actually help with different ports
I essentially am trying to access my project by simply typing 'laravel.test' on the browser for example.
Also open for any other suggestions to achieve this. Thanks
**Update ** After all this search I actually decided to change my workflow to only have one app running at a time so now I am just using localhost and my CPU and RAM loves it, so if you are here moving from homestead to docker, ask yourself do you really need to run all these apps at the same time. If answer is yes research on, if not just use localhost, there is nothing wrong with it
...ANSWER
Answered 2021-Feb-12 at 20:06To change the local name in Sail from the default 'laravel.test' and the port, add the following to your .env file:
APP_SERVICE="yourProject.local"
APP_PORT=89
This will take effect when you build (or rebuild using sail build --no-cache
) your Sail container.
And to be able to type in 'yourProject.local' in your web browser and have it load your web page, ensure you have your hosts file updated by adding
127.0.0.1 yourProject.local
to your hosts file. This file is located:
- Windows 10 – “C:\Windows\System32\drivers\etc\hosts”
- Linux – “/etc/hosts”
- Mac OS X – “/private/etc/hosts”
You'll need to close all browser instances and reopen after making chnages to the hosts file. With this, try entering the alias both with and without the port number to see which works. Since you already set the port via .env you may not need to include it in your alias.
If this doesn't work, change the .env APP_URL=http://yourProject.local:89
Ok another option, in /routes/web.php I assume you have a route set up that may either return a view or call a controller method. You could test to see if you can have this ‘return redirect('http://yourProject.local:89');’ This may involve a little playing around with the routes/controller, but this may be worth looking into.
QUESTION
There is a Java 11 (SpringBoot 2.5.1) application with simple workflow:
- Upload archives (as multipart files with size 50-100 Mb each)
- Unpack them in memory
- Send each unpacked file as a message to a queue via JMS
When I run the app locally java -jar app.jar
its memory usage (in VisualVM) looks like a saw: high peaks (~ 400 Mb) over a stable baseline (~ 100 Mb).
When I run the same app in a Docker container memory consumption grows up to 700 Mb and higher until an OutOfMemoryError. It appears that GC does not work at all. Even when memory options are present (java -Xms400m -Xmx400m -jar app.jar
) the container seems to completely ignore them still consuming much more memory.
So the behavior in the container and in OS are dramatically different.
I tried this Docker image in DockerDesktop Windows 10
and in OpenShift 4.6
and got two similar pictures for the memory usage.
Dockerfile
...ANSWER
Answered 2021-Jun-13 at 03:31In Java 11, you can find out the flags that have been passed to the JVM and the "ergonomic" ones that have been set by the JVM by adding -XX:+PrintCommandLineFlags
to the JVM options.
That should tell you if the container you are using is overriding the flags you have given.
Having said that, its is (IMO) unlikely that the container is what is overriding the parameters.
It is not unusual for a JVM to use more memory that the -Xmx
option says. The explanation is that that option only controls the size of the Java heap. A JVM consumes a lot of memory that is not part of the Java heap; e.g. the executable and native libraries, the native heap, metaspace, off-heap memory allocations, stack frames, mapped files, and so on. Depending on your application, this could easily exceed 300MB.
Secondly, OOMEs are not necessarily caused by running out of heap space. Check what the "reason" string says.
Finally, this could be a difference in your app's memory utilization in a containerized environment versus when you run it locally.
QUESTION
I am new to Spark and am trying to run on a hadoop cluster a simple spark jar file built through maven in intellij. But I am getting classnotfoundexception in all the ways I tried to submit the application through spark-submit.
My pom.xml:
...ANSWER
Answered 2021-Jun-14 at 09:36You need to add scala-compiler configuration to your pom.xml
. The problem is without that there is nothing to compile your SparkTrans.scala file into java classes.
Add:
QUESTION
I am currently doing a course of Version control using git from coursera. There is a project which I have to complete and make a git workflow. Here is the final gitflow graph of my project
My graph has 3 "feature 2 wip" commits but the other project graph has only one "feature 2 wip" commit. Here is the gitflow graph of other project
I am not able to understand whether my graph is correct or the other project graph is correct. We have to follow the instructions given in the project. I am also attaching the images of the instructions as well. If I am wrong then please explain my mistake in detail.
...ANSWER
Answered 2021-Jun-13 at 19:15Finally done it. Use Rebase interactively and feature 2 wip is required only once with the latest commit and the old ones can be merged into the new ones.
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