I've been working on a small set of command line programs in Scala. While
developing I used SBT, and tested the program with run within the console. At
this point the programs had a fast startup time (when re-run after initial compilation); nearly instant, even
with additional dependencies.
Now that I'm trying to actually utilize them on my system outside of sbt, the speeds have noticeable lag. I'm looking for ways to
reduce this, since the nature of these utilities requires little to no delay.
The best speeds I've achieved so far has been through utilizing Drip. I include all dependencies in a lib directory by utilizing Pack and then run by executing a shell script like this:
#!/bin/sh
SCRIPT=$(readlink -f "$0")
SCRIPT_PATH=$(dirname "$SCRIPT")
PROG_HOME=`cd "$SCRIPT_PATH/../" && pwd`
CLASSPATH_SUFFIX=""
# Path separator used in EXTRA_CLASSPATH
PSEP=":"
exec drip \
-cp "${PROG_HOME}/lib/*${CLASSPATH_SUFFIX}" \ # Add lib directory to classpath
TagWorkspace "$#" # TagWorkspace is the main class
This is still noticeably slower then invoking run from within SBT.
I'm curious as to why SBT is able to startup the application so much faster, and if there is someway for me to levarage its strategy, or SBT itself, even if that means keeping a long living process around to actually run a command through.
Unless you have forking turned on for your run task, this is likely due to VM startup time. When you run from inside an active SBT session, you have an already initialized VM pointing at your classes - all SBT needs to do is create a new ClassLoader and point it at your build output directory. This bypasses all of the other (not insignificant) stuff that happens when you fire up a new VM.
Have you tried using the client VM to start your utility from the command line? Sadly, this isn't an option with 64-bit Java, since Oracle apparently doesn't want to support it, but if you're using a 32-bit VM, try adding the -client argument to the list that you give the VM from the command line.
If you are using a 64-bit VM, some googling will find you some unofficial forks of OpenJDK that have the client VM re-enabled. It's really just a #define in the JVM build itself - it works fine once it's been compiled in.
The only slowness I have is launching SBT. Running a hello-word Scala app with java (no Drip) version 1.8 on a 7381 bogomips CPU takes only 0.2 seconds.
If you're not in that magnitude, I suspect your application startup requires loading thousands of classes, and creating instances of them.
Related
I have a gradle build, which runs a few tests on our application. Currently the tests that store assets in mongoDB fail if the developer forgets to run mongod first. So I want any build that uses mongoDB to fail with a message the user that clearly tells him to start mongoDB. Ideally, later we would start mongoDB from gradle.
I already found this nice article about how to see if mongoDB is running under Linux, which is quite simple. I am sure something similar can be done under Windows using tasklist /FI "IMAGENAME eq mongod", etc. But I need to know how to use this correctly in gradle.
Is there a cross platform way to check if a service or normal process is running in gradle?
The suggestion provided by Orid to use the Gradle Mongo Plugin should work if you set the necessary Gradle tasks to be dependent on a startManagedMongoDb task.
While that may seem to be the easiest way, it may be breaking with how MongoDb will be used in non-development environments or on a continuous integration build-server, where the MongoDb service will already be running.
A very simple solution would be to add the MongoDb checking functionality to the top of a customized gradlew.bat (and the gradlew bash script if it will be run on a *nix operating system).
Another simple solution that wouldn’t require changing the gradlew.bat script would be to create your own MongoDb checking script that then called gradlew.bat, passing on command line arguments. I’m not sure if there is an equivalent to the bash $# for all positional arguments in windows, but looping through the arguments with SHIFT %1 can be used to generate the gradlew.bat command line.
It's Typesafe Activator 1.2.10 on Windows 7, Scala 2.11.4, sbt 0.13.7. All packages installed using .msi.
When I run activator ui I get error:
Error: Could not find or load main class ui
and nothing happens then.
It appears that you're facing permission-related problems.
I can't give you the exact steps to sort it out (as I'm on Mac OS), but you should be able to work it around by running cmd as Administrator and then executing activator ui again.
There's also the version 1.2.12 so you may have more success with it. You don't need separate installations of Scala and sbt, either, as activator is going to take care of them (that's one of the many reasons to use the tool after all).
I have memory related problem in my application on solaris9 environment where Tcl_DeleteInterp() function calls lot of free() and mutex_unlock() functions. To debug the problem i followed the below steps to compile tcl on solaris server (with TCL_MEM_DEBUG flag) but still i couldn't use the 'memory' command in my interpreter.
Ran configure script on server (./configure –prefix=<directory needs to be installed> --enable-symbols=mem)
Make clean all
Make install (tcl libraries and tlcsh exe is copied to the path specified in step1)
Compilation generated two libraries (libtcl8.4g.so and libtclstub8.4g.a), I copied libtcl8.4g.so as libtcl8.4.so to my app
Copied tcl8.4 directory as well.
I also copied the tclsh8.4 to $PROVHOME/bin and created soft link as tclsh-> tclsh8.4.
From my application i linked the debug symbol enabled libraries to the place where exactly i created the Tcl interpreter.
Initialized the Tcl interpreter to using Tcl_InitMemory() function (so that the memory command will be registered in the supplied(arg) interpreter.
When i used the interpreter exe (tclsh) separately i could execute the memory command, but when i used the same exe on my application its not working. Can someone help me what could be the possible reason for this problem ?
Also help me how can i cross verify the libraries that they are compiled with TCL_MEM_DEBUG flag.
Will the Tcl source code tar file contain Solaris directory where i have to build the libraries or should i use the unix source code for solaris platform as well ?
Thanks
Are you using [mem] interactively (which does expansion of unambiguous short command names) and forgetting to use the full name ([memory]) in your scripts?
You're using Tcl embedded in your code? You need to call Tcl_InitMemory (passing in the handle to the interpreter where you want the memory command created) after creation of the interpreter and before you run user scripts, i.e., straight after the Tcl_CreateInterp gives you the handle (which should in turn come after the Tcl_FindExecutable call that initializes the shared parts of the library).
You must also make sure that everything is built with that flag set so that the correct memory allocation APIs are used in both your code when it integrates with Tcl, and you must make sure that you are linking against the debugging build. It's probably the linking that has gone wrong, but I've not done that level of development on Solaris for many years.
I think you'll find that “Getting a list of used libraries by a running process (unix)” is relevant to your problems.
So I've been playing with Akka Actors for a while now, and have written some code that can distribute computation across several machines in a cluster. Before I run the "main" code, I need to have an ActorSystem waiting on each machine I will be deploying over, and I usually do this via a Python script that SSH's into all the machines and starts the process by doing something like cd /into/the/proper/folder/ and then sbt 'run-main ActorSystemCode'.
I run this Python script on one of the machines (call it "Machine X"), so I will see the output of SSH'ing into all the other machines in my Machine X SSH session. Whenever I do run the script, it seems all the machines are re-compiling the entire code before actually running it, making me sit there for a few minutes before anything useful is done.
My question is this:
Why do they need to re-compile at all? The same JVM is available on all machines, so shouldn't it just run immediately?
How do I get around this problem of making each machine compile "it's own copy"?
sbt is a build tool and not an application runner. Use sbt-assembly to build an all in one jar and put the jar on each machine and run it with scala or java command.
It's usual for cluster to have a single partition mounted on every node (via NFS or samba). You just need to copy the artifact on that partition and they will be directly accessible in each node. If it's not the case, you should ask your sysadmin to install it.
Then you will need to launch the application. Again, most clusters come
with MPI. The tools mpirun (or mpiexec) are not restricted to real MPI applications and will launch any script you want on several nodes.
I have downloaded a project which uses sbt as its build system and I want to build it. You'd think it would be as simple as typing "sbt" or something, but no.
I thought I'd add a question for this because it can take literally hours to figure this out on your own. I'm not joking.
tl;dr:
sbt compile
If you want to run it:
sbt run
To see what other targets are available:
sbt tasks
To get some (other) help, but mostly targeted at commands typed from the sbt console (ie, running sbt without parameters):
sbt help
This all assumes sbt version >= 0.10.0. To see what version of sbt is in use, do:
grep sbt.version project/build.properties
If there's no such file, and there's a file with extension ".sbt" on the base directory (not the project directory), then it's >= 0.10.0. Of course, if the grep works, it should tell you the version.
First, you'll want to use sbt-extras, because that automatically downloads and uses the right version of sbt. Trying to use the wrong version of sbt (newer or older than what the project you're trying to build says it requires) won't necessarily work, and may cause strange errors.
Run it:
~/path/to/sbt-extras/sbt
Wait for it to start up and download everything. If you need to use an authenticated proxy, you'll need to edit the script to specify the username and password for the proxy.
Check the version of Scala that sbt thinks it needs to build against (at the end of the output, if everything worked). If this is OK, fine, you don't need to do anything. If it isn't, you can temporarily specify a version explicitly with ++, e.g.:
++2.8.1
(If you want to make this permanent, you can edit the build definition files, but as that involves making a change to files under version control, that might not be what you want to do.)
Now, if you are using an older version of sbt, don't skip the next step! You could get strange errors if you do.
update
Now you can build and test what you've built:
test
If you get an error "Filename too long", this is not an sbt-specific problem, it's a scala problem, which most frequently affects Ubuntu users (technically, for Unbuntu users it's generally related to home directories encrypted with encfs). If you are using Scala >= 2.9, edit the build to use the scalac command-line option that allows you to specify a maximum filename length. Otherwise, if you are on Linux, you can redirect the build to /dev/shm or /tmp, by running these commands in a shell prompt (don't background sbt with CTRL+Z on Unix, because it may appear to stop working properly):
rm -rf target
ln -s /dev/shm target
(you may have to execute these commands in project/build instead or as well.)
Actually, it's probably better, and may even be more secure, to create a subdirectory of /dev/shm or /tmp and use that instead.
The compilation result should appear in target. You might then want to run it, if it's something you can run:
run
If everything looks OK, you can optionally publish the result locally so that the result can then be picked up automatically by other sbt builds:
publish-local
I don't think I could explain it better that the Getting Started Guide could. Please read the first 6 parts of it, which shouldn't too long time, to get it up and running.