* Convert UniqueID::nil() to a constructor
* Cleanup actor handle pickling code
* Add new actor handles to the task spec
* Pass in new actor handles
* Add new handles to the actor registration
* Regression test for actor handle forking and GC
* lint and doc
* Handle pickled actor handles in the backend and some refactoring
* Add regression test for dummy object GC and pickled actor handles
* Check for duplicate actor tasks on submission
* Regression test for forking twice, fix failed named actor leak
* Fix bug for forking twice
* lint
* Revert "Fix bug for forking twice"
This reverts commit 3da85e59d401e53606c2e37ffbebcc8653ff27ac.
* Add new actor handles when task is assigned, not finished
* Remove comment
* remove UniqueID()
* Updates
* update
* fix
* fix java
* fixes
* fix
## What do these changes do?
This PR exposes the CL option for using a config parameter. This is important for certain tests (i.e., FT tests that removing nodes) to run quickly.
Note that this is bad practice and should be replaced with GFLAGS or some equivalent as soon as possible.
#3239 depends on this.
TODO:
- [x] Add documentation to method arguments before merging.
- [x] Add test to verify this works?
## Related issue number
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## What do these changes do?
support raylet, which is started by java runManager, to start python default_worker.py .
So when doing local test of java call python task, it helps auto start python worker.
## Related issue number
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## What do these changes do?
remove TaskExecutionException, use RayException instead
<!-- Please give a short brief about these changes. -->
## Related issue number
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## What do these changes do?
Before this PR, if we want to specify some resources, we must do as following codes:
```java
@RayRemote(Resources={ResourceItem("CPU", 10)})
public static void f1() {
// do sth
}
@RayRemote(Resources={ResourceItem("CPU", 10)})
class Demo {
// sth
}
```
Unfortunately, it's no way for us to create another actor or task with different resources required.
After this PR, the thing will be:
```java
ActorCreationOptions option = new ActorCreationOptions();
option.resources.put("CPU", 4.0);
RayActor<Echo> echo1 = Ray.createActor(Echo::new, option);
option.resources.put("Res-A", 4.0);
RayActor<Echo> echo2 = Ray.createActor(Echo::new, option);
//if we don't specify resource, the resources will be `{"cpu":0.0}` by default.
Ray.call(Echo::echo, echo2, 100);
```
## Related issue number
N/A
## What do these changes do?
1. Add a configuration item `driver.resource-path`.
2. Load driver resources from the local path which is specified in the `ray.conf`.
Before this change, we should add all driver resources(like user's jar package, dependencies package and config files) into `classpath`.
After this change, we should add the driver resources into the mount path which we can configure it in `ray.conf`, and we shouldn't configure `classpath` for driver resources any more.
## Related issue number
N/A
If we set `ray.home` configuration item to `""`.
The current `RayConfig` will set it to current work directory, like `/User/My/Ray`.
But the some other configuration items(like `redisServerExecutablePath`) will be set to `/User/My/Ray//build/src/common/thirdparty/redis/src/redis-server` by mistake.
Note: There are 2 `/` between current work directory and `build/src/common....`
This PR will fix this issue.
## What do these changes do?
Previously, Java worker configuration is complicated, because it requires setting environment variables as well as command-line arguments.
This PR aims to simplify Java worker's configuration.
1) Configuration management is now migrated to [lightbend config](https://github.com/lightbend/config), thus doesn't require setting environment variables.
2) Many unused config items are removed.
3) Provide a simple `example.conf` file, so users can get started quickly.
4) All possible options and their default values are declared and documented in `ray.default.conf` file.
This PR also simplifies and refines the following code:
1) The process of `Ray.init()`.
2) `RunManager`.
3) `WorkerContext`.
### How to use this configuration?
1. Copy `example.conf` into your classpath and rename it to `ray.conf`.
2. Modify/add your configuration items. The all items are declared in `ray.default.conf`.
3. You can also set the items in java system prosperities.
Note: configuration is read in this priority:
System properties > `ray.conf` > `ray.default.conf`
## Related issue number
N/A
Update the version in maven from 0.1 to 0.1-SNAPSHOT, because SNAPSHOT is the conventional version name in dev process. Non-snapshot versions are only used for release.
This PR adds a `function_desc` field into task spec. a function descriptor is a list of strings that can uniquely describe a function.
- For a Python function, it should be: [module_name, class_name, function_name]
- For a Java function, it should be: [class_name, method_name, type_descriptor]
There're a couple of purposes to add this field:
In this PR:
- Java worker needs to know function's class name to load it. Previously, since task spec didn't have such a field to hold this info, we did a hack by appending the class name to the argument list. With this change, we fixed that hack and significantly simplified function management in Java.
Will be done in subsequent PRs:
- Support cross-language invocation (#2576): currently Python worker manages functions by saving them in GCS and pass function id in task spec. However, if we want to call a Python function from Java, we cannot save it in GCS and get the function id. But instead, we can pass the function descriptor (module name, class name, function name) in task spec and use it to load the function.
- Support deployment: one major problem of Python worker's current function management mechanism is #2327. In prod env, we should have a mechanism to deploy code and dependencies to the cluster. And when code is already deployed, we don't need to save functions to GCS any more and can use `function_desc` to manage functions.
Wang Qing