## 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.
* add java code lint check and fix the java code lint error
* add java doc lint check and fix the java doc lint error
* add java code and doc lint to the CI
* Enable java worker support
--------------------------
This commit includes a tailored version of the Java worker implementation from Ant Financial.
The changes for build system, python module, src module and arrow are in other commits, this commit consists of the following modules:
- java/api: Ray API definition
- java/common: utilities
- java/hook: binary rewrite of the Java byte-code for remote execution
- java/runtime-common: common implementation of the runtime in worker
- java/runtime-dev: a pure-java mock implementation of the runtime for fast development
- java/runtime-native: a native implementation of the runtime
- java/test: various tests
Contributors for this work:
Guyang Song, Peng Cao, Senlin Zhu,Xiaoying Chu, Yiming Yu, Yujie Liu, Zhenyu Guo
* change the format of java help document from markdown to RST
* update the vesion of Arrow for java worker
* adapt the new version of plasma java client from arrow which use byte[] instead of custom type
* add java worker test to ci
* add the example module for better usage guide
