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.
Previous changes broke single-process mode in raylet. This PR fixes the hello-world example work in single-process mode. Follow-up diffs will completely fix single-process mode and add tests.
* Trigger reconstruction in ray.wait and mark worker as blocked.
* Add test.
* Linting.
* Don't run new test with legacy Ray.
* Only call HandleClientUnblocked if it actually blocked in ray.wait.
* Reduce time to ray.wait in the test.
* use cmake to build ray project, no need to appply build.sh before cmake, fix some abuse of cmake, improve the build performance
* support boost external project, avoid using the system or build.sh boost
* keep compatible with build.sh, remove boost and arrow build from it.
* bugfix: parquet bison version control, plasma_java lib install problem
* bugfix: cmake, do not compile plasma java client if no need
* bugfix: component failures test timeout machenism has problem for plasma manager failed case
* bugfix: arrow use lib64 in centos, travis check-git-clang-format-output.sh does not support other branches except master
* revert some fix
* set arrow python executable, fix format error in component_failures_test.py
* make clean arrow python build directory
* update cmake code style, back to support cmake minimum version 3.4
Previously `Ray.createActor` only support creating an actor without any parameter. This PR adds the support for creating an actor with parameters. Moreover, besides using a constructor, it's now also allowed to create an actor with a factory method. For more usage, prefer refer to `ActorTest.java`.
API module (`ray/java/api` dir) includes all public APIs provided by Ray, it should be the only module that normal Ray users need to face.
The purpose of this PR to first improve the code quality of the API module. Subsequent PRs will improve other modules later. The changes of this PR include the following aspects:
1) Only keep interfaces in api module, to hide implementation details from users and fix circular dependencies among modules.
2) Document everything in the api module.
3) Improve naming.
4) Add more tests for API.
5) Also fix/improve related code in other modules.
6) Remove some unused code.
(Apologize for posting such a large PR. Java worker code has been lack of maintenance for a while. There're a lot of code quality issues that need to be fixed. We plan to use a couple of large PRs to address them. After that, future changes will come in small PRs.)
1) Renamed the native JNI methods and some parameters of JNI methods.
2) Fixed native JNI methods' signatures by `javah` tool.
3) Removed some useless native methods.
* Limit number of concurrent workers started by hardware concurrency.
* Check if std:🧵:hardware_concurrency() returns 0.
* Pass in max concurrency from Python.
* Fix Java call to startRaylet.
* Fix typo
* Remove unnecessary cast.
* Fix linting.
* Cleanups on Java side.
* Comment back in actor test.
* Require maximum_startup_concurrency to be at least 1.
* Fix linting and test.
* Improve documentation.
* Fix typo.
## What do these changes do?
Because the logic of generating `TaskID` in java is different from python's, there are many tests fail when we change the `Ray Core` code.
In this change, I rewrote the logic of generating `TaskID` in java which is the same as the python's.
In java, we call the native method `_generateTaskId()` to generate a `TaskID` which is also used in python. We change `computePutId()`'s logic too.
## Related issue number
[#2608](https://github.com/ray-project/ray/issues/2608)
Currently, log directory in Java is a relative path . This PR changes it to `/tmp/raylogs` (with the same format as Python, e.g., `local_scheduler-2018-51-17_17-8-6-05164.err`). It also cleans up some relative code.
* Support building Java and Python version at the same time.
* Remove duplicated definition.
* Refine the building process of local_scheduler
* Refine
* Add comment for languages
* Modify instruction and add python,jave building to CI.
* change according to comment
## What do these changes do?
This implements basic task reconstruction in raylet. There are two parts to this PR:
1. Reconstruction suppression through the `TaskReconstructionLog`. This prevents two raylets from reconstructing the same task if they decide simultaneously (via the logic in #2497) that reconstruction is necessary.
2. Task resubmission once a raylet becomes responsible for reconstructing a task.
Reconstruction is quite slow in this PR, especially for long chains of dependent tasks. This is mainly due to the lease table mechanism, where nodes may wait too long before trying to reconstruct a task. There are two ways to improve this:
1. Expire entries in the lease table using Redis `PEXPIRE`. This is a WIP and I may include it in this PR.
2. Introduce a "fast path" for reconstructing dependencies of a re-executed task. Normally, we wait for an initial timeout before checking whether a task requires reconstruction. However, if a task requires reconstruction, then it's likely that its dependencies also require reconstruction. In this case, we could skip the initial timeout before checking the GCS to see whether reconstruction is necessary (e.g., if the object has been evicted).
Since handling failures of other raylets is probably not yet complete in master, this only turns back on Python tests for reconstructing evicted objects.
* 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
Local-scheduler-forked workers will be killed by local scheduler itself,
don't need to be killed here. See:
570c3153cd/src/local_scheduler/local_scheduler.cc (L184-L192)
Also, using `ps | grep | kill` might be dangerous, because it
could also kill irrelevant processes, e.g., `vim DefaultWorker.java`.
* 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
