[Core] Add gRPC streaming support by moving to the async callback/reactor API. #15279

clarkzinzow · 2021-04-13T19:49:10Z

Why are these changes needed?

Our current gRPC layer only supports unary RPCs, while some of our current communication patterns, such as object location subscriptions, actor method calls, and within-lease task submissions, and future communication patterns, such as a non-Redis GCS-based pub/sub, are best suited to streaming RPCs. Streaming RPCs take full advantage of HTTP/2, streaming requests and/or responses within an existing HTTP/2 request/response, ridding ourselves of the overhead of e.g. creating a new HTTP/2 request for each unary call. Moreover, we have ordering guarantees within a single RPC, which saves us from RPC reordering issues that we may encounter when using unary RPCs that would normally have to be handled in the application-level protocol.

The current async gRPC layer is implemented using the completion queue API, where both the client and the server implement RPC call abstractions that transition through a state machine representing stages of a unary RPC call. Although we could attempt to extend this completion queue state machine to support streaming RPCs, this PR adds support for gRPC streaming by creating a new gRPC layer that uses the experimental (but soon to be stable) async callback/reactor API. This provides a gRPC-native callback API for unary RPCs, and a reactor API for each of the streaming RPCs. Although there isn't a callback API for the server-side of unary RPCs, we wrap the unary reactor API with a callback API ourselves, so the common unary RPC case can be entirely implemented with callbacks at the application-level, and is defined via macros such as:

UNARY_CALLBACK_RPC_CLIENT_METHOD(NodeManagerService, RequestResourceReport, grpc_client_, )

on the client and

UNARY_CALLBACK_RPC_SERVICE_HANDLER(NodeManagerService, RequestResourceReport)

on the server, maintaining application-level API compatibility with the completion queue gRPC layer for unary RPCs. This allows us to gradually port each gRPC client and server to the new callback-based layer by only updating the gRPC client and server (i.e. macro) definitions, with no application-level changes necessary. Also note that this is entirely a layer on top of gRPC without any observable transport-level effects, meaning that the client and server for a given gRPC service can be ported independently. Beyond being simpler to implement than extending the completion queue state machine, this should eliminate a lot of technical debt in our current gRPC layer and allow us to take advantage of upstream work on this callback/reactor API (which is active!) instead of maintaining and extending our own completion queue --> callback layer.

Note that this PR (currently) ports the raylet gRPC client and server to the callback API. This is primarily to demonstrate the API and that there are no performance regressions. If we wish, we could merge this PR without porting any of the gRPC services to the callback API and wait until we think the layer is stable (either gating behind a feature flag or removing the port entirely for now).

Streaming Reactor API Design

See the gRFC for the async callback API design and see the de-experimentalization PR for examples. Both the client and server macros provide a thin layer that essentially exposes these APIs to the application layer. An end-to-end streaming RPC example will be implemented in a future PR.

Risks

The nexting threadpool that's used to process the underlying gRPC completion queue is configured and owned by the C++ gRPC library, and doesn't provide any hooks to e.g. configure how many threads are used (currently set to num_cores / 2, clamped to the range [2, 16]) or how many completion queues to use (currently set to 1). Compared to the completion queue implementation, where we can control both the number of completion queues and the number of nexting threads, this puts us in quite an opinionated box that could result in performance regressions in some cases (e.g., taking valuable CPU resources from the core worker). However, preliminary benchmarking (with the raylet using the new gRPC layer) has actually shown performance improvements over our existing CQ-based gRPC layer. This is possibly due to the num_cores / 2 nexting threads being a much more aggressive gRPC-level resource allocation than what is done when using the completion queue layer.
Directly using the reactor APIs for streaming RPCs can introduce a good bit of transport-level complexity to the application layer. For this reason, I believe that we should experiment with exposing a user-friendly reader/writer API implemented on top of reactors, where the client-side API takes a callback (or exposes a reader interface) to handle responses from the server and exposes a writer interface to push new requests onto the stream, and the server-side API takes a callback (or exposes a reader interface) to handle requests from the client and exposes a writer interface to push new responses onto the stream; any requirements for statefulness in the callbacks can be achieved by the callbacks closing over stateful objects and using said objects in their request/response processing. We've added an experimental client-side response handler callback + request writer API for client-side streaming RPCs (currently unused) to demonstrate this idea, see here. If it proves difficult to provide generic callback or reader/writer APIs on top of the streaming reactors, we can isolate the reactors in shared application-level abstractions whose APIs are transport-agnostic (e.g. a pub/sub abstraction) or within application-level clients (e.g. the RayletClient or GcsClient) that would handle the reactors themselves and expose transport-agnostic APIs.
Unexpected edge cases where the callback/reactor API fails due to a bug internal to gRPC. I think that the risk of this is pretty low; although it's technically still an experimental API, it has been used internally at Google, in production, for at least 2 years.

Other Niceties

The client and server contexts are now exposed to the application layer, which means that application code will be able to tell when an RPC has been cancelled, will be able to issue out-of-band client-side and in-band server-side RPC cancellations, and will be able to use hooks for adding custom metadata to RPCs and getting RPC performance metrics.

TODOs

Related issue number

Closes #15219

Checks

I've run scripts/format.sh to lint the changes in this PR.
I've included any doc changes needed for https://docs.ray.io/en/master/.
I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
Testing Strategy
- Unit tests
- Release tests
- This PR is not tested :(

clarkzinzow · 2021-04-13T20:01:13Z

bazel/ray_deps_setup.bzl

-        url = "https://github.com/grpc/grpc/archive/4790ab6d97e634a1ede983be393f3bb3c132b2f7.tar.gz",
-        sha256 = "df83bd8a08975870b8b254c34afbecc94c51a55198e6e3a5aab61d62f40b7274",
+        # url = "https://github.com/grpc/grpc/archive/53ba4a101e80e1a67d4ec741b7e1aad6ea8d790f.tar.gz",
+        # url = "https://github.com/grpc/grpc/archive/refs/tags/v1.36.4.tar.gz",


Will remove these alternatives before merging.

clarkzinzow · 2021-04-13T20:03:34Z

src/ray/rpc/client_call.h

@@ -287,7 +287,7 @@ class ClientCallManager {
  std::atomic<unsigned int> rr_index_;

  /// The gRPC `CompletionQueue` object used to poll events.
-  std::vector<grpc::CompletionQueue> cqs_;
+  std::vector<std::unique_ptr<grpc::CompletionQueue>> cqs_;


gRPC completion queues are no longer copyable.

rkooo567 · 2021-04-15T03:38:07Z

Hey @clarkzinzow Do we still need this PR -> #14598 after yours?

clarkzinzow · 2021-04-15T04:51:27Z

@rkooo567 That PR will still be necessary until we've ported every gRPC service to use the new gRPC layer, so I think that PR should still be merged.

rkooo567 · 2021-04-22T07:50:14Z

Makes sense. Can you remove the tag once tests are in the passing state?

qicosmos · 2021-04-22T08:20:31Z

src/ray/rpc/grpc_callback_client.h

+        // capturing `this` since the gRPC-level callback may outlive this
+        // GrpcCallbackClient instance, while we're more confident that it will not
+        // outlive the event loop, which should only be destroyed on process exit.
+        [&io_context = io_context_, response, callback = std::move(callback), ctx,


The callback is not safe, we need to use shared_form_this to return a shared_ptr of this and capture it in callback to make sure async safe callback.

Hmm I'd agree if we were going to reference a method or member on this client object in the callback, but the only member that we're going to reference is io_context_, which we pass in to the callback by reference explicitly. The lifetime assumption that is made here is that the IO context will outlive the gRPC-internal nexting thread (where this callback is invoked), which I'm less sure about, but that wouldn't be solved by capturing a this shared pointer.

qicosmos · 2021-04-22T08:22:27Z

src/ray/rpc/grpc_callback_client.h

+      const ClientCallback<Reply> &callback,
+      std::shared_ptr<grpc::ClientContext> ctx = nullptr,
+      const std::string call_name = "UNKNOWN_RPC") {
+    auto reactor = new ClientWriterReactor<GrpcService, Request, Reply>(


Use shared_ptr maybe better, and no need to delete this after callback, more safer.

I didn't go with a shared pointer given that (1) the gRPC stub method expects a raw pointer, (2) the gRPC library guarantees that the reactor will never be used after OnDone() is called. If we were to use a shared pointer for this, (1) would still require us to give gRPC a raw pointer to the reactor which would result in a leaked pointer in the shared pointer's reference counting and would require us to guarantee that the application-level shared pointer to ClientWriterReactor outlives the raw pointer held within the gRPC library (otherwise the gRPC library would do a use-after-free), which seems impossible to guarantee.

Given that (2) gives us clear semantics for when the reactor should be deleted, it should be easier to create the reactor as a raw pointer, and explicitly delete itself at the end of OnDone() (we can document in the reactor API that it shouldn't be used after OnDone() is called).

I know that this is still not ideal, so definitely lmk if you have any ideas on how to make this reactor lifecycle management better!

clarkzinzow · 2021-06-22T01:08:41Z

FYI, the callback API is no longer considered to be experimental.

clarkzinzow · 2021-06-22T03:31:22Z

Current CI failures:

Java tests: Double free somehow getting hit within the metric tests. Still need to debug this.
Python small + large tests: test_job_timestamps is failing with timestamps that differ by a millisecond. I've seen this test be flaky before with off-by-one timestamps, so maybe this PR is making it consistently fail with a slight add in overhead that's making these timestamps separate. Still need to look into this.
rllib two_step_game_qmix example: Not sure how to interpret the periodic updates in the test logs, although I did notice that /tmp is being used for the object store instead of /dev/shm, although I doubt that's it. May have to ping someone that knows more about rllib for this one. Note that this test is currently pretty flaky.
Dask-on-Ray tests with Ray Client: Known backwards compatibility break that's been fixed in more recent master, should resolve upon another rebase.
Windows build: Currently appears to be failing to find Python headers within a gRPC Bazel rule. May be due to the gRPC upgrade, possibly in combination with our grpc-python patch.

rkooo567

It actually looks a lot simpler than I thought, and it definitely makes code smaller!! (which is great!). Here is a couple thoughts;

Does this use any of existing grpc code? (e.g., client_call.h)? I am asking it because you seem to import the file, but I couldn't find the usage.
Looks like it is not experimental anymore according to https://github.com/grpc/grpc/pull/25728/files#diff-79410abf9a4d8c0b0cfb8544485bc610c5eadffb1025d1206ab7f0c177e6a635R194, but we still seem to use them? Any reason why we don't use the non-experimental apis?
Also, I think we can definitely break this down. One thing we can do is;

only porting Unary RPC implementation first (and test it before merging -> revert) -> 2. Port all RPCs to the Unary RPCs in this layer first -> 3. implement streaming. Ideally, we should have some gap between 2~3 to make sure stability is guaranteed. Another possible approach is to modify the macro a little bit to feature flag them. At least for Unary RPCs, it seems to have the same macro definition.

rkooo567 · 2021-08-03T08:44:55Z

src/ray/rpc/grpc_callback_client.h

+    }
+    auto response = std::make_shared<Reply>();
+    auto stats_handle = io_context_.RecordStart(call_name);
+    (stub_->experimental_async()->*method)(


Looks like this experimental flag is gone now?

Yep, once we update gRPC again we'll be able to use the callback/reactor API from the stable namespace.

rkooo567 · 2021-08-03T08:46:22Z

src/ray/rpc/grpc_callback_client.h

+#include "ray/common/grpc_util.h"
+#include "ray/common/ray_config.h"
+#include "ray/common/status.h"
+#include "ray/rpc/client_call.h"


What are we using from this file?

We're only using the ClientCallback type definition. If we want to remove that dependency, we can duplicate that type definition in this file.

rkooo567 · 2021-08-03T08:47:46Z

thirdparty/patches/grpc-python.patch

@@ -1,23 +1,63 @@
 diff --git third_party/py/python_configure.bzl third_party/py/python_configure.bzl
 --- third_party/py/python_configure.bzl
 +++ third_party/py/python_configure.bzl
-@@ -163,1 +163,1 @@
+@@ -177,7 +177,7 @@ def _get_bash_bin(repository_ctx):


Can you tell me why we need to change this file?

We updated our gRPC dependency, so these patches were no longer applying to the correct lines, i.e. the correct code.

rkooo567 · 2021-08-03T08:48:11Z

thirdparty/patches/grpc-cython-copts.patch

+-            name = shared_object_name,
+            name = cc_kwargs.pop("name", shared_object_name),
+-            srcs = [stem + ".cpp"],
+            srcs = [stem + ".cpp"] + cc_kwargs.pop("srcs", []),


It makes sense why you added this, but do we need this change in this PR?

We updated our gRPC dependency, so these patches were no longer applying to the correct lines, i.e. the correct code.

clarkzinzow · 2021-08-09T19:52:44Z

It actually looks a lot simpler than I thought, and it definitely makes code smaller!! (which is great!)

Agreed! 😁

Does this use any of existing grpc code? (e.g., client_call.h)? I am asking it because you seem to import the file, but I couldn't find the usage.

It does not use any existing gRPC layer code except for the ClientCallback type definition. If we want to remove that dependency, we can duplicate that type definition in grpc_callback_client.h.

Looks like it is not experimental anymore according to https://github.com/grpc/grpc/pull/25728/files#diff-79410abf9a4d8c0b0cfb8544485bc610c5eadffb1025d1206ab7f0c177e6a635R194, but we still seem to use them? Any reason why we don't use the non-experimental apis?

The non-experimental APIs are the experimental APIs moved out of the experimental namespace; we can update our gRPC layer to use the non-experimental APIs after we update our gRPC dependency (the APIs were de-experimentalized while this PR was open).

Also, I think we can definitely break this down. One thing we can do is;

only porting Unary RPC implementation first (and test it before merging -> revert) -> 2. Port all RPCs to the Unary RPCs in this layer first -> 3. implement streaming. Ideally, we should have some gap between 2~3 to make sure stability is guaranteed. Another possible approach is to modify the macro a little bit to feature flag them. At least for Unary RPCs, it seems to have the same macro definition.

We can definitely break this down, but I should clarify a few things

only porting Unary RPC implementation first (and test it before merging -> revert) -> 2. Port all RPCs to the Unary RPCs in this layer first

Since the old gRPC layer only supports unary RPCs, there are only unary RPCs to port! 😄

Another possible approach is to modify the macro a little bit to feature flag them. At least for Unary RPCs, it seems to have the same macro definition.

The macro could be shared, but then application code won't have access to the ClientContext or the ServerContext, which is a big feature win for the new gRPC layer. We still won't be able to easily feature flag it, since the old gRPC client requires a ClientCallManager while the new gRPC client requires a raw io_context (no client call manager needed), and the old gRPC service doesn't derive from the same base class as the new gRPC service (see node_manager_server.h diff and new CALLBACK_SERVICE macro).

We could do something fancier for feature flagging, but it will probably require modifying the existing gRPC layer, which I was trying to avoid. Shouldn't be that difficult though.

richardliaw

setup changes lgtm as codeowner

MissiontoMars · 2021-09-09T02:34:50Z

Switching to gRPC streaming is really cool! But there are still some corner cases we should concern:

Does gRPC allow the user to set timeout parameters? Including connection timeout and RPC call timeout.
Does reconnection supported or not?
In Ant, we have encountered the above problems in our production environment. Currently, we use brpc instead of grpc in internal codebase, also consider switching to grpc If there is a solution to these problems.

qicosmos · 2021-09-30T23:51:12Z

Maybe we could replace the ugly macros with generic templates, i think coroutine will be the ultra improvement of async callbacks, the async code will be much more simple and clean.
i will do some tests with coroutine.

clarkzinzow · 2021-10-01T20:58:51Z

Maybe we could replace the ugly macros with generic templates, i think coroutine will be the ultra improvement of async callbacks, the async code will be much more simple and clean.
i will do some tests with coroutine.

Agreed on both points! I didn't deviate from the macros or the asio event loop model since I'm hoping to keep this PR small, but we're hoping to do both soon.

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…C layer.

… proxy for the asio event loop's lifetime.

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clarkzinzow force-pushed the core/feat/grpc-streaming branch from 0324b89 to 5e94229 Compare April 13, 2021 19:58

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clarkzinzow added 4 commits February 19, 2022 08:11

Add callback/reactor-based gRPC layer.

d7446e9

Port NodeManagerService and AgentManagerService to callback-based gRP…

21b6db6

…C layer.

Add an atomic shutdown flag to the gRPC callback client to serve as a…

67b9a03

… proxy for the asio event loop's lifetime.

Don't capture the client context in the asio event loop handler.

f70d662

clarkzinzow force-pushed the core/feat/grpc-streaming branch from 6372201 to f70d662 Compare February 19, 2022 08:12

fishbone mentioned this pull request Mar 24, 2022

[scheduling][5] Refactor resource syncer. #23270

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[Core] Add gRPC streaming support by moving to the async callback/reactor API. #15279

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[Core] Add gRPC streaming support by moving to the async callback/reactor API. #15279

[Core] Add gRPC streaming support by moving to the async callback/reactor API. #15279

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clarkzinzow commented Apr 13, 2021 • edited Loading

Why are these changes needed?

Streaming Reactor API Design

Risks

Other Niceties

TODOs

Related issue number

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