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Cleanup info logs in raylet (#17015)

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Eric Liang 2021-07-12 19:43:44 -07:00 • committed by GitHub
parent a8b57c78d6
commit 7a1e8fdb8b
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5 changed files with 24 additions and 24 deletions
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8
src/ray/raylet/local_object_manager.cc
View file

@ -161,7 +161,7 @@ bool LocalObjectManager::SpillObjectsOfSize(int64_t num_bytes_to_spill) {
SpillObjectsInternal(objects_to_spill, [this, bytes_to_spill, objects_to_spill,
start_time](const Status &status) {
if (!status.ok()) {
RAY_LOG(INFO) << "Failed to spill objects: " << status.ToString();
RAY_LOG(DEBUG) << "Failed to spill objects: " << status.ToString();
} else {
auto now = absl::GetCurrentTimeNanos();
RAY_LOG(DEBUG) << "Spilled " << bytes_to_spill << " bytes in "
@ -283,9 +283,9 @@ void LocalObjectManager::UnpinSpilledObjectCallback(
std::shared_ptr<size_t> num_remaining,
std::function<void(const ray::Status &)> callback, ray::Status status) {
if (!status.ok()) {
RAY_LOG(INFO) << "Failed to send spilled url for object " << object_id
<< " to object directory, considering the object to have been freed: "
<< status.ToString();
RAY_LOG(DEBUG) << "Failed to send spilled url for object " << object_id
<< " to object directory, considering the object to have been freed: "
<< status.ToString();
} else {
RAY_LOG(DEBUG) << "Object " << object_id << " spilled to " << object_url
<< " and object directory has been informed";

7
src/ray/raylet/node_manager.cc
View file

@ -17,6 +17,7 @@
#include <cctype>
#include <fstream>
#include <memory>
#include "boost/filesystem.hpp"
#include "boost/system/error_code.hpp"
#include "ray/common/asio/asio_util.h"
@ -1675,8 +1676,8 @@ void NodeManager::HandleCancelResourceReserve(
const rpc::CancelResourceReserveRequest &request,
rpc::CancelResourceReserveReply *reply, rpc::SendReplyCallback send_reply_callback) {
auto bundle_spec = BundleSpecification(request.bundle_spec());
RAY_LOG(INFO) << "Request to cancel reserved resource is received, "
<< bundle_spec.DebugString();
RAY_LOG(DEBUG) << "Request to cancel reserved resource is received, "
<< bundle_spec.DebugString();
// Kill all workers that are currently associated with the placement group.
// NOTE: We can't traverse directly with `leased_workers_`, because `DestroyWorker` will
@ -1790,7 +1791,7 @@ void NodeManager::MarkObjectsAsFailed(
status = store_client_.Seal(object_id);
}
if (!status.ok() && !status.IsObjectExists()) {
RAY_LOG(INFO) << "Marking plasma object failed " << object_id;
RAY_LOG(DEBUG) << "Marking plasma object failed " << object_id;
// If we failed to save the error code, log a warning and push an error message
// to the driver.
std::ostringstream stream;

8
src/ray/raylet/placement_group_resource_manager.cc
View file

@ -51,8 +51,8 @@ bool NewPlacementGroupResourceManager::PrepareBundle(
if (iter->second->state_ == CommitState::COMMITTED) {
// If the bundle state is already committed, it means that prepare request is just
// stale.
RAY_LOG(INFO) << "Duplicate prepare bundle request, skip it directly. This should "
"only happen when GCS restarts.";
RAY_LOG(DEBUG) << "Duplicate prepare bundle request, skip it directly. This should "
"only happen when GCS restarts.";
return true;
} else {
// If there was a bundle in prepare state, it already locked resources, we will
@ -92,7 +92,7 @@ void NewPlacementGroupResourceManager::CommitBundle(
} else {
// Ignore request If the bundle state is already committed.
if (it->second->state_ == CommitState::COMMITTED) {
RAY_LOG(INFO) << "Duplicate committ bundle request, skip it directly.";
RAY_LOG(DEBUG) << "Duplicate committ bundle request, skip it directly.";
return;
}
}
@ -119,7 +119,7 @@ void NewPlacementGroupResourceManager::ReturnBundle(
const BundleSpecification &bundle_spec) {
auto it = pg_bundles_.find(bundle_spec.BundleId());
if (it == pg_bundles_.end()) {
RAY_LOG(INFO) << "Duplicate cancel request, skip it directly.";
RAY_LOG(DEBUG) << "Duplicate cancel request, skip it directly.";
return;
}
const auto &bundle_state = it->second;

23
src/ray/raylet/scheduling/cluster_task_manager.cc
View file

@ -1,8 +1,9 @@
#include "ray/raylet/scheduling/cluster_task_manager.h"
#include <google/protobuf/map.h>
#include <boost/range/join.hpp>
#include "ray/raylet/scheduling/cluster_task_manager.h"
#include "ray/stats/stats.h"
#include "ray/util/logging.h"
@ -172,11 +173,11 @@ void ClusterTaskManager::DispatchScheduledTasksToWorkers(
// The task's args cannot be pinned due to lack of memory. We should
// retry dispatching the task once another task finishes and releases
// its arguments.
RAY_LOG(INFO) << "Dispatching task " << task_id
<< " would put this node over the max memory allowed for "
"arguments of executing tasks ("
<< max_pinned_task_arguments_bytes_
<< "). Waiting to dispatch task until other tasks complete";
RAY_LOG(DEBUG) << "Dispatching task " << task_id
<< " would put this node over the max memory allowed for "
"arguments of executing tasks ("
<< max_pinned_task_arguments_bytes_
<< "). Waiting to dispatch task until other tasks complete";
RAY_CHECK(!executing_task_args_.empty() && !pinned_task_arguments_.empty())
<< "Cannot dispatch task " << task_id
<< " until another task finishes and releases its arguments, but no other "
@ -349,7 +350,7 @@ bool ClusterTaskManager::PinTaskArgsIfMemoryAvailable(const TaskSpecification &s
// This can happen if the task's arguments were all local at some
// point, but then at least one was evicted before the task could
// be dispatched to a worker.
RAY_LOG(INFO)
RAY_LOG(DEBUG)
<< "Task " << spec.TaskId() << " argument " << deps[i]
<< " was evicted before the task could be dispatched. This can happen "
"when there are many objects needed on this node. The task will be "
@ -409,8 +410,8 @@ void ClusterTaskManager::PinTaskArgs(const TaskSpecification &spec,
it->second.second++;
}
} else {
RAY_LOG(INFO) << "Scheduler received duplicate task " << spec.TaskId()
<< ", most likely because the first execution failed";
RAY_LOG(DEBUG) << "Scheduler received duplicate task " << spec.TaskId()
<< ", most likely because the first execution failed";
}
}
@ -931,8 +932,8 @@ void ClusterTaskManager::Spillback(const NodeID &spillback_to, const Work &work)
if (!cluster_resource_scheduler_->AllocateRemoteTaskResources(
spillback_to.Binary(), task_spec.GetRequiredResources().GetResourceMap())) {
RAY_LOG(INFO) << "Tried to allocate resources for request " << task_spec.TaskId()
<< " on a remote node that are no longer available";
RAY_LOG(DEBUG) << "Tried to allocate resources for request " << task_spec.TaskId()
<< " on a remote node that are no longer available";
}
auto node_info_opt = get_node_info_(spillback_to);

2
src/ray/raylet/worker_pool_test.cc
View file

@ -1001,7 +1001,6 @@ TEST_F(WorkerPoolTest, TestWorkerCapping) {
// Start two IO workers. These don't count towards the limit.
{
RAY_LOG(INFO) << "XXX";
Process proc = worker_pool_->StartWorkerProcess(
Language::PYTHON, rpc::WorkerType::SPILL_WORKER, job_id);
auto worker = CreateSpillWorker(Process());
@ -1012,7 +1011,6 @@ TEST_F(WorkerPoolTest, TestWorkerCapping) {
worker_pool_->PushSpillWorker(worker);
}
{
RAY_LOG(INFO) << "YYY";
Process proc = worker_pool_->StartWorkerProcess(
Language::PYTHON, rpc::WorkerType::RESTORE_WORKER, job_id);
auto worker = CreateRestoreWorker(Process());