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Posted to github@arrow.apache.org by GitBox <gi...@apache.org> on 2022/03/03 10:27:43 UTC
[GitHub] [arrow-datafusion] yahoNanJing opened a new pull request #1911: Refactor scheduler server
yahoNanJing opened a new pull request #1911:
URL: https://github.com/apache/arrow-datafusion/pull/1911
# Which issue does this PR close?
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Closes #1908.
# Rationale for this change
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Why are you proposing this change? If this is already explained clearly in the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand your changes and offer better suggestions for fixes.
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Reorganize the scheduler contents for better code review and easy feature additions.
# What changes are included in this PR?
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There is no need to duplicate the description in the issue here but it is sometimes worth providing a summary of the individual changes in this PR.
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The following separate mod are extracted from the scheduler contents:
- external_scaler, for exposing scheduler internal metrics
- grpc, for grpc service
# Are there any user-facing changes?
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[GitHub] [arrow-datafusion] thinkharderdev commented on a change in pull request #1911: Refactor scheduler server
Posted by GitBox <gi...@apache.org>.
thinkharderdev commented on a change in pull request #1911:
URL: https://github.com/apache/arrow-datafusion/pull/1911#discussion_r819829732
##########
File path: ballista/rust/scheduler/src/scheduler_server/mod.rs
##########
@@ -0,0 +1,294 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::collections::HashMap;
+use std::marker::PhantomData;
+use std::sync::Arc;
+
+use log::{debug, error, info, warn};
+use tonic::Status;
+
+use crate::state::{ConfigBackendClient, SchedulerState};
+use ballista_core::config::{BallistaConfig, TaskSchedulingPolicy};
+use ballista_core::error::BallistaError;
+use ballista_core::execution_plans::ShuffleWriterExec;
+use ballista_core::serde::protobuf::executor_grpc_client::ExecutorGrpcClient;
+use ballista_core::serde::protobuf::{LaunchTaskParams, TaskDefinition};
+use ballista_core::serde::scheduler::to_proto::hash_partitioning_to_proto;
+use ballista_core::serde::scheduler::ExecutorData;
+use ballista_core::serde::{AsExecutionPlan, AsLogicalPlan, BallistaCodec};
+use datafusion::prelude::{ExecutionConfig, ExecutionContext};
+use std::time::{Duration, SystemTime, UNIX_EPOCH};
+use tokio::sync::{mpsc, RwLock};
+use tonic::transport::Channel;
+
+// include the generated protobuf source as a submodule
+#[allow(clippy::all)]
+pub mod externalscaler {
+ include!(concat!(env!("OUT_DIR"), "/externalscaler.rs"));
+}
+
+mod external_scaler;
+mod grpc;
+
+type ExecutorsClient = Arc<RwLock<HashMap<String, ExecutorGrpcClient<Channel>>>>;
+
+#[derive(Clone)]
+pub struct SchedulerServer<T: 'static + AsLogicalPlan, U: 'static + AsExecutionPlan> {
+ pub(crate) state: Arc<SchedulerState<T, U>>,
+ pub start_time: u128,
+ policy: TaskSchedulingPolicy,
+ scheduler_env: Option<SchedulerEnv>,
+ executors_client: Option<ExecutorsClient>,
+ ctx: Arc<RwLock<ExecutionContext>>,
+ codec: BallistaCodec<T, U>,
+}
+
+#[derive(Clone)]
+pub struct SchedulerEnv {
+ pub tx_job: mpsc::Sender<String>,
+}
+
+impl<T: 'static + AsLogicalPlan, U: 'static + AsExecutionPlan> SchedulerServer<T, U> {
+ pub fn new(
+ config: Arc<dyn ConfigBackendClient>,
+ namespace: String,
+ ctx: Arc<RwLock<ExecutionContext>>,
+ codec: BallistaCodec<T, U>,
+ ) -> Self {
+ SchedulerServer::new_with_policy(
+ config,
+ namespace,
+ TaskSchedulingPolicy::PullStaged,
+ None,
+ ctx,
+ codec,
+ )
+ }
+
+ pub fn new_with_policy(
+ config: Arc<dyn ConfigBackendClient>,
+ namespace: String,
+ policy: TaskSchedulingPolicy,
+ scheduler_env: Option<SchedulerEnv>,
+ ctx: Arc<RwLock<ExecutionContext>>,
+ codec: BallistaCodec<T, U>,
+ ) -> Self {
+ let state = Arc::new(SchedulerState::new(config, namespace, codec.clone()));
+
+ let executors_client = if matches!(policy, TaskSchedulingPolicy::PushStaged) {
+ Some(Arc::new(RwLock::new(HashMap::new())))
+ } else {
+ None
+ };
+ Self {
+ state,
+ start_time: SystemTime::now()
+ .duration_since(UNIX_EPOCH)
+ .unwrap()
+ .as_millis(),
+ policy,
+ scheduler_env,
+ executors_client,
+ ctx,
+ codec,
+ }
+ }
+
+ pub async fn init(&self) -> Result<(), BallistaError> {
+ let ctx = self.ctx.read().await;
+ self.state.init(&ctx).await?;
+
+ Ok(())
+ }
+
+ async fn schedule_job(&self, job_id: String) -> Result<(), BallistaError> {
+ let mut available_executors = self.state.get_available_executors_data();
+
+ // In case of there's no enough resources, reschedule the tasks of the job
+ if available_executors.is_empty() {
+ let tx_job = self.scheduler_env.as_ref().unwrap().tx_job.clone();
+ // TODO Maybe it's better to use an exclusive runtime for this kind task scheduling
+ warn!("Not enough available executors for task running");
+ tokio::time::sleep(Duration::from_millis(100)).await;
+ tx_job.send(job_id).await.unwrap();
+ return Ok(());
+ }
+
+ let (tasks_assigment, num_tasks) =
+ self.fetch_tasks(&mut available_executors, &job_id).await?;
+ if num_tasks > 0 {
+ for (idx_executor, tasks) in tasks_assigment.into_iter().enumerate() {
+ if !tasks.is_empty() {
+ let executor_data = &available_executors[idx_executor];
+ debug!(
+ "Start to launch tasks {:?} to executor {:?}",
+ tasks, executor_data.executor_id
+ );
+ let mut client = {
+ let clients =
+ self.executors_client.as_ref().unwrap().read().await;
+ info!("Size of executor clients: {:?}", clients.len());
+ clients.get(&executor_data.executor_id).unwrap().clone()
+ };
+ // Update the resources first
+ self.state.save_executor_data(executor_data.clone());
+ // TODO check whether launching task is successful or not
+ client.launch_task(LaunchTaskParams { task: tasks }).await?;
+ } else {
+ // Since the task assignment policy is round robin,
+ // if find tasks for one executor is empty, just break fast
+ break;
+ }
+ }
+ return Ok(());
+ }
+
+ Ok(())
+ }
+
+ async fn fetch_tasks(
+ &self,
+ available_executors: &mut [ExecutorData],
+ job_id: &str,
+ ) -> Result<(Vec<Vec<TaskDefinition>>, usize), BallistaError> {
+ let mut ret: Vec<Vec<TaskDefinition>> =
+ Vec::with_capacity(available_executors.len());
+ for _idx in 0..available_executors.len() {
+ ret.push(Vec::new());
+ }
+ let mut num_tasks = 0;
+ loop {
+ info!("Go inside fetching task loop");
Review comment:
realize you didn't add this here, but can we change this to debug level? could add a lot of noise to the logs
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[GitHub] [arrow-datafusion] liukun4515 commented on pull request #1911: Refactor scheduler server
Posted by GitBox <gi...@apache.org>.
liukun4515 commented on pull request #1911:
URL: https://github.com/apache/arrow-datafusion/pull/1911#issuecomment-1059922833
> cc @realno @liukun4515
I go through this pull request, and it's just split the code into some separated files.
looks good to me.
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[GitHub] [arrow-datafusion] alamb merged pull request #1911: Refactor scheduler server
Posted by GitBox <gi...@apache.org>.
alamb merged pull request #1911:
URL: https://github.com/apache/arrow-datafusion/pull/1911
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[GitHub] [arrow-datafusion] alamb commented on pull request #1911: Refactor scheduler server
Posted by GitBox <gi...@apache.org>.
alamb commented on pull request #1911:
URL: https://github.com/apache/arrow-datafusion/pull/1911#issuecomment-1059771098
Rather than allow PRs to accumulate, I'll merge them in as they seem uncontroversial and have been reviewed. We can always continue reorganizing as we move forward.
Thanks @yahoNanJing for the code and @thinkharderdev for the review
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[GitHub] [arrow-datafusion] alamb commented on pull request #1911: Refactor scheduler server
Posted by GitBox <gi...@apache.org>.
alamb commented on pull request #1911:
URL: https://github.com/apache/arrow-datafusion/pull/1911#issuecomment-1059771423
cc @realno @liukun4515
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