Azure / Azure/azure-functions-durable-python

Events added to in-memory queue are not being raised after ContinueAsNew called. #676

未关闭
#331 5 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看
bug Enhancement fixed-in-v2 P2
主要语言
Python
星标
157
派生
70
平均合并
2 天 10 小时
30 天内合并 PR
2

描述

🐛 **Describe the bug**
I had the exact same problem as described in the c# library (https://github.com/Azure/azure-functions-durable-extension/issues/676): only the first event is processed when raising event in a quick succession.

🤔 **Expected behavior**
I was expecting **continue_as_new** to resume the orchestrator_function and to pick the next event in the queue.

☕ **Steps to reproduce**
> What Durable Functions patterns are you using, if any?

I was testing the singleton orchestrator patterns. Instead of directly invoking the orchestrator, I use **raise_event** to communicate with the orchestrator. The orchestrator listens to the incoming event with **wait_for_external_event** and triggers the processing.

> Any minimal reproducer we can use?

The orchestrator function

```python
def orchestrator_function(context: df.DurableOrchestrationContext):
logging.warning("orchestrator starts")
result = yield context.wait_for_external_event('wait_for_request')
req = json.loads(result)
yield context.call_activity('Hello1', json.dumps(req))
yield context.call_activity('Hello1', json.dumps(req))
yield context.call_activity('Hello1', json.dumps(req))
logging.warning("orchestrator ends", req)
context.continue_as_new(None)
```
The Hello1 activity function uses time.sleep(5) to simulate extended processing.

The HttpStarter
```python
async def main(req: func.HttpRequest, starter: str) -> func.HttpResponse:
client = df.DurableOrchestrationClient(starter)
req_body = req.get_json()
function_name = "orchestrator_function"

h = hashlib.sha256()
h.update(str.encode(req_body['endpoint']))
instance_id = h.hexdigest()
existing_instance = await client.get_status(instance_id)

logging.warning(req_body)

logging.warning(f"Start orchestration with ID = '{instance_id}'.")
if existing_instance.runtime_status in [
df.OrchestrationRuntimeStatus.Completed,
df.OrchestrationRuntimeStatus.Failed,
df.OrchestrationRuntimeStatus.Terminated,
None]:
instance_id = await client.start_new(function_name, instance_id, None)
logging.warning(f"Started orchestration with ID = '{instance_id}'.")

await client.raise_event(instance_id, 'wait_for_request', req_body)
return client.create_check_status_response(req, instance_id)
```
When sending two HTTP requests to the HttpStarter consecutively (not simultaneously but with a bit gap), the orchestrator gets the first message and finishes the processing, but never picks up the second message.

> Are you running this locally or on Azure?

I have tested both locally and on Azure. I currently work on a prototype that uses the singleton durable function to control the traffic to endpoints. Some endpoints may allow concurrent traffic and some may not.

⚡**If deployed to Azure**
> We have access to a lot of telemetry that can help with investigations. Please provide as much of the following information as you can to help us investigate!

- **Timeframe issue observed**: 2021-11-02
- **Function App name**: tao-func-test1
- **Function name(s)**: adapter_controller (orchestrator), http_trigger (HttpStarter)
- **Azure region**: US east
- **Orchestration instance ID(s)**: 5e0c90d2d434f24b1ec3df57316653d00de3cc27b2001902cd0983c18e381b78
- **Azure storage account name**: taofunctest1

> If you don't want to share your Function App or storage account name GitHub, please at least share the orchestration instance ID. Otherwise it's extremely difficult to look up information.

贡献指南

打开贡献指南

调研方向

Start with the orchestrator_function and HttpStarter examples in the issue, then reproduce the behavior by sending two requests in quick succession. Trace how wait_for_external_event, raise_event, and continue_as_new handle the in-memory event queue. Done means the event raised after the first request's processing is received and processed by the restarted orchestrator.

由索引模型根据 Issue 内容生成。

评估

技术栈
azure, python
领域
backend, cloud
Issue 类型
缺陷
难度
3/5
预计耗时
1-2 天
活跃度
冷清
描述清晰度
基本清楚
新手友好度
45/100

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。