为什么我在使用 Dataflow 管道时遇到“错误同步 pod”？

Question

当我想使用 PyPI 中的特定库时，我用我的 Dataflow 管道试验了一个奇怪的错误。

我需要jsonschema中的 jsonschema，因此，在我的requirements.txt文件中，我添加了jsonschema==3.2.0 。 我使用下面的命令行启动我的管道：

python -m gcs_to_all \
    --runner DataflowRunner \
    --project <my-project-id> \
    --region europe-west1 \
    --temp_location gs://<my-bucket-name>/temp/ \
    --input_topic "projects/<my-project-id>/topics/<my-topic>" \
    --network=<my-network> \
    --subnetwork=<my-subnet> \
    --requirements_file=requirements.txt \
    --experiments=allow_non_updatable_job \
    --streaming  

在终端中，一切似乎都很好：

INFO:root:2020-01-03T09:18:35.569Z: JOB_MESSAGE_BASIC: Worker configuration: n1-standard-4 in europe-west1-b.
INFO:root:2020-01-03T09:18:35.806Z: JOB_MESSAGE_WARNING: The network default doesn't have rules that open TCP ports 12345-12346 for internal connection with other VMs. Only rules with a target tag 'dataflow' or empty target tags set apply. If you don't specify such a rule, any pipeline with more than one worker that shuffles data will hang. Causes: Firewall rules associated with your network don't open TCP ports 12345-12346 for Dataflow instances. If a firewall rule opens connection in these ports, ensure target tags aren't specified, or that the rule includes the tag 'dataflow'.
INFO:root:2020-01-03T09:18:48.549Z: JOB_MESSAGE_DETAILED: Workers have started successfully.

Dataflow网页上的日志选项卡中没有错误，但在stackdriver中：

message: "Error syncing pod 6515c378c6bed37a2c0eec1fcfea300c ("<dataflow-id>--01030117-c9pc-harness-5lkv_default(6515c378c6bed37a2c0eec1fcfea300c)"), skipping: [failed to "StartContainer" for "sdk0" with CrashLoopBackOff: "Back-off 10s restarting failed container=sdk0 pod=<dataflow-id>--01030117-c9pc-harness-5lkv_default(6515c378c6bed37a2c0eec1fcfea300c)""
message: ", failed to "StartContainer" for "sdk1" with CrashLoopBackOff: "Back-off 5m0s restarting failed container=sdk1 pod=<dataflow-id>--01030117-c9pc-harness-5lkv_default(6515c378c6bed37a2c0eec1fcfea300c)"" 
message: ", failed to "StartContainer" for "sdk2" with CrashLoopBackOff: "Back-off 5m0s restarting failed container=sdk2 pod=<dataflow-id>--01030117-c9pc-harness-5lkv_default(6515c378c6bed37a2c0eec1fcfea300c)"" 
message: ", failed to "StartContainer" for "sdk3" with CrashLoopBackOff: "Back-off 5m0s restarting failed container=sdk3 pod=<dataflow-id>--01030117-c9pc-harness-5lkv_default(6515c378c6bed37a2c0eec1fcfea300c)"" 

我也发现了这个错误（在信息模式下）：

Collecting jsonschema (from -r /var/opt/google/staged/requirements.txt (line 1))
  Installing build dependencies: started
Looking in links: /var/opt/google/staged
  Installing build dependencies: started
Collecting jsonschema (from -r /var/opt/google/staged/requirements.txt (line 1))
  Installing build dependencies: started
Looking in links: /var/opt/google/staged
Collecting jsonschema (from -r /var/opt/google/staged/requirements.txt (line 1))
  Installing build dependencies: started
  Installing build dependencies: finished with status 'error'
  ERROR: Command errored out with exit status 1:
   command: /usr/local/bin/python3 /usr/local/lib/python3.7/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-mdurhav9/overlay --no-warn-script-location --no-binary :none: --only-binary :none: --no-index --find-links /var/opt/google/staged -- 'setuptools>=40.6.0' wheel
       cwd: None
  Complete output (5 lines):
  Looking in links: /var/opt/google/staged
  Collecting setuptools>=40.6.0
  Collecting wheel
    ERROR: Could not find a version that satisfies the requirement wheel (from versions: none)
  ERROR: No matching distribution found for wheel

但我不知道为什么它可以得到这种依赖......

你知道我该如何调试吗？ 或者为什么我会遇到这个错误？

谢谢

Answer 1

当 Dataflow Worker 启动时，它们会执行几个步骤：

1. 从requirements.txt安装包
2. 安装指定为extra_packages软件包
3. 安装工作流 tarball 并执行setup.py提供的操作。

使用CrashLoopBackOff消息Error syncing pod时CrashLoopBackOff可能与依赖冲突有关。 您需要验证与用于作业的库和版本没有冲突。 请参阅有关暂存管道所需依赖项的文档。

另外，查看预安装的依赖项和这个StackOverflow 线程。

您可以尝试更改jsonschema的版本并尝试再次运行它。 如果没有帮助，请提供requirements.txt文件。

我希望它会帮助你。

Answer 2

这个错误有一个剧本： https://cloud.google.com/dataflow/docs/guides/common-errors#error-syncing-pod