Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

add hdfs error for dag #2326

Merged
merged 1 commit into from
Nov 17, 2022
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions docs-2.0/nebula-explorer/deploy-connect/ex-ug-deploy.md
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,12 @@

License 仅在企业版提供,申请 License 需填写 [Nebula Explorer 试用申请](https://wj.qq.com/s2/10158890/69a8)。

- 如果需要使用图计算,需要部署 HDFS。namenode 默认使用 8020 端口,datanode 默认使用 50010 端口。

!!! caution

如果 HDFS 端口不通,可能会提示连接超时。

## 注意事项

Explorer 从 3.2.0 版本开始内置了 Dag Controller 安装包,用于提供图计算服务。用户可以自行决定是否启动 Dag Controller 服务。如果没有启动 Dag Controller 服务, Explorer 中的 **Workflow** 菜单将显示为灰色无法点击。
Expand Down
14 changes: 14 additions & 0 deletions docs-2.0/nebula-explorer/faq.md
Original file line number Diff line number Diff line change
Expand Up @@ -68,6 +68,20 @@ Dag Controller 包含图查询组件和图计算组件。图查询是发送请

3. 修改上述配置后需要重启 Dag Controller 使配置生效。

## 任务运行失败,报错`no available namenodes: dial tcp xx.xx.xx.xx:8020: connect: connection timed out`怎么办?

请检查 HDFS 的 namenode 端口是否开放。

## 任务运行失败,报错`org.apache.hadoop.net.ConnectTimeoutException: 60000 millis timeout`怎么办?

请检查 HDFS 的 datanode 端口是否开放。

如果没有开放端口,还可能报类似如下错误:

- `Check failed: false close hdfs-file failed`
- `org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /analytics/xx/tasks/analytics_xxx/xxx.csv could only be replicated to 0 nodes instead of minReplication`


## 任务运行失败,报错`broadcast.hpp:193] Check failed: (size_t)recv_bytes >= sizeof(chunk_tail_t) recv message too small: 0`怎么办?

任务要处理的数据量过小,但是配置的计算节点数与进程数太多。需要在提交作业时设置较小的`clusterSize`和`processes`。