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Orca: add grpc error to orca known issues (#5309)

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* feat: add grpc error to orca known issues

* refactor: update short name and style.

* refactor: refine error explanation

* Update known_issues.md

* Update known_issues.md
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Cengguang Zhang 2022-08-08 18:10:29 +08:00 committed by GitHub
parent 41f602fcec
commit 985aec4425
1 changed files with 17 additions and 3 deletions
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20
docs/readthedocs/source/doc/Orca/Overview/known_issues.md
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@ -12,18 +12,32 @@ To solve this issue, you need to set the path of `libhdfs.so` in Cloudera to the
3. If you are using `init_orca_context(cluster_mode="yarn-client")`:
```
conf = {"spark.executorEnv.ARROW_LIBHDFS_DIR": "/opt/cloudera/parcels/CDH-5.15.2-1.cdh5.15.2.p0.3/lib64"}
init_orca_context(cluster_mode="yarn", conf=conf)
init_orca_context(cluster_mode="yarn-client", conf=conf)
```
If you are using `init_orca_context(cluster_mode="spark-submit")`:
```
# For yarn-client mode
spark-submit --conf spark.executorEnv.ARROW_LIBHDFS_DIR=/opt/cloudera/parcels/CDH-5.15.2-1.cdh5.15.2.p0.3/lib64
# For yarn-cluster mode
spark-submit --conf spark.executorEnv.ARROW_LIBHDFS_DIR=/opt/cloudera/parcels/CDH-5.15.2-1.cdh5.15.2.p0.3/lib64 \
--conf spark.yarn.appMasterEnv.ARROW_LIBHDFS_DIR=/opt/cloudera/parcels/CDH-5.15.2-1.cdh5.15.2.p0.3/lib64
```
### UnkownError: Could not start gRPC server
This error occurs while running Orca TF2 Estimator with spark backend, which may because the previous pyspark tensorflow job was not cleaned completely. You can retry later or you can set spark config `spark.python.worker.reuse=false` in your application.
If you are using `init_orca_context(cluster_mode="yarn-client")`:
```
conf = {"spark.python.worker.reuse": "false"}
init_orca_context(cluster_mode="yarn-client", conf=conf)
```
If you are using `init_orca_context(cluster_mode="spark-submit")`:
```
spark-submit --conf spark.python.worker.reuse=false
```
## **Orca Context Issues**
### **Exception: Failed to read dashbord log: [Errno 2] No such file or directory: '/tmp/ray/.../dashboard.log'**
@ -42,4 +56,4 @@ You could follow below steps to workaround:
ray_ctx.is_local=True
```
2. If you really need to use ray on spark, please install bigdl-orca under a conda environment. Detailed information please refer to [here](./orca.html).
2. If you really need to use ray on spark, please install bigdl-orca under a conda environment. Detailed information please refer to [here](./orca.html).