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Doc: add yarn cluster running results (#7562)

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* feat(yarn.md): add yarn cluster run results

* fix(yarn.md): rm extra |

* docs(yarn.md): perf description

* docs(yarn.md): perf

* feat(yarn.md): how to see logs

* fix(yarn.md): perf: time

* perf(yarn.md): rm which python

* fix(yarn.md): hide internal info

* docs(yarn.md): perf

* fix(yarn.md): url
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Yinchen Ni 2023-02-15 20:02:06 +08:00 committed by GitHub
parent 213cfd985b
commit 479042a93a
1 changed files with 23 additions and 3 deletions
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26
docs/readthedocs/source/doc/Orca/Tutorial/yarn.md
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@ -43,7 +43,27 @@ The difference between yarn-client mode and yarn-cluster mode is where you run y
For yarn-client, the Spark driver runs in the client process, and the application master is only used for requesting resources from YARN, while for yarn-cluster the Spark driver runs inside an application master process which is managed by YARN in the cluster.
For more details, please see [Launching Spark on YARN](https://spark.apache.org/docs/latest/running-on-yarn.html#launching-spark-on-yarn).
Please see more details in [Launching Spark on YARN](https://spark.apache.org/docs/latest/running-on-yarn.html#launching-spark-on-yarn).
For **yarn-client** mode, you can directly find the driver logs in the console.
For **yarn-cluster** mode, an `application_time_id` will be returned (`application_1668477395550_1045` in the following log) when the application master process is completed.
```bash
23/02/15 15:30:26 INFO yarn.Client: Application report for application_1668477395550_1045 (state: FINISHED)
23/02/15 15:30:26 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: ...
ApplicationMaster RPC port: 46652
queue: ...
start time: 1676446090408
final status: SUCCEEDED
tracking URL: http://.../application_1668477395550_1045/
user: ...
```
Visit the tracking URL and then click `logs` in the table `ApplicationMaster` to see the driver logs.
### 1.3 Distributed storage on YARN
__Note__:
@ -255,7 +275,7 @@ bigdl-submit \
--driver-memory 2g \
--py-files model.py \
--archives /path/to/environment.tar.gz#environment \
--conf spark.pyspark.driver.python=/path/to/python \
--conf spark.pyspark.driver.python=python \
--conf spark.pyspark.python=environment/bin/python \
train.py --cluster_mode bigdl-submit --data_dir hdfs://path/to/remote/data
```
@ -345,7 +365,7 @@ ${SPARK_HOME}/bin/spark-submit \
--driver-memory 2g \
--archives /path/to/environment.tar.gz#environment \
--properties-file ${BIGDL_HOME}/conf/spark-bigdl.conf \
--conf spark.pyspark.driver.python=/path/to/python \
--conf spark.pyspark.driver.python=python \
--conf spark.pyspark.python=environment/bin/python \
--py-files ${BIGDL_HOME}/python/bigdl-spark_${SPARK_VERSION}-${BIGDL_VERSION}-python-api.zip,model.py \
--jars ${BIGDL_HOME}/jars/bigdl-assembly-spark_${SPARK_VERSION}-${BIGDL_VERSION}-jar-with-dependencies.jar \