Update k8s tutorial and script (#7356)
* debug * update train * update remote dir * remove print * update train * update
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2 changed files with 16 additions and 16 deletions
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@ -234,7 +234,7 @@ cp /path/to/fashion-mnist/data/fashion/* /bigdl/nfsdata/dataset/FashionMNIST/raw
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gzip -d /bigdl/nfsdata/dataset/FashionMNIST/raw/*
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```
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In the given example, you can specify the argument `--remote_dir` to be the directory on NFS for the Fashion-MNIST dataset. The directory should contain `FashionMNIST/raw/train-images-idx3-ubyte` and `FashionMNIST/raw/t10k-images-idx3`.
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In the given example, you can specify the argument `--data_dir` to be the directory on NFS for the Fashion-MNIST dataset. The directory should contain `FashionMNIST/raw/train-images-idx3-ubyte` and `FashionMNIST/raw/t10k-images-idx3`.
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---
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@ -304,7 +304,7 @@ See [here](#init-orca-context) for the runtime configurations.
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#### 6.1.1 K8s-Client
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Run the example with the following command by setting the cluster_mode to "k8s-client":
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```bash
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python train.py --cluster_mode k8s-client --remote_dir file:///bigdl/nfsdata/dataset
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python train.py --cluster_mode k8s-client --data_dir /bigdl/nfsdata/dataset
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```
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@ -333,7 +333,7 @@ conda pack -o environment.tar.gz
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Run the example with the following command by setting the cluster_mode to "k8s-cluster":
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```bash
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python /bigdl/nfsdata/train.py --cluster_mode k8s-cluster --remote_dir /bigdl/nfsdata/dataset
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python /bigdl/nfsdata/train.py --cluster_mode k8s-cluster --data_dir /bigdl/nfsdata/dataset
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```
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@ -395,7 +395,7 @@ ${SPARK_HOME}/bin/spark-submit \
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--conf spark.executor.extraClassPath=${BIGDL_HOME}/jars/* \
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--conf spark.kubernetes.executor.volumes.persistentVolumeClaim.${RUNTIME_PERSISTENT_VOLUME_CLAIM}.options.claimName=${RUNTIME_PERSISTENT_VOLUME_CLAIM} \
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--conf spark.kubernetes.executor.volumes.persistentVolumeClaim.${RUNTIME_PERSISTENT_VOLUME_CLAIM}.mount.path=/bigdl/nfsdata \
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train.py --cluster_mode spark-submit --remote_dir /bigdl/nfsdata/dataset
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train.py --cluster_mode spark-submit --data_dir /bigdl/nfsdata/dataset
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```
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In the `spark-submit` script:
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@ -447,7 +447,7 @@ ${SPARK_HOME}/bin/spark-submit \
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--conf spark.kubernetes.driver.volumes.persistentVolumeClaim.${RUNTIME_PERSISTENT_VOLUME_CLAIM}.mount.path=/bigdl/nfsdata \
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--conf spark.kubernetes.executor.volumes.persistentVolumeClaim.${RUNTIME_PERSISTENT_VOLUME_CLAIM}.options.claimName=${RUNTIME_PERSISTENT_VOLUME_CLAIM} \
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--conf spark.kubernetes.executor.volumes.persistentVolumeClaim.${RUNTIME_PERSISTENT_VOLUME_CLAIM}.mount.path=/bigdl/nfsdata \
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file:///bigdl/nfsdata/train.py --cluster_mode spark-submit --remote_dir /bigdl/nfsdata/dataset
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file:///bigdl/nfsdata/train.py --cluster_mode spark-submit --data_dir /bigdl/nfsdata/dataset
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```
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In the `spark-submit` script:
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@ -544,7 +544,7 @@ spec:
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--conf spark.executor.extraClassPath=local://${BIGDL_HOME}/jars/* \
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local:///bigdl/nfsdata/train.py
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--cluster_mode spark-submit
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--remote_dir file:///bigdl/nfsdata/dataset
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--data_dir file:///bigdl/nfsdata/dataset
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"]
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securityContext:
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privileged: true
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@ -688,7 +688,7 @@ spec:
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--conf spark.executor.extraClassPath=local://${BIGDL_HOME}/jars/* \
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local:///bigdl/nfsdata/train.py
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--cluster_mode spark-submit
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--remote_dir file:///bigdl/nfsdata/dataset
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--data_dir file:///bigdl/nfsdata/dataset
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"]
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securityContext:
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privileged: true
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@ -861,7 +861,7 @@ spec:
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--conf spark.executor.extraClassPath=local://${BIGDL_HOME}/jars/* \
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local:///bigdl/nfsdata/train.py
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--cluster_mode spark-submit
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--remote_dir file:///bigdl/nfsdata/dataset
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--data_dir file:///bigdl/nfsdata/dataset
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"]
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securityContext:
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privileged: true
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@ -999,7 +999,7 @@ spec:
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--conf spark.executor.extraClassPath=local://${BIGDL_HOME}/jars/* \
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local:///bigdl/nfsdata/train.py
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--cluster_mode spark-submit
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--remote_dir file:///bigdl/nfsdata/dataset
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--data_dir file:///bigdl/nfsdata/dataset
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"]
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securityContext:
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privileged: true
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@ -127,7 +127,7 @@ Then upload it to a distributed storage. Sample command to upload data to HDFS i
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```bash
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hdfs dfs -put /path/to/local/data/FashionMNIST hdfs://path/to/remote/data
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```
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In the given example, you can specify the argument `--remote_dir` to be the directory on a distributed storage for the Fashion-MNIST dataset. The directory should contain `FashionMNIST/raw/train-images-idx3-ubyte` and `FashionMNIST/raw/t10k-images-idx3`.
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In the given example, you can specify the argument `--data_dir` to be the directory on a distributed storage for the Fashion-MNIST dataset. The directory should contain `FashionMNIST/raw/train-images-idx3-ubyte` and `FashionMNIST/raw/t10k-images-idx3`.
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---
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## 4. Prepare Custom Modules
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@ -192,14 +192,14 @@ See [here](#init-orca-context) for the runtime configurations.
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#### 5.1.1 Yarn Client
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Run the example with the following command by setting the cluster_mode to "yarn-client":
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```bash
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python train.py --cluster_mode yarn-client --remote_dir hdfs://path/to/remote/data
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python train.py --cluster_mode yarn-client --data_dir hdfs://path/to/remote/data
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```
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#### 5.1.2 Yarn Cluster
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Run the example with the following command by setting the cluster_mode to "yarn-cluster":
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```bash
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python train.py --cluster_mode yarn-cluster --remote_dir hdfs://path/to/remote/data
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python train.py --cluster_mode yarn-cluster --data_dir hdfs://path/to/remote/data
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```
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@ -254,7 +254,7 @@ bigdl-submit \
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--archives /path/to/environment.tar.gz#environment \
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--conf spark.pyspark.driver.python=/path/to/python \
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--conf spark.pyspark.python=environment/bin/python \
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train.py --cluster_mode bigdl-submit --remote_dir hdfs://path/to/remote/data
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train.py --cluster_mode bigdl-submit --data_dir hdfs://path/to/remote/data
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```
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In the `bigdl-submit` script:
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* `--master`: the spark master, set it to "yarn".
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@ -277,7 +277,7 @@ bigdl-submit \
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--archives /path/to/environment.tar.gz#environment \
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--conf spark.yarn.appMasterEnv.PYSPARK_PYTHON=environment/bin/python \
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--conf spark.executorEnv.PYSPARK_PYTHON=environment/bin/python \
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train.py --cluster_mode bigdl-submit --remote_dir hdfs://path/to/remote/data
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train.py --cluster_mode bigdl-submit --data_dir hdfs://path/to/remote/data
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```
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In the `bigdl-submit` script:
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* `--master`: the spark master, set it to "yarn".
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@ -344,7 +344,7 @@ ${SPARK_HOME}/bin/spark-submit \
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--conf spark.pyspark.python=environment/bin/python \
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--py-files ${BIGDL_HOME}/python/bigdl-spark_${SPARK_VERSION}-${BIGDL_VERSION}-python-api.zip,model.py \
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--jars ${BIGDL_HOME}/jars/bigdl-assembly-spark_${SPARK_VERSION}-${BIGDL_VERSION}-jar-with-dependencies.jar \
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train.py --cluster_mode spark-submit --remote_dir hdfs://path/to/remote/data
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train.py --cluster_mode spark-submit --data_dir hdfs://path/to/remote/data
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```
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In the `spark-submit` script:
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* `--master`: the spark master, set it to "yarn".
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@ -368,7 +368,7 @@ ${SPARK_HOME}/bin/spark-submit \
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--conf spark.executorEnv.PYSPARK_PYTHON=environment/bin/python \
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--py-files ${BIGDL_HOME}/python/bigdl-spark_${SPARK_VERSION}-${BIGDL_VERSION}-python-api.zip,model.py \
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--jars ${BIGDL_HOME}/jars/bigdl-assembly-spark_${SPARK_VERSION}-${BIGDL_VERSION}-jar-with-dependencies.jar \
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train.py --cluster_mode spark-submit --remote_dir hdfs://path/to/remote/data
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train.py --cluster_mode spark-submit --data_dir hdfs://path/to/remote/data
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```
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In the `spark-submit` script:
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* `--master`: the spark master, set it to "yarn".
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