ModelType=lrDemo
if [ $# -gt 0 ];then
    if [ $1 == "df" ];then
        ModelType=lrDemo_df
    fi
fi
echo -e "\n--------------------\nModelType: ${ModelType}\n--------------------\n"

CUR_PATH=$(cd "$(dirname "$0")";pwd)
echo $CUR_PATH
#
#input_path_1=hdfs://192.168.199.27:9000/user/sxkj/train.txt
#input_path_2=hdfs://192.168.199.27:9000/user/sxkj/test.txt
#output_path=hdfs://192.168.199.27:9000/tmp/sparkDemo/${ModelType}

inputs='{"train_df": "hdfs://192.168.199.27:9000/user/sxkj/train.txt", "test_df": "hdfs://192.168.199.27:9000/user/sxkj/test.txt"}'
outputs='["hdfs://192.168.199.27:9000/tmp/sparkDemo/lrDemo/target/output1"]'

# hdfs dfs -rm -r $output_path

sourceDIR=/home/sxkj/bigdata

who=sxkj

# CUR_PATH=$(cd "$(dirname "$0")";pwd)
# sourceDIR=${CUR_PATH}
YARN_QUEUE=
#DEPLOY_MODE=cluster
DEPLOY_MODE=client


${SPARK_HOME}/bin/spark-submit \
  --master yarn \
  --name "spark_${ModelType}_${who}" \
  --deploy-mode cluster \
  --driver-memory 1g \
  --driver-cores 1 \
  --executor-memory 1g \
  --executor-cores 1 \
  --num-executors 1 \
  --archives ${sourceDIR}/py37.zip#python3env \
  --conf spark.default.parallelism=1 \
  --conf spark.executor.memoryOverhead=1g \
  --conf spark.driver.memoryOverhead=1g \
  --conf spark.yarn.maxAppAttempts=3 \
  --conf spark.yarn.submit.waitAppCompletion=true \
  --conf spark.pyspark.driver.python=${sourceDIR}/py37/bin/python \
  --conf spark.yarn.appMasterEnv.PYSPARK_PYTHON=python3env/py37/bin/python \
  --conf spark.pyspark.python=python3env/py37/bin/python \
  ./lr_df_demo.py "$inputs" "$outputs"