# -*- coding:utf-8 -*-

from typing import Dict, Union, List

from dw_base.utils.config_utils import parse_args
from dw_base.spark.spark_sql import SparkSQL
from pyspark.sql import SparkSession

"""
@author xunxu
提供一种类似spark-submit提交方式的SparkSession初始化工具类
xxx.py \
--name "spark-sql-test-job" \
--queue cts \
--num-executors 2 \
--executor-memory 1g \
--executor-cores 1 \
--conf spark.sql.shuffle.partitions=300 \
--conf spark.default.parallelism=300 \
--conf spark.dynamicAllocation.enabled=true \
--py-files dw_base/spark/udf/customs/common_clean.py,dw_base/spark/udf/spark_eng_ent_name_clean.py \
-dt="" -cdt="" -ydt="" ...
"""


def get_spark(argv: list) -> (SparkSQL, SparkSession):
    """
    Args:
        argv: sys.argv parsed from the command line
    Returns: tendata SparkSQL and SparkSession Tuple
    """
    conf_args: Dict[str, Union[str, bool, List[str]]]
    conf_args, _ = parse_args(argv[1:])

    spark_conf_dict = {
        "hive.exec.dynamic.partition": "true",
        "hive.exec.dynamic.partition.mode": "nonstrict",
        "spark.dynamicAllocation.enabled": "true"
    }

    # 添加所有的--conf配置到extra_spark_conf中
    if conf_args.__contains__('conf'):
        spark_conf = conf_args['conf']
        if isinstance(spark_conf, list):
            spark_conf_dict.update(
                dict(map(lambda kv_str: kv_str.split("="), spark_conf))
            )
        elif isinstance(spark_conf, str):
            k, v = spark_conf.split("=")
            spark_conf_dict[k] = v

    td_spark = SparkSQL(
        session_name=conf_args.get("name", argv[0]),
        master=conf_args.get("master", "yarn"),
        spark_yarn_queue=conf_args.get("queue", "default"),
        spark_driver_memory=conf_args.get("driver-memory", "1g"),
        spark_driver_cores=conf_args.get("driver-core", 1),
        spark_executor_instances=conf_args.get("num-executors", 2),
        spark_executor_cores=conf_args.get("executor-cores", 2),
        spark_executor_memory=conf_args.get("executor-memory", "6g"),
        extra_spark_config=spark_conf_dict,
        udf_files=conf_args['py-files'].split(",") if conf_args.__contains__('py-files') else None
    )
    spark: SparkSession = td_spark.get_spark_session()
    return td_spark, spark


# if __name__ == "__main__":
#     spark: SparkSession
#     td_spark, spark = get_spark(sys.argv)
#     spark.sql("show databases").show(100, truncate=False)