Spark-Submit日期参数

Question

---

我有一个关于如何通过两个日期作为参数传递的查询 提交火花，需要代码使用。

spark-submit gis.py'2019-03-04''2019-03-07'

使用了以下Spark提交，日期是表中的字符串

from pyspark.sql import sparksession
from pyspark.sql import functions as F
from pyspark import HiveContext
hiveContext= HiveContext(sc)

start_date=arg1
end_dater =arg2

def UDF_df(i):
    print(i[0])
ABC2 = spark.sql(
    "select * From A where day ='{0}'".format(i[0])
)
Join = ABC2.join(
    Tab2,
     (
        ABC2.ID == Tab2.ID
    )
).select(
    Tab2.skey,
    ABC2.Day,
    ABC2.Name,
    ABC2.Description
)
Join.select(
    "Tab2.skey",
    "ABC2.Day",
    "ABC2.Name",
    "ABC2.Description"
).write.mode("append").format("parquet").insertinto("Table")

ABC=spark.sql(
    "select distinct day from A where day>= start_date and day<=end_date"
)
Tab2=spark.sql("select * from B where day is not null")
for in in ABC.collect():
    UDF_df(i)

Above code isn't taking arg 1 & 2 and is thus resulting in an error

Answer 1

如果它是python脚本，请尝试使用sys模块。

import sys 
start_date=sys.argv[1]
end_date=sys.argv[2]

Answer 2

尝试一下-

spark-submit \
.
.
--conf "spark.service.user.startdate=2019-03-04" \
--conf "spark.service.user.enddate=2019-03-07"   \
.
.


In your code refer above config property as -

spark.sparkContext.getConf.get("spark.service.user.startdate")
spark.sparkContext.getConf.get("spark.service.user.enddate")

希望这会有所帮助。

Answer 3

将参数传递给Spark脚本的最干净方法是使用args解析器模块传递命名参数。

pip安装argparse

示例代码：

parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--date1', help='pass the first date')
parser.add_argument('--date2', help='pass the 2nd date')

args = parser.parse_args()

start_date=arg1.date1
end_dater =arg2.date2

有关args解析器的更多信息： https://docs.python.org/2/library/argparse.html