Created 04-25-2022 10:13 PM
I have written python function and run in pyspark - cloudera shell but it throwing error while running it. But when I run the same function in my pyspark - local shell it's working perfectly fine.
Complete Code:
from pyspark.sql.functions import *
df=spark.createDataFrame([
('America/New_York','2020-02-01 10:00:00')
,('Europe/Lisbon','2020-02-01 10:00:00')
,('Europe/Madrid','2020-02-01 10:00:00')
,('Europe/London', '2020-02-01 10:00:00')
,('America/Sao_Paulo', '2020-02-01 10:00:00')
]
,["OriginTz","Time"])
df2=spark.createDataFrame([
('Africa/Nairobi', '2020-02-01 10:00:00')
,('Asia/Damascus', '2020-02-01 10:00:00')
,('Asia/Singapore', '2020-02-01 10:00:00')
,('Atlantic/Bermuda','2020-02-01 10:00:00')
,('Canada/Mountain','2020-02-01 10:00:00')
,('Pacific/Tahiti','2020-02-01 10:00:00')
]
,["OriginTz", "Time"])
df.createOrReplaceTempView("test")
df2.createOrReplaceTempView("test2")
tables = ["test", "test2"]
frames = list(range(0,2))
def hive_read_func(tables, frames):
for table, frame in zip(tables, frames):
globals()["dtf"+str(frame)] = eval(f'spark.sql("select * from {table}")')
hive_read_func(tables, frames)
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when I run the function hive_read_func in cloudera getting below error:
but when I run in my local system its running perfectly fine:
can some one please look into this and help me to solve
Created 04-26-2022 02:42 AM
I got the answer myself: this is because of version f-string is available after python 3.1 but I run it in python version 2.6. so got error, now I rewrite the function with out f-string:
def hive_read_func(tables, frames):
for table, frame in zip(tables, frames):
inner_code = "select * from"+" "+ str(table)
globals()["dttf"+str(frame)] = spark.sql(inner_code)
Created 04-26-2022 02:42 AM
I got the answer myself: this is because of version f-string is available after python 3.1 but I run it in python version 2.6. so got error, now I rewrite the function with out f-string:
def hive_read_func(tables, frames):
for table, frame in zip(tables, frames):
inner_code = "select * from"+" "+ str(table)
globals()["dttf"+str(frame)] = spark.sql(inner_code)