pandas.read_sql is extremely slow on python 3 kernel compared to python 2
2
I have a simple parameterized select query hitting an Oracle database via pyodbc connection and fetching data in a dataframe via pandas.read_sql.
The code is super efficient and fast in Python 2 kernel whereas, extremely slow in Python 3.
Following is the code:
import pandas
import pyodbc
import time
connection = pyodbc.connect('dsn=oracle;userid=userid;pwd=password')
sql = """
select * from order_table
where
order_key = ?
"""
start_time = time.time()
dataframe = pandas.read_sql(sql=sql, con=connection, params=['key-1'])
print(time.time()-start_time)
Python 2 execution time:
0.193000078201
Python 3 execution time:
53.687000036239624
python python-3.x python-2.7 pandas pandasql
edited Nov 11 at 17:55
eyllanesc
73.4k103056
asked Nov 11 at 17:41
nikhil
112
add a comment |
2
I have a simple parameterized select query hitting an Oracle database via pyodbc connection and fetching data in a dataframe via pandas.read_sql.
The code is super efficient and fast in Python 2 kernel whereas, extremely slow in Python 3.
Following is the code:
import pandas
import pyodbc
import time
connection = pyodbc.connect('dsn=oracle;userid=userid;pwd=password')
sql = """
select * from order_table
where
order_key = ?
"""
start_time = time.time()
dataframe = pandas.read_sql(sql=sql, con=connection, params=['key-1'])
print(time.time()-start_time)
Python 2 execution time:
0.193000078201
Python 3 execution time:
53.687000036239624
python python-3.x python-2.7 pandas pandasql
edited Nov 11 at 17:55
eyllanesc
73.4k103056
asked Nov 11 at 17:41
nikhil
112
Which versions ofpandasandpypyodbcare you using?
– Xukrao
Nov 11 at 18:05
Is the environment (except the Python version) exactly the same... eg - you're accessing the same database with the same schema, searching for the same key with the DB at about the same workload, checked there hasn't been any transaction locks preventing your read occurring immediately etc... etc...?
– Jon Clements♦
Nov 11 at 18:27
Thank you for your reply. Everything remains the same. In the Jupyter Notebook, I go to "Kernel" => "Change Kernel" => "Python 3/2".
– nikhil
Nov 11 at 19:27
pyodbc version 4.0.24, pandas version 0.23.4
– nikhil
Nov 11 at 19:28
add a comment |
2
2
2
1
I have a simple parameterized select query hitting an Oracle database via pyodbc connection and fetching data in a dataframe via pandas.read_sql.
The code is super efficient and fast in Python 2 kernel whereas, extremely slow in Python 3.
Following is the code:
import pandas
import pyodbc
import time
connection = pyodbc.connect('dsn=oracle;userid=userid;pwd=password')
sql = """
select * from order_table
where
order_key = ?
"""
start_time = time.time()
dataframe = pandas.read_sql(sql=sql, con=connection, params=['key-1'])
print(time.time()-start_time)
Python 2 execution time:
0.193000078201
Python 3 execution time:
53.687000036239624
python python-3.x python-2.7 pandas pandasql
edited Nov 11 at 17:55
eyllanesc
73.4k103056
asked Nov 11 at 17:41
nikhil
112
I have a simple parameterized select query hitting an Oracle database via pyodbc connection and fetching data in a dataframe via pandas.read_sql.
The code is super efficient and fast in Python 2 kernel whereas, extremely slow in Python 3.
Following is the code:
import pandas
import pyodbc
import time
connection = pyodbc.connect('dsn=oracle;userid=userid;pwd=password')
sql = """
select * from order_table
where
order_key = ?
"""
start_time = time.time()
dataframe = pandas.read_sql(sql=sql, con=connection, params=['key-1'])
print(time.time()-start_time)
Python 2 execution time:
0.193000078201
Python 3 execution time:
53.687000036239624
python python-3.x python-2.7 pandas pandasql
python python-3.x python-2.7 pandas pandasql
edited Nov 11 at 17:55
eyllanesc
73.4k103056
asked Nov 11 at 17:41
nikhil
112
edited Nov 11 at 17:55
eyllanesc
73.4k103056
asked Nov 11 at 17:41
nikhil
112
edited Nov 11 at 17:55
eyllanesc
73.4k103056
edited Nov 11 at 17:55
eyllanesc
73.4k103056
edited Nov 11 at 17:55
eyllanesc
73.4k103056
73.4k103056
asked Nov 11 at 17:41
nikhil
112
asked Nov 11 at 17:41
nikhil
112
asked Nov 11 at 17:41
nikhil
112
112
Which versions ofpandasandpypyodbcare you using?
– Xukrao
Nov 11 at 18:05
Is the environment (except the Python version) exactly the same... eg - you're accessing the same database with the same schema, searching for the same key with the DB at about the same workload, checked there hasn't been any transaction locks preventing your read occurring immediately etc... etc...?
– Jon Clements♦
Nov 11 at 18:27
Thank you for your reply. Everything remains the same. In the Jupyter Notebook, I go to "Kernel" => "Change Kernel" => "Python 3/2".
– nikhil
Nov 11 at 19:27
pyodbc version 4.0.24, pandas version 0.23.4
– nikhil
Nov 11 at 19:28
add a comment |
Which versions ofpandasandpypyodbcare you using?
– Xukrao
Nov 11 at 18:05
Is the environment (except the Python version) exactly the same... eg - you're accessing the same database with the same schema, searching for the same key with the DB at about the same workload, checked there hasn't been any transaction locks preventing your read occurring immediately etc... etc...?
– Jon Clements♦
Nov 11 at 18:27
Thank you for your reply. Everything remains the same. In the Jupyter Notebook, I go to "Kernel" => "Change Kernel" => "Python 3/2".
– nikhil
Nov 11 at 19:27
pyodbc version 4.0.24, pandas version 0.23.4
– nikhil
Nov 11 at 19:28
Which versions of
pandas and pypyodbc are you using?– Xukrao
Nov 11 at 18:05
Which versions of
pandas and pypyodbc are you using?– Xukrao
Nov 11 at 18:05
Is the environment (except the Python version) exactly the same... eg - you're accessing the same database with the same schema, searching for the same key with the DB at about the same workload, checked there hasn't been any transaction locks preventing your read occurring immediately etc... etc...?
– Jon Clements♦
Nov 11 at 18:27
Is the environment (except the Python version) exactly the same... eg - you're accessing the same database with the same schema, searching for the same key with the DB at about the same workload, checked there hasn't been any transaction locks preventing your read occurring immediately etc... etc...?
– Jon Clements♦
Nov 11 at 18:27
Thank you for your reply. Everything remains the same. In the Jupyter Notebook, I go to "Kernel" => "Change Kernel" => "Python 3/2".
– nikhil
Nov 11 at 19:27
Thank you for your reply. Everything remains the same. In the Jupyter Notebook, I go to "Kernel" => "Change Kernel" => "Python 3/2".
– nikhil
Nov 11 at 19:27
pyodbc version 4.0.24, pandas version 0.23.4
– nikhil
Nov 11 at 19:28
pyodbc version 4.0.24, pandas version 0.23.4
– nikhil
Nov 11 at 19:28
add a comment |
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Which versions of
pandasandpypyodbcare you using?– Xukrao
Nov 11 at 18:05
Is the environment (except the Python version) exactly the same... eg - you're accessing the same database with the same schema, searching for the same key with the DB at about the same workload, checked there hasn't been any transaction locks preventing your read occurring immediately etc... etc...?
– Jon Clements♦
Nov 11 at 18:27
Thank you for your reply. Everything remains the same. In the Jupyter Notebook, I go to "Kernel" => "Change Kernel" => "Python 3/2".
– nikhil
Nov 11 at 19:27
pyodbc version 4.0.24, pandas version 0.23.4
– nikhil
Nov 11 at 19:28