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_low_random.log
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_low_random.log
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Python: 3.6.3 | packaged by conda-forge | (default, Nov 4 2017, 10:10:56)
[GCC 4.8.2 20140120 (Red Hat 4.8.2-15)]
PyEXASOL: 0.4.1
PyODBC: 4.0.16
TurbODBC: 2.4.1
Creating random data set for tests, 10000000 rows
Please wait, it may take a few minutes
Test data was prepared
time python 01_pyodbc_fetch.py
real 1m45.655s
user 1m37.095s
sys 0m3.062s
time python 02_turbodbc_fetch.py
real 0m55.927s
user 0m46.963s
sys 0m2.063s
time python 03_pyexasol_fetch.py
real 0m32.446s
user 0m23.080s
sys 0m2.298s
time python 04_turbodbc_pandas_numpy.py
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10000000 entries, 0 to 9999999
Data columns (total 8 columns):
USER_ID int64
USER_NAME object
REGISTER_DT datetime64[ns]
LAST_VISIT_TS datetime64[ns]
IS_FEMALE bool
USER_RATING float64
USER_SCORE float64
STATUS object
dtypes: bool(1), datetime64[ns](2), float64(2), int64(1), object(2)
memory usage: 543.6+ MB
real 0m15.162s
user 0m8.252s
sys 0m1.470s
time python 05_turbodbc_pandas_arrow.py
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10000000 entries, 0 to 9999999
Data columns (total 8 columns):
USER_ID int64
USER_NAME object
REGISTER_DT datetime64[ns]
LAST_VISIT_TS datetime64[ns]
IS_FEMALE bool
USER_RATING float64
USER_SCORE float64
STATUS object
dtypes: bool(1), datetime64[ns](2), float64(2), int64(1), object(2)
memory usage: 543.6+ MB
real 0m13.608s
user 0m7.307s
sys 0m1.477s
time python 06_pyexasol_pandas.py
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10000000 entries, 0 to 9999999
Data columns (total 8 columns):
USER_ID int64
USER_NAME object
REGISTER_DT object
LAST_VISIT_TS object
IS_FEMALE int64
USER_RATING float64
USER_SCORE int64
STATUS object
dtypes: float64(1), int64(3), object(4)
memory usage: 610.4+ MB
real 0m11.188s
user 0m10.062s
sys 0m1.302s
time python 07_pyexasol_pandas_compress.py
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 10000000 entries, 0 to 9999999
Data columns (total 8 columns):
USER_ID int64
USER_NAME object
REGISTER_DT object
LAST_VISIT_TS object
IS_FEMALE int64
USER_RATING float64
USER_SCORE int64
STATUS object
dtypes: float64(1), int64(3), object(4)
memory usage: 610.4+ MB
real 0m27.732s
user 0m12.998s
sys 0m1.053s
time python 08_pyexasol_pandas_parallel.py
1:2090271
0:1998136
4:1901869
2:2182436
3:1827288
real 0m5.036s
user 0m12.086s
sys 0m1.967s