Speed Up Your Data Processing Parallel and Asynchronous ...
Speed Up Your Data Processing
Parallel and Asynchronous Programming in
Data Science
By: Chin Hwee Ong (@ongchinhwee)
23 July 2020
About me
Ong Chin Hwee Íõ¾´»Ý
¡ñ Data Engineer @ ST Engineering
¡ñ Background in aerospace
engineering + computational
modelling
¡ñ Contributor to pandas 1.0 release
¡ñ Mentor team at BigDataX
@ongchinhwee
A typical data science workflow
1.
2.
3.
4.
Extract raw data
Process data
Train model
Evaluate and deploy model
@ongchinhwee
Bottlenecks in a data science project
¡ñ Lack of data / Poor quality data
¡ñ Data processing
¡ð The 80/20 data science dilemma
¡ö In reality, it¡¯s closer to 90/10
@ongchinhwee
Data Processing in Python
¡ñ For loops in Python
¡ð Run on the interpreter, not compiled
¡ð Slow compared with C
a_list = []
for i in range(100):
a_list.append(i*i)
@ongchinhwee
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