Einführung in das Data Engineering
Vincent Vankrunkelsven
Data Engineer @ DataCamp
Grundlage moderner Datenverarbeitungstools
Grundidee


Betrieb einer Schneiderei
Ziel: 100 Hemden
Mehrere Schneider, die zusammenarbeiten > bester Schneider
RAM-Speicherchip:

Kommunikationsaufwand
Parallele Verlangsamung:


multiprocessing.Pool
from multiprocessing import Pooldef take_mean_age(year_and_group): year, group = year_and_group return pd.DataFrame({"Age": group["Age"].mean()}, index=[year])with Pool(4) as p: results = p.map(take_mean_age, athlete_events.groupby("Year"))result_df = pd.concat(results)
dask
import dask.dataframe as dd# Partition dataframe into 4 athlete_events_dask = dd.from_pandas(athlete_events, npartitions = 4)# Run parallel computations on each partition result_df = athlete_events_dask.groupby('Year').Age.mean().compute()
Einführung in das Data Engineering