In the previous article, we have talked about how FireDucks can take care pushdown-projection related optimization for read_parquet(), read_csv() etc. In today’s article, we will focus on the efficient caching mechanism by its JIT compiler. Let’s consider the below sample query for the same data, used in previous article: import pandas as pd df = pd.read_parquet("sample_data.parquet") f_df = df.loc[df["a"] > 3, ["x", "y", "z"]] r1 = f_df.groupby("x")["z"].sum() print(r1) When executing th...
