How to spilt a big DataFrame into Vec by group in Polars
Polars has a DataFrame::partition_by function for this.
I stored some financial market data in a Polars DataFrame. As for analysis, it is is fast to run some groupby("date").agg() action.
But in a realtime scenario , the new data is coming time by time, I don't want to concat the new data with old data again and again, it is slow and use a lot of memory. So is there a blazing fast way to spilt the old data DataFrame into small DataFrame groupby datetime column which stored in a vector or hashmap, so when the new data comes, I just push the new into vector for future calculation?