Objective is to understand the principles of Distributed Computing and MapReduce in Python
A number of historical stok files are given do trades as follows, 1.Load the library into RAM. Use the MapReduce model; write a program to trade every single stock based on the following rule:
- Buy a stock at 10am on Tue (if the market is closed on Tue, then skip this trade)
- Sell the shares at 12pm on Wed (if the market is close on Wed, then sell on the next trading day at 12pm) Trade 2 2.Load the library into RAM. Use the MapReduce model, write a program to trade the stocks based on the following rule:
- At 10am on each day, find the stock that has gained the most from market open to 10am, then buy the stock.
- Sell the shares at 12pm on the same day.
In Conclusion I increased the number of processes and measured the execution time.