Amazon has web server logs from multiple hosts.
Each log entry consists of:
- a Session ID
- a Web Page ID
Example (conceptual):
session_id, web_page_id
0001, product_1
0001, cart
0002, product_2
0003, home_page
0005, help
0001, checkout
0002, cart
0001, help
0001, product_1
0002, checkout
0005, checkout
0002, help
We want to find the 3-page pattern that is visited most frequently across all sessions.
In the example, the sequence <cart, checkout, help> appears twice, so it is the most frequent 3-page pattern.
Given logs in the form:
logs = [
session:0001, web:product_1
session:0001, web:cart
session:0002, web:product_2
session:0003, web:home_page
session:0005, web:help
session:0001, web:checkout
session:0002, web:cart
session:0001, web:help
session:0001, web:product_1
session:0002, web:checkout
session:0005, web:checkout
session:0002, web:help
]
Return the 3-page sequence that is most frequently visited, counting only in-order sequences within the same session.
Group logs by session ID, sort each session’s pages by time if needed, then within each session slide a window of size 3 to extract all 3-page sequences. Use a hash map to count frequencies, and return the sequence with the highest count.
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