SELECT
COUNT(user_id) AS login_count,
TUMBLE_START(event_time, INTERVAL '1' MINUTE) AS window_start
FROM login_attempts
GROUP BY TUMBLE(event_time, INTERVAL '1' MINUTE);
After you have what number of login makes an attempt a consumer has within the window, you’ll be able to filter for a better worth (say > 10), triggering enterprise logic inside a UDF to lock them out quickly as an anti-hacking function.
Lastly, you may as well be part of information from a number of streams along with only a few easy instructions. Becoming a member of streams as streams (or as tables) is definitely fairly difficult to do effectively with no streaming framework, notably when accounting for fault tolerance, scalability, and efficiency. On this instance, we’re becoming a member of Product information on Orders information with the product ID, returning an enriched Order + Product consequence.
SELECT * FROM Orders
INNER JOIN Product
ON Orders.productId = Product.id
Observe that not all streaming frameworks (SQL or in any other case) help primary-to-foreign-key joins. Some solely can help you do primary-to-primary-key joins. Why? The quick reply is that it may be fairly difficult to implement a majority of these joins when accounting for fault tolerance, scalability, and efficiency. In actual fact, it’s best to examine how your streaming SQL framework handles joins, and if it might help each international and first key joins, or just simply the latter.
