This commit changes the collection type that holds all of the
hooks from a hashmap to a btree. This allows for better
flexibility for operations that need to perform range searches
and scanning of the collection.
This commit ensures that the TIMEOUT is always checked prior to
returning data to the client, and that the elapsed command time
cannot be greater than the timeout value.
This issues fixes an issue where a search command with a where
clause using the "z" field would not match correctly for point
that where contained inside a GeoJSON Feature type.
Tile38 now extracts the Z coordinate from Point and Feature/Point
types.
fixes#622
This commit changes the collection type that holds all of the
hooks from a hashmap to a btree. This allows for better
flexibility for operations that need to perform range searches
and scanning of the collection.
This commit ensures that the TIMEOUT is always checked prior to
returning data to the client, and that the elapsed command time
cannot be greater than the timeout value.
This commit changes the logic for managing the expiration of
objects in the database.
Before: There was a server-wide hashmap that stored the
collection key, id, and expiration timestamp for all objects
that had a TTL. The hashmap was occasionally probed at 20
random positions, looking for objects that have expired. Those
expired objects were immediately deleted, and if there was 5
or more objects deleted, then the probe happened again, with
no delay. If the number of objects was less than 5 then the
there was a 1/10th of a second delay before the next probe.
Now: Rather than a server-wide hashmap, each collection has
its own ordered priority queue that stores objects with TTLs.
Rather than probing, there is a background routine that
executes every 1/10th of a second, which pops the expired
objects from the collection queues, and deletes them.
The collection/queue method is a more stable approach than
the hashmap/probing method. With probing, we can run into
major cache misses for some cases where there is wide
TTL duration, such as in the hours or days. This may cause
the system to occasionally fall behind, leaving should-be
expired objects in memory. Using a queue, there is no
cache misses, all objects that should be expired will be
right away, regardless of the TTL durations.
Fixes#616