This commit fixes an issue where Tile38 was using lots of extra
memory to track objects that are marked to expire. This was
creating problems with applications that set big TTLs.
How it worked before:
Every collection had a unique hashmap that stores expiration
timestamps for every object in that collection. Along with
the hashmaps, there's also one big server-wide list that gets
appended every time a new SET+EX is performed.
From a background routine, this list is looped over at least
10 times per second and is randomly searched for potential
candidates that might need expiring. The routine then removes
those entries from the list and tests if the objects matching
the entries have actually expired. If so, these objects are
deleted them from the database. When at least 25% of
the 20 candidates are deleted the loop is immediately
continued, otherwise the loop backs off with a 100ms pause.
Why this was a problem.
The list grows one entry for every SET+EX. When TTLs are long,
like 24-hours or more, it would take at least that much time
before the entry is removed. So for databased that have objects
that use TTLs and are updated often this could lead to a very
large list.
How it was fixed.
The list was removed and the hashmap is now search randomly. This
required a new hashmap implementation, as the built-in Go map
does not provide an operation for randomly geting entries. The
chosen implementation is a robinhood-hash because it provides
open-addressing, which makes for simple random bucket selections.
Issue #502
The big change is that the GeoJSON package has been completely
rewritten to fix a few of geometry calculation bugs, increase
performance, and to better follow the GeoJSON spec RFC 7946.
GeoJSON updates
- A LineString now requires at least two points.
- All json members, even foreign, now persist with the object.
- The bbox member persists too but is no longer used for geometry
calculations. This is change in behavior. Previously Tile38 would
treat the bbox as the object's physical rectangle.
- Corrections to geometry intersects and within calculations.
Faster spatial queries
- The performance of Point-in-polygon and object intersect operations
are greatly improved for complex polygons and line strings. It went
from O(n) to roughly O(log n).
- The same for all collection types with many children, including
FeatureCollection, GeometryCollection, MultiPoint, MultiLineString,
and MultiPolygon.
Codebase changes
- The pkg directory has been renamed to internal
- The GeoJSON internal package has been moved to a seperate repo at
https://github.com/tidwall/geojson. It's now vendored.
Please look out for higher memory usage for datasets using complex
shapes. A complex shape is one that has 64 or more points. For these
shapes it's expected that there will be increase of least 54 bytes per
point.
commit a1a37d335a8e89ac89d85c00c8585d3fc02e064a
Author: Josh Baker <joshbaker77@gmail.com>
Date: Thu Oct 5 07:36:54 2017 -0700
use symlink instead of copy
commit 96399c2c92620f633611c778e5473200bfd48d41
Author: Josh Baker <joshbaker77@gmail.com>
Date: Thu Oct 5 07:19:26 2017 -0700
use dep for vendoring
Performance gains for pipelining commands over the network.
Using tile38-benchmark and the -P flag it's possible to see 2x-10x boost
in requests per second.
JSET key id path value [RAW]
JGET key id path [RAW]
JDEL key id path
Allows for working with JSON strings, for example:
JSET user 901 name Tom
JGET user 901
> '{"name":"Tom"}'
JSET user 901 name.first Tom
JSET user 901 name.last Anderson
> '{"name":{"first":"Tom","last":"Anderson"}'
JDEL user 901 name.last
> '{"name":{"first":"Tom"}'
All commands use the GJSON path syntax, for more information:
Setting JSON: https://github.com/tidwall/sjson
Getting JSON: https://github.com/tidwall/gjson
tidwall