mirror of
https://github.com/pgpointcloud/pointcloud.git
synced 2025-12-08 20:36:04 +00:00
58 lines
2.1 KiB
ReStructuredText
58 lines
2.1 KiB
ReStructuredText
.. _faq:
|
|
|
|
******************************************************************************
|
|
FAQ
|
|
******************************************************************************
|
|
|
|
**What can be done with pgPointcloud?**
|
|
|
|
- pgPointcloud offers a way to efficiently store points in a postgres
|
|
database. In fact, pgpPointCloud stores groups of points (``pcPoints``)
|
|
called ``pcPatch`` storing groups of point allows efficient compression of
|
|
data. This patch have a bounding box which can be used by PostGIS spatial
|
|
features to greatly accelerate queries. pgPointcloud allows then to
|
|
efficiently query very big point cloud. Querying can be done using spatial
|
|
criteria (which points are in this area), as well as point attributes
|
|
criteria (which points have a value of this attribute between .. and ...
|
|
?).
|
|
|
|
- The point cloud being in a server, they can be used for processing or
|
|
visualization, or streamed.
|
|
|
|
|
|
|
|
|
**Why use pgPointcloud to store Lidar points into postgreSQL and not in point cloud files?**
|
|
|
|
The traditional way of storing point cloud is using several files containing
|
|
each a part of the point cloud. This has some severe limitations:
|
|
|
|
- Not efficient data query (to get a few points, you need to read the whole file)
|
|
- No concurrency (only one user can modify points at a time/read points at
|
|
a time)
|
|
- Files tends to get duplicated a lot (each worker has it's own private
|
|
version) no security of data ( file could be corrupted by a processing,
|
|
hard to manage who access what)
|
|
- Hard to use several different point cloud at the same time
|
|
- Hard to use point cloud with other spatial data (vector, raster, images)
|
|
|
|
pgPointcloud solves all of this problem, at a very low cost: you have to use a
|
|
DBMS.
|
|
|
|
|
|
|
|
|
**Does pgPointcloud scale?**
|
|
|
|
pgPointcloud is a young project, yet it has been proven to work fast (1ms query
|
|
time) with a 5 billions points cloud.
|
|
|
|
Currently pgPointcloud is fast for:
|
|
|
|
- Load data into DB
|
|
- Automatically compress data
|
|
- Query patches based on spatial or other attributes
|
|
|
|
It is slow for:
|
|
|
|
- Data output (100k pts/sec)
|
|
- In base conversion (no functions)
|