Skip to main content

Improving TileDrawer rendering speed

I have been playing with TileDrawer recently. After a first rapid successful test on a throw-away EC2 instance I decided to deploy one on a vm for intranet use.

The installation process is pretty straightforward, just run the script copied from the TileDrawer page as root. FYI make sure you have installed curl and python-cssutils before launching the script.

After the script completed I started browsing the map and noticed that tiles took a looong time to render.
A look at top from the server console showed that postgres was hogging the cpu. Memory was fine with no signs of swapping (it is a 1GB instance which I promptly upgraded to 2, running on server class hardware with Xeon CPU). Even after the memory upgrade tile rendering was so slow that the browser would sometime give up and show a white tile.

I decided to look into it a little further and started by using the technique I have already described in another article. The database cache looked fine though as most relationships were completely cached and database size is a measly 300MB which is no problem at all as the postgres param shared_buffers was already set to 512MB.

I then decided to enable slow queries logging (scroll down to 18.8.2) in postgresql.conf:

log_min_duration_statement = 100

I started with a threshold of 100ms, which means pg will log all queries that take more than 100ms to complete. The log quickly filled with lots of queries. Armed with patience I started indexing all the obvious fields like landuse, z_order, amenity, etc.

Eventually I used EXPLAIN on a frequent query that was well above 500ms and to my surprise found out that the planet_osm_polygon table was missing the spatial index on the way geometry. After the index was created no long queries were logged at all and tile rendering was snappy enough to not require cache seeding.

The complete list of all indexes I have created on the database planet_osm (copy and paste):

create index planet_osm_polygon_landuse_idx on planet_osm_polygon(landuse);
create index planet_osm_polygon_x_idx on planet_osm_polygon(z_order);
create index planet_osm_line_highway_idx on planet_osm_line(highway);
create index planet_osm_polygon_amenity_idx on planet_osm_polygon(amenity);
create index planet_osm_line_waterway_idx on planet_osm_line(waterway);
create index planet_osm_poly_building_idx on planet_osm_polygon(building);
create index planet_osm_poly_wayarea_idx on planet_osm_polygon(way_area);
create index planet_osm_poly_natural_idx on planet_osm_polygon("natural");
create index planet_osm_poly_buildingnn_idx on planet_osm_polygon(building) where (building is not null);
create index planet_osm_poly_way_idx on planet_osm_polygon using gist(way);


Comments

Popular posts from this blog

Indexing Apache access logs with ELK (Elasticsearch+Logstash+Kibana)

Who said that grepping Apache logs has to be boring?

The truth is that, as Enteprise applications move to the browser too, Apache access logs are a gold mine, it does not matter what your role is: developer, support or sysadmin. If you are not mining them you are most likely missing out a ton of information and, probably, making the wrong decisions.
ELK (Elasticsearch, Logstash, Kibana) is a terrific, Open Source stack for visually analyzing Apache (or nginx) logs (but also any other timestamped data).

From 0 to ZFS replication in 5m with syncoid

The ZFS filesystem has many features that once you try them you can never go back. One of the lesser known is probably the support for replicating a zfs filesystem by sending the changes over the network with zfs send/receive.
Technically the filesystem changes don't even need to be sent over a network: you could as well dump them on a removable disk, then receive  from the same removable disk.

Mirth: recover space when mirthdb grows out of control

I was recently asked to recover a mirth instance whose embedded database had grown to fill all available space so this is just a note-to-self kind of post.
Btw: the recovery, depending on db size and disk speed, is going to take long.

The problem A 1.8 Mirth Connect instance was started, then forgotten (well neglected, actually). The user also forgot to setup pruning so the messages filled the embedded Derby database until it grew to fill all the available space on the disk. The SO is linux.

The solution First of all: free some disk space so that the database can be started in embedded mode from the cli. You can also copy the whole mirth install to another server if you cannot free space. Depending on db size you will need a corresponding amount of space: in my case a 5GB db required around 2GB to start, process logs and then store the temp files during shrinking.

Then open a shell as the user that mirth runs as (you're not running it as root, are you?) and cd into the mirth home. …