ecognition/linux_js repository overview

⁠Trimble eCognition GRID Job Scheduler for Linux

Trimble eCognition software is used by GIS professionals, remote sensing experts & data scientists to automate geospatial data analytics. Users can design feature extraction solutions to transform geo-data into geo-information.

Trimble eCognition GRID consists of these components:

• Engine Server (ecognition/linux_es⁠ or ecognition/win_es⁠)
• Job Scheduler
• Command-line tools. For job submitting, monitoring and etc. (ecognition/linux_cle⁠ or ecognition/win_cle⁠)

You should only use eCognition GRID if your rule set is using one of the following process algorithms:

• submit scenes for analysis
• read subscene statistics
• create scene copy
• create scene subset
• create scene tiles
• delete scenes In all other cases, eCognition Command-line Engine should be enough.(ecognition/linux_cle⁠ or ecognition/win_cle⁠)

The Linux version of Docker image for Trimble eCognition JobScheduler. You will need a valid Trimble eCognition Server license to run it.

⁠Prerequisite

This component is managing the job queue processed by Engine Server component. You will only need one instance of this component and it should be accessible to all Engine Server components by exposing port 8184 on it.

To use the eCognition Job Scheduler requires at least one valid eCognition Server license and the latest eCognition License Server⁠.

Note: If License Server is running on a different machine than container, you will need to make sure license server ports (default: 27000-27009) and vendor daemon (random by default) are open. You can set those ports via license server admin console using your favorite browser: http://[LicenseServer IP address]:8090 (or http://localhost:8090⁠ from within License Server machine). in Administration tab you can set those in "Vendor Daemon Configuration" and "Server Configuration" sections.

⁠Run

Job Scheduler is managing jobs for processing by Engine Server. You will only need one container instance per GRID. By default, it listens to TCP port 8184, you will need to to expose this port to other eCognition GRID components. Here is a sample command to run it:

docker pull ecognition/linux_js:10.5.0
docker run --rm -d --name ecog_linux_js -p 8184:8184/tcp --ip=172.28.5.1 -e LM_LICENSE_FILE=@myLicenseIP --network=grid_network -m 8g --cpus=2 ecognition/linux_js:10.5.0

The above example assumes network grid_network being available. You can create it with command like this:

docker network create -d bridge --subnet=172.28.0.0/16 --gateway=172.28.5.254 grid_network

Job Scheduler is using file-based database for managing jobs, to make database permanent you can place it on a shared volume by explicitly specifying database path via environment variables:

docker run .... -e ECOG_CONFIG_DiaJobScheduler_general="database folder=/myFolder;database file prefix=myPrefix"

Optionally, you may want to mount shared folder for data sharing and explicit log file path and detail level, by adding these parameters to docker run command:

-v /myShare:/mnt -e ECOG_CONFIG_logging="log path=/mnt/logs;trace level=Detailed"

Once running, you can connect to web interface of Job Scheduler by following its IP address and exposed port in your favorite browser (for example, http://localhost:8184⁠ on a host machine).

Note: It is recommended to give at least 4GB of RAM for container as it might be resource intensive (docker -m 4GB .. will do it)

⁠Configuration via environment

While running container any configuration setting (found in config/eCognition.cfg) can be set via environment variable use the following notation: ECOG_CONFIG_{config-group}="key1=value1;key2=value2;.."

for example, to set log file location and trace level (this overrides appropriate <logging> values in eCognition.cfg):

docker run -it -e ECOG_CONFIG_logging="log path=/mnt/logs;trace level=Detailed" ...