LinkedPipes ETL is an RDF based, lightweight ETL tool.
docker compose
is supported by modern versions of Docker You can run LP-ETL in Docker, or build it from the source.
To start LP-ETL you can use:
git clone https://github.com/linkedpipes/etl.git
cd etl
docker compose up
This would use pre-build images stored at GitHub Packages. The images are build from the main branch.
Alternatively you can use one liner.
For example to run LP-ETL from develop
branch on http://localhost:9080
use can use following command:
curl https://raw.githubusercontent.com/linkedpipes/etl/develop/docker-compose.yml | LP_ETL_PORT=9080 LP_VERSION=develop docker-compose -f - up
You may need to run the docker
command as sudo
or be in the docker
group.
You can build LP-ETL images your self. Note that on Windows, there is an issue with buildkit. See the temporary workaround.
Environment variables:
LP_VERSION
- default value main
, determine the version of Docker images.LP_ETL_DOMAIN
- The URL of the instance, this is used instead of the domain.uri
from the configuration. LP_ETL_PORT
- Specify port mapping for frontend, this is where you can connect to your instance.
This does NOT have to be the same as port in LP_ETL_DOMAIN
in case of reverse-proxying.docker compose
utilizes several volumes that can be used to access/provide data.
See docker-compose.yml
comments for examples and configuration.
You may want to create your own docker-compose.yml
for custom configuration.
$ git clone https://github.com/linkedpipes/etl.git
$ cd etl
$ mvn install
The configuration file deploy/configuration.properties
can be edited, mainly changing paths to working, storage, log and library directories.
$ cd deploy
$ ./executor.sh >> executor.log &
$ ./executor-monitor.sh >> executor-monitor.log &
$ ./storage.sh >> storage.log &
$ ./frontend.sh >> frontend.log &
See example service files in the deploy/systemd
folder.
Note that it is also possible to use Bash on Ubuntu on Windows or Cygwin and proceed as with Linux.
git clone https://github.com/linkedpipes/etl.git
cd etl
mvn install
The configuration file deploy/configuration.properties
can be edited, mainly changing paths to working, storage, log and library directories.
In the deploy
folder, run
executor.bat
executor-monitor.bat
storage.bat
frontend.bat
You can copy pipelines and templates data from one instance to another directly.
Assume that you have copy of a data directory ./data-source
with pipelines
and templates
subdirectories.
You can obtain the directory from any running instance, you can even merge content of multiple of those directories together.
In the next step you would like to import the data into a new instance.
You can just copy the files to respective directories under ./data-target
.
Keep in mind that this would preserve the IRIs.
Should you need to change the IRIs, you should employ import and export functionality available in the frontend.
The components live in the jars
directory.
If you need to create your own component, you can copy an existing component and change it.
Update note 5: 2019-09-03 breaking changes in the configuration file. Remove
/api/v1
from theexecutor-monitor.webserver.uri
, so it looks like:executor-monitor.webserver.uri = http://localhost:8081
. You can also removeexecutor.execution.uriPrefix
as the value is derived fromdomain.uri
.Update note 4: 2019-07-03 we changed the way frontend is run. If you do not use our script to run it, you need to update yours.
Update note 3: When upgrading from develop prior to 2017-02-14, you need to delete
{deploy}/jars
and{deploy}/osgi
.Update note 2: When upgrading from master prior to 2016-11-04, you need to move your pipelines folder from e.g.,
/data/lp/etl/pipelines
to/data/lp/etl/storage/pipelines
, update the configuration.properites file and possibly the update/restart scripts as there is a new component,storage
.Update note 1: When upgrading from master prior to 2016-04-07, you need to delete your old execution data (e.g., in /data/lp/etl/working/data)