lakesuperior_legacy

LAKEsuperior

LAKEsuperior is an alternative Fedora Repository implementation.

Guiding Principles

LAKEsuperior aims at being an uncomplicated, efficient Fedora 4 implementation.

Its main goals are:

• Reliability: Based on solid technologies with stability in mind.
• Efficiency: Small memory and CPU footprint, high scalability.
• Ease of management: Tools to perform monitoring and maintenance included.
• Simplicity of design: Straight-forward architecture, robustness over features.

Key features

• Drop-in replacement for Fedora4 (with some caveats); currently being tested with Hyrax 2
• Very stable persistence layer based on LMDB and filesystem. Fully ACID-compliant writes guarantee consistency of data.
• Term-based search (planned) and SPARQL Query API + UI
• No performance penalty for storing many resources under the same container; no kudzu pairtree segmentation ¹
• Extensible provenance metadata tracking
• Multi-modal access: HTTP (REST), command line interface and native Python API.
• Fits in a pocket: you can carry 50M triples in an 8Gb memory stick.

Implementation of the official Fedora API specs (Fedora 5.x and beyond) is not foreseen in the short term, however it would be a natural evolution of this project if it gains support.

Please make sure you read the Delta document for divergences with the official Fedora4 implementation.

Target Audience

LAKEsuperior is for anybody who cares about preserving data in the long term.

Less vaguely, LAKEsuperior is targeted at who needs to store large quantities of highly linked metadata and documents.

Its Python/C environment and API make it particularly well suited for academic and scientific environments who would be able to embed it in a Python application as a library or extend it via plug-ins.

LAKEsuperior is able to be exposed to the Web as a Linked Data Platform server. It also acts as a SPARQL query (read-only) endpoint, however it is not meant to be used as a full-fledged triplestore at the moment.

In its current status, LAKEsuperior is aimed at developers and hands-on managers who are interested in evaluating this project.

Quick Install: Running in Docker

You can run LAKEsuperior in Docker for a hands-off quickstart.

Docker is a containerization platform that allows you to run services in lightweight virtual machine environments without having to worry about installing all of the prerequisites on your host machine.

1. Install the correct Docker Community Edition for your operating system.
2. Clone this repo: git clone https://github.com/scossu/lakesuperior.git
3. cd into repo folder
4. Run docker-compose up

LAKEsuperior should now be available at http://localhost:8000/.

The provided Docker configuration includes persistent storage as a self-container Docker volume, meaning your data will persist between runs. If you want to clear the decks, simply run docker-compose down -v.

Manual Install (a bit less quick, a bit more power)

Note: These instructions have been tested on Linux. They may work on Darwin with little modification, and possibly on Windows with some modifications. Feedback is welcome.

Dependencies

1. Python 3.5 or greater.
2. A message broker supporting the STOMP protocol. For testing and evaluation purposes, CoilMQ is included with the dependencies and should be automatically installed.

Installation steps

1. Create a virtualenv in a project folder: virtualenv -p <python 3.5+ exec path> <virtualenv folder>
2. Activate the virtualenv: source <path_to_virtualenv>/bin/activate
3. Clone this repo: git clone https://github.com/scossu/lakesuperior.git
4. cd into repo folder
5. Install dependencies: pip install -r requirements.txt
6. Start your STOMP broker, e.g.: coilmq &. If you have another queue manager listening to port 61613 you can either configure a different port on the application configuration, or use the existing message queue.
7. Run ./lsup-admin bootstrap to initialize the binary and graph stores
8. Run ./fcrepo.

Configuration

The app should run for testing and evaluation purposes without any further configuration. All the application data are stored by default in the data directory.

To change the default configuration you should:

1. Copy the etc.skeleton folder to a separate location
2. Set the configuration folder location in the environment: export FCREPO_CONFIG_DIR=<your config dir location> (you can add this line at the end of your virtualenv activate script)
3. Configure the application
4. Bootstrap the app or copy the original data folders to the new location if any loction options changed
5. (Re)start the server: ./fcrepo

The configuration options are documented in the files.

Note: test.yml must specify a different location for the graph and for the binary stores than the default one, otherwise running a test suite will destroy your main data store. The application will issue an error message and refuse to start if these locations overlap.

Production deployment

If you like fried repositories for lunch, deploy before 11AM.

Status and development

LAKEsuperior is in alpha status. Please see the project issues list for a rudimentary road map.

Contributing

This has been so far a single person's off-hours project (with much input from several sides). In order to turn into anything close to a Beta release and eventually to a production-ready implementation, it needs some community love.

Contributions are welcome in all forms, including ideas, issue reports, or even just spinning up the software and providing some feedback. LAKEsuperior is meant to live as a community project.

Technical documentation

Architecture Overview

Content Model

Messaging

Migration, Backup & Restore

Command-Line Reference

Storage Implementation

Performance Benchmarks

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1 However if your client splits pairtrees upstream, such as Hyrax does, that obviously needs to change to get rid of the path segments. ↩