Halyard
Halyard is an extremely horizontally scalable triple store with support for named graphs, designed for integration of extremely large semantic data models and for storage and SPARQL 1.1 querying of complete Linked Data universe snapshots. Halyard implementation is based on Eclipse RDF4J framework and Apache HBase database, and it is completely written in Java.
Author: Adam Sotona
Discussion group: https://groups.google.com/d/forum/halyard-users
Documentation: https://merck.github.io/Halyard
Get started
Download and unzip the latest halyard-sdk-<version>.zip
bundle to a Apache Hadoop cluster node with configured Apache HBase client.
Halyard is expected to run on an Apache Hadoop cluster node with configured Apache HBase client. Apache Hadoop and Apache HBase components are not bundled with Halyard. The runtime requirements are:
- Apache Hadoop version 2.5.1 or higher
- Apache HBase version 1.1.2 or higher
- Java 8 Runtime
Note: Recommended Apache Hadoop distribution is the latest version of Hortonworks Data Platform (HDP) or Amazon Elastic Map Reduce (EMR).
See Documentation for usage examples, architecture information, and more.
Repository contents
common
- a library for direct mapping between an RDF data model and Apache HBasestrategy
- a generic parallel asynchronous implementation of RDF4J Evaluation Strategysail
- an implementation of the RDF4J Storage and Inference Layer on top of Apache HBasetools
- a set of command line and Apache Hadoop MapReduce tools for loading, updating, querying, and exporting the data with maximum performancesdk
- a distributable bundle of Eclipse RDF4J and Halyard for command line use on an Apache Hadoop cluster with configured HBasewebapps
- a re-distribution of Eclipse RDF4J Web Applications (RDF4J-Server and RDF4J-Workbench), patched and enhanced to include Halyard as another RDF repository option