Improving the Lifecycle Query Engine performance by compacting indexed data

Each time you index the data from your lifecycle management applications, the amount of space required to store that data increases. Over time, as the index files get larger and the amount of available hard disk space decreases, you might experience server performance issues. You can take steps to prevent this situation by monitoring the hard disk usage and, when required, compacting the indexed data.

Because disk space is not reclaimed when you delete data from the index, you should consider running a compaction any time you delete or reindex the data.

If you deployed Lifecycle Query Engine (LQE) across several nodes, you can select specific nodes for data compaction.

When you start to compact indexed data, the indexing service is turned off. You can, however, run queries while the data is being compacted. When the compacting process ends, the older index is replaced with the new compacted index.

During compaction, the indexed data is exported to N-Quads format, which is a line-based, plain text format for encoding an resource description framework (RDF) data set. For more information about the N-Quads format, see RDF N-Quads on the W3C website.