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Command used:

[dspace]/bin/dspace stats-util

Java class:

org.dspace.statistics.util.StatisticsClient

Arguments (short and long forms):

Description

-s or --shard-solr-index

Splits the data in the main Solr core up into a separate solr core for each year, this .  This will upgrade the performance of the solrSolr.

Notes:

Yearly Solr sharding is a routine that can drastically improve the performance of your DSpace SOLR statistics. It was introduced in DSpace 3.0 and is not backwards compatible. The routine decreases the load created by the logging of new usage events by reducing the size of the SOLR Core in which new usage data are being logged. By running the script, you effectively split your current SOLR core, containing all of your usage events, into different SOLR cores that each contain the data for one year. In case your DSpace has been logging usage events for less than one year, you will see no notable performance improvements until you run the script after the start of a new year. Both writing new usage events as well as read operations should be more performant over several smaller SOLR Shards instead of one monolithic one.

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Technical implementation details

After sharding, the Solr data cores are located in the [dspace.dir]/solr directory. There is no need to define the location of each individual core in solr.xml because they are automatically retrieved at runtime. This retrieval happens in the static method located in the org.dspace.statistics.SolrLogger class. These cores are stored in the statisticYearCores list.  Each time a query is made to Solr, these cores are added as shards by the addAdditionalSolrYearCores method. The cores share a common configuration copied from your original statistics core. Therefore, no issues should be resulting from subsequent ant updates.

The actual sharding of the of the original Solr core into individual cores by year is done in the shardSolrIndex method in the org.dspace.statistics.SolrLogger class. The sharding is done by first running a facet on the time to get the facets split by year. Once we have our years from our logs we query the main Solr data server for all information on each year & download these as CSVs. When we have all data for one year, we upload it to the newly created core of that year by using the update csv handler. Once all data of one year have been uploaded, those data are removed from the main Solr (by doing it this way if our Solr crashes we do not need to start from scratch).

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Testing Solr Shards

Testing Solr Shards