ELM-Python-Client
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oslcquery speed up large --percontribution querying by parallelising query with processing of results from previous query
One example doing counting of artifacts/module in a very large GC project with 1253 contributions containing 25886 modules and total of 6722401 bindings was spending about 50% of the time processing results, sequentially with the queries; if the processing can be done in parallel with the next query that's a significant speedup. Probably doesn't need anything more fancy/complicated than processing in parallel with the next query, but I suppose some more speedup might be possible with a controlled number of queries in parallel, at the cost of server load.
-q rdm_types:ArtifactFormat=jazz_rm:Module -s oslc_rm:uses,dcterms:title,dcterms:identifier