Claus Stadler created JENA-2309:
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             Summary: Enhancing Riot for Big Data
                 Key: JENA-2309
                 URL: https://issues.apache.org/jira/browse/JENA-2309
             Project: Apache Jena
          Issue Type: Improvement
          Components: RIOT
    Affects Versions: Jena 4.5.0
            Reporter: Claus Stadler


We have successfully managed to adapt Jena Riot to quite efficiently work 
within Apache Spark, however we needed to make certain adaption that rely on 
brittle reflection hacks and APIs that are marked for removal (namely 
PipedRDFIterator):

In principle, for writing RDF data out, we implemented a mapPartition operation 
that maps the input RDF to lines of text via StreamRDF which is understood by 
apache spark's RDD.saveAsText();
 
However, for use with Big Data we need to
* disable blank node relabeling
* preconfigure the StreamRDF with a given set of prefixes (that is broadcasted 
to each node)

Furthermore
* The default PrefixMapping implementation is very inefficient when it comes to 
handling a dump of prefix.cc. I am using 2500 prefixes. Each RDF term in the 
output results in a scan of the full prefix map
* Even if the PrefixMapping is optimized, the recently added PrefixMap adapter 
again does scanning - and its a final class so no easy override.

And finally, we have a use case to allow for relative IRIs in the RDF: We are 
creating DCAT catalogs from directory content as in this file:

DCAT catalog with relative IRIs over directory content: [work-in-progress 
example|https://hobbitdata.informatik.uni-leipzig.de/lsqv2/dumps/dcat.trig]

If you retrieve the file with a semantic web client (riot, rapper, etc) it will 
automatically use the download location as the base url and thus giving 
absolute URLs to the published artifacts - regardless under which URL that 
directory is hosted.

*IRIxResolver: We rely on IRIProviderJDK which states "do not use in 
production" however it is the only one the let us achieve the goal. [our 
code|https://github.com/Scaseco/jenax/blob/dd51ef9a39013d4ddbb4806fcad36b03a4dbaa7c/jenax-arq-parent/jenax-arq-utils/src/main/java/org/aksw/jenax/arq/util/irixresolver/IRIxResolverUtils.java#L30]
* Prologue: We use reflection to set the resolver and would like the 
setResolver method [our 
code|https://github.com/Scaseco/jenax/blob/dd51ef9a39013d4ddbb4806fcad36b03a4dbaa7c/jenax-arq-parent/jenax-arq-utils/src/main/java/org/aksw/jenax/arq/util/prologue/PrologueUtils.java#L65]
* WriterStreamRDFBase: We need to be able to create instances of 
WriterStreamRDF classes which we can configure with our own PrefixMap instance 
(e.g. trie-backed), and our own LabelToNode stragegy ("asGiven") - [our 
code|https://github.com/SANSA-Stack/SANSA-Stack/blob/40fa6f89f421eee22c9789973ec828ec3f970c33/sansa-spark-jena-java/src/main/java/net/sansa_stack/spark/io/rdf/output/RddRdfWriter.java#L387]
* PrefixMapAdapter: We need an adapter that inherits the performance 
characteristics of the backing PrefixMapping [our 
code|https://github.com/Scaseco/jenax/blob/dd51ef9a39013d4ddbb4806fcad36b03a4dbaa7c/jenax-arq-parent/jenax-arq-utils/src/main/java/org/aksw/jenax/arq/util/prefix/PrefixMapAdapter.java#L57]
* PrefixMapping: We need a trie-based implementation for efficiency. We created 
one based on the trie class in jena which on initial experiments was 
sufficiently fast. Though we did not benchmark whether e.g. PatriciaTrie from 
commons collection would be faster. [our 
code|https://github.com/Scaseco/jenax/blob/dd51ef9a39013d4ddbb4806fcad36b03a4dbaa7c/jenax-arq-parent/jenax-arq-utils/src/main/java/org/aksw/jenax/arq/util/prefix/PrefixMappingTrie.java#L27]
With PrefixMapTrie the profiler showed that the amout of time spent on 
abbreviate went from ~100% to 1% - though not totally sure about standard 
conformance here.
* PipedRDFIterator / AsyncParser: We can read trig as a Splittable format 
(which is pretty cool) - however this requires being able to start and stop the 
RDF parser at will for probing. In other words, AsyncParser needs to return 
ClosableIterators whose close method actually stops the parsing thread. Also 
when scanning for prefixes we want to be able to create rules such as "as long 
as the parser emits a prefix with less than e.g. 100 non-prefix events in 
between keep looking for prefixes" - AsyncParser has the API for it with 
EltStreamRDF but it is private.

For future-proofness  we'd have these use cases to be reflected in jena.
Because we have sorted all the above issues mostly out and I'd  prefer to 
address these things with only a one or a few PRs (well maybe the 
ClosableIterators on AsyncParsers would be more work - because our code only 
did that for PipedRDFIterator).




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