#2. Apply the karma Model outputRDD = workflow.run_karma(inputRDD, "https://raw.githubusercontent.com/american-art/npg/master/NPGConstituents/NPGConstituents-model.ttl", "http://americanartcollaborative.org/npg/", "http://www.cidoc-crm.org/cidoc-crm/E39_Actor1", "https://raw.githubusercontent.com/american-art/aac-alignment/master/karma-context.json", num_partitions=numPartitions, data_type="csv", additional_settings={"karma.input.delimiter":","}) #3. Save the output # fileUtil.save_file(outputRDD, outputFilename, "text", "json") #4. Reduce rdds reducedRDD = workflow.reduce_rdds(numFramerPartitions, outputRDD) reducedRDD.persist() types = [ {"name": "E39_Actor", "uri": "http://www.cidoc-crm.org/cidoc-crm/E39_Actor"}, {"name": "E82_Actor_Appellation", "uri": "http://www.cidoc-crm.org/cidoc-crm/E82_Actor_Appellation"}, {"name": "E67_Birth", "uri": "http://www.cidoc-crm.org/cidoc-crm/E67_Birth"}, {"name": "E69_Death", "uri": "http://www.cidoc-crm.org/cidoc-crm/E69_Death"}, {"name": "E52_Time-Span", "uri": "http://www.cidoc-crm.org/cidoc-crm/E52_Time-Span"} ] frames = [ {"name": "npgConstituents", "url": "https://raw.githubusercontent.com/american-art/aac-alignment/master/frames/npgConsitituents.json-ld"} ] type_to_rdd_json = workflow.apply_partition_on_types(reducedRDD, types)
inputRDD = workflow.batch_read_csv(inputFilename) #2. Apply the karma Model outputRDD = workflow.run_karma( inputRDD, "https://raw.githubusercontent.com/american-art/npg/master/NPGConstituents/NPGConstituents-model.ttl", "http://dig.isi.edu/npgConstituents/", "http://www.cidoc-crm.org/cidoc-crm/E39_Actor1", "https://raw.githubusercontent.com/american-art/aac-alignment/master/karma-context.json", data_type="csv", additional_settings={"karma.input.delimiter": ","}) #3. Save the output # fileUtil.save_file(outputRDD, outputFilename, "text", "json") reducedRDD = workflow.reduce_rdds(outputRDD) reducedRDD.persist() types = [{ "name": "E39_Actor", "uri": "http://www.cidoc-crm.org/cidoc-crm/E39_Actor" }, { "name": "E82_Actor_Appellation", "uri": "http://www.cidoc-crm.org/cidoc-crm/E82_Actor_Appellation" }, { "name": "E67_Birth", "uri": "http://www.cidoc-crm.org/cidoc-crm/E67_Birth" }, { "name": "E69_Death", "uri": "http://www.cidoc-crm.org/cidoc-crm/E69_Death" }, { "name": "E52_Time-Span",
# inputRDD = workflow.batch_read_csv(inputFilename) #2. Apply the karma Model outputRDD = workflow.run_karma(inputRDD, "https://raw.githubusercontent.com/american-art/autry/master/AutryMakers/AutryMakers-model.ttl", "http://dig.isi.edu/AutryMakers/", "http://www.cidoc-crm.org/cidoc-crm/E22_Man-Made_Object1", "https://raw.githubusercontent.com/american-art/aac-alignment/master/karma-context.json", data_type="csv", additional_settings={"karma.input.delimiter":","}) #3. Save the output # fileUtil.save_file(outputRDD, outputFilename, "text", "json") reducedRDD = workflow.reduce_rdds(outputRDD) reducedRDD.persist() types = [ {"name": "E82_Actor_Appellation", "uri": "http://www.cidoc-crm.org/cidoc-crm/E82_Actor_Appellation"} ] frames = [ {"name": "AutryMakers", "url": "https://raw.githubusercontent.com/american-art/aac-alignment/master/frames/autryMakers.json-ld"} ] context = workflow.read_json_file(contextUrl) framer_output = workflow.apply_framer(reducedRDD, types, frames) for frame_name in framer_output: outputRDD = workflow.apply_context(framer_output[frame_name], context, contextUrl) #apply mapValues function outputRDD_after = outputRDD.mapValues(mapFunc)