Merge branch 'master' of https://code-repo.d4science.org/D-Net/dnet-hadoop
This commit is contained in:
commit
27e96767e0
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@ -62,7 +62,7 @@ object SparkGenerateDoiBoost {
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val orcidPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/orcidPublication").as[Publication].map(p => (p.getId, p))
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fj.joinWith(orcidPublication, fj("_1").equalTo(orcidPublication("_1")), "left").map(applyMerge).write.mode(SaveMode.Overwrite).save(s"$workingDirPath/secondJoin")
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logger.info("Phase 3) Join Result with MAG")
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logger.info("Phase 4) Join Result with MAG")
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val sj: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/secondJoin").as[Publication].map(p => (p.getId, p))
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val magPublication: Dataset[(String, Publication)] = spark.read.load(s"$workingDirPath/magPublication").as[Publication].map(p => (p.getId, p))
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@ -21,15 +21,17 @@ object SparkImportMagIntoDataset {
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val stream = Map(
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"Affiliations" -> Tuple2("mag/Affiliations.txt", Seq("AffiliationId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "GridId:string", "OfficialPage:string", "WikiPage:string", "PaperCount:long", "CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
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"Authors" -> Tuple2("mag/Authors.txt", Seq("AuthorId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "LastKnownAffiliationId:long?", "PaperCount:long", "CitationCount:long", "CreatedDate:DateTime")),
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"ConferenceInstances" -> Tuple2("mag/ConferenceInstances.txt", Seq("ConferenceInstanceId:long", "NormalizedName:string", "DisplayName:string", "ConferenceSeriesId:long", "Location:string", "OfficialUrl:string", "StartDate:DateTime?", "EndDate:DateTime?", "AbstractRegistrationDate:DateTime?", "SubmissionDeadlineDate:DateTime?", "NotificationDueDate:DateTime?", "FinalVersionDueDate:DateTime?", "PaperCount:long", "CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
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"Affiliations" -> Tuple2("mag/Affiliations.txt", Seq("AffiliationId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "GridId:string", "OfficialPage:string", "WikiPage:string", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "Iso3166Code:string", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
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"AuthorExtendedAttributes" -> Tuple2("mag/AuthorExtendedAttributes.txt", Seq("AuthorId:long", "AttributeType:int", "AttributeValue:string")),
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"Authors" -> Tuple2("mag/Authors.txt", Seq("AuthorId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "LastKnownAffiliationId:long?", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "CreatedDate:DateTime")),
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"ConferenceInstances" -> Tuple2("mag/ConferenceInstances.txt", Seq("ConferenceInstanceId:long", "NormalizedName:string", "DisplayName:string", "ConferenceSeriesId:long", "Location:string", "OfficialUrl:string", "StartDate:DateTime?", "EndDate:DateTime?", "AbstractRegistrationDate:DateTime?", "SubmissionDeadlineDate:DateTime?", "NotificationDueDate:DateTime?", "FinalVersionDueDate:DateTime?", "PaperCount:long", "PaperFamilyCount:long" ,"CitationCount:long", "Latitude:float?", "Longitude:float?", "CreatedDate:DateTime")),
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"ConferenceSeries" -> Tuple2("mag/ConferenceSeries.txt", Seq("ConferenceSeriesId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "PaperCount:long", "CitationCount:long", "CreatedDate:DateTime")),
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"EntityRelatedEntities" -> Tuple2("advanced/EntityRelatedEntities.txt", Seq("EntityId:long", "EntityType:string", "RelatedEntityId:long", "RelatedEntityType:string", "RelatedType:int", "Score:float")),
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"FieldOfStudyChildren" -> Tuple2("advanced/FieldOfStudyChildren.txt", Seq("FieldOfStudyId:long", "ChildFieldOfStudyId:long")),
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"FieldOfStudyExtendedAttributes" -> Tuple2("advanced/FieldOfStudyExtendedAttributes.txt", Seq("FieldOfStudyId:long", "AttributeType:int", "AttributeValue:string")),
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"FieldsOfStudy" -> Tuple2("advanced/FieldsOfStudy.txt", Seq("FieldOfStudyId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "MainType:string", "Level:int", "PaperCount:long", "CitationCount:long", "CreatedDate:DateTime")),
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"Journals" -> Tuple2("mag/Journals.txt", Seq("JournalId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "Issn:string", "Publisher:string", "Webpage:string", "PaperCount:long", "CitationCount:long", "CreatedDate:DateTime")),
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// ['FieldOfStudyId:long', 'Rank:uint', 'NormalizedName:string', 'DisplayName:string', 'MainType:string', 'Level:int', 'PaperCount:long', 'PaperFamilyCount:long', 'CitationCount:long', 'CreatedDate:DateTime']
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"FieldsOfStudy" -> Tuple2("advanced/FieldsOfStudy.txt", Seq("FieldOfStudyId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "MainType:string", "Level:int", "PaperCount:long", "PaperFamilyCount:long", "CitationCount:long", "CreatedDate:DateTime")),
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"Journals" -> Tuple2("mag/Journals.txt", Seq("JournalId:long", "Rank:uint", "NormalizedName:string", "DisplayName:string", "Issn:string", "Publisher:string", "Webpage:string", "PaperCount:long", "PaperFamilyCount:long" ,"CitationCount:long", "CreatedDate:DateTime")),
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"PaperAbstractsInvertedIndex" -> Tuple2("nlp/PaperAbstractsInvertedIndex.txt.*", Seq("PaperId:long", "IndexedAbstract:string")),
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"PaperAuthorAffiliations" -> Tuple2("mag/PaperAuthorAffiliations.txt", Seq("PaperId:long", "AuthorId:long", "AffiliationId:long?", "AuthorSequenceNumber:uint", "OriginalAuthor:string", "OriginalAffiliation:string")),
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"PaperCitationContexts" -> Tuple2("nlp/PaperCitationContexts.txt", Seq("PaperId:long", "PaperReferenceId:long", "CitationContext:string")),
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@ -39,7 +41,7 @@ object SparkImportMagIntoDataset {
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"PaperReferences" -> Tuple2("mag/PaperReferences.txt", Seq("PaperId:long", "PaperReferenceId:long")),
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"PaperResources" -> Tuple2("mag/PaperResources.txt", Seq("PaperId:long", "ResourceType:int", "ResourceUrl:string", "SourceUrl:string", "RelationshipType:int")),
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"PaperUrls" -> Tuple2("mag/PaperUrls.txt", Seq("PaperId:long", "SourceType:int?", "SourceUrl:string", "LanguageCode:string")),
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"Papers" -> Tuple2("mag/Papers.txt", Seq("PaperId:long", "Rank:uint", "Doi:string", "DocType:string", "PaperTitle:string", "OriginalTitle:string", "BookTitle:string", "Year:int?", "Date:DateTime?", "Publisher:string", "JournalId:long?", "ConferenceSeriesId:long?", "ConferenceInstanceId:long?", "Volume:string", "Issue:string", "FirstPage:string", "LastPage:string", "ReferenceCount:long", "CitationCount:long", "EstimatedCitation:long", "OriginalVenue:string", "FamilyId:long?", "CreatedDate:DateTime")),
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"Papers" -> Tuple2("mag/Papers.txt", Seq("PaperId:long", "Rank:uint", "Doi:string", "DocType:string", "PaperTitle:string", "OriginalTitle:string", "BookTitle:string", "Year:int?", "Date:DateTime?", "OnlineDate:DateTime?", "Publisher:string", "JournalId:long?", "ConferenceSeriesId:long?", "ConferenceInstanceId:long?", "Volume:string", "Issue:string", "FirstPage:string", "LastPage:string", "ReferenceCount:long", "CitationCount:long", "EstimatedCitation:long", "OriginalVenue:string", "FamilyId:long?", "FamilyRank:uint?", "CreatedDate:DateTime")),
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"RelatedFieldOfStudy" -> Tuple2("advanced/RelatedFieldOfStudy.txt", Seq("FieldOfStudyId1:long", "Type1:string", "FieldOfStudyId2:long", "Type2:string", "Rank:float"))
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)
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@ -26,12 +26,15 @@ object SparkPreProcessMAG {
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.master(parser.get("master")).getOrCreate()
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val sourcePath = parser.get("sourcePath")
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val workingPath = parser.get("workingPath")
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val targetPath = parser.get("targetPath")
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import spark.implicits._
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implicit val mapEncoderPubs: Encoder[Publication] = org.apache.spark.sql.Encoders.kryo[Publication]
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implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
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logger.info("Phase 1) make uninque DOI in Papers:")
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val d: Dataset[MagPapers] = spark.read.load(s"${parser.get("sourcePath")}/Papers").as[MagPapers]
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val d: Dataset[MagPapers] = spark.read.load(s"$sourcePath/Papers").as[MagPapers]
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// Filtering Papers with DOI, and since for the same DOI we have multiple version of item with different PapersId we get the last one
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val result: RDD[MagPapers] = d.where(col("Doi").isNotNull)
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@ -41,11 +44,12 @@ object SparkPreProcessMAG {
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.map(_._2)
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val distinctPaper: Dataset[MagPapers] = spark.createDataset(result)
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distinctPaper.write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/Papers_distinct")
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distinctPaper.write.mode(SaveMode.Overwrite).save(s"$workingPath/Papers_distinct")
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logger.info("Phase 0) Enrich Publication with description")
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val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
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pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
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val pa = spark.read.load(s"$sourcePath/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
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pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"$workingPath/PaperAbstract")
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logger.info("Phase 3) Group Author by PaperId")
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val authors = spark.read.load(s"$sourcePath/Authors").as[MagAuthor]
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@ -64,24 +68,24 @@ object SparkPreProcessMAG {
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} else
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mpa
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}).groupBy("PaperId").agg(collect_list(struct($"author", $"affiliation")).as("authors"))
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.write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_1_paper_authors")
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_1_paper_authors")
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logger.info("Phase 4) create First Version of publication Entity with Paper Journal and Authors")
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val journals = spark.read.load(s"$sourcePath/Journals").as[MagJournal]
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val papers = spark.read.load((s"${parser.get("targetPath")}/Papers_distinct")).as[MagPapers]
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val papers = spark.read.load((s"$workingPath/Papers_distinct")).as[MagPapers]
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val paperWithAuthors = spark.read.load(s"${parser.get("targetPath")}/merge_step_1_paper_authors").as[MagPaperWithAuthorList]
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val paperWithAuthors = spark.read.load(s"$workingPath/merge_step_1_paper_authors").as[MagPaperWithAuthorList]
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val firstJoin = papers.joinWith(journals, papers("JournalId").equalTo(journals("JournalId")), "left")
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firstJoin.joinWith(paperWithAuthors, firstJoin("_1.PaperId").equalTo(paperWithAuthors("PaperId")), "left")
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.map { a => ConversionUtil.createOAFFromJournalAuthorPaper(a) }
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.write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_2")
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.write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_2")
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var magPubs: Dataset[(String, Publication)] =
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spark.read.load(s"${parser.get("targetPath")}/merge_step_2").as[Publication]
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spark.read.load(s"$workingPath/merge_step_2").as[Publication]
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.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
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@ -95,10 +99,10 @@ object SparkPreProcessMAG {
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.map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
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.write
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.mode(SaveMode.Overwrite)
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.save(s"${parser.get("targetPath")}/merge_step_2_conference")
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.save(s"$workingPath/merge_step_2_conference")
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magPubs= spark.read.load(s"${parser.get("targetPath")}/merge_step_2_conference").as[Publication]
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magPubs= spark.read.load(s"$workingPath/merge_step_2_conference").as[Publication]
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.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
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val paperUrlDataset = spark.read.load(s"$sourcePath/PaperUrls").as[MagPaperUrl].groupBy("PaperId").agg(collect_list(struct("sourceUrl")).as("instances")).as[MagUrl]
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@ -108,27 +112,27 @@ object SparkPreProcessMAG {
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magPubs.joinWith(paperUrlDataset, col("_1").equalTo(paperUrlDataset("PaperId")), "left")
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.map { a: ((String, Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2)) }
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.write.mode(SaveMode.Overwrite)
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.save(s"${parser.get("targetPath")}/merge_step_3")
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.save(s"$workingPath/merge_step_3")
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// logger.info("Phase 6) Enrich Publication with description")
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// val pa = spark.read.load(s"${parser.get("sourcePath")}/PaperAbstractsInvertedIndex").as[MagPaperAbstract]
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// pa.map(ConversionUtil.transformPaperAbstract).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/PaperAbstract")
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val paperAbstract = spark.read.load((s"${parser.get("targetPath")}/PaperAbstract")).as[MagPaperAbstract]
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val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
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magPubs = spark.read.load(s"${parser.get("targetPath")}/merge_step_3").as[Publication]
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magPubs = spark.read.load(s"$workingPath/merge_step_3").as[Publication]
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.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
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magPubs.joinWith(paperAbstract, col("_1").equalTo(paperAbstract("PaperId")), "left")
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.map(item => ConversionUtil.updatePubsWithDescription(item)
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).write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/merge_step_4")
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).write.mode(SaveMode.Overwrite).save(s"$workingPath/merge_step_4")
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logger.info("Phase 7) Enrich Publication with FieldOfStudy")
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magPubs = spark.read.load(s"${parser.get("targetPath")}/merge_step_4").as[Publication]
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magPubs = spark.read.load(s"$workingPath/merge_step_4").as[Publication]
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.map(p => (ConversionUtil.extractMagIdentifier(p.getOriginalId.asScala), p)).as[(String, Publication)]
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val fos = spark.read.load(s"$sourcePath/FieldsOfStudy").select($"FieldOfStudyId".alias("fos"), $"DisplayName", $"MainType")
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@ -144,14 +148,14 @@ object SparkPreProcessMAG {
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.equalTo(paperField("PaperId")), "left")
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.map(item => ConversionUtil.updatePubsWithSubject(item))
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.write.mode(SaveMode.Overwrite)
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.save(s"${parser.get("targetPath")}/mag_publication")
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.save(s"$workingPath/mag_publication")
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val s:RDD[Publication] = spark.read.load(s"${parser.get("targetPath")}/mag_publication").as[Publication]
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val s:RDD[Publication] = spark.read.load(s"$workingPath/mag_publication").as[Publication]
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.map(p=>Tuple2(p.getId, p)).rdd.reduceByKey((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
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.map(_._2)
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spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"${parser.get("targetPath")}/mag_publication_u")
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spark.createDataset(s).as[Publication].write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
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}
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}
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@ -1,6 +1,7 @@
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package eu.dnetlib.doiboost.orcid
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import eu.dnetlib.dhp.schema.oaf.{Author, Publication}
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import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
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import eu.dnetlib.dhp.schema.orcid.OrcidDOI
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import eu.dnetlib.doiboost.DoiBoostMappingUtil
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import eu.dnetlib.doiboost.DoiBoostMappingUtil.{ORCID, PID_TYPES, createSP, generateDataInfo, generateIdentifier}
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import org.apache.commons.lang.StringUtils
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@ -43,16 +44,19 @@ object ORCIDToOAF {
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}
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def convertTOOAF(input:ORCIDElement) :Publication = {
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val doi = input.doi
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def convertTOOAF(input:OrcidDOI) :Publication = {
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val doi = input.getDoi
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val pub:Publication = new Publication
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pub.setPid(List(createSP(doi, "doi", PID_TYPES)).asJava)
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pub.setPid(List(createSP(doi.toLowerCase, "doi", PID_TYPES)).asJava)
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pub.setDataInfo(generateDataInfo())
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pub.setId(generateIdentifier(pub, doi.toLowerCase))
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try{
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pub.setAuthor(input.authors.map(a=> {
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generateAuthor(a.name, a.surname, a.creditName, a.oid)
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}).asJava)
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val l:List[Author]= input.getAuthors.asScala.map(a=> {
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generateAuthor(a.getName, a.getSurname, a.getCreditName, a.getOid)
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})(collection.breakOut)
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pub.setAuthor(l.asJava)
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pub.setCollectedfrom(List(DoiBoostMappingUtil.createORIDCollectedFrom()).asJava)
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pub.setDataInfo(DoiBoostMappingUtil.generateDataInfo())
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pub
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@ -63,6 +67,13 @@ object ORCIDToOAF {
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}
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}
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def generateOricPIDDatainfo():DataInfo = {
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val di =DoiBoostMappingUtil.generateDataInfo("0.91")
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di.getProvenanceaction.setClassid("sysimport:crosswalk:entityregistry")
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di.getProvenanceaction.setClassname("Harvested")
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di
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}
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def generateAuthor(given: String, family: String, fullName:String, orcid: String): Author = {
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val a = new Author
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a.setName(given)
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@ -72,7 +83,7 @@ object ORCIDToOAF {
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else
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a.setFullname(s"$given $family")
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if (StringUtils.isNotBlank(orcid))
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a.setPid(List(createSP(orcid, ORCID, PID_TYPES)).asJava)
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a.setPid(List(createSP(orcid, ORCID, PID_TYPES, generateOricPIDDatainfo())).asJava)
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a
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}
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|
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@ -1,21 +1,72 @@
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package eu.dnetlib.doiboost.orcid
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import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
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import eu.dnetlib.dhp.application.ArgumentApplicationParser
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import eu.dnetlib.dhp.oa.merge.AuthorMerger
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import eu.dnetlib.dhp.schema.oaf.Publication
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import eu.dnetlib.dhp.schema.orcid.OrcidDOI
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import eu.dnetlib.doiboost.mag.ConversionUtil
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import org.apache.commons.io.IOUtils
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import org.apache.spark.SparkConf
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import org.apache.spark.rdd.RDD
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import org.apache.spark.sql.expressions.Aggregator
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import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
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import org.slf4j.{Logger, LoggerFactory}
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object SparkConvertORCIDToOAF {
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val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
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def getPublicationAggregator(): Aggregator[(String, Publication), Publication, Publication] = new Aggregator[(String, Publication), Publication, Publication]{
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override def zero: Publication = new Publication()
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override def reduce(b: Publication, a: (String, Publication)): Publication = {
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b.mergeFrom(a._2)
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b.setAuthor(AuthorMerger.mergeAuthor(a._2.getAuthor, b.getAuthor))
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if (b.getId == null)
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b.setId(a._2.getId)
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b
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}
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override def merge(wx: Publication, wy: Publication): Publication = {
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wx.mergeFrom(wy)
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wx.setAuthor(AuthorMerger.mergeAuthor(wy.getAuthor, wx.getAuthor))
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if(wx.getId == null && wy.getId.nonEmpty)
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wx.setId(wy.getId)
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wx
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}
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override def finish(reduction: Publication): Publication = reduction
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override def bufferEncoder: Encoder[Publication] =
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Encoders.kryo(classOf[Publication])
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override def outputEncoder: Encoder[Publication] =
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Encoders.kryo(classOf[Publication])
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}
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|
||||
def run(spark:SparkSession,sourcePath:String, targetPath:String):Unit = {
|
||||
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
|
||||
implicit val mapOrcid: Encoder[OrcidDOI] = Encoders.kryo[OrcidDOI]
|
||||
implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
|
||||
|
||||
val mapper = new ObjectMapper()
|
||||
mapper.getDeserializationConfig.withFeatures(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES)
|
||||
|
||||
val dataset:Dataset[OrcidDOI] = spark.createDataset(spark.sparkContext.textFile(sourcePath).map(s => mapper.readValue(s,classOf[OrcidDOI])))
|
||||
|
||||
logger.info("Converting ORCID to OAF")
|
||||
dataset.map(o => ORCIDToOAF.convertTOOAF(o)).filter(p=>p!=null)
|
||||
.map(d => (d.getId, d))
|
||||
.groupByKey(_._1)(Encoders.STRING)
|
||||
.agg(getPublicationAggregator().toColumn)
|
||||
.map(p => p._2)
|
||||
.write.mode(SaveMode.Overwrite).save(targetPath)
|
||||
}
|
||||
|
||||
def main(args: Array[String]): Unit = {
|
||||
|
||||
val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
|
||||
|
||||
val conf: SparkConf = new SparkConf()
|
||||
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json")))
|
||||
parser.parseArgument(args)
|
||||
|
|
@ -26,19 +77,12 @@ object SparkConvertORCIDToOAF {
|
|||
.appName(getClass.getSimpleName)
|
||||
.master(parser.get("master")).getOrCreate()
|
||||
|
||||
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
|
||||
implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
|
||||
import spark.implicits._
|
||||
|
||||
|
||||
val sourcePath = parser.get("sourcePath")
|
||||
val targetPath = parser.get("targetPath")
|
||||
val dataset:Dataset[ORCIDElement] = spark.read.json(sourcePath).as[ORCIDElement]
|
||||
run(spark, sourcePath, targetPath)
|
||||
|
||||
|
||||
logger.info("Converting ORCID to OAF")
|
||||
val d:RDD[Publication] = dataset.map(o => ORCIDToOAF.convertTOOAF(o)).filter(p=>p!=null).map(p=>(p.getId,p)).rdd.reduceByKey(ConversionUtil.mergePublication)
|
||||
.map(_._2)
|
||||
|
||||
spark.createDataset(d).as[Publication].write.mode(SaveMode.Overwrite).save(targetPath)
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -39,14 +39,7 @@
|
|||
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
|
||||
<action name="ResetWorkingPath">
|
||||
<fs>
|
||||
<delete path='${workingDirPath}'/>
|
||||
<mkdir path='${workingDirPath}'/>
|
||||
</fs>
|
||||
<ok to="CreateDOIBoost"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
|
||||
<action name="CreateDOIBoost">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
|
|
|
|||
|
|
@ -8,6 +8,10 @@
|
|||
<name>targetPath</name>
|
||||
<description>the working dir base path</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>workingPath</name>
|
||||
<description>the working dir base path</description>
|
||||
</property>
|
||||
<property>
|
||||
<name>sparkDriverMemory</name>
|
||||
<description>memory for driver process</description>
|
||||
|
|
@ -31,10 +35,10 @@
|
|||
|
||||
<action name="ResetWorkingPath">
|
||||
<fs>
|
||||
<delete path='${targetPath}'/>
|
||||
<mkdir path='${targetPath}'/>
|
||||
<delete path='${workingPath}'/>
|
||||
<mkdir path='${workingPath}'/>
|
||||
</fs>
|
||||
<ok to="PreprocessMag"/>
|
||||
<ok to="ConvertMagToDataset"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
|
|
@ -52,10 +56,10 @@
|
|||
${sparkExtraOPT}
|
||||
</spark-opts>
|
||||
<arg>--sourcePath</arg><arg>${sourcePath}</arg>
|
||||
<arg>--targetPath</arg><arg>${targetPath}</arg>
|
||||
<arg>--targetPath</arg><arg>${workingPath}</arg>
|
||||
<arg>--master</arg><arg>yarn-cluster</arg>
|
||||
</spark>
|
||||
<ok to="End"/>
|
||||
<ok to="PreprocessMag"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
|
|
@ -65,7 +69,7 @@
|
|||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Convert Mag to Dataset</name>
|
||||
<name>Convert Mag to OAF Dataset</name>
|
||||
<class>eu.dnetlib.doiboost.mag.SparkPreProcessMAG</class>
|
||||
<jar>dhp-doiboost-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
|
|
@ -75,7 +79,8 @@
|
|||
--conf spark.sql.shuffle.partitions=3840
|
||||
${sparkExtraOPT}
|
||||
</spark-opts>
|
||||
<arg>--sourcePath</arg><arg>${sourcePath}</arg>
|
||||
<arg>--sourcePath</arg><arg>${workingPath}</arg>
|
||||
<arg>--workingPath</arg><arg>${workingPath}/process</arg>
|
||||
<arg>--targetPath</arg><arg>${targetPath}</arg>
|
||||
<arg>--master</arg><arg>yarn-cluster</arg>
|
||||
</spark>
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
[
|
||||
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the base path of MAG input", "paramRequired": true},
|
||||
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the working dir path", "paramRequired": true},
|
||||
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the target dir path", "paramRequired": true},
|
||||
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the working dir path", "paramRequired": true},
|
||||
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
|
||||
|
||||
]
|
||||
|
|
@ -1,5 +1,8 @@
|
|||
package eu.dnetlib.doiboost.orcid
|
||||
|
||||
import eu.dnetlib.dhp.schema.oaf.Publication
|
||||
import eu.dnetlib.doiboost.orcid.SparkConvertORCIDToOAF.getClass
|
||||
import org.apache.spark.sql.{Encoder, Encoders, SparkSession}
|
||||
import org.codehaus.jackson.map.ObjectMapper
|
||||
import org.junit.jupiter.api.Assertions._
|
||||
import org.junit.jupiter.api.Test
|
||||
|
|
@ -21,6 +24,30 @@ class MappingORCIDToOAFTest {
|
|||
})
|
||||
}
|
||||
|
||||
// @Test
|
||||
// def testOAFConvert():Unit ={
|
||||
//
|
||||
// val spark: SparkSession =
|
||||
// SparkSession
|
||||
// .builder()
|
||||
// .appName(getClass.getSimpleName)
|
||||
// .master("local[*]").getOrCreate()
|
||||
//
|
||||
//
|
||||
// SparkConvertORCIDToOAF.run( spark,"/Users/sandro/Downloads/orcid", "/Users/sandro/Downloads/orcid_oaf")
|
||||
// implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
|
||||
//
|
||||
// val df = spark.read.load("/Users/sandro/Downloads/orcid_oaf").as[Publication]
|
||||
// println(df.first.getId)
|
||||
// println(mapper.writeValueAsString(df.first()))
|
||||
//
|
||||
//
|
||||
//
|
||||
//
|
||||
// }
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue