forked from D-Net/dnet-hadoop
merge with beta - resolved conflict in pom
This commit is contained in:
commit
b3f9370125
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@ -70,7 +70,7 @@ case object Crossref2Oaf {
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"reference-book" -> "0002 Book",
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"reference-book" -> "0002 Book",
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"monograph" -> "0002 Book",
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"monograph" -> "0002 Book",
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"journal-article" -> "0001 Article",
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"journal-article" -> "0001 Article",
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"dissertation" -> "0006 Doctoral thesis",
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"dissertation" -> "0044 Thesis",
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"other" -> "0038 Other literature type",
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"other" -> "0038 Other literature type",
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"peer-review" -> "0015 Review",
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"peer-review" -> "0015 Review",
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"proceedings" -> "0004 Conference object",
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"proceedings" -> "0004 Conference object",
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@ -206,11 +206,16 @@ case object Crossref2Oaf {
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else {
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else {
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instance.setDateofacceptance(asField(createdDate.getValue))
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instance.setDateofacceptance(asField(createdDate.getValue))
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}
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}
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val s: String = (json \ "URL").extract[String]
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val s: List[String] = List("https://doi.org/" + doi)
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val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null).distinct
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// val links: List[String] = ((for {JString(url) <- json \ "link" \ "URL"} yield url) ::: List(s)).filter(p => p != null && p.toLowerCase().contains(doi.toLowerCase())).distinct
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if (links.nonEmpty) {
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// if (links.nonEmpty) {
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instance.setUrl(links.asJava)
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// instance.setUrl(links.asJava)
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}
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// }
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if(s.nonEmpty)
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{
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instance.setUrl(s.asJava)
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}
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result.setInstance(List(instance).asJava)
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result.setInstance(List(instance).asJava)
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//IMPORTANT
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//IMPORTANT
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@ -111,26 +111,9 @@ object SparkProcessMAG {
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.map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
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.map(item => ConversionUtil.updatePubsWithConferenceInfo(item))
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.write
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.write
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.mode(SaveMode.Overwrite)
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.mode(SaveMode.Overwrite)
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.save(s"$workingPath/merge_step_2_conference")
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magPubs= spark.read.load(s"$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"$sourcePath/PaperUrls").as[MagPaperUrl].groupBy("PaperId").agg(collect_list(struct("sourceUrl")).as("instances")).as[MagUrl]
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logger.info("Phase 5) enrich publication with URL and Instances")
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magPubs.joinWith(paperUrlDataset, col("_1").equalTo(paperUrlDataset("PaperId")), "left")
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.map { a: ((String, Publication), MagUrl) => ConversionUtil.addInstances((a._1._2, a._2)) }
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.write.mode(SaveMode.Overwrite)
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.save(s"$workingPath/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"${parser.get("targetPath")}/PaperAbstract")
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val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
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val paperAbstract = spark.read.load((s"$workingPath/PaperAbstract")).as[MagPaperAbstract]
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@ -162,12 +145,14 @@ object SparkProcessMAG {
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.write.mode(SaveMode.Overwrite)
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.write.mode(SaveMode.Overwrite)
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.save(s"$workingPath/mag_publication")
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.save(s"$workingPath/mag_publication")
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spark.read.load(s"$workingPath/mag_publication").as[Publication]
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.filter(p => p.getId == null)
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.groupByKey(p => p.getId)
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.reduceGroups((a:Publication, b:Publication) => ConversionUtil.mergePublication(a,b))
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.map(_._2)
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.write.mode(SaveMode.Overwrite).save(s"$targetPath/magPublication")
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val s:RDD[Publication] = spark.read.load(s"$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"$targetPath/magPublication")
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}
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}
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}
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}
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@ -612,4 +612,26 @@ class CrossrefMappingTest {
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}
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}
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@Test
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def testMultipleURLs() :Unit = {
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val json = Source.fromInputStream(getClass.getResourceAsStream("multiple_urls.json")).mkString
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assertNotNull(json)
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assertFalse(json.isEmpty);
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val resultList: List[Oaf] = Crossref2Oaf.convert(json)
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assertTrue(resultList.nonEmpty)
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val item : Result = resultList.filter(p => p.isInstanceOf[Result]).head.asInstanceOf[Result]
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assertEquals(1, item.getInstance().size())
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assertEquals(1, item.getInstance().get(0).getUrl().size())
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assertEquals("https://doi.org/10.1016/j.jas.2019.105013", item.getInstance().get(0).getUrl().get(0))
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//println(mapper.writeValueAsString(item))
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}
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}
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}
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@ -0,0 +1,614 @@
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{
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"indexed": {
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"date-parts": [
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[
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2021,
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10,
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31
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]
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],
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"date-time": "2021-10-31T15:48:01Z",
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"timestamp": 1635695281393
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},
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"reference-count": 39,
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"publisher": "Elsevier BV",
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"license": [
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{
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"start": {
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"date-parts": [
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[
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2019,
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12,
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|
1
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]
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],
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"date-time": "2019-12-01T00:00:00Z",
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"timestamp": 1575158400000
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},
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"content-version": "tdm",
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"delay-in-days": 0,
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"URL": "https://www.elsevier.com/tdm/userlicense/1.0/"
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},
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{
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|
"start": {
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"date-parts": [
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[
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2019,
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9,
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13
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]
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],
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||||||
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"date-time": "2019-09-13T00:00:00Z",
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"timestamp": 1568332800000
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},
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"content-version": "vor",
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"delay-in-days": 0,
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"URL": "http://creativecommons.org/licenses/by/4.0/"
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}
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],
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"funder": [
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{
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"DOI": "10.13039/100001182",
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"name": "INSTAP",
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"doi-asserted-by": "publisher"
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},
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{
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"DOI": "10.13039/100014440",
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"name": "Ministry of Science, Innovation and Universities",
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"doi-asserted-by": "publisher",
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"award": [
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"RYC-2016-19637"
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]
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},
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{
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"DOI": "10.13039/100010661",
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"name": "European Union’s Horizon 2020",
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"doi-asserted-by": "publisher",
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||||||
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"award": [
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"746446"
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]
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}
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],
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"content-domain": {
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"domain": [
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"elsevier.com",
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"sciencedirect.com"
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],
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"crossmark-restriction": true
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|
},
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|
"short-container-title": [
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"Journal of Archaeological Science"
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||||||
|
],
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||||||
|
"published-print": {
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||||||
|
"date-parts": [
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||||||
|
[
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||||||
|
2019,
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|
12
|
||||||
|
]
|
||||||
|
]
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||||||
|
},
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||||||
|
"DOI": "10.1016/j.jas.2019.105013",
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"type": "journal-article",
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||||||
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"created": {
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||||||
|
"date-parts": [
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||||||
|
[
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||||||
|
2019,
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||||||
|
9,
|
||||||
|
25
|
||||||
|
]
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||||||
|
],
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||||||
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"date-time": "2019-09-25T20:05:08Z",
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||||||
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"timestamp": 1569441908000
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||||||
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},
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||||||
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"page": "105013",
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||||||
|
"update-policy": "http://dx.doi.org/10.1016/elsevier_cm_policy",
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"source": "Crossref",
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||||||
|
"is-referenced-by-count": 21,
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||||||
|
"title": [
|
||||||
|
"A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery"
|
||||||
|
],
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||||||
|
"prefix": "10.1016",
|
||||||
|
"volume": "112",
|
||||||
|
"author": [
|
||||||
|
{
|
||||||
|
"given": "H.A.",
|
||||||
|
"family": "Orengo",
|
||||||
|
"sequence": "first",
|
||||||
|
"affiliation": [
|
||||||
|
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"given": "A.",
|
||||||
|
"family": "Garcia-Molsosa",
|
||||||
|
"sequence": "additional",
|
||||||
|
"affiliation": [
|
||||||
|
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"member": "78",
|
||||||
|
"reference": [
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib1",
|
||||||
|
"doi-asserted-by": "crossref",
|
||||||
|
"first-page": "85",
|
||||||
|
"DOI": "10.1080/17538947.2016.1250829",
|
||||||
|
"article-title": "Remote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applications",
|
||||||
|
"volume": "10",
|
||||||
|
"author": "Agapiou",
|
||||||
|
"year": "2017",
|
||||||
|
"journal-title": "Int. J. Digit. Earth"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib2",
|
||||||
|
"series-title": "Extracting Meaning from Ploughsoil Assemblages",
|
||||||
|
"first-page": "1",
|
||||||
|
"article-title": "Extracting meaning from ploughsoil assemblages: assessments of the past, strategies for the future",
|
||||||
|
"author": "Alcock",
|
||||||
|
"year": "2000"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib3",
|
||||||
|
"series-title": "Side-by-Side Survey. Comparative Regional Studies in the Mediterranean World",
|
||||||
|
"first-page": "1",
|
||||||
|
"article-title": "Introduction",
|
||||||
|
"author": "Alcock",
|
||||||
|
"year": "2004"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib4",
|
||||||
|
"doi-asserted-by": "crossref",
|
||||||
|
"first-page": "93",
|
||||||
|
"DOI": "10.1111/j.1538-4632.1995.tb00338.x",
|
||||||
|
"article-title": "Local indicators of spatial association—LISA",
|
||||||
|
"volume": "27",
|
||||||
|
"author": "Anselin",
|
||||||
|
"year": "1995",
|
||||||
|
"journal-title": "Geogr. Anal."
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib5",
|
||||||
|
"series-title": "Archaeological Survey",
|
||||||
|
"author": "Banning",
|
||||||
|
"year": "2002"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"issue": "1/2",
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib6",
|
||||||
|
"doi-asserted-by": "crossref",
|
||||||
|
"first-page": "123",
|
||||||
|
"DOI": "10.2307/3181488",
|
||||||
|
"article-title": "GIS, archaeological survey and landscape archaeology on the island of Kythera, Greece",
|
||||||
|
"volume": "29",
|
||||||
|
"author": "Bevan",
|
||||||
|
"year": "2004",
|
||||||
|
"journal-title": "J. Field Archaeol."
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"issue": "1",
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib8",
|
||||||
|
"doi-asserted-by": "crossref",
|
||||||
|
"first-page": "5",
|
||||||
|
"DOI": "10.1023/A:1010933404324",
|
||||||
|
"article-title": "Random forests",
|
||||||
|
"volume": "45",
|
||||||
|
"author": "Breiman",
|
||||||
|
"year": "2001",
|
||||||
|
"journal-title": "Mach. Learn."
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib9",
|
||||||
|
"series-title": "Sampling in Contemporary British Archaeology",
|
||||||
|
"author": "Cherry",
|
||||||
|
"year": "1978"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"issue": "3",
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib10",
|
||||||
|
"doi-asserted-by": "crossref",
|
||||||
|
"first-page": "273",
|
||||||
|
"DOI": "10.1016/0734-189X(84)90197-X",
|
||||||
|
"article-title": "Segmentation of a high-resolution urban scene using texture operators",
|
||||||
|
"volume": "25",
|
||||||
|
"author": "Conners",
|
||||||
|
"year": "1984",
|
||||||
|
"journal-title": "Comput. Vis. Graph Image Process"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib11",
|
||||||
|
"first-page": "31",
|
||||||
|
"article-title": "Old land surfaces and modern ploughsoil: implications of recent work at Maxey, Cambridgeshire",
|
||||||
|
"volume": "2",
|
||||||
|
"author": "Crowther",
|
||||||
|
"year": "1983",
|
||||||
|
"journal-title": "Scott. Archaeol. Rev."
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib12",
|
||||||
|
"series-title": "Settlement Pattern Studies in the Americas: Fifty Years since Virú",
|
||||||
|
"first-page": "203",
|
||||||
|
"article-title": "Conclusions: the settlement pattern concept from an Americanist perspective",
|
||||||
|
"author": "Fish",
|
||||||
|
"year": "1999"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib13",
|
||||||
|
"doi-asserted-by": "crossref",
|
||||||
|
"first-page": "21",
|
||||||
|
"DOI": "10.3390/geosciences9010021",
|
||||||
|
"article-title": "Remote sensing and historical morphodynamics of alluvial plains. The 1909 indus flood and the city of Dera Gazhi Khan (province of Punjab, Pakistan)",
|
||||||
|
"volume": "9",
|
||||||
|
"author": "Garcia",
|
||||||
|
"year": "2019",
|
||||||
|
"journal-title": "Geosciences"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib14",
|
||||||
|
"unstructured": "Georgiadis, M.; Garcia-Molsosa, A.; Orengo, H.A.; Kefalidou, E. and Kallintzi, K. In Preparation. APAX Project 2015-2018: A Preliminary Report. (Hesperia)."
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib15",
|
||||||
|
"series-title": "Geographical Information Systems and Landscape Archaeology",
|
||||||
|
"first-page": "35",
|
||||||
|
"article-title": "Regional survey and GIS: the boeotia project",
|
||||||
|
"author": "Gillings",
|
||||||
|
"year": "1999"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"key": "10.1016/j.jas.2019.105013_bib16",
|
||||||
|
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{
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},
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{
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"URL": "https://api.elsevier.com/content/article/PII:S0305440319301001?httpAccept=text/plain",
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"content-type": "text/plain",
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"content-version": "vor",
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"intended-application": "text-mining"
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}
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],
|
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"deposited": {
|
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|
"date-parts": [
|
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[
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2019,
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11,
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25
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]
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],
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"date-time": "2019-11-25T06:46:34Z",
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"timestamp": 1574664394000
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},
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"score": 1,
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"subtitle": [
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],
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"short-title": [
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|
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],
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"issued": {
|
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"date-parts": [
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[
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2019,
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12
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]
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]
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},
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"references-count": 39,
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"alternative-id": [
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"S0305440319301001"
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],
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"URL": "http://dx.doi.org/10.1016/j.jas.2019.105013",
|
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|
"relation": {
|
||||||
|
|
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|
},
|
||||||
|
"ISSN": [
|
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|
"0305-4403"
|
||||||
|
],
|
||||||
|
"issn-type": [
|
||||||
|
{
|
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|
"value": "0305-4403",
|
||||||
|
"type": "print"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"subject": [
|
||||||
|
"Archaeology",
|
||||||
|
"Archaeology"
|
||||||
|
],
|
||||||
|
"published": {
|
||||||
|
"date-parts": [
|
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|
[
|
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|
2019,
|
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|
12
|
||||||
|
]
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|
]
|
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|
},
|
||||||
|
"assertion": [
|
||||||
|
{
|
||||||
|
"value": "Elsevier",
|
||||||
|
"name": "publisher",
|
||||||
|
"label": "This article is maintained by"
|
||||||
|
},
|
||||||
|
{
|
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|
"value": "A brave new world for archaeological survey: Automated machine learning-based potsherd detection using high-resolution drone imagery",
|
||||||
|
"name": "articletitle",
|
||||||
|
"label": "Article Title"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"value": "Journal of Archaeological Science",
|
||||||
|
"name": "journaltitle",
|
||||||
|
"label": "Journal Title"
|
||||||
|
},
|
||||||
|
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|
||||||
|
"value": "https://doi.org/10.1016/j.jas.2019.105013",
|
||||||
|
"name": "articlelink",
|
||||||
|
"label": "CrossRef DOI link to publisher maintained version"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"value": "article",
|
||||||
|
"name": "content_type",
|
||||||
|
"label": "Content Type"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"value": "© 2019 The Authors. Published by Elsevier Ltd.",
|
||||||
|
"name": "copyright",
|
||||||
|
"label": "Copyright"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"article-number": "105013"
|
||||||
|
}
|
|
@ -0,0 +1,107 @@
|
||||||
|
package eu.dnetlib.dhp.oa.graph.resolution
|
||||||
|
|
||||||
|
import com.fasterxml.jackson.databind.ObjectMapper
|
||||||
|
import eu.dnetlib.dhp.application.ArgumentApplicationParser
|
||||||
|
import eu.dnetlib.dhp.common.HdfsSupport
|
||||||
|
import eu.dnetlib.dhp.schema.common.EntityType
|
||||||
|
import eu.dnetlib.dhp.schema.oaf.{OtherResearchProduct, Publication, Result, Software, Dataset => OafDataset}
|
||||||
|
import org.apache.commons.io.IOUtils
|
||||||
|
import org.apache.hadoop.fs.{FileSystem, Path}
|
||||||
|
import org.apache.spark.SparkConf
|
||||||
|
import org.apache.spark.sql._
|
||||||
|
import org.slf4j.{Logger, LoggerFactory}
|
||||||
|
|
||||||
|
object SparkResolveEntities {
|
||||||
|
|
||||||
|
val mapper = new ObjectMapper()
|
||||||
|
val entities = List(EntityType.dataset,EntityType.publication, EntityType.software, EntityType.otherresearchproduct)
|
||||||
|
|
||||||
|
def main(args: Array[String]): Unit = {
|
||||||
|
val log: Logger = LoggerFactory.getLogger(getClass)
|
||||||
|
val conf: SparkConf = new SparkConf()
|
||||||
|
val parser = new ArgumentApplicationParser(IOUtils.toString(getClass.getResourceAsStream("/eu/dnetlib/dhp/oa/graph/resolution/resolve_params.json")))
|
||||||
|
parser.parseArgument(args)
|
||||||
|
val spark: SparkSession =
|
||||||
|
SparkSession
|
||||||
|
.builder()
|
||||||
|
.config(conf)
|
||||||
|
.appName(getClass.getSimpleName)
|
||||||
|
.master(parser.get("master")).getOrCreate()
|
||||||
|
|
||||||
|
|
||||||
|
val graphBasePath = parser.get("graphBasePath")
|
||||||
|
log.info(s"graphBasePath -> $graphBasePath")
|
||||||
|
val workingPath = parser.get("workingPath")
|
||||||
|
log.info(s"workingPath -> $workingPath")
|
||||||
|
val unresolvedPath = parser.get("unresolvedPath")
|
||||||
|
log.info(s"unresolvedPath -> $unresolvedPath")
|
||||||
|
|
||||||
|
val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
|
||||||
|
fs.mkdirs(new Path(workingPath))
|
||||||
|
|
||||||
|
resolveEntities(spark, workingPath, unresolvedPath)
|
||||||
|
generateResolvedEntities(spark, workingPath, graphBasePath)
|
||||||
|
|
||||||
|
// TO BE conservative we keep the original entities in the working dir
|
||||||
|
// and save the resolved entities on the graphBasePath
|
||||||
|
//In future these lines of code should be removed
|
||||||
|
entities.foreach {
|
||||||
|
e =>
|
||||||
|
fs.rename(new Path(s"$graphBasePath/$e"), new Path(s"$workingPath/${e}_old"))
|
||||||
|
fs.rename(new Path(s"$workingPath/resolvedGraph/$e"), new Path(s"$graphBasePath/$e"))
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def resolveEntities(spark: SparkSession, workingPath: String, unresolvedPath: String) = {
|
||||||
|
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||||
|
import spark.implicits._
|
||||||
|
|
||||||
|
val rPid: Dataset[(String, String)] = spark.read.load(s"$workingPath/relationResolvedPid").as[(String, String)]
|
||||||
|
val up: Dataset[(String, Result)] = spark.read.text(unresolvedPath).as[String].map(s => mapper.readValue(s, classOf[Result])).map(r => (r.getId, r))(Encoders.tuple(Encoders.STRING, resEncoder))
|
||||||
|
|
||||||
|
rPid.joinWith(up, rPid("_2").equalTo(up("_1")), "inner").map {
|
||||||
|
r =>
|
||||||
|
val result = r._2._2
|
||||||
|
val dnetId = r._1._1
|
||||||
|
result.setId(dnetId)
|
||||||
|
result
|
||||||
|
}.write.mode(SaveMode.Overwrite).save(s"$workingPath/resolvedEntities")
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def deserializeObject(input:String, entity:EntityType ) :Result = {
|
||||||
|
|
||||||
|
entity match {
|
||||||
|
case EntityType.publication => mapper.readValue(input, classOf[Publication])
|
||||||
|
case EntityType.dataset => mapper.readValue(input, classOf[OafDataset])
|
||||||
|
case EntityType.software=> mapper.readValue(input, classOf[Software])
|
||||||
|
case EntityType.otherresearchproduct=> mapper.readValue(input, classOf[OtherResearchProduct])
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
def generateResolvedEntities(spark:SparkSession, workingPath: String, graphBasePath:String) = {
|
||||||
|
|
||||||
|
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||||
|
import spark.implicits._
|
||||||
|
|
||||||
|
val re:Dataset[Result] = spark.read.load(s"$workingPath/resolvedEntities").as[Result]
|
||||||
|
entities.foreach {
|
||||||
|
e =>
|
||||||
|
|
||||||
|
spark.read.text(s"$graphBasePath/$e").as[String]
|
||||||
|
.map(s => deserializeObject(s, e))
|
||||||
|
.union(re)
|
||||||
|
.groupByKey(_.getId)
|
||||||
|
.reduceGroups {
|
||||||
|
(x, y) =>
|
||||||
|
x.mergeFrom(y)
|
||||||
|
x
|
||||||
|
}.map(_._2)
|
||||||
|
.filter(r => r.getClass.getSimpleName.toLowerCase != "result")
|
||||||
|
.map(r => mapper.writeValueAsString(r))(Encoders.STRING)
|
||||||
|
.write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$workingPath/resolvedGraph/$e")
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
|
@ -96,6 +96,21 @@ object SparkResolveRelation {
|
||||||
.text(s"$graphBasePath/relation")
|
.text(s"$graphBasePath/relation")
|
||||||
}
|
}
|
||||||
|
|
||||||
|
def extractInstanceCF(input: String): List[(String, String)] = {
|
||||||
|
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
|
||||||
|
lazy val json: json4s.JValue = parse(input)
|
||||||
|
val result: List[(String, String)] = for {
|
||||||
|
JObject(iObj) <- json \ "instance"
|
||||||
|
JField("collectedfrom", JObject(cf)) <- iObj
|
||||||
|
JField("instancetype", JObject(instancetype)) <- iObj
|
||||||
|
JField("value", JString(collectedFrom)) <- cf
|
||||||
|
JField("classname", JString(classname)) <- instancetype
|
||||||
|
} yield (classname, collectedFrom)
|
||||||
|
|
||||||
|
result
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
def extractPidsFromRecord(input: String): (String, List[(String, String)]) = {
|
def extractPidsFromRecord(input: String): (String, List[(String, String)]) = {
|
||||||
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
|
implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
|
||||||
|
@ -108,14 +123,7 @@ object SparkResolveRelation {
|
||||||
JField("classid", JString(pidType)) <- qualifier
|
JField("classid", JString(pidType)) <- qualifier
|
||||||
} yield (pidValue, pidType)
|
} yield (pidValue, pidType)
|
||||||
|
|
||||||
val alternateIds: List[(String, String)] = for {
|
(id, result)
|
||||||
JObject(pids) <- json \\ "alternateIdentifier"
|
|
||||||
JField("value", JString(pidValue)) <- pids
|
|
||||||
JField("qualifier", JObject(qualifier)) <- pids
|
|
||||||
JField("classid", JString(pidType)) <- qualifier
|
|
||||||
} yield (pidValue, pidType)
|
|
||||||
|
|
||||||
(id, result ::: alternateIds)
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@ -128,7 +136,7 @@ object SparkResolveRelation {
|
||||||
source != null
|
source != null
|
||||||
}
|
}
|
||||||
|
|
||||||
private def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
|
def extractPidResolvedTableFromJsonRDD(spark: SparkSession, graphPath: String, workingPath: String) = {
|
||||||
import spark.implicits._
|
import spark.implicits._
|
||||||
|
|
||||||
val d: RDD[(String, String)] = spark.sparkContext.textFile(s"$graphPath/*")
|
val d: RDD[(String, String)] = spark.sparkContext.textFile(s"$graphPath/*")
|
||||||
|
|
|
@ -4,6 +4,10 @@
|
||||||
<name>graphBasePath</name>
|
<name>graphBasePath</name>
|
||||||
<description>the path of the graph</description>
|
<description>the path of the graph</description>
|
||||||
</property>
|
</property>
|
||||||
|
<property>
|
||||||
|
<name>unresolvedPath</name>
|
||||||
|
<description>the path of the unresolved Entities</description>
|
||||||
|
</property>
|
||||||
</parameters>
|
</parameters>
|
||||||
|
|
||||||
<start to="ResolveRelations"/>
|
<start to="ResolveRelations"/>
|
||||||
|
@ -36,5 +40,33 @@
|
||||||
<ok to="End"/>
|
<ok to="End"/>
|
||||||
<error to="Kill"/>
|
<error to="Kill"/>
|
||||||
</action>
|
</action>
|
||||||
|
|
||||||
|
<action name="ResolveEntities">
|
||||||
|
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||||
|
<master>yarn</master>
|
||||||
|
<mode>cluster</mode>
|
||||||
|
<name>Resolve Relations in raw graph</name>
|
||||||
|
<class>eu.dnetlib.dhp.oa.graph.resolution.SparkResolveEntities</class>
|
||||||
|
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
|
||||||
|
<spark-opts>
|
||||||
|
--executor-memory=${sparkExecutorMemory}
|
||||||
|
--executor-cores=${sparkExecutorCores}
|
||||||
|
--driver-memory=${sparkDriverMemory}
|
||||||
|
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||||
|
--conf spark.sql.shuffle.partitions=10000
|
||||||
|
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||||
|
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||||
|
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||||
|
</spark-opts>
|
||||||
|
<arg>--master</arg><arg>yarn</arg>
|
||||||
|
<arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
|
||||||
|
<arg>--unresolvedPath</arg><arg>${unresolvedPath}</arg>
|
||||||
|
<arg>--workingPath</arg><arg>${workingDir}</arg>
|
||||||
|
</spark>
|
||||||
|
<ok to="End"/>
|
||||||
|
<error to="Kill"/>
|
||||||
|
</action>
|
||||||
|
|
||||||
|
|
||||||
<end name="End"/>
|
<end name="End"/>
|
||||||
</workflow-app>
|
</workflow-app>
|
|
@ -0,0 +1,6 @@
|
||||||
|
[
|
||||||
|
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
|
||||||
|
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the source Path", "paramRequired": true},
|
||||||
|
{"paramName":"u", "paramLongName":"unresolvedPath", "paramDescription": "the source Path", "paramRequired": true},
|
||||||
|
{"paramName":"g", "paramLongName":"graphBasePath", "paramDescription": "the path of the raw graph", "paramRequired": true}
|
||||||
|
]
|
|
@ -0,0 +1,190 @@
|
||||||
|
package eu.dnetlib.dhp.oa.graph.resolution
|
||||||
|
|
||||||
|
|
||||||
|
import com.fasterxml.jackson.databind.ObjectMapper
|
||||||
|
import eu.dnetlib.dhp.schema.common.EntityType
|
||||||
|
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils
|
||||||
|
import eu.dnetlib.dhp.schema.oaf.{Result, StructuredProperty}
|
||||||
|
import org.apache.commons.io.FileUtils
|
||||||
|
import org.apache.spark.SparkConf
|
||||||
|
import org.apache.spark.sql._
|
||||||
|
import org.junit.jupiter.api.Assertions._
|
||||||
|
import org.junit.jupiter.api.TestInstance.Lifecycle
|
||||||
|
import org.junit.jupiter.api.{AfterAll, BeforeAll, Test, TestInstance}
|
||||||
|
|
||||||
|
import java.nio.file.{Files, Path}
|
||||||
|
import scala.collection.JavaConverters._
|
||||||
|
import scala.io.Source
|
||||||
|
|
||||||
|
@TestInstance(Lifecycle.PER_CLASS)
|
||||||
|
class ResolveEntitiesTest extends Serializable {
|
||||||
|
|
||||||
|
var workingDir:Path = null
|
||||||
|
|
||||||
|
val FAKE_TITLE = "FAKETITLE"
|
||||||
|
val FAKE_SUBJECT = "FAKESUBJECT"
|
||||||
|
|
||||||
|
var sparkSession:Option[SparkSession] = None
|
||||||
|
|
||||||
|
|
||||||
|
@BeforeAll
|
||||||
|
def setUp() :Unit = {
|
||||||
|
workingDir = Files.createTempDirectory(getClass.getSimpleName)
|
||||||
|
|
||||||
|
val conf = new SparkConf()
|
||||||
|
sparkSession = Some(SparkSession
|
||||||
|
.builder()
|
||||||
|
.config(conf)
|
||||||
|
.appName(getClass.getSimpleName)
|
||||||
|
.master("local[*]").getOrCreate())
|
||||||
|
populateDatasets(sparkSession.get)
|
||||||
|
generateUpdates(sparkSession.get)
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@AfterAll
|
||||||
|
def tearDown():Unit = {
|
||||||
|
FileUtils.deleteDirectory(workingDir.toFile)
|
||||||
|
sparkSession.get.stop()
|
||||||
|
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def generateUpdates(spark:SparkSession):Unit = {
|
||||||
|
val template = Source.fromInputStream(this.getClass.getResourceAsStream("updates")).mkString
|
||||||
|
|
||||||
|
|
||||||
|
val pids:List[String] = template.lines.map{id =>
|
||||||
|
val r = new Result
|
||||||
|
r.setId(id.toLowerCase.trim)
|
||||||
|
r.setSubject(List(OafMapperUtils.structuredProperty(FAKE_SUBJECT, OafMapperUtils.qualifier("fos","fosCS", "fossSchema", "fossiFIgo"), null)).asJava)
|
||||||
|
r.setTitle(List(OafMapperUtils.structuredProperty(FAKE_TITLE, OafMapperUtils.qualifier("fos","fosCS", "fossSchema", "fossiFIgo"), null)).asJava)
|
||||||
|
r
|
||||||
|
}.map{r =>
|
||||||
|
val mapper = new ObjectMapper()
|
||||||
|
|
||||||
|
mapper.writeValueAsString(r)}.toList
|
||||||
|
|
||||||
|
|
||||||
|
val sc =spark.sparkContext
|
||||||
|
|
||||||
|
println(sc.parallelize(pids).count())
|
||||||
|
|
||||||
|
spark.createDataset(sc.parallelize(pids))(Encoders.STRING).write.mode(SaveMode.Overwrite).option("compression", "gzip").text(s"$workingDir/updates")
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
import spark.implicits._
|
||||||
|
implicit val resEncoder: Encoder[Result] = Encoders.bean(classOf[Result])
|
||||||
|
val ds = spark.read.text(s"$workingDir/updates").as[String].map{s => val mapper = new ObjectMapper()
|
||||||
|
mapper.readValue(s, classOf[Result])}.collect()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
assertEquals(4, ds.length)
|
||||||
|
ds.foreach{r => assertNotNull(r.getSubject)}
|
||||||
|
ds.foreach{r => assertEquals(1,r.getSubject.size())}
|
||||||
|
ds.foreach{r => assertNotNull(r.getTitle)}
|
||||||
|
ds.foreach{r => assertEquals(1,r.getTitle.size())}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
ds.flatMap(r => r.getTitle.asScala.map(t => t.getValue)).foreach(t => assertEquals(FAKE_TITLE,t))
|
||||||
|
ds.flatMap(r => r.getSubject.asScala.map(t => t.getValue)).foreach(t => assertEquals(FAKE_SUBJECT,t))
|
||||||
|
|
||||||
|
println("generated Updates")
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def populateDatasets(spark:SparkSession):Unit = {
|
||||||
|
import spark.implicits._
|
||||||
|
val entities =SparkResolveEntities.entities
|
||||||
|
|
||||||
|
entities.foreach{
|
||||||
|
e =>
|
||||||
|
val template = Source.fromInputStream(this.getClass.getResourceAsStream(s"$e")).mkString
|
||||||
|
spark.createDataset(spark.sparkContext.parallelize(template.lines.toList)).as[String].write.option("compression", "gzip").text(s"$workingDir/graph/$e")
|
||||||
|
println(s"Created Dataset $e")
|
||||||
|
}
|
||||||
|
SparkResolveRelation.extractPidResolvedTableFromJsonRDD(spark, s"$workingDir/graph", s"$workingDir/work")
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@Test
|
||||||
|
def testResolution():Unit = {
|
||||||
|
val spark:SparkSession = sparkSession.get
|
||||||
|
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||||
|
SparkResolveEntities.resolveEntities(spark,s"$workingDir/work", s"$workingDir/updates" )
|
||||||
|
|
||||||
|
val ds = spark.read.load(s"$workingDir/work/resolvedEntities").as[Result]
|
||||||
|
|
||||||
|
assertEquals(3, ds.count())
|
||||||
|
|
||||||
|
ds.collect().foreach{
|
||||||
|
r =>
|
||||||
|
assertTrue(r.getId.startsWith("50"))
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
private def structuredPContainsValue(l:java.util.List[StructuredProperty], exptectedValue:String):Boolean = {
|
||||||
|
l.asScala.exists(p =>p.getValue!= null && p.getValue.equalsIgnoreCase(exptectedValue))
|
||||||
|
}
|
||||||
|
|
||||||
|
@Test
|
||||||
|
def testUpdate():Unit = {
|
||||||
|
val spark:SparkSession = sparkSession.get
|
||||||
|
import spark.implicits._
|
||||||
|
implicit val resEncoder: Encoder[Result] = Encoders.kryo(classOf[Result])
|
||||||
|
val m = new ObjectMapper()
|
||||||
|
SparkResolveEntities.resolveEntities(spark,s"$workingDir/work", s"$workingDir/updates" )
|
||||||
|
SparkResolveEntities.generateResolvedEntities(spark,s"$workingDir/work",s"$workingDir/graph" )
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
val pubDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/publication").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.publication))
|
||||||
|
val t = pubDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
val datDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/dataset").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.dataset))
|
||||||
|
val td = datDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||||
|
|
||||||
|
|
||||||
|
val softDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/software").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.software))
|
||||||
|
val ts = softDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||||
|
|
||||||
|
|
||||||
|
val orpDS:Dataset[Result] = spark.read.text(s"$workingDir/work/resolvedGraph/otherresearchproduct").as[String].map(s => SparkResolveEntities.deserializeObject(s, EntityType.otherresearchproduct))
|
||||||
|
val to = orpDS.filter(p => p.getTitle!=null && p.getSubject!=null).filter(p => p.getTitle.asScala.exists(t => t.getValue.equalsIgnoreCase("FAKETITLE"))).count()
|
||||||
|
|
||||||
|
|
||||||
|
assertEquals(0, t)
|
||||||
|
assertEquals(2, td)
|
||||||
|
assertEquals(1, ts)
|
||||||
|
assertEquals(0, to)
|
||||||
|
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
}
|
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|
@ -0,0 +1,4 @@
|
||||||
|
unresolved::10.17026/dans-x3z-fsq5::doi
|
||||||
|
unresolved::10.17026/dans-xsw-qtnx::doi
|
||||||
|
unresolved::10.5281/zenodo.1473694::doi
|
||||||
|
unresolved::10.17632/fake::doi
|
2
pom.xml
2
pom.xml
|
@ -753,7 +753,7 @@
|
||||||
<mockito-core.version>3.3.3</mockito-core.version>
|
<mockito-core.version>3.3.3</mockito-core.version>
|
||||||
<mongodb.driver.version>3.4.2</mongodb.driver.version>
|
<mongodb.driver.version>3.4.2</mongodb.driver.version>
|
||||||
<vtd.version>[2.12,3.0)</vtd.version>
|
<vtd.version>[2.12,3.0)</vtd.version>
|
||||||
<dhp-schemas.version>[2.8.22-SNAPSHOT]</dhp-schemas.version>
|
<dhp-schemas.version>[2.8.22]</dhp-schemas.version>
|
||||||
<dnet-actionmanager-api.version>[4.0.3]</dnet-actionmanager-api.version>
|
<dnet-actionmanager-api.version>[4.0.3]</dnet-actionmanager-api.version>
|
||||||
<dnet-actionmanager-common.version>[6.0.5]</dnet-actionmanager-common.version>
|
<dnet-actionmanager-common.version>[6.0.5]</dnet-actionmanager-common.version>
|
||||||
<dnet-openaire-broker-common.version>[3.1.6]</dnet-openaire-broker-common.version>
|
<dnet-openaire-broker-common.version>[3.1.6]</dnet-openaire-broker-common.version>
|
||||||
|
|
Loading…
Reference in New Issue