From db36e119127a88930892e9dd5ad7a61aad91baed Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Mon, 30 Nov 2020 20:14:23 +0100 Subject: [PATCH 01/10] classes test classes and resources for production of the actionset to include bipFinder score in results --- .../bipfinder/BipDeserialize.java | 23 + .../dhp/actionmanager/bipfinder/BipScore.java | 25 + .../dhp/actionmanager/bipfinder/KeyValue.java | 25 + .../bipfinder/PreparedResult.java | 24 + .../dhp/actionmanager/bipfinder/Score.java | 26 + .../bipfinder/SparkAtomicActionScoreJob.java | 203 +++ .../bipfinder/input_parameters.json | 32 + .../SparkAtomicActionScoreJobTest.java | 160 +++ .../actionmanager/bipfinder/bip_scores.json | 1101 +++++++++++++++++ .../actionmanager/bipfinder/publication.json | 18 + 10 files changed, 1637 insertions(+) create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json create mode 100644 dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java create mode 100644 dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json create mode 100644 dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/publication.json diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java new file mode 100644 index 0000000000..e68b912b2a --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java @@ -0,0 +1,23 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import java.io.Serializable; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; + + +public class BipDeserialize extends HashMap> implements Serializable { + + public BipDeserialize(){ + super(); + } + + public List get(String key) { + + if (super.get(key) == null) { + return new ArrayList<>(); + } + return super.get(key); + } + +} diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java new file mode 100644 index 0000000000..b1e381955b --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java @@ -0,0 +1,25 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import java.io.Serializable; +import java.util.List; + +public class BipScore implements Serializable { + private String id; + private List scoreList; + + public String getId() { + return id; + } + + public void setId(String id) { + this.id = id; + } + + public List getScoreList() { + return scoreList; + } + + public void setScoreList(List scoreList) { + this.scoreList = scoreList; + } +} diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java new file mode 100644 index 0000000000..1fadae6fec --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java @@ -0,0 +1,25 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import java.io.Serializable; + +public class KeyValue implements Serializable { + + private String key; + private String value; + + public String getKey() { + return key; + } + + public void setKey(String key) { + this.key = key; + } + + public String getValue() { + return value; + } + + public void setValue(String value) { + this.value = value; + } +} diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java new file mode 100644 index 0000000000..bb7648f0c8 --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java @@ -0,0 +1,24 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import java.io.Serializable; + +public class PreparedResult implements Serializable { + private String id; //openaire id + private String value; //doi + + public String getId() { + return id; + } + + public void setId(String id) { + this.id = id; + } + + public String getValue() { + return value; + } + + public void setValue(String value) { + this.value = value; + } +} diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java new file mode 100644 index 0000000000..b14d971cdf --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java @@ -0,0 +1,26 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import java.io.Serializable; +import java.util.List; + +public class Score implements Serializable { + + private String id; + private List unit; + + public String getId() { + return id; + } + + public void setId(String id) { + this.id = id; + } + + public List getUnit() { + return unit; + } + + public void setUnit(List unit) { + this.unit = unit; + } +} diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java new file mode 100644 index 0000000000..658555e058 --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java @@ -0,0 +1,203 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import com.fasterxml.jackson.databind.ObjectMapper; +import eu.dnetlib.dhp.application.ArgumentApplicationParser; +import eu.dnetlib.dhp.common.HdfsSupport; +import eu.dnetlib.dhp.schema.action.AtomicAction; +import eu.dnetlib.dhp.schema.oaf.*; +import eu.dnetlib.dhp.schema.oaf.KeyValue; +import org.apache.commons.io.IOUtils; +import org.apache.hadoop.hdfs.qjournal.protocol.QJournalProtocolProtos; +import org.apache.hadoop.io.Text; +import org.apache.hadoop.mapred.SequenceFileOutputFormat; +import org.apache.spark.SparkConf; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.FlatMapFunction; +import org.apache.spark.api.java.function.MapFunction; +import org.apache.spark.api.java.function.MapGroupsFunction; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Encoders; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SparkSession; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; +import scala.Tuple2; + +import java.io.Serializable; +import java.util.List; +import java.util.Optional; +import java.util.stream.Collectors; + +import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession; + +public class SparkAtomicActionScoreJob implements Serializable { + + private static String DOI = "doi"; + private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionScoreJob.class); + private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); + + public static void main(String[] args) throws Exception { + + String jsonConfiguration = IOUtils + .toString( + SparkAtomicActionScoreJob.class + .getResourceAsStream( + "/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json")); + + final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration); + + parser.parseArgument(args); + + Boolean isSparkSessionManaged = Optional + .ofNullable(parser.get("isSparkSessionManaged")) + .map(Boolean::valueOf) + .orElse(Boolean.TRUE); + + log.info("isSparkSessionManaged: {}", isSparkSessionManaged); + + final String inputPath = parser.get("inputPath"); + log.info("inputPath {}: ", inputPath); + + final String outputPath = parser.get("outputPath"); + log.info("outputPath {}: ", outputPath); + + final String bipScorePath = parser.get("bipScorePath"); + log.info("bipScorePath: {}", bipScorePath); + + final String resultClassName = parser.get("resultTableName"); + log.info("resultTableName: {}", resultClassName); + + Class inputClazz = (Class) Class.forName(resultClassName); + + SparkConf conf = new SparkConf(); + + runWithSparkSession( + conf, + isSparkSessionManaged, + spark -> { + removeOutputDir(spark, outputPath); + prepareResults(spark, inputPath, outputPath, bipScorePath, inputClazz); + }); + } + + private static void prepareResults(SparkSession spark, String inputPath, String outputPath, + String bipScorePath, Class inputClazz) { + + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + + JavaRDD bipDeserializeJavaRDD = sc.textFile(bipScorePath) + .map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class)); + + + Dataset bipScores = spark.createDataset(bipDeserializeJavaRDD.flatMap(entry -> + entry.keySet().stream().map(key -> { + BipScore bs = new BipScore(); + bs.setId(key); + bs.setScoreList(entry.get(key)); + return bs; + }).collect(Collectors.toList()).iterator() + ).rdd(), Encoders.bean(BipScore.class)); + + System.out.println(bipScores.count()); + + Dataset results = readPath(spark, inputPath, inputClazz); + + results.createOrReplaceTempView("result"); + + Dataset preparedResult = spark.sql("select pIde.value value, id " + + "from result " + + "lateral view explode (pid) p as pIde " + + "where dataInfo.deletedbyinference = false and pIde.qualifier.classid = '" + DOI + "'") + .as(Encoders.bean(PreparedResult.class)); + + Dataset tmp = bipScores.joinWith(preparedResult, bipScores.col("id").equalTo(preparedResult.col("value")), + "inner") + .map((MapFunction, BipScore>) value -> { + BipScore ret = value._1(); + ret.setId(value._2().getId()); + return ret; + }, Encoders.bean(BipScore.class)); + + tmp.groupByKey((MapFunction) value -> value.getId(), Encoders.STRING()) + .mapGroups((MapGroupsFunction) (k, it) -> + { + Result ret = inputClazz.newInstance(); + BipScore first = it.next(); + ret.setId(first.getId()); + + ret.setMeasures(getMeasure(first)); + it.forEachRemaining(value -> ret.getMeasures().addAll(getMeasure(value))); + + return (I)ret; + }, Encoders.bean(inputClazz)) + .toJavaRDD() + .map(p -> new AtomicAction(inputClazz, p)) + .mapToPair( + aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()), + new Text(OBJECT_MAPPER.writeValueAsString(aa)))) + .saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class); + ; + } + + public static Dataset getBipScoreDataset(Dataset bipdeserialized){ + return bipdeserialized.flatMap((FlatMapFunction) bip -> + bip.keySet().stream().map(key -> { + BipScore bs = new BipScore(); + bs.setId(key); + bs.setScoreList(bip.get(key)); + return bs; + }).collect(Collectors.toList()).iterator() + , Encoders.bean(BipScore.class)); + } + + private static List getMeasure(BipScore value) { + return value.getScoreList() + .stream() + .map(score -> { + Measure m = new Measure(); + m.setId(score.getId()); + m.setUnit(score.getUnit().stream() + .map(unit -> { + KeyValue kv = new KeyValue(); + kv.setValue(unit.getValue()); + kv.setKey(unit.getKey()); + kv.setDataInfo(getDataInfo()); + return kv; + }).collect(Collectors.toList())); + return m; + }).collect(Collectors.toList()); + } + + + + private static DataInfo getDataInfo() { + DataInfo di = new DataInfo(); + di.setInferred(false); + di.setInvisible(false); + di.setDeletedbyinference(false); + di.setTrust(""); + Qualifier qualifier = new Qualifier(); + qualifier.setClassid("sysimport:actionset"); + qualifier.setClassname("Harvested"); + qualifier.setSchemename("dnet:provenanceActions"); + qualifier.setSchemeid("dnet:provenanceActions"); + di.setProvenanceaction(qualifier); + return di; + } + + + private static void removeOutputDir(SparkSession spark, String path) { + HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration()); + } + + public static Dataset readPath( + SparkSession spark, String inputPath, Class clazz) { + return spark + .read() + .textFile(inputPath) + .map((MapFunction) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz)); + } + + +} diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json new file mode 100644 index 0000000000..ae844a0c9c --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json @@ -0,0 +1,32 @@ +[ + { + "paramName": "issm", + "paramLongName": "isSparkSessionManaged", + "paramDescription": "when true will stop SparkSession after job execution", + "paramRequired": false +}, +{ +"paramName": "ip", +"paramLongName": "inputPath", +"paramDescription": "the URL from where to get the programme file", +"paramRequired": true +}, +{ +"paramName": "o", +"paramLongName": "outputPath", +"paramDescription": "the path of the new ActionSet", +"paramRequired": true +}, + { + "paramName": "rtn", + "paramLongName": "resultTableName", + "paramDescription": "the path of the new ActionSet", + "paramRequired": true + }, + { + "paramName": "bsp", + "paramLongName": "bipScorePath", + "paramDescription": "the path of the new ActionSet", + "paramRequired": true + } +] \ No newline at end of file diff --git a/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java b/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java new file mode 100644 index 0000000000..64518234e3 --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java @@ -0,0 +1,160 @@ +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import com.fasterxml.jackson.databind.ObjectMapper; +import eu.dnetlib.dhp.schema.action.AtomicAction; +import eu.dnetlib.dhp.schema.oaf.*; +import eu.dnetlib.dhp.schema.oaf.KeyValue; +import org.apache.commons.io.FileUtils; +import org.apache.hadoop.io.Text; +import org.apache.hadoop.mapred.SequenceFileOutputFormat; +import org.apache.spark.SparkConf; +import org.apache.spark.api.java.JavaRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.FilterFunction; +import org.apache.spark.api.java.function.ForeachFunction; +import org.apache.spark.api.java.function.MapFunction; +import org.apache.spark.api.java.function.MapGroupsFunction; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Encoders; +import org.apache.spark.sql.SparkSession; +import org.junit.jupiter.api.AfterAll; +import org.junit.jupiter.api.Assertions; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.Test; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; +import scala.Tuple2; + +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.List; +import java.util.stream.Collectors; + +public class SparkAtomicActionScoreJobTest { + + private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); + + private static SparkSession spark; + + private static Path workingDir; + private static final Logger log = LoggerFactory + .getLogger(SparkAtomicActionScoreJobTest.class); + + @BeforeAll + public static void beforeAll() throws IOException { + workingDir = Files + .createTempDirectory(SparkAtomicActionScoreJobTest.class.getSimpleName()); + log.info("using work dir {}", workingDir); + + SparkConf conf = new SparkConf(); + conf.setAppName(SparkAtomicActionScoreJobTest.class.getSimpleName()); + + conf.setMaster("local[*]"); + conf.set("spark.driver.host", "localhost"); + conf.set("hive.metastore.local", "true"); + conf.set("spark.ui.enabled", "false"); + conf.set("spark.sql.warehouse.dir", workingDir.toString()); + conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString()); + + spark = SparkSession + .builder() + .appName(SparkAtomicActionScoreJobTest.class.getSimpleName()) + .config(conf) + .getOrCreate(); + } + + @AfterAll + public static void afterAll() throws IOException { + FileUtils.deleteDirectory(workingDir.toFile()); + spark.stop(); + } + + @Test + public void numberDistinctProjectTest() throws Exception { + String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); + String inputPath = getClass() + .getResource( + "/eu/dnetlib/dhp/actionmanager/bipfinder/publication.json") + .getPath(); + + SparkAtomicActionScoreJob.main( + new String[] { + "-isSparkSessionManaged", + Boolean.FALSE.toString(), + "-inputPath", + inputPath, + "-bipScorePath", + bipScoresPath, + "-resultTableName", + "eu.dnetlib.dhp.schema.oaf.Publication", + "-outputPath", + workingDir.toString() + "/actionSet" + }); + + + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + + JavaRDD tmp = sc + .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) + .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) + .map(aa -> ((Publication) aa.getPayload())); + + Assertions.assertTrue(tmp.count() == 1); + +// Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); +// verificationDataset.createOrReplaceTempView("project"); + +// Dataset execverification = spark +// .sql( +// "SELECT id, class classification, h2020topiccode, h2020topicdescription FROM project LATERAL VIEW EXPLODE(h2020classification) c as class "); +// +// Assertions +// .assertEquals( +// "H2020-EU.3.4.7.", +// execverification +// .filter("id = '40|corda__h2020::2c7298913008865ba784e5c1350a0aa5'") +// .select("classification.h2020Programme.code") +// .collectAsList() +// .get(0) +// .getString(0)); + + + + + } + + private static List getMeasure(BipScore value) { + return value.getScoreList() + .stream() + .map(score -> { + Measure m = new Measure(); + m.setId(score.getId()); + m.setUnit(score.getUnit().stream() + .map(unit -> { + eu.dnetlib.dhp.schema.oaf.KeyValue kv = new KeyValue(); + kv.setValue(unit.getValue()); + kv.setKey(unit.getKey()); + kv.setDataInfo(getDataInfo()); + return kv; + }).collect(Collectors.toList())); + return m; + }).collect(Collectors.toList()); + } + + + private static DataInfo getDataInfo() { + DataInfo di = new DataInfo(); + di.setInferred(false); + di.setInvisible(false); + di.setDeletedbyinference(false); + di.setTrust(""); + Qualifier qualifier = new Qualifier(); + qualifier.setClassid("sysimport:actionset"); + qualifier.setClassname("Harvested"); + qualifier.setSchemename("dnet:provenanceActions"); + qualifier.setSchemeid("dnet:provenanceActions"); + di.setProvenanceaction(qualifier); + return di; + } +} diff --git a/dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json b/dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json new file mode 100644 index 0000000000..a4f3fa8b82 --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json @@ -0,0 +1,1101 @@ +{"10.1001/10-v4n2-hsf10003": [{"id": "influence", "unit": [{"value": "1.62759106106e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "0.22519296", "key": "score"}]}]} +{"10.1001/2012.jama.10456": [{"id": "influence", "unit": [{"value": "1.66083991022e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "0.8690688", "key": "score"}]}]} +{"10.1001/2013.jamadermatol.729": [{"id": "influence", "unit": [{"value": "2.0769133069e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "0.0279936", "key": "score"}]}]} +{"10.1001/archderm.107.6.853": [{"id": "influence", "unit": [{"value": "1.95361113607e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "0.600657255944", "key": "score"}]}]} +{"10.1001/archderm.1926.02370130020002": [{"id": "influence", "unit": [{"value": "1.48611319422e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "8.20903253662e-16", "key": "score"}]}]} +{"10.1001/archpediatrics.2012.157": [{"id": "influence", "unit": [{"value": "1.42089114725e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "0.1575936", "key": "score"}]}]} +{"10.1002/bjs.1800830139": [{"id": "influence", "unit": [{"value": "3.73834652128e-08", "key": "score"}]}, {"id": "popularity", "unit": [{"value": "1.73174997252", "key": "score"}]}]} 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Ce qui nous frappe en premier lieu dans le roman de Melchior Mbonimpa, Le Totem des Baranda, c'est l'efficacité de sa fonction didactique. Le livre est porteur d'un message, d'une vision sur l'histoire de l'Afrique des Grands Lacs qu'on rencontre rarement dans l'actualité ou l'histoire immédiate que nous livrent les médias.

Cette thèse se penchera sur un aspect de ce roman qui a particulièrement attiré notre attention: la représentation de la résistance à travers l'affirmation identitaire des personnages féminins. Dans notre analyse de ce thème, nous accordons une grande importance au contexte socioculturel et à l'imaginaire collectif qui nourrissent l'auteur et dans lesquels s'inscrivent ses personnages. L'étude soulignera la fonction sociale de l'écrivain et relèvera la contribution de la fiction à la culture africaine. Nous mettrons en évidence les positions idéologiques de l'auteur et le message de sensibilisation qu'il adresse à diverses catégories de lecteurs: ceux qui se trouvent en Afrique, les Africains de la diaspora, et les lecteurs non-Africains qui s'intéressent à son œuvre. Cette orientation idéologique affecte évidemment la manière dont s'exprime la résistance des pnncIpaux personnages féminins du roman. Elle détermine la place que cette fiction accorde à la femme, et qui correspond sans doute à la place que, selon les souhaits de l'auteur, la femme devrait occuper dans le contexte culturel africain. Notre étude insiste aussi sur le fait que dans ce roman, la modernité se nourrit de la culture traditionnelle et ne renie pas les valeurs du passé.

Ainsi, le parcours narratif montre que dans leur résistance, les héroïnes de la généalogie vivent à leur époque, mais chacune porte plus loin une mission transmise par les précédentes.

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The superconducting transition in the magnetic resistance of members of the family of bismuth based high temperature superconductors was investigated. Measurements were performed in magnetic fields up to 1.7 T. Small current densities ranging from 0.03 A/cm² to 3.0 A/cm² were applied. The resistivity of Bi₂Sr₂CaCu₂Ox single crystals was analyzed in terms of the thermally activated flux flow expression, ρ =ρ₀U/T exp(-U/T) where T is the temperature. It was found that the activation energy was given by Uα(Hsinθ)^(⁻α) where α≈1/3 and that the prefactor had the form, ρ₀Hsinθ, where H was the applied field and θ the angle of the field with respect to the CuO₂ planes. Results demonstrated that dissipation could be accounted for by the motion of two-dimensional vortices whose density is given by the field, Hsinθ, projected on the CuO₂ planes. Measurements of the resistivity and current dependent resistivity were performed with two Sn-doped and two Sb-doped polycrystalline Bi(1.7)Pb(0.3)Sr₂Ca₂Cu₃O(y) samples. Features in the temperature derivative of the resistivity curves were associated with the presence of a superconducting transition between superconducting grains, coupled by weak links with a distribution of critical currents and critical temperatures, and the superconducting transition within grains. The transition between grains was more strongly suppressed in temperature with the application of a magnetic field in samples with weaker coupling between grains. The presence of a transition in a magnetic field due to weak links between grains was verified at 77 K by the observation of a current dependent resistivity in a magnetic field. Measurements of a Bi₂Sr₂CaCu₂Ox diffusion grown thick film ring were done. The transverse voltage, the voltage at the centre of a 120 μm thick branch with respect to the centre of a 76 μm thick branch, was measured. A higher critical temperature from the presence of more texturing in the 76 μm branch as determined by separate resistivity, x-ray and scanning electron microscopy measurements was consistent with the measurement of a crossover from a negative to positive transverse voltage as the temperature of the sample went through its superconducting transition.

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This study examines Leonard Cohen's novel Beautiful Losers through the lenses of allegorical and authorial theories to appreciate how the novel uses allegorical techniques to code into symbolic terms an exploration of the polysemous nature of the word ''translation.'' The first chapter studies the stylistic and conceptual dimensions of allegory as a literary genre - as critics like Northrop Frye, Angus Fletchet, and Maureen Quilligan help to define it - while arguing that Cohen's novel is consciously allegorical, challenging readers to interpret what it \"means,\" or may mean. The second chapter performs an intensive re-reading of Beautiful Losers, examining how the novel uses complex systems of verbal play (particularly puns) to coordinate a reunification of various dichotomies historical \"reality\"/imaginative myth, secularity/spirituality, enslavement/sanctification, among others - employed throughout the text. The thesis concludes that the novel is perpetually playing with various types of translation (spiritual, linguistic, physical, and so forth), affirming the need for emotionally-charged, devotional forms of expression (like song and prayer) over more clinical attempts to reorder or recreate the world and its inhabitants. Ultimately, this discussion argues that an understanding of the allegorical dimensions of Beautiful Losers may illuminate how Cohen's other works (particularly his songs) may be studied as attempts to associate word with voice, to emphasize the process of expression (translation) rather than just the finished product.

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La NDI a été étudiée dans le cas de diverses applications, y compris en aéronautique et en aérospatiale. Elle permet de calculer des lois de contrôle capables de linéariser et de découpler un modèle non-linéaire à tout point de fonctionnement de son enveloppe d'état. Cependant cette méthode est intrinsèquement non-robuste aux erreurs de modélisation et aux saturations en entrée. En outre, dans un contexte non-linéaire, l'obtention d'une garantie quantifiable du domaine de stabilité atteint reste à l'heure actuelle complexe. Contrairement aux approches classiques de la NDI, notre méthodologie peut être considérée comme un cadre de compensation non-linéaire généralisé qui permet d'intégrer les incertitudes et les saturations en entrée dans le processus de conception. En utilisant des stratégies de contrôle antiwindup, la loi de pilotage peut être calculée grâce à un simple processus en deux phases. Dans ce cadre de travail généralisé des transformations linéaires fractionnaires (LFT - Linear Fractional Transformations) de la boucle fermée non-linéaire peuvent être facilement déduites pour l'analyse de la stabilité robuste en utilisant des outils standards pour de systèmes linéaires. La méthode proposée est testée pour le pilotage d'un véhicule de rentrée atmosphérique de type aile delta lors de ses phases hypersonique, transsonique et subsonique. Pour cette thèse, un simulateur du vol incluant divers facteurs externes ainsi que des erreurs de modélisation a été développé dans Simulink.\n\nThis thesis work is devoted to extending Nonlinear Dynamic Inversion (NDI) for a large scale of\nnonlinear systems while guaranteeing sufficient stability conditions. NDI has been studied in a wide range of applications, including aeronautics and aerospace. It allows to compute nonlinear control laws able to decouple and linearize a model at any operating point of its state envelope. However, this method is inherently non-robust to modelling errors and input saturations. Moreover, obtaining a quantifiable guarantee of the attained stability domain in a nonlinear control context is not a very straightforward task. Unlike standard NDI approaches, our methodology can be viewed as a generalized nonlinear compensation framework which allows to incorporate uncertainties and input saturations in the design process. Paralleling anti-windup strategies, the controller can be computed through a single multichannel optimization problem or through a simple two-step process. Within this framework, linear fractional transformations of the nonlinear closed-loop can be easily derived for robust stability analysis using standard tools for linear systems. The proposed method is tested for the flight control of a delta wing type reentry vehicle at hypersonic, transonic and subsonic phases of the atmospheric reentry. For this thesis work, a Flight Mechanics simulator including diverse external factors and modelling errors was developed in Simulink."}],"externalReference":[],"extraInfo":[],"format":[],"fulltext":[],"id":"50|artemis___fr::630e47d8b572e3df0e91327d6d8f036d","instance":[{"accessright":{"classid":"OPEN","classname":"Open Access","schemeid":"dnet:access_modes","schemename":"dnet:access_modes"},"collectedfrom":{"key":"10|driver______::66c20c26ac26136628f5207819ae1abc","value":"Archives des thèses et mémoires de l’ISAE (ArTeMIS)"},"dateofacceptance":{"dataInfo":{"deletedbyinference":false,"inferenceprovenance":"","inferred":false,"invisible":false,"provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"Harvested","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"},"trust":"0.9"},"value":"2012-09-21"},"distributionlocation":"","hostedby":{"key":"10|driver______::66c20c26ac26136628f5207819ae1abc","value":"Archives des thèses et mémoires de l’ISAE 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b/dhp-schemas/src/main/java/eu/dnetlib/dhp/schema/oaf/Measure.java index c0c14d10de..78a4c68015 100644 --- a/dhp-schemas/src/main/java/eu/dnetlib/dhp/schema/oaf/Measure.java +++ b/dhp-schemas/src/main/java/eu/dnetlib/dhp/schema/oaf/Measure.java @@ -1,6 +1,7 @@ package eu.dnetlib.dhp.schema.oaf; +import java.io.Serializable; import java.util.List; import com.google.common.base.Objects; @@ -8,7 +9,7 @@ import com.google.common.base.Objects; /** * Represent a measure, must be further described by a system available resource providing name and descriptions. */ -public class Measure { +public class Measure implements Serializable { /** * Unique measure identifier. @@ -16,7 +17,7 @@ public class Measure { private String id; /** - * List of units associated with this measure. KeyValue provides a pair to store the laber (key) and the value, plus + * List of units associated with this measure. KeyValue provides a pair to store the label (key) and the value, plus * common provenance information. */ private List unit; From 719da15f04356d550ce162e8328644fd4fb021bc Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 12:42:30 +0100 Subject: [PATCH 03/10] added test resources --- .../actionmanager/bipfinder/publication_2.json | 18 ++++++++++++++++++ .../actionmanager/bipfinder/publication_3.json | 18 ++++++++++++++++++ 2 files changed, 36 insertions(+) create mode 100644 dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/publication_2.json create mode 100644 dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/publication_3.json diff --git a/dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/publication_2.json b/dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/actionmanager/bipfinder/publication_2.json new file mode 100644 index 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Ce qui nous frappe en premier lieu dans le roman de Melchior Mbonimpa, Le Totem des Baranda, c'est l'efficacité de sa fonction didactique. Le livre est porteur d'un message, d'une vision sur l'histoire de l'Afrique des Grands Lacs qu'on rencontre rarement dans l'actualité ou l'histoire immédiate que nous livrent les médias.

Cette thèse se penchera sur un aspect de ce roman qui a particulièrement attiré notre attention: la représentation de la résistance à travers l'affirmation identitaire des personnages féminins. Dans notre analyse de ce thème, nous accordons une grande importance au contexte socioculturel et à l'imaginaire collectif qui nourrissent l'auteur et dans lesquels s'inscrivent ses personnages. L'étude soulignera la fonction sociale de l'écrivain et relèvera la contribution de la fiction à la culture africaine. Nous mettrons en évidence les positions idéologiques de l'auteur et le message de sensibilisation qu'il adresse à diverses catégories de lecteurs: ceux qui se trouvent en Afrique, les Africains de la diaspora, et les lecteurs non-Africains qui s'intéressent à son œuvre. Cette orientation idéologique affecte évidemment la manière dont s'exprime la résistance des pnncIpaux personnages féminins du roman. Elle détermine la place que cette fiction accorde à la femme, et qui correspond sans doute à la place que, selon les souhaits de l'auteur, la femme devrait occuper dans le contexte culturel africain. Notre étude insiste aussi sur le fait que dans ce roman, la modernité se nourrit de la culture traditionnelle et ne renie pas les valeurs du passé.

Ainsi, le parcours narratif montre que dans leur résistance, les héroïnes de la généalogie vivent à leur époque, mais chacune porte plus loin une mission transmise par les précédentes.

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The superconducting transition in the magnetic resistance of members of the family of bismuth based high temperature superconductors was investigated. Measurements were performed in magnetic fields up to 1.7 T. Small current densities ranging from 0.03 A/cm² to 3.0 A/cm² were applied. The resistivity of Bi₂Sr₂CaCu₂Ox single crystals was analyzed in terms of the thermally activated flux flow expression, ρ =ρ₀U/T exp(-U/T) where T is the temperature. It was found that the activation energy was given by Uα(Hsinθ)^(⁻α) where α≈1/3 and that the prefactor had the form, ρ₀Hsinθ, where H was the applied field and θ the angle of the field with respect to the CuO₂ planes. Results demonstrated that dissipation could be accounted for by the motion of two-dimensional vortices whose density is given by the field, Hsinθ, projected on the CuO₂ planes. Measurements of the resistivity and current dependent resistivity were performed with two Sn-doped and two Sb-doped polycrystalline Bi(1.7)Pb(0.3)Sr₂Ca₂Cu₃O(y) samples. Features in the temperature derivative of the resistivity curves were associated with the presence of a superconducting transition between superconducting grains, coupled by weak links with a distribution of critical currents and critical temperatures, and the superconducting transition within grains. The transition between grains was more strongly suppressed in temperature with the application of a magnetic field in samples with weaker coupling between grains. The presence of a transition in a magnetic field due to weak links between grains was verified at 77 K by the observation of a current dependent resistivity in a magnetic field. Measurements of a Bi₂Sr₂CaCu₂Ox diffusion grown thick film ring were done. The transverse voltage, the voltage at the centre of a 120 μm thick branch with respect to the centre of a 76 μm thick branch, was measured. A higher critical temperature from the presence of more texturing in the 76 μm branch as determined by separate resistivity, x-ray and scanning electron microscopy measurements was consistent with the measurement of a crossover from a negative to positive transverse voltage as the temperature of the sample went through its superconducting transition.

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This study examines Leonard Cohen's novel Beautiful Losers through the lenses of allegorical and authorial theories to appreciate how the novel uses allegorical techniques to code into symbolic terms an exploration of the polysemous nature of the word ''translation.'' The first chapter studies the stylistic and conceptual dimensions of allegory as a literary genre - as critics like Northrop Frye, Angus Fletchet, and Maureen Quilligan help to define it - while arguing that Cohen's novel is consciously allegorical, challenging readers to interpret what it \"means,\" or may mean. The second chapter performs an intensive re-reading of Beautiful Losers, examining how the novel uses complex systems of verbal play (particularly puns) to coordinate a reunification of various dichotomies historical \"reality\"/imaginative myth, secularity/spirituality, enslavement/sanctification, among others - employed throughout the text. The thesis concludes that the novel is perpetually playing with various types of translation (spiritual, linguistic, physical, and so forth), affirming the need for emotionally-charged, devotional forms of expression (like song and prayer) over more clinical attempts to reorder or recreate the world and its inhabitants. Ultimately, this discussion argues that an understanding of the allegorical dimensions of Beautiful Losers may illuminate how Cohen's other works (particularly his songs) may be studied as attempts to associate word with voice, to emphasize the process of expression (translation) rather than just the finished product.

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La NDI a été étudiée dans le cas de diverses applications, y compris en aéronautique et en aérospatiale. Elle permet de calculer des lois de contrôle capables de linéariser et de découpler un modèle non-linéaire à tout point de fonctionnement de son enveloppe d'état. Cependant cette méthode est intrinsèquement non-robuste aux erreurs de modélisation et aux saturations en entrée. En outre, dans un contexte non-linéaire, l'obtention d'une garantie quantifiable du domaine de stabilité atteint reste à l'heure actuelle complexe. Contrairement aux approches classiques de la NDI, notre méthodologie peut être considérée comme un cadre de compensation non-linéaire généralisé qui permet d'intégrer les incertitudes et les saturations en entrée dans le processus de conception. En utilisant des stratégies de contrôle antiwindup, la loi de pilotage peut être calculée grâce à un simple processus en deux phases. Dans ce cadre de travail généralisé des transformations linéaires fractionnaires (LFT - Linear Fractional Transformations) de la boucle fermée non-linéaire peuvent être facilement déduites pour l'analyse de la stabilité robuste en utilisant des outils standards pour de systèmes linéaires. La méthode proposée est testée pour le pilotage d'un véhicule de rentrée atmosphérique de type aile delta lors de ses phases hypersonique, transsonique et subsonique. Pour cette thèse, un simulateur du vol incluant divers facteurs externes ainsi que des erreurs de modélisation a été développé dans Simulink.\n\nThis thesis work is devoted to extending Nonlinear Dynamic Inversion (NDI) for a large scale of\nnonlinear systems while guaranteeing sufficient stability conditions. NDI has been studied in a wide range of applications, including aeronautics and aerospace. It allows to compute nonlinear control laws able to decouple and linearize a model at any operating point of its state envelope. 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central problem for the function and manufacture of materials where performance relies on nanoscale structure is to control the compatibility and interactions of the building blocks. 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Ce qui nous frappe en premier lieu dans le roman de Melchior Mbonimpa, Le Totem des Baranda, c'est l'efficacité de sa fonction didactique. Le livre est porteur d'un message, d'une vision sur l'histoire de l'Afrique des Grands Lacs qu'on rencontre rarement dans l'actualité ou l'histoire immédiate que nous livrent les médias.

Cette thèse se penchera sur un aspect de ce roman qui a particulièrement attiré notre attention: la représentation de la résistance à travers l'affirmation identitaire des personnages féminins. Dans notre analyse de ce thème, nous accordons une grande importance au contexte socioculturel et à l'imaginaire collectif qui nourrissent l'auteur et dans lesquels s'inscrivent ses personnages. L'étude soulignera la fonction sociale de l'écrivain et relèvera la contribution de la fiction à la culture africaine. Nous mettrons en évidence les positions idéologiques de l'auteur et le message de sensibilisation qu'il adresse à diverses catégories de lecteurs: ceux qui se trouvent en Afrique, les Africains de la diaspora, et les lecteurs non-Africains qui s'intéressent à son œuvre. Cette orientation idéologique affecte évidemment la manière dont s'exprime la résistance des pnncIpaux personnages féminins du roman. Elle détermine la place que cette fiction accorde à la femme, et qui correspond sans doute à la place que, selon les souhaits de l'auteur, la femme devrait occuper dans le contexte culturel africain. Notre étude insiste aussi sur le fait que dans ce roman, la modernité se nourrit de la culture traditionnelle et ne renie pas les valeurs du passé.

Ainsi, le parcours narratif montre que dans leur résistance, les héroïnes de la généalogie vivent à leur époque, mais chacune porte plus loin une mission transmise par les précédentes.

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The superconducting transition in the magnetic resistance of members of the family of bismuth based high temperature superconductors was investigated. Measurements were performed in magnetic fields up to 1.7 T. Small current densities ranging from 0.03 A/cm² to 3.0 A/cm² were applied. The resistivity of Bi₂Sr₂CaCu₂Ox single crystals was analyzed in terms of the thermally activated flux flow expression, ρ =ρ₀U/T exp(-U/T) where T is the temperature. It was found that the activation energy was given by Uα(Hsinθ)^(⁻α) where α≈1/3 and that the prefactor had the form, ρ₀Hsinθ, where H was the applied field and θ the angle of the field with respect to the CuO₂ planes. Results demonstrated that dissipation could be accounted for by the motion of two-dimensional vortices whose density is given by the field, Hsinθ, projected on the CuO₂ planes. Measurements of the resistivity and current dependent resistivity were performed with two Sn-doped and two Sb-doped polycrystalline Bi(1.7)Pb(0.3)Sr₂Ca₂Cu₃O(y) samples. Features in the temperature derivative of the resistivity curves were associated with the presence of a superconducting transition between superconducting grains, coupled by weak links with a distribution of critical currents and critical temperatures, and the superconducting transition within grains. The transition between grains was more strongly suppressed in temperature with the application of a magnetic field in samples with weaker coupling between grains. The presence of a transition in a magnetic field due to weak links between grains was verified at 77 K by the observation of a current dependent resistivity in a magnetic field. Measurements of a Bi₂Sr₂CaCu₂Ox diffusion grown thick film ring were done. The transverse voltage, the voltage at the centre of a 120 μm thick branch with respect to the centre of a 76 μm thick branch, was measured. A higher critical temperature from the presence of more texturing in the 76 μm branch as determined by separate resistivity, x-ray and scanning electron microscopy measurements was consistent with the measurement of a crossover from a negative to positive transverse voltage as the temperature of the sample went through its superconducting transition.

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This study examines Leonard Cohen's novel Beautiful Losers through the lenses of allegorical and authorial theories to appreciate how the novel uses allegorical techniques to code into symbolic terms an exploration of the polysemous nature of the word ''translation.'' The first chapter studies the stylistic and conceptual dimensions of allegory as a literary genre - as critics like Northrop Frye, Angus Fletchet, and Maureen Quilligan help to define it - while arguing that Cohen's novel is consciously allegorical, challenging readers to interpret what it \"means,\" or may mean. The second chapter performs an intensive re-reading of Beautiful Losers, examining how the novel uses complex systems of verbal play (particularly puns) to coordinate a reunification of various dichotomies historical \"reality\"/imaginative myth, secularity/spirituality, enslavement/sanctification, among others - employed throughout the text. The thesis concludes that the novel is perpetually playing with various types of translation (spiritual, linguistic, physical, and so forth), affirming the need for emotionally-charged, devotional forms of expression (like song and prayer) over more clinical attempts to reorder or recreate the world and its inhabitants. Ultimately, this discussion argues that an understanding of the allegorical dimensions of Beautiful Losers may illuminate how Cohen's other works (particularly his songs) may be studied as attempts to associate word with voice, to emphasize the process of expression (translation) rather than just the finished product.

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Dans ce cadre de travail généralisé des transformations linéaires fractionnaires (LFT - Linear Fractional Transformations) de la boucle fermée non-linéaire peuvent être facilement déduites pour l'analyse de la stabilité robuste en utilisant des outils standards pour de systèmes linéaires. La méthode proposée est testée pour le pilotage d'un véhicule de rentrée atmosphérique de type aile delta lors de ses phases hypersonique, transsonique et subsonique. Pour cette thèse, un simulateur du vol incluant divers facteurs externes ainsi que des erreurs de modélisation a été développé dans Simulink.\n\nThis thesis work is devoted to extending Nonlinear Dynamic Inversion (NDI) for a large scale of\nnonlinear systems while guaranteeing sufficient stability conditions. NDI has been studied in a wide range of applications, including aeronautics and aerospace. It allows to compute nonlinear control laws able to decouple and linearize a model at any operating point of its state envelope. 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reentry"},{"dataInfo":{"deletedbyinference":false,"inferenceprovenance":"","inferred":false,"invisible":false,"provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"Harvested","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"},"trust":"0.9"},"qualifier":{"classid":"keyword","classname":"keyword","schemeid":"dnet:result_subject","schemename":"dnet:result_subject"},"value":"629.8"}],"title":[{"dataInfo":{"deletedbyinference":false,"inferenceprovenance":"","inferred":false,"invisible":false,"provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"Harvested","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"},"trust":"0.9"},"qualifier":{"classid":"main title","classname":"main title","schemeid":"dnet:dataCite_title","schemename":"dnet:dataCite_title"},"value":"Cadre de travail généralisé de compensation non-linéaire robuste : application à la rentrée atmosphérique"},{"dataInfo":{"deletedbyinference":false,"inferenceprovenance":"","inferred":false,"invisible":false,"provenanceaction":{"classid":"sysimport:crosswalk:repository","classname":"Harvested","schemeid":"dnet:provenanceActions","schemename":"dnet:provenanceActions"},"trust":"0.9"},"qualifier":{"classid":"main title","classname":"main title","schemeid":"dnet:dataCite_title","schemename":"dnet:dataCite_title"},"value":"A generalized framework for robust nonlinear compensation : application to an atmospheric reentry control problem"}]} \ No newline at end of file From 0051ebede575a5effa945e8ec9813c52f3ff6356 Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 12:43:03 +0100 Subject: [PATCH 04/10] extending test --- .../SparkAtomicActionScoreJobTest.java | 196 ++++++++++++++---- 1 file changed, 150 insertions(+), 46 deletions(-) diff --git a/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java b/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java index 64518234e3..3b360f6edc 100644 --- a/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java +++ b/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java @@ -16,6 +16,7 @@ import org.apache.spark.api.java.function.MapFunction; import org.apache.spark.api.java.function.MapGroupsFunction; import org.apache.spark.sql.Dataset; import org.apache.spark.sql.Encoders; +import org.apache.spark.sql.Row; import org.apache.spark.sql.SparkSession; import org.junit.jupiter.api.AfterAll; import org.junit.jupiter.api.Assertions; @@ -71,7 +72,7 @@ public class SparkAtomicActionScoreJobTest { } @Test - public void numberDistinctProjectTest() throws Exception { + public void matchOne() throws Exception { String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); String inputPath = getClass() .getResource( @@ -102,59 +103,162 @@ public class SparkAtomicActionScoreJobTest { Assertions.assertTrue(tmp.count() == 1); -// Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); -// verificationDataset.createOrReplaceTempView("project"); + Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); + verificationDataset.createOrReplaceTempView("publication"); -// Dataset execverification = spark -// .sql( -// "SELECT id, class classification, h2020topiccode, h2020topicdescription FROM project LATERAL VIEW EXPLODE(h2020classification) c as class "); -// -// Assertions -// .assertEquals( -// "H2020-EU.3.4.7.", -// execverification -// .filter("id = '40|corda__h2020::2c7298913008865ba784e5c1350a0aa5'") -// .select("classification.h2020Programme.code") -// .collectAsList() -// .get(0) -// .getString(0)); + Dataset execVerification = spark.sql("Select p.id oaid, mes.id, mUnit.value from publication p " + + "lateral view explode(measures) m as mes " + + "lateral view explode(mes.unit) u as mUnit "); + + Assertions.assertEquals(2, execVerification.count()); + + Assertions.assertEquals("50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb", + execVerification.select("oaid").collectAsList().get(0).getString(0)); + + Assertions.assertEquals("1.47565045883e-08", + execVerification.filter("id = 'influence'").select("value").collectAsList().get(0).getString(0)); + + Assertions.assertEquals("0.227515392", + execVerification.filter("id = 'popularity'").select("value").collectAsList().get(0).getString(0)); + + } + + @Test + public void matchOneWithTwo() throws Exception { + String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); + String inputPath = getClass() + .getResource( + "/eu/dnetlib/dhp/actionmanager/bipfinder/publication_2.json") + .getPath(); + + SparkAtomicActionScoreJob.main( + new String[] { + "-isSparkSessionManaged", + Boolean.FALSE.toString(), + "-inputPath", + inputPath, + "-bipScorePath", + bipScoresPath, + "-resultTableName", + "eu.dnetlib.dhp.schema.oaf.Publication", + "-outputPath", + workingDir.toString() + "/actionSet" + }); + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + + JavaRDD tmp = sc + .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) + .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) + .map(aa -> ((Publication) aa.getPayload())); + + Assertions.assertTrue(tmp.count() == 1); + + Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); + verificationDataset.createOrReplaceTempView("publication"); + + Dataset execVerification = spark.sql("Select p.id oaid, mes.id, mUnit.value from publication p " + + "lateral view explode(measures) m as mes " + + "lateral view explode(mes.unit) u as mUnit "); + + Assertions.assertEquals(4, execVerification.count()); + + + Assertions.assertEquals("50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb", + execVerification.select("oaid").collectAsList().get(0).getString(0)); + + Assertions.assertEquals(2, + execVerification.filter("id = 'influence'").count()); + + Assertions.assertEquals(2, + execVerification.filter("id = 'popularity'").count()); + + List tmp_ds = execVerification.filter("id = 'influence'").select("value").collectAsList(); + String tmp_influence = tmp_ds.get(0).getString(0); + Assertions.assertTrue("1.47565045883e-08".equals(tmp_influence)|| + "1.98956540239e-08".equals(tmp_influence) ); + + tmp_influence = tmp_ds.get(1).getString(0); + Assertions.assertTrue("1.47565045883e-08".equals(tmp_influence)|| + "1.98956540239e-08".equals(tmp_influence) ); + + Assertions.assertTrue(!tmp_ds.get(0).getString(0).equals(tmp_ds.get(1).getString(0))); } - private static List getMeasure(BipScore value) { - return value.getScoreList() - .stream() - .map(score -> { - Measure m = new Measure(); - m.setId(score.getId()); - m.setUnit(score.getUnit().stream() - .map(unit -> { - eu.dnetlib.dhp.schema.oaf.KeyValue kv = new KeyValue(); - kv.setValue(unit.getValue()); - kv.setKey(unit.getKey()); - kv.setDataInfo(getDataInfo()); - return kv; - }).collect(Collectors.toList())); - return m; - }).collect(Collectors.toList()); - } + @Test + public void matchTwo() throws Exception { + String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); + String inputPath = getClass() + .getResource( + "/eu/dnetlib/dhp/actionmanager/bipfinder/publication_3.json") + .getPath(); + + SparkAtomicActionScoreJob.main( + new String[] { + "-isSparkSessionManaged", + Boolean.FALSE.toString(), + "-inputPath", + inputPath, + "-bipScorePath", + bipScoresPath, + "-resultTableName", + "eu.dnetlib.dhp.schema.oaf.Publication", + "-outputPath", + workingDir.toString() + "/actionSet" + }); - private static DataInfo getDataInfo() { - DataInfo di = new DataInfo(); - di.setInferred(false); - di.setInvisible(false); - di.setDeletedbyinference(false); - di.setTrust(""); - Qualifier qualifier = new Qualifier(); - qualifier.setClassid("sysimport:actionset"); - qualifier.setClassname("Harvested"); - qualifier.setSchemename("dnet:provenanceActions"); - qualifier.setSchemeid("dnet:provenanceActions"); - di.setProvenanceaction(qualifier); - return di; + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + + JavaRDD tmp = sc + .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) + .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) + .map(aa -> ((Publication) aa.getPayload())); + + Assertions.assertTrue(tmp.count() == 2); + + Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); + verificationDataset.createOrReplaceTempView("publication"); + + Dataset execVerification = spark.sql("Select p.id oaid, mes.id, mUnit.value from publication p " + + "lateral view explode(measures) m as mes " + + "lateral view explode(mes.unit) u as mUnit "); + + Assertions.assertEquals(4, execVerification.count()); + + + Assertions.assertEquals(2, + execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb'").count()); + + Assertions.assertEquals(2, + execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09'").count()); + + + Assertions.assertEquals(2, + execVerification.filter("id = 'influence'").count()); + + Assertions.assertEquals(2, + execVerification.filter("id = 'popularity'").count()); + + Assertions.assertEquals("1.47565045883e-08" , + execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb' " + + "and id = 'influence'").select("value").collectAsList().get(0).getString(0)); + + Assertions.assertEquals( + "1.98956540239e-08", execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09' " + + "and id = 'influence'").select("value").collectAsList().get(0).getString(0)); + + Assertions.assertEquals( + "0.282046161584", execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09' " + + "and id = 'popularity'").select("value").collectAsList().get(0).getString(0)); + + Assertions.assertEquals("0.227515392" , + execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb' " + + "and id = 'popularity'").select("value").collectAsList().get(0).getString(0)); + } + } From 45d06c45c7a9bea15dcfeeb93eac217ba0de36de Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 14:29:18 +0100 Subject: [PATCH 05/10] collecting all the atoic actions for result type and save them all in the AS path --- .../bipfinder/CollectAndSave.java | 85 +++++++++ .../bipfinder/input_actionset_parameter.json | 32 ++++ .../bipfinder/oozie_app/config-default.xml | 58 +++++++ .../bipfinder/oozie_app/workflow.xml | 163 ++++++++++++++++++ 4 files changed, 338 insertions(+) create mode 100644 dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java create mode 100644 dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json create mode 100644 dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/config-default.xml create mode 100644 dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java new file mode 100644 index 0000000000..7164fc5ed1 --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java @@ -0,0 +1,85 @@ + +package eu.dnetlib.dhp.actionmanager.bipfinder; + +import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession; + +import java.io.Serializable; +import java.util.Optional; + +import org.apache.commons.io.IOUtils; +import org.apache.hadoop.io.Text; +import org.apache.hadoop.mapred.SequenceFileOutputFormat; +import org.apache.spark.SparkConf; +import org.apache.spark.api.java.JavaPairRDD; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.api.java.function.MapFunction; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Encoders; +import org.apache.spark.sql.SparkSession; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import com.fasterxml.jackson.databind.ObjectMapper; + +import eu.dnetlib.dhp.application.ArgumentApplicationParser; +import eu.dnetlib.dhp.common.HdfsSupport; +import eu.dnetlib.dhp.schema.oaf.Result; + +public class CollectAndSave implements Serializable { + + private static final Logger log = LoggerFactory.getLogger(CollectAndSave.class); + private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); + + public static void main(String[] args) throws Exception { + + String jsonConfiguration = IOUtils + .toString( + CollectAndSave.class + .getResourceAsStream( + "/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json")); + + final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration); + + parser.parseArgument(args); + + Boolean isSparkSessionManaged = Optional + .ofNullable(parser.get("isSparkSessionManaged")) + .map(Boolean::valueOf) + .orElse(Boolean.TRUE); + + log.info("isSparkSessionManaged: {}", isSparkSessionManaged); + + final String inputPath = parser.get("inputPath"); + log.info("inputPath {}: ", inputPath); + + final String outputPath = parser.get("outputPath"); + log.info("outputPath {}: ", outputPath); + + SparkConf conf = new SparkConf(); + + runWithSparkSession( + conf, + isSparkSessionManaged, + spark -> { + removeOutputDir(spark, outputPath); + collectAndSave(spark, inputPath, outputPath); + }); + } + + private static void collectAndSave(SparkSession spark, String inputPath, String outputPath) { + JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext()); + + sc + .sequenceFile(inputPath + "/publication", Text.class, Text.class) + .union(sc.sequenceFile(inputPath + "/dataset", Text.class, Text.class)) + .union(sc.sequenceFile(inputPath + "/otherresearchproduct", Text.class, Text.class)) + .union(sc.sequenceFile(inputPath + "/software", Text.class, Text.class)) + .saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class); + ; + } + + private static void removeOutputDir(SparkSession spark, String path) { + HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration()); + } + +} diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json new file mode 100644 index 0000000000..ae844a0c9c --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json @@ -0,0 +1,32 @@ +[ + { + "paramName": "issm", + "paramLongName": "isSparkSessionManaged", + "paramDescription": "when true will stop SparkSession after job execution", + "paramRequired": false +}, +{ +"paramName": "ip", +"paramLongName": "inputPath", +"paramDescription": "the URL from where to get the programme file", +"paramRequired": true +}, +{ +"paramName": "o", +"paramLongName": "outputPath", +"paramDescription": "the path of the new ActionSet", +"paramRequired": true +}, + { + "paramName": "rtn", + "paramLongName": "resultTableName", + "paramDescription": "the path of the new ActionSet", + "paramRequired": true + }, + { + "paramName": "bsp", + "paramLongName": "bipScorePath", + "paramDescription": "the path of the new ActionSet", + "paramRequired": true + } +] \ No newline at end of file diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/config-default.xml b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/config-default.xml new file mode 100644 index 0000000000..a1755f329b --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/config-default.xml @@ -0,0 +1,58 @@ + + + jobTracker + yarnRM + + + nameNode + hdfs://nameservice1 + + + oozie.use.system.libpath + true + + + oozie.action.sharelib.for.spark + spark2 + + + hive_metastore_uris + thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083 + + + spark2YarnHistoryServerAddress + http://iis-cdh5-test-gw.ocean.icm.edu.pl:18089 + + + spark2ExtraListeners + com.cloudera.spark.lineage.NavigatorAppListener + + + spark2SqlQueryExecutionListeners + com.cloudera.spark.lineage.NavigatorQueryListener + + + oozie.launcher.mapreduce.user.classpath.first + true + + + sparkExecutorNumber + 4 + + + spark2EventLogDir + /user/spark/spark2ApplicationHistory + + + sparkDriverMemory + 15G + + + sparkExecutorMemory + 6G + + + sparkExecutorCores + 1 + + \ No newline at end of file diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml new file mode 100644 index 0000000000..c710c8b553 --- /dev/null +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml @@ -0,0 +1,163 @@ + + + + projectFileURL + the url where to get the projects file + + + + programmeFileURL + the url where to get the programme file + + + + topicFileURL + the url where to get the topic file + + + outputPath + path where to store the action set + + + + + + Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}] + + + + + + + + + + + + + + + eu.dnetlib.dhp.actionmanager.project.utils.ReadCSV + --hdfsNameNode${nameNode} + --fileURL${projectFileURL} + --hdfsPath${workingDir}/projects + --classForNameeu.dnetlib.dhp.actionmanager.project.utils.CSVProject + + + + + + + + eu.dnetlib.dhp.actionmanager.project.utils.ReadCSV + --hdfsNameNode${nameNode} + --fileURL${programmeFileURL} + --hdfsPath${workingDir}/programme + --classForNameeu.dnetlib.dhp.actionmanager.project.utils.CSVProgramme + + + + + + + + eu.dnetlib.dhp.actionmanager.project.utils.ReadExcel + --hdfsNameNode${nameNode} + --fileURL${topicFileURL} + --hdfsPath${workingDir}/topic + --classForNameeu.dnetlib.dhp.actionmanager.project.utils.EXCELTopic + + + + + + + + eu.dnetlib.dhp.actionmanager.project.ReadProjectsFromDB + --hdfsPath${workingDir}/dbProjects + --hdfsNameNode${nameNode} + --postgresUrl${postgresURL} + --postgresUser${postgresUser} + --postgresPassword${postgresPassword} + + + + + + + + yarn + cluster + PrepareProgramme + eu.dnetlib.dhp.actionmanager.project.PrepareProgramme + dhp-aggregation-${projectVersion}.jar + + --executor-cores=${sparkExecutorCores} + --executor-memory=${sparkExecutorMemory} + --driver-memory=${sparkDriverMemory} + --conf spark.extraListeners=${spark2ExtraListeners} + --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} + --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} + --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} + --conf spark.sql.shuffle.partitions=3840 + + --programmePath${workingDir}/programme + --outputPath${workingDir}/preparedProgramme + + + + + + + + yarn + cluster + PrepareProjects + eu.dnetlib.dhp.actionmanager.project.PrepareProjects + dhp-aggregation-${projectVersion}.jar + + --executor-cores=${sparkExecutorCores} + --executor-memory=${sparkExecutorMemory} + --driver-memory=${sparkDriverMemory} + --conf spark.extraListeners=${spark2ExtraListeners} + --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} + --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} + --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} + --conf spark.sql.shuffle.partitions=3840 + + --projectPath${workingDir}/projects + --outputPath${workingDir}/preparedProjects + --dbProjectPath${workingDir}/dbProjects + + + + + + + + yarn + cluster + ProjectProgrammeAS + eu.dnetlib.dhp.actionmanager.project.SparkAtomicActionJob + dhp-aggregation-${projectVersion}.jar + + --executor-cores=${sparkExecutorCores} + --executor-memory=${sparkExecutorMemory} + --driver-memory=${sparkDriverMemory} + --conf spark.extraListeners=${spark2ExtraListeners} + --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} + --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} + --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} + --conf spark.sql.shuffle.partitions=3840 + + --projectPath${workingDir}/preparedProjects + --programmePath${workingDir}/preparedProgramme + --topicPath${workingDir}/topic + --outputPath${outputPath} + + + + + + + \ No newline at end of file From 62ff4999e336b1524aaccfa80757baabb0deb634 Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 14:30:56 +0100 Subject: [PATCH 06/10] added workflow and last step of collection and save --- .../bipfinder/input_actionset_parameter.json | 14 +- .../bipfinder/oozie_app/workflow.xml | 178 +++++++++--------- 2 files changed, 94 insertions(+), 98 deletions(-) diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json index ae844a0c9c..67911eef1f 100644 --- a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/input_actionset_parameter.json @@ -16,17 +16,5 @@ "paramLongName": "outputPath", "paramDescription": "the path of the new ActionSet", "paramRequired": true -}, - { - "paramName": "rtn", - "paramLongName": "resultTableName", - "paramDescription": "the path of the new ActionSet", - "paramRequired": true - }, - { - "paramName": "bsp", - "paramLongName": "bipScorePath", - "paramDescription": "the path of the new ActionSet", - "paramRequired": true - } +} ] \ No newline at end of file diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml index c710c8b553..6f74146f18 100644 --- a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml @@ -1,22 +1,17 @@ - + - projectFileURL - the url where to get the projects file + inputPath + the input path of the resources to be extended - programmeFileURL - the url where to get the programme file - - - - topicFileURL - the url where to get the topic file + bipScorePath + the path where to find the bipFinder scores outputPath - path where to store the action set + the path where to store the actionset @@ -31,128 +26,141 @@ - + - - - eu.dnetlib.dhp.actionmanager.project.utils.ReadCSV - --hdfsNameNode${nameNode} - --fileURL${projectFileURL} - --hdfsPath${workingDir}/projects - --classForNameeu.dnetlib.dhp.actionmanager.project.utils.CSVProject - - - - + + + + + + - - - eu.dnetlib.dhp.actionmanager.project.utils.ReadCSV - --hdfsNameNode${nameNode} - --fileURL${programmeFileURL} - --hdfsPath${workingDir}/programme - --classForNameeu.dnetlib.dhp.actionmanager.project.utils.CSVProgramme - - - - - - - - eu.dnetlib.dhp.actionmanager.project.utils.ReadExcel - --hdfsNameNode${nameNode} - --fileURL${topicFileURL} - --hdfsPath${workingDir}/topic - --classForNameeu.dnetlib.dhp.actionmanager.project.utils.EXCELTopic - - - - - - - - eu.dnetlib.dhp.actionmanager.project.ReadProjectsFromDB - --hdfsPath${workingDir}/dbProjects - --hdfsNameNode${nameNode} - --postgresUrl${postgresURL} - --postgresUser${postgresUser} - --postgresPassword${postgresPassword} - - - - - - + yarn cluster - PrepareProgramme - eu.dnetlib.dhp.actionmanager.project.PrepareProgramme + Produces the atomic action with the bip finder scores for publications + eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob dhp-aggregation-${projectVersion}.jar - --executor-cores=${sparkExecutorCores} --executor-memory=${sparkExecutorMemory} + --executor-cores=${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners=${spark2ExtraListeners} --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} - --conf spark.sql.shuffle.partitions=3840 + --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir} - --programmePath${workingDir}/programme - --outputPath${workingDir}/preparedProgramme + --inputPath${inputPath}/publication + --resultTableNameeu.dnetlib.dhp.schema.oaf.Publication + --outputPath${workingDir}/publication + --bipScorePath${bipScorePath} - + - + yarn cluster - PrepareProjects - eu.dnetlib.dhp.actionmanager.project.PrepareProjects + Produces the atomic action with the bip finder scores for datasets + eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob dhp-aggregation-${projectVersion}.jar - --executor-cores=${sparkExecutorCores} --executor-memory=${sparkExecutorMemory} + --executor-cores=${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners=${spark2ExtraListeners} --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} - --conf spark.sql.shuffle.partitions=3840 + --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir} - --projectPath${workingDir}/projects - --outputPath${workingDir}/preparedProjects - --dbProjectPath${workingDir}/dbProjects + --inputPath${inputPath}/dataset + --resultTableNameeu.dnetlib.dhp.schema.oaf.Dataset + --outputPath${workingDir}/otherresearchproduct + --bipScorePath${bipScorePath} - + - + yarn cluster - ProjectProgrammeAS - eu.dnetlib.dhp.actionmanager.project.SparkAtomicActionJob + Produces the atomic action with the bip finder scores for orp + eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob dhp-aggregation-${projectVersion}.jar - --executor-cores=${sparkExecutorCores} --executor-memory=${sparkExecutorMemory} + --executor-cores=${sparkExecutorCores} --driver-memory=${sparkDriverMemory} --conf spark.extraListeners=${spark2ExtraListeners} --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} - --conf spark.sql.shuffle.partitions=3840 + --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir} - --projectPath${workingDir}/preparedProjects - --programmePath${workingDir}/preparedProgramme - --topicPath${workingDir}/topic + --inputPath${inputPath}/otherresearchproduct + --resultTableNameeu.dnetlib.dhp.schema.oaf.OtherResearchProduct + --outputPath${workingDir}/otherresearchproduct + --bipScorePath${bipScorePath} + + + + + + + + yarn + cluster + Produces the atomic action with the bip finder scores for software + eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob + dhp-aggregation-${projectVersion}.jar + + --executor-memory=${sparkExecutorMemory} + --executor-cores=${sparkExecutorCores} + --driver-memory=${sparkDriverMemory} + --conf spark.extraListeners=${spark2ExtraListeners} + --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} + --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} + --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} + --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir} + + --inputPath${inputPath}/software + --resultTableNameeu.dnetlib.dhp.schema.oaf.Software + --outputPath${workingDir}/software + --bipScorePath${bipScorePath} + + + + + + + + + + yarn + cluster + saves all the aa produced for the several types of results in the as output path + eu.dnetlib.dhp.actionmanager.bipfinder.CollectAndSave + dhp-aggregation-${projectVersion}.jar + + --executor-memory=${sparkExecutorMemory} + --executor-cores=${sparkExecutorCores} + --driver-memory=${sparkDriverMemory} + --conf spark.extraListeners=${spark2ExtraListeners} + --conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners} + --conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress} + --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir} + --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir} + + --inputPath${workingDir} --outputPath${outputPath} From 5b3ed70808422c8fc34cf20562f01b3f9cbb3d9e Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 14:31:34 +0100 Subject: [PATCH 07/10] refactoring --- .../bipfinder/BipDeserialize.java | 22 +- .../dhp/actionmanager/bipfinder/BipScore.java | 29 +- .../dhp/actionmanager/bipfinder/KeyValue.java | 29 +- .../bipfinder/PreparedResult.java | 29 +- .../dhp/actionmanager/bipfinder/Score.java | 29 +- .../bipfinder/SparkAtomicActionScoreJob.java | 306 ++++++------ .../SparkAtomicActionScoreJobTest.java | 437 ++++++++++-------- 7 files changed, 480 insertions(+), 401 deletions(-) diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java index e68b912b2a..2ec3679ced 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java @@ -1,3 +1,4 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; @@ -5,19 +6,18 @@ import java.util.ArrayList; import java.util.HashMap; import java.util.List; +public class BipDeserialize extends HashMap> implements Serializable { -public class BipDeserialize extends HashMap> implements Serializable { + public BipDeserialize() { + super(); + } - public BipDeserialize(){ - super(); - } + public List get(String key) { - public List get(String key) { - - if (super.get(key) == null) { - return new ArrayList<>(); - } - return super.get(key); - } + if (super.get(key) == null) { + return new ArrayList<>(); + } + return super.get(key); + } } diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java index b1e381955b..3aa2488cd1 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java @@ -1,25 +1,26 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; import java.util.List; public class BipScore implements Serializable { - private String id; - private List scoreList; + private String id; + private List scoreList; - public String getId() { - return id; - } + public String getId() { + return id; + } - public void setId(String id) { - this.id = id; - } + public void setId(String id) { + this.id = id; + } - public List getScoreList() { - return scoreList; - } + public List getScoreList() { + return scoreList; + } - public void setScoreList(List scoreList) { - this.scoreList = scoreList; - } + public void setScoreList(List scoreList) { + this.scoreList = scoreList; + } } diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java index 1fadae6fec..6909a96344 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/KeyValue.java @@ -1,25 +1,26 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; public class KeyValue implements Serializable { - private String key; - private String value; + private String key; + private String value; - public String getKey() { - return key; - } + public String getKey() { + return key; + } - public void setKey(String key) { - this.key = key; - } + public void setKey(String key) { + this.key = key; + } - public String getValue() { - return value; - } + public String getValue() { + return value; + } - public void setValue(String value) { - this.value = value; - } + public void setValue(String value) { + this.value = value; + } } diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java index bb7648f0c8..3e55ec6bc6 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java @@ -1,24 +1,25 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; public class PreparedResult implements Serializable { - private String id; //openaire id - private String value; //doi + private String id; // openaire id + private String value; // doi - public String getId() { - return id; - } + public String getId() { + return id; + } - public void setId(String id) { - this.id = id; - } + public void setId(String id) { + this.id = id; + } - public String getValue() { - return value; - } + public String getValue() { + return value; + } - public void setValue(String value) { - this.value = value; - } + public void setValue(String value) { + this.value = value; + } } diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java index b14d971cdf..17423fe966 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java @@ -1,3 +1,4 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; @@ -5,22 +6,22 @@ import java.util.List; public class Score implements Serializable { - private String id; - private List unit; + private String id; + private List unit; - public String getId() { - return id; - } + public String getId() { + return id; + } - public void setId(String id) { - this.id = id; - } + public void setId(String id) { + this.id = id; + } - public List getUnit() { - return unit; - } + public List getUnit() { + return unit; + } - public void setUnit(List unit) { - this.unit = unit; - } + public void setUnit(List unit) { + this.unit = unit; + } } diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java index 658555e058..1628fca395 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java @@ -1,11 +1,13 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; -import com.fasterxml.jackson.databind.ObjectMapper; -import eu.dnetlib.dhp.application.ArgumentApplicationParser; -import eu.dnetlib.dhp.common.HdfsSupport; -import eu.dnetlib.dhp.schema.action.AtomicAction; -import eu.dnetlib.dhp.schema.oaf.*; -import eu.dnetlib.dhp.schema.oaf.KeyValue; +import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession; + +import java.io.Serializable; +import java.util.List; +import java.util.Optional; +import java.util.stream.Collectors; + import org.apache.commons.io.IOUtils; import org.apache.hadoop.hdfs.qjournal.protocol.QJournalProtocolProtos; import org.apache.hadoop.io.Text; @@ -22,182 +24,188 @@ import org.apache.spark.sql.Row; import org.apache.spark.sql.SparkSession; import org.slf4j.Logger; import org.slf4j.LoggerFactory; + +import com.fasterxml.jackson.databind.ObjectMapper; + +import eu.dnetlib.dhp.application.ArgumentApplicationParser; +import eu.dnetlib.dhp.common.HdfsSupport; +import eu.dnetlib.dhp.schema.action.AtomicAction; +import eu.dnetlib.dhp.schema.oaf.*; +import eu.dnetlib.dhp.schema.oaf.KeyValue; import scala.Tuple2; -import java.io.Serializable; -import java.util.List; -import java.util.Optional; -import java.util.stream.Collectors; - -import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession; - public class SparkAtomicActionScoreJob implements Serializable { - private static String DOI = "doi"; - private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionScoreJob.class); - private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); + private static String DOI = "doi"; + private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionScoreJob.class); + private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); - public static void main(String[] args) throws Exception { + public static void main(String[] args) throws Exception { - String jsonConfiguration = IOUtils - .toString( - SparkAtomicActionScoreJob.class - .getResourceAsStream( - "/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json")); + String jsonConfiguration = IOUtils + .toString( + SparkAtomicActionScoreJob.class + .getResourceAsStream( + "/eu/dnetlib/dhp/actionmanager/bipfinder/input_parameters.json")); - final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration); + final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration); - parser.parseArgument(args); + parser.parseArgument(args); - Boolean isSparkSessionManaged = Optional - .ofNullable(parser.get("isSparkSessionManaged")) - .map(Boolean::valueOf) - .orElse(Boolean.TRUE); + Boolean isSparkSessionManaged = Optional + .ofNullable(parser.get("isSparkSessionManaged")) + .map(Boolean::valueOf) + .orElse(Boolean.TRUE); - log.info("isSparkSessionManaged: {}", isSparkSessionManaged); + log.info("isSparkSessionManaged: {}", isSparkSessionManaged); - final String inputPath = parser.get("inputPath"); - log.info("inputPath {}: ", inputPath); + final String inputPath = parser.get("inputPath"); + log.info("inputPath {}: ", inputPath); - final String outputPath = parser.get("outputPath"); - log.info("outputPath {}: ", outputPath); + final String outputPath = parser.get("outputPath"); + log.info("outputPath {}: ", outputPath); - final String bipScorePath = parser.get("bipScorePath"); - log.info("bipScorePath: {}", bipScorePath); + final String bipScorePath = parser.get("bipScorePath"); + log.info("bipScorePath: {}", bipScorePath); - final String resultClassName = parser.get("resultTableName"); - log.info("resultTableName: {}", resultClassName); + final String resultClassName = parser.get("resultTableName"); + log.info("resultTableName: {}", resultClassName); - Class inputClazz = (Class) Class.forName(resultClassName); + Class inputClazz = (Class) Class.forName(resultClassName); - SparkConf conf = new SparkConf(); + SparkConf conf = new SparkConf(); - runWithSparkSession( - conf, - isSparkSessionManaged, - spark -> { - removeOutputDir(spark, outputPath); - prepareResults(spark, inputPath, outputPath, bipScorePath, inputClazz); - }); - } + runWithSparkSession( + conf, + isSparkSessionManaged, + spark -> { + removeOutputDir(spark, outputPath); + prepareResults(spark, inputPath, outputPath, bipScorePath, inputClazz); + }); + } - private static void prepareResults(SparkSession spark, String inputPath, String outputPath, - String bipScorePath, Class inputClazz) { + private static void prepareResults(SparkSession spark, String inputPath, String outputPath, + String bipScorePath, Class inputClazz) { - final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); - JavaRDD bipDeserializeJavaRDD = sc.textFile(bipScorePath) - .map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class)); + JavaRDD bipDeserializeJavaRDD = sc + .textFile(bipScorePath) + .map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class)); + Dataset bipScores = spark + .createDataset(bipDeserializeJavaRDD.flatMap(entry -> entry.keySet().stream().map(key -> { + BipScore bs = new BipScore(); + bs.setId(key); + bs.setScoreList(entry.get(key)); + return bs; + }).collect(Collectors.toList()).iterator()).rdd(), Encoders.bean(BipScore.class)); - Dataset bipScores = spark.createDataset(bipDeserializeJavaRDD.flatMap(entry -> - entry.keySet().stream().map(key -> { - BipScore bs = new BipScore(); - bs.setId(key); - bs.setScoreList(entry.get(key)); - return bs; - }).collect(Collectors.toList()).iterator() - ).rdd(), Encoders.bean(BipScore.class)); + System.out.println(bipScores.count()); - System.out.println(bipScores.count()); + Dataset results = readPath(spark, inputPath, inputClazz); - Dataset results = readPath(spark, inputPath, inputClazz); + results.createOrReplaceTempView("result"); - results.createOrReplaceTempView("result"); + Dataset preparedResult = spark + .sql( + "select pIde.value value, id " + + "from result " + + "lateral view explode (pid) p as pIde " + + "where dataInfo.deletedbyinference = false and pIde.qualifier.classid = '" + DOI + "'") + .as(Encoders.bean(PreparedResult.class)); - Dataset preparedResult = spark.sql("select pIde.value value, id " + - "from result " + - "lateral view explode (pid) p as pIde " + - "where dataInfo.deletedbyinference = false and pIde.qualifier.classid = '" + DOI + "'") - .as(Encoders.bean(PreparedResult.class)); + Dataset tmp = bipScores + .joinWith( + preparedResult, bipScores.col("id").equalTo(preparedResult.col("value")), + "inner") + .map((MapFunction, BipScore>) value -> { + BipScore ret = value._1(); + ret.setId(value._2().getId()); + return ret; + }, Encoders.bean(BipScore.class)); - Dataset tmp = bipScores.joinWith(preparedResult, bipScores.col("id").equalTo(preparedResult.col("value")), - "inner") - .map((MapFunction, BipScore>) value -> { - BipScore ret = value._1(); - ret.setId(value._2().getId()); - return ret; - }, Encoders.bean(BipScore.class)); + tmp + .groupByKey((MapFunction) value -> value.getId(), Encoders.STRING()) + .mapGroups((MapGroupsFunction) (k, it) -> { + Result ret = inputClazz.newInstance(); + BipScore first = it.next(); + ret.setId(first.getId()); - tmp.groupByKey((MapFunction) value -> value.getId(), Encoders.STRING()) - .mapGroups((MapGroupsFunction) (k, it) -> - { - Result ret = inputClazz.newInstance(); - BipScore first = it.next(); - ret.setId(first.getId()); + ret.setMeasures(getMeasure(first)); + it.forEachRemaining(value -> ret.getMeasures().addAll(getMeasure(value))); - ret.setMeasures(getMeasure(first)); - it.forEachRemaining(value -> ret.getMeasures().addAll(getMeasure(value))); + return (I) ret; + }, Encoders.bean(inputClazz)) + .toJavaRDD() + .map(p -> new AtomicAction(inputClazz, p)) + .mapToPair( + aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()), + new Text(OBJECT_MAPPER.writeValueAsString(aa)))) + .saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class); + ; + } - return (I)ret; - }, Encoders.bean(inputClazz)) - .toJavaRDD() - .map(p -> new AtomicAction(inputClazz, p)) - .mapToPair( - aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()), - new Text(OBJECT_MAPPER.writeValueAsString(aa)))) - .saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class); - ; - } + public static Dataset getBipScoreDataset(Dataset bipdeserialized) { + return bipdeserialized + .flatMap((FlatMapFunction) bip -> bip.keySet().stream().map(key -> { + BipScore bs = new BipScore(); + bs.setId(key); + bs.setScoreList(bip.get(key)); + return bs; + }).collect(Collectors.toList()).iterator(), Encoders.bean(BipScore.class)); + } - public static Dataset getBipScoreDataset(Dataset bipdeserialized){ - return bipdeserialized.flatMap((FlatMapFunction) bip -> - bip.keySet().stream().map(key -> { - BipScore bs = new BipScore(); - bs.setId(key); - bs.setScoreList(bip.get(key)); - return bs; - }).collect(Collectors.toList()).iterator() - , Encoders.bean(BipScore.class)); - } + private static List getMeasure(BipScore value) { + return value + .getScoreList() + .stream() + .map(score -> { + Measure m = new Measure(); + m.setId(score.getId()); + m + .setUnit( + score + .getUnit() + .stream() + .map(unit -> { + KeyValue kv = new KeyValue(); + kv.setValue(unit.getValue()); + kv.setKey(unit.getKey()); + kv.setDataInfo(getDataInfo()); + return kv; + }) + .collect(Collectors.toList())); + return m; + }) + .collect(Collectors.toList()); + } - private static List getMeasure(BipScore value) { - return value.getScoreList() - .stream() - .map(score -> { - Measure m = new Measure(); - m.setId(score.getId()); - m.setUnit(score.getUnit().stream() - .map(unit -> { - KeyValue kv = new KeyValue(); - kv.setValue(unit.getValue()); - kv.setKey(unit.getKey()); - kv.setDataInfo(getDataInfo()); - return kv; - }).collect(Collectors.toList())); - return m; - }).collect(Collectors.toList()); - } + private static DataInfo getDataInfo() { + DataInfo di = new DataInfo(); + di.setInferred(false); + di.setInvisible(false); + di.setDeletedbyinference(false); + di.setTrust(""); + Qualifier qualifier = new Qualifier(); + qualifier.setClassid("sysimport:actionset"); + qualifier.setClassname("Harvested"); + qualifier.setSchemename("dnet:provenanceActions"); + qualifier.setSchemeid("dnet:provenanceActions"); + di.setProvenanceaction(qualifier); + return di; + } + private static void removeOutputDir(SparkSession spark, String path) { + HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration()); + } - - private static DataInfo getDataInfo() { - DataInfo di = new DataInfo(); - di.setInferred(false); - di.setInvisible(false); - di.setDeletedbyinference(false); - di.setTrust(""); - Qualifier qualifier = new Qualifier(); - qualifier.setClassid("sysimport:actionset"); - qualifier.setClassname("Harvested"); - qualifier.setSchemename("dnet:provenanceActions"); - qualifier.setSchemeid("dnet:provenanceActions"); - di.setProvenanceaction(qualifier); - return di; - } - - - private static void removeOutputDir(SparkSession spark, String path) { - HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration()); - } - - public static Dataset readPath( - SparkSession spark, String inputPath, Class clazz) { - return spark - .read() - .textFile(inputPath) - .map((MapFunction) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz)); - } - + public static Dataset readPath( + SparkSession spark, String inputPath, Class clazz) { + return spark + .read() + .textFile(inputPath) + .map((MapFunction) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz)); + } } diff --git a/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java b/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java index 3b360f6edc..4b02e7485c 100644 --- a/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java +++ b/dhp-workflows/dhp-aggregation/src/test/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJobTest.java @@ -1,9 +1,12 @@ + package eu.dnetlib.dhp.actionmanager.bipfinder; -import com.fasterxml.jackson.databind.ObjectMapper; -import eu.dnetlib.dhp.schema.action.AtomicAction; -import eu.dnetlib.dhp.schema.oaf.*; -import eu.dnetlib.dhp.schema.oaf.KeyValue; +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.util.List; +import java.util.stream.Collectors; + import org.apache.commons.io.FileUtils; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.SequenceFileOutputFormat; @@ -24,241 +27,305 @@ import org.junit.jupiter.api.BeforeAll; import org.junit.jupiter.api.Test; import org.slf4j.Logger; import org.slf4j.LoggerFactory; -import scala.Tuple2; -import java.io.IOException; -import java.nio.file.Files; -import java.nio.file.Path; -import java.util.List; -import java.util.stream.Collectors; +import com.fasterxml.jackson.databind.ObjectMapper; + +import eu.dnetlib.dhp.schema.action.AtomicAction; +import eu.dnetlib.dhp.schema.oaf.*; +import eu.dnetlib.dhp.schema.oaf.KeyValue; +import scala.Tuple2; public class SparkAtomicActionScoreJobTest { - private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); + private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper(); - private static SparkSession spark; + private static SparkSession spark; - private static Path workingDir; - private static final Logger log = LoggerFactory - .getLogger(SparkAtomicActionScoreJobTest.class); + private static Path workingDir; + private static final Logger log = LoggerFactory + .getLogger(SparkAtomicActionScoreJobTest.class); - @BeforeAll - public static void beforeAll() throws IOException { - workingDir = Files - .createTempDirectory(SparkAtomicActionScoreJobTest.class.getSimpleName()); - log.info("using work dir {}", workingDir); + @BeforeAll + public static void beforeAll() throws IOException { + workingDir = Files + .createTempDirectory(SparkAtomicActionScoreJobTest.class.getSimpleName()); + log.info("using work dir {}", workingDir); - SparkConf conf = new SparkConf(); - conf.setAppName(SparkAtomicActionScoreJobTest.class.getSimpleName()); + SparkConf conf = new SparkConf(); + conf.setAppName(SparkAtomicActionScoreJobTest.class.getSimpleName()); - conf.setMaster("local[*]"); - conf.set("spark.driver.host", "localhost"); - conf.set("hive.metastore.local", "true"); - conf.set("spark.ui.enabled", "false"); - conf.set("spark.sql.warehouse.dir", workingDir.toString()); - conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString()); + conf.setMaster("local[*]"); + conf.set("spark.driver.host", "localhost"); + conf.set("hive.metastore.local", "true"); + conf.set("spark.ui.enabled", "false"); + conf.set("spark.sql.warehouse.dir", workingDir.toString()); + conf.set("hive.metastore.warehouse.dir", workingDir.resolve("warehouse").toString()); - spark = SparkSession - .builder() - .appName(SparkAtomicActionScoreJobTest.class.getSimpleName()) - .config(conf) - .getOrCreate(); - } + spark = SparkSession + .builder() + .appName(SparkAtomicActionScoreJobTest.class.getSimpleName()) + .config(conf) + .getOrCreate(); + } - @AfterAll - public static void afterAll() throws IOException { - FileUtils.deleteDirectory(workingDir.toFile()); - spark.stop(); - } + @AfterAll + public static void afterAll() throws IOException { + FileUtils.deleteDirectory(workingDir.toFile()); + spark.stop(); + } - @Test - public void matchOne() throws Exception { - String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); - String inputPath = getClass() - .getResource( - "/eu/dnetlib/dhp/actionmanager/bipfinder/publication.json") - .getPath(); + @Test + public void matchOne() throws Exception { + String bipScoresPath = getClass() + .getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json") + .getPath(); + String inputPath = getClass() + .getResource( + "/eu/dnetlib/dhp/actionmanager/bipfinder/publication.json") + .getPath(); - SparkAtomicActionScoreJob.main( - new String[] { - "-isSparkSessionManaged", - Boolean.FALSE.toString(), - "-inputPath", - inputPath, - "-bipScorePath", - bipScoresPath, - "-resultTableName", - "eu.dnetlib.dhp.schema.oaf.Publication", - "-outputPath", - workingDir.toString() + "/actionSet" - }); + SparkAtomicActionScoreJob + .main( + new String[] { + "-isSparkSessionManaged", + Boolean.FALSE.toString(), + "-inputPath", + inputPath, + "-bipScorePath", + bipScoresPath, + "-resultTableName", + "eu.dnetlib.dhp.schema.oaf.Publication", + "-outputPath", + workingDir.toString() + "/actionSet" + }); + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); - final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + JavaRDD tmp = sc + .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) + .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) + .map(aa -> ((Publication) aa.getPayload())); - JavaRDD tmp = sc - .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) - .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) - .map(aa -> ((Publication) aa.getPayload())); + Assertions.assertTrue(tmp.count() == 1); - Assertions.assertTrue(tmp.count() == 1); + Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); + verificationDataset.createOrReplaceTempView("publication"); - Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); - verificationDataset.createOrReplaceTempView("publication"); + Dataset execVerification = spark + .sql( + "Select p.id oaid, mes.id, mUnit.value from publication p " + + "lateral view explode(measures) m as mes " + + "lateral view explode(mes.unit) u as mUnit "); - Dataset execVerification = spark.sql("Select p.id oaid, mes.id, mUnit.value from publication p " + - "lateral view explode(measures) m as mes " + - "lateral view explode(mes.unit) u as mUnit "); + Assertions.assertEquals(2, execVerification.count()); - Assertions.assertEquals(2, execVerification.count()); + Assertions + .assertEquals( + "50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb", + execVerification.select("oaid").collectAsList().get(0).getString(0)); - Assertions.assertEquals("50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb", - execVerification.select("oaid").collectAsList().get(0).getString(0)); + Assertions + .assertEquals( + "1.47565045883e-08", + execVerification.filter("id = 'influence'").select("value").collectAsList().get(0).getString(0)); - Assertions.assertEquals("1.47565045883e-08", - execVerification.filter("id = 'influence'").select("value").collectAsList().get(0).getString(0)); + Assertions + .assertEquals( + "0.227515392", + execVerification.filter("id = 'popularity'").select("value").collectAsList().get(0).getString(0)); - Assertions.assertEquals("0.227515392", - execVerification.filter("id = 'popularity'").select("value").collectAsList().get(0).getString(0)); + } - } + @Test + public void matchOneWithTwo() throws Exception { + String bipScoresPath = getClass() + .getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json") + .getPath(); + String inputPath = getClass() + .getResource( + "/eu/dnetlib/dhp/actionmanager/bipfinder/publication_2.json") + .getPath(); - @Test - public void matchOneWithTwo() throws Exception { - String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); - String inputPath = getClass() - .getResource( - "/eu/dnetlib/dhp/actionmanager/bipfinder/publication_2.json") - .getPath(); + SparkAtomicActionScoreJob + .main( + new String[] { + "-isSparkSessionManaged", + Boolean.FALSE.toString(), + "-inputPath", + inputPath, + "-bipScorePath", + bipScoresPath, + "-resultTableName", + "eu.dnetlib.dhp.schema.oaf.Publication", + "-outputPath", + workingDir.toString() + "/actionSet" + }); - SparkAtomicActionScoreJob.main( - new String[] { - "-isSparkSessionManaged", - Boolean.FALSE.toString(), - "-inputPath", - inputPath, - "-bipScorePath", - bipScoresPath, - "-resultTableName", - "eu.dnetlib.dhp.schema.oaf.Publication", - "-outputPath", - workingDir.toString() + "/actionSet" - }); + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + JavaRDD tmp = sc + .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) + .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) + .map(aa -> ((Publication) aa.getPayload())); - final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + Assertions.assertTrue(tmp.count() == 1); - JavaRDD tmp = sc - .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) - .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) - .map(aa -> ((Publication) aa.getPayload())); + Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); + verificationDataset.createOrReplaceTempView("publication"); - Assertions.assertTrue(tmp.count() == 1); + Dataset execVerification = spark + .sql( + "Select p.id oaid, mes.id, mUnit.value from publication p " + + "lateral view explode(measures) m as mes " + + "lateral view explode(mes.unit) u as mUnit "); - Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); - verificationDataset.createOrReplaceTempView("publication"); + Assertions.assertEquals(4, execVerification.count()); - Dataset execVerification = spark.sql("Select p.id oaid, mes.id, mUnit.value from publication p " + - "lateral view explode(measures) m as mes " + - "lateral view explode(mes.unit) u as mUnit "); + Assertions + .assertEquals( + "50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb", + execVerification.select("oaid").collectAsList().get(0).getString(0)); - Assertions.assertEquals(4, execVerification.count()); + Assertions + .assertEquals( + 2, + execVerification.filter("id = 'influence'").count()); + Assertions + .assertEquals( + 2, + execVerification.filter("id = 'popularity'").count()); - Assertions.assertEquals("50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb", - execVerification.select("oaid").collectAsList().get(0).getString(0)); + List tmp_ds = execVerification.filter("id = 'influence'").select("value").collectAsList(); + String tmp_influence = tmp_ds.get(0).getString(0); + Assertions + .assertTrue( + "1.47565045883e-08".equals(tmp_influence) || + "1.98956540239e-08".equals(tmp_influence)); - Assertions.assertEquals(2, - execVerification.filter("id = 'influence'").count()); + tmp_influence = tmp_ds.get(1).getString(0); + Assertions + .assertTrue( + "1.47565045883e-08".equals(tmp_influence) || + "1.98956540239e-08".equals(tmp_influence)); - Assertions.assertEquals(2, - execVerification.filter("id = 'popularity'").count()); + Assertions.assertTrue(!tmp_ds.get(0).getString(0).equals(tmp_ds.get(1).getString(0))); - List tmp_ds = execVerification.filter("id = 'influence'").select("value").collectAsList(); - String tmp_influence = tmp_ds.get(0).getString(0); - Assertions.assertTrue("1.47565045883e-08".equals(tmp_influence)|| - "1.98956540239e-08".equals(tmp_influence) ); + } - tmp_influence = tmp_ds.get(1).getString(0); - Assertions.assertTrue("1.47565045883e-08".equals(tmp_influence)|| - "1.98956540239e-08".equals(tmp_influence) ); + @Test + public void matchTwo() throws Exception { + String bipScoresPath = getClass() + .getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json") + .getPath(); + String inputPath = getClass() + .getResource( + "/eu/dnetlib/dhp/actionmanager/bipfinder/publication_3.json") + .getPath(); - Assertions.assertTrue(!tmp_ds.get(0).getString(0).equals(tmp_ds.get(1).getString(0))); + SparkAtomicActionScoreJob + .main( + new String[] { + "-isSparkSessionManaged", + Boolean.FALSE.toString(), + "-inputPath", + inputPath, + "-bipScorePath", + bipScoresPath, + "-resultTableName", + "eu.dnetlib.dhp.schema.oaf.Publication", + "-outputPath", + workingDir.toString() + "/actionSet" + }); + final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); - } + JavaRDD tmp = sc + .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) + .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) + .map(aa -> ((Publication) aa.getPayload())); - @Test - public void matchTwo() throws Exception { - String bipScoresPath = getClass().getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores.json").getPath(); - String inputPath = getClass() - .getResource( - "/eu/dnetlib/dhp/actionmanager/bipfinder/publication_3.json") - .getPath(); + Assertions.assertTrue(tmp.count() == 2); - SparkAtomicActionScoreJob.main( - new String[] { - "-isSparkSessionManaged", - Boolean.FALSE.toString(), - "-inputPath", - inputPath, - "-bipScorePath", - bipScoresPath, - "-resultTableName", - "eu.dnetlib.dhp.schema.oaf.Publication", - "-outputPath", - workingDir.toString() + "/actionSet" - }); + Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); + verificationDataset.createOrReplaceTempView("publication"); + Dataset execVerification = spark + .sql( + "Select p.id oaid, mes.id, mUnit.value from publication p " + + "lateral view explode(measures) m as mes " + + "lateral view explode(mes.unit) u as mUnit "); - final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext()); + Assertions.assertEquals(4, execVerification.count()); - JavaRDD tmp = sc - .sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class) - .map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class)) - .map(aa -> ((Publication) aa.getPayload())); + Assertions + .assertEquals( + 2, + execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb'").count()); - Assertions.assertTrue(tmp.count() == 2); + Assertions + .assertEquals( + 2, + execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09'").count()); - Dataset verificationDataset = spark.createDataset(tmp.rdd(), Encoders.bean(Publication.class)); - verificationDataset.createOrReplaceTempView("publication"); + Assertions + .assertEquals( + 2, + execVerification.filter("id = 'influence'").count()); - Dataset execVerification = spark.sql("Select p.id oaid, mes.id, mUnit.value from publication p " + - "lateral view explode(measures) m as mes " + - "lateral view explode(mes.unit) u as mUnit "); + Assertions + .assertEquals( + 2, + execVerification.filter("id = 'popularity'").count()); - Assertions.assertEquals(4, execVerification.count()); + Assertions + .assertEquals( + "1.47565045883e-08", + execVerification + .filter( + "oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb' " + + "and id = 'influence'") + .select("value") + .collectAsList() + .get(0) + .getString(0)); + Assertions + .assertEquals( + "1.98956540239e-08", + execVerification + .filter( + "oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09' " + + "and id = 'influence'") + .select("value") + .collectAsList() + .get(0) + .getString(0)); - Assertions.assertEquals(2, - execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb'").count()); + Assertions + .assertEquals( + "0.282046161584", + execVerification + .filter( + "oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09' " + + "and id = 'popularity'") + .select("value") + .collectAsList() + .get(0) + .getString(0)); - Assertions.assertEquals(2, - execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09'").count()); + Assertions + .assertEquals( + "0.227515392", + execVerification + .filter( + "oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb' " + + "and id = 'popularity'") + .select("value") + .collectAsList() + .get(0) + .getString(0)); - - Assertions.assertEquals(2, - execVerification.filter("id = 'influence'").count()); - - Assertions.assertEquals(2, - execVerification.filter("id = 'popularity'").count()); - - Assertions.assertEquals("1.47565045883e-08" , - execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb' " + - "and id = 'influence'").select("value").collectAsList().get(0).getString(0)); - - Assertions.assertEquals( - "1.98956540239e-08", execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09' " + - "and id = 'influence'").select("value").collectAsList().get(0).getString(0)); - - Assertions.assertEquals( - "0.282046161584", execVerification.filter("oaid = '50|acm_________::faed5b7a1bd8f51118d13ed29cfaee09' " + - "and id = 'popularity'").select("value").collectAsList().get(0).getString(0)); - - Assertions.assertEquals("0.227515392" , - execVerification.filter("oaid = '50|355e65625b88::ffa5bad14f4adc0c9a15c00efbbccddb' " + - "and id = 'popularity'").select("value").collectAsList().get(0).getString(0)); - - } + } } From 17680296b97a3e70c758fed78508cd789dc4209c Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 15:02:31 +0100 Subject: [PATCH 08/10] removed unnecessary variable and unused method --- .../bipfinder/SparkAtomicActionScoreJob.java | 18 ++++-------------- 1 file changed, 4 insertions(+), 14 deletions(-) diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java index 1628fca395..ddf1b30499 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java @@ -8,6 +8,7 @@ import java.util.List; import java.util.Optional; import java.util.stream.Collectors; +import eu.dnetlib.dhp.schema.common.ModelSupport; import org.apache.commons.io.IOUtils; import org.apache.hadoop.hdfs.qjournal.protocol.QJournalProtocolProtos; import org.apache.hadoop.io.Text; @@ -115,7 +116,7 @@ public class SparkAtomicActionScoreJob implements Serializable { "where dataInfo.deletedbyinference = false and pIde.qualifier.classid = '" + DOI + "'") .as(Encoders.bean(PreparedResult.class)); - Dataset tmp = bipScores + bipScores .joinWith( preparedResult, bipScores.col("id").equalTo(preparedResult.col("value")), "inner") @@ -123,9 +124,7 @@ public class SparkAtomicActionScoreJob implements Serializable { BipScore ret = value._1(); ret.setId(value._2().getId()); return ret; - }, Encoders.bean(BipScore.class)); - - tmp + }, Encoders.bean(BipScore.class)) .groupByKey((MapFunction) value -> value.getId(), Encoders.STRING()) .mapGroups((MapGroupsFunction) (k, it) -> { Result ret = inputClazz.newInstance(); @@ -143,18 +142,9 @@ public class SparkAtomicActionScoreJob implements Serializable { aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()), new Text(OBJECT_MAPPER.writeValueAsString(aa)))) .saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class); - ; + } - public static Dataset getBipScoreDataset(Dataset bipdeserialized) { - return bipdeserialized - .flatMap((FlatMapFunction) bip -> bip.keySet().stream().map(key -> { - BipScore bs = new BipScore(); - bs.setId(key); - bs.setScoreList(bip.get(key)); - return bs; - }).collect(Collectors.toList()).iterator(), Encoders.bean(BipScore.class)); - } private static List getMeasure(BipScore value) { return value From 3d62d99d5dadf3a9f96e829bec637de3c1dcb08c Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 15:02:49 +0100 Subject: [PATCH 09/10] fixed issue in workflow variable --- .../dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml index 6f74146f18..ea2e9f58ab 100644 --- a/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml +++ b/dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/bipfinder/oozie_app/workflow.xml @@ -82,7 +82,7 @@ --inputPath${inputPath}/dataset --resultTableNameeu.dnetlib.dhp.schema.oaf.Dataset - --outputPath${workingDir}/otherresearchproduct + --outputPath${workingDir}/dataset --bipScorePath${bipScorePath} From 888175baf7f751826a13d622f0699353eb9f7612 Mon Sep 17 00:00:00 2001 From: "miriam.baglioni" Date: Tue, 1 Dec 2020 18:36:29 +0100 Subject: [PATCH 10/10] added java doc --- .../dhp/actionmanager/bipfinder/BipDeserialize.java | 5 +++++ .../eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java | 8 ++++++-- .../dhp/actionmanager/bipfinder/CollectAndSave.java | 8 ++++---- .../dhp/actionmanager/bipfinder/PreparedResult.java | 3 +++ .../eu/dnetlib/dhp/actionmanager/bipfinder/Score.java | 3 +++ .../bipfinder/SparkAtomicActionScoreJob.java | 7 +++---- 6 files changed, 24 insertions(+), 10 deletions(-) diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java index 2ec3679ced..d5b2ced7cb 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipDeserialize.java @@ -6,6 +6,11 @@ import java.util.ArrayList; import java.util.HashMap; import java.util.List; +/** + * Class that maps the model of the bipFinder! input data. + * Only needed for deserialization purposes + */ + public class BipDeserialize extends HashMap> implements Serializable { public BipDeserialize() { diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java index 3aa2488cd1..da9a4bd0ce 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/BipScore.java @@ -4,9 +4,13 @@ package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; import java.util.List; +/** + * Rewriting of the bipFinder input data by extracting the identifier of the result (doi) + */ + public class BipScore implements Serializable { - private String id; - private List scoreList; + private String id; //doi + private List scoreList; //unit as given in the inputfile public String getId() { return id; diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java index 7164fc5ed1..0bebe2fb0e 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/CollectAndSave.java @@ -10,11 +10,7 @@ import org.apache.commons.io.IOUtils; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.SequenceFileOutputFormat; import org.apache.spark.SparkConf; -import org.apache.spark.api.java.JavaPairRDD; import org.apache.spark.api.java.JavaSparkContext; -import org.apache.spark.api.java.function.MapFunction; -import org.apache.spark.sql.Dataset; -import org.apache.spark.sql.Encoders; import org.apache.spark.sql.SparkSession; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -25,6 +21,10 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser; import eu.dnetlib.dhp.common.HdfsSupport; import eu.dnetlib.dhp.schema.oaf.Result; +/** + * Just collects all the atomic actions produced for the different results and saves them in + * outputpath for the ActionSet + */ public class CollectAndSave implements Serializable { private static final Logger log = LoggerFactory.getLogger(CollectAndSave.class); diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java index 3e55ec6bc6..493e944177 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/PreparedResult.java @@ -3,6 +3,9 @@ package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; +/** + * Subset of the information of the generic results that are needed to create the atomic action + */ public class PreparedResult implements Serializable { private String id; // openaire id private String value; // doi diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java index 17423fe966..7cc21b44da 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/Score.java @@ -4,6 +4,9 @@ package eu.dnetlib.dhp.actionmanager.bipfinder; import java.io.Serializable; import java.util.List; +/** + * represents the score in the input file + */ public class Score implements Serializable { private String id; diff --git a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java index ddf1b30499..23764f38e4 100644 --- a/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java +++ b/dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/bipfinder/SparkAtomicActionScoreJob.java @@ -8,20 +8,16 @@ import java.util.List; import java.util.Optional; import java.util.stream.Collectors; -import eu.dnetlib.dhp.schema.common.ModelSupport; import org.apache.commons.io.IOUtils; -import org.apache.hadoop.hdfs.qjournal.protocol.QJournalProtocolProtos; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.SequenceFileOutputFormat; import org.apache.spark.SparkConf; import org.apache.spark.api.java.JavaRDD; import org.apache.spark.api.java.JavaSparkContext; -import org.apache.spark.api.java.function.FlatMapFunction; import org.apache.spark.api.java.function.MapFunction; import org.apache.spark.api.java.function.MapGroupsFunction; import org.apache.spark.sql.Dataset; import org.apache.spark.sql.Encoders; -import org.apache.spark.sql.Row; import org.apache.spark.sql.SparkSession; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -35,6 +31,9 @@ import eu.dnetlib.dhp.schema.oaf.*; import eu.dnetlib.dhp.schema.oaf.KeyValue; import scala.Tuple2; +/** + * created the Atomic Action for each tipe of results + */ public class SparkAtomicActionScoreJob implements Serializable { private static String DOI = "doi";