conflict resolution in the comparator test class

This commit is contained in:
Michele De Bonis 2024-11-18 14:59:30 +01:00
commit c97facf5e6
91 changed files with 1954 additions and 804 deletions

1
.gitignore vendored
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@ -28,3 +28,4 @@ spark-warehouse
/**/.scalafmt.conf
/.java-version
/dhp-shade-package/dependency-reduced-pom.xml
/**/job.properties

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@ -1,5 +1,5 @@
package eu.dnetlib.dhp.actionmanager.personentity;
package eu.dnetlib.dhp.common.person;
import java.util.Arrays;
import java.util.Iterator;
@ -61,7 +61,7 @@ public class CoAuthorshipIterator implements Iterator<Relation> {
private Relation getRelation(String orcid1, String orcid2) {
String source = PERSON_PREFIX + IdentifierFactory.md5(orcid1);
String target = PERSON_PREFIX + IdentifierFactory.md5(orcid2);
return OafMapperUtils
Relation relation = OafMapperUtils
.getRelation(
source, target, ModelConstants.PERSON_PERSON_RELTYPE,
ModelConstants.PERSON_PERSON_SUBRELTYPE,
@ -76,5 +76,7 @@ public class CoAuthorshipIterator implements Iterator<Relation> {
ModelConstants.DNET_PROVENANCE_ACTIONS, ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91"),
null);
relation.setValidated(true);
return relation;
}
}

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@ -1,12 +1,9 @@
package eu.dnetlib.dhp.actionmanager.personentity;
package eu.dnetlib.dhp.common.person;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import eu.dnetlib.dhp.schema.oaf.Relation;
public class Coauthors implements Serializable {
private List<String> coauthors;

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@ -2,8 +2,7 @@
package eu.dnetlib.dhp.oa.merge;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import static org.apache.spark.sql.functions.col;
import static org.apache.spark.sql.functions.when;
import static org.apache.spark.sql.functions.*;
import java.util.Map;
import java.util.Optional;
@ -135,7 +134,9 @@ public class GroupEntitiesSparkJob {
.applyCoarVocabularies(entity, vocs),
OAFENTITY_KRYO_ENC)
.groupByKey((MapFunction<OafEntity, String>) OafEntity::getId, Encoders.STRING())
.mapGroups((MapGroupsFunction<String, OafEntity, OafEntity>) MergeUtils::mergeById, OAFENTITY_KRYO_ENC)
.mapGroups(
(MapGroupsFunction<String, OafEntity, OafEntity>) (key, group) -> MergeUtils.mergeById(group, vocs),
OAFENTITY_KRYO_ENC)
.map(
(MapFunction<OafEntity, Tuple2<String, OafEntity>>) t -> new Tuple2<>(
t.getClass().getName(), t),

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@ -2,7 +2,6 @@
package eu.dnetlib.dhp.schema.oaf.utils;
import static eu.dnetlib.dhp.schema.common.ModelConstants.*;
import static eu.dnetlib.dhp.schema.common.ModelConstants.OPENAIRE_META_RESOURCE_TYPE;
import static eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils.getProvenance;
import java.net.MalformedURLException;
@ -363,6 +362,8 @@ public class GraphCleaningFunctions extends CleaningFunctions {
// nothing to clean here
} else if (value instanceof Project) {
// nothing to clean here
} else if (value instanceof Person) {
// nothing to clean here
} else if (value instanceof Organization) {
Organization o = (Organization) value;
if (Objects.isNull(o.getCountry()) || StringUtils.isBlank(o.getCountry().getClassid())) {
@ -694,6 +695,7 @@ public class GraphCleaningFunctions extends CleaningFunctions {
}
}
// set ORCID_PENDING to all orcid values that are not coming from ORCID provenance
for (Author a : r.getAuthor()) {
if (Objects.isNull(a.getPid())) {
a.setPid(Lists.newArrayList());
@ -750,6 +752,40 @@ public class GraphCleaningFunctions extends CleaningFunctions {
.collect(Collectors.toList()));
}
}
// Identify clashing ORCIDS:that is same ORCID associated to multiple authors in this result
Map<String, Integer> clashing_orcid = new HashMap<>();
for (Author a : r.getAuthor()) {
a
.getPid()
.stream()
.filter(
p -> StringUtils
.contains(StringUtils.lowerCase(p.getQualifier().getClassid()), ORCID_PENDING))
.map(StructuredProperty::getValue)
.distinct()
.forEach(orcid -> clashing_orcid.compute(orcid, (k, v) -> (v == null) ? 1 : v + 1));
}
Set<String> clashing = clashing_orcid
.entrySet()
.stream()
.filter(ee -> ee.getValue() > 1)
.map(Map.Entry::getKey)
.collect(Collectors.toSet());
// filter out clashing orcids
for (Author a : r.getAuthor()) {
a
.setPid(
a
.getPid()
.stream()
.filter(p -> !clashing.contains(p.getValue()))
.collect(Collectors.toList()));
}
}
if (value instanceof Publication) {
@ -808,7 +844,7 @@ public class GraphCleaningFunctions extends CleaningFunctions {
return author;
}
private static Optional<String> cleanDateField(Field<String> dateofacceptance) {
public static Optional<String> cleanDateField(Field<String> dateofacceptance) {
return Optional
.ofNullable(dateofacceptance)
.map(Field::getValue)

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@ -204,6 +204,7 @@ public class IdentifierFactory implements Serializable {
.map(
pp -> pp
.stream()
.filter(p -> StringUtils.isNotBlank(p.getValue()))
// filter away PIDs provided by a DS that is not considered an authority for the
// given PID Type
.filter(p -> shouldFilterPidByCriteria(collectedFrom, p, mapHandles))

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@ -23,24 +23,30 @@ import org.apache.commons.lang3.tuple.Pair;
import com.github.sisyphsu.dateparser.DateParserUtils;
import com.google.common.base.Joiner;
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup;
import eu.dnetlib.dhp.oa.merge.AuthorMerger;
import eu.dnetlib.dhp.schema.common.AccessRightComparator;
import eu.dnetlib.dhp.schema.common.EntityType;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport;
import eu.dnetlib.dhp.schema.oaf.*;
public class MergeUtils {
public static <T extends Oaf> T mergeById(String s, Iterator<T> oafEntityIterator) {
return mergeGroup(s, oafEntityIterator, true);
public static <T extends Oaf> T mergeById(Iterator<T> oafEntityIterator, VocabularyGroup vocs) {
return mergeGroup(oafEntityIterator, true, vocs);
}
public static <T extends Oaf> T mergeGroup(String s, Iterator<T> oafEntityIterator) {
return mergeGroup(s, oafEntityIterator, false);
public static <T extends Oaf> T mergeGroup(Iterator<T> oafEntityIterator) {
return mergeGroup(oafEntityIterator, false);
}
public static <T extends Oaf> T mergeGroup(String s, Iterator<T> oafEntityIterator,
boolean checkDelegateAuthority) {
public static <T extends Oaf> T mergeGroup(Iterator<T> oafEntityIterator, boolean checkDelegateAuthority) {
return mergeGroup(oafEntityIterator, checkDelegateAuthority, null);
}
public static <T extends Oaf> T mergeGroup(Iterator<T> oafEntityIterator,
boolean checkDelegateAuthority, VocabularyGroup vocs) {
ArrayList<T> sortedEntities = new ArrayList<>();
oafEntityIterator.forEachRemaining(sortedEntities::add);
@ -49,13 +55,55 @@ public class MergeUtils {
Iterator<T> it = sortedEntities.iterator();
T merged = it.next();
while (it.hasNext()) {
merged = checkedMerge(merged, it.next(), checkDelegateAuthority);
if (!it.hasNext() && merged instanceof Result && vocs != null) {
return enforceResultType(vocs, (Result) merged);
} else {
while (it.hasNext()) {
merged = checkedMerge(merged, it.next(), checkDelegateAuthority);
}
}
return merged;
}
private static <T extends Oaf> T enforceResultType(VocabularyGroup vocs, Result mergedResult) {
if (Optional.ofNullable(mergedResult.getInstance()).map(List::isEmpty).orElse(true)) {
return (T) mergedResult;
} else {
final Instance i = mergedResult.getInstance().get(0);
if (!vocs.vocabularyExists(ModelConstants.DNET_RESULT_TYPOLOGIES)) {
return (T) mergedResult;
} else {
final String expectedResultType = Optional
.ofNullable(
vocs
.lookupTermBySynonym(
ModelConstants.DNET_RESULT_TYPOLOGIES, i.getInstancetype().getClassid()))
.orElse(ModelConstants.ORP_DEFAULT_RESULTTYPE)
.getClassid();
// there is a clash among the result types
if (!expectedResultType.equals(mergedResult.getResulttype().getClassid())) {
Result result = (Result) Optional
.ofNullable(ModelSupport.oafTypes.get(expectedResultType))
.map(r -> {
try {
return r.newInstance();
} catch (InstantiationException | IllegalAccessException e) {
throw new IllegalStateException(e);
}
})
.orElse(new OtherResearchProduct());
result.setId(mergedResult.getId());
return (T) mergeResultFields(result, mergedResult);
} else {
return (T) mergedResult;
}
}
}
}
public static <T extends Oaf> T checkedMerge(final T left, final T right, boolean checkDelegateAuthority) {
return (T) merge(left, right, checkDelegateAuthority);
}
@ -106,7 +154,7 @@ public class MergeUtils {
return mergeSoftware((Software) left, (Software) right);
}
return mergeResultFields((Result) left, (Result) right);
return left;
} else if (sameClass(left, right, Datasource.class)) {
// TODO
final int trust = compareTrust(left, right);
@ -654,16 +702,9 @@ public class MergeUtils {
}
private static Field<String> selectOldestDate(Field<String> d1, Field<String> d2) {
if (d1 == null || StringUtils.isBlank(d1.getValue())) {
if (!GraphCleaningFunctions.cleanDateField(d1).isPresent()) {
return d2;
} else if (d2 == null || StringUtils.isBlank(d2.getValue())) {
return d1;
}
if (StringUtils.contains(d1.getValue(), "null")) {
return d2;
}
if (StringUtils.contains(d2.getValue(), "null")) {
} else if (!GraphCleaningFunctions.cleanDateField(d2).isPresent()) {
return d1;
}
@ -715,7 +756,11 @@ public class MergeUtils {
private static String spKeyExtractor(StructuredProperty sp) {
return Optional
.ofNullable(sp)
.map(s -> Joiner.on("||").join(qualifierKeyExtractor(s.getQualifier()), s.getValue()))
.map(
s -> Joiner
.on("||")
.useForNull("")
.join(qualifierKeyExtractor(s.getQualifier()), s.getValue()))
.orElse(null);
}

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@ -1,6 +1,12 @@
package eu.dnetlib.dhp.schema.oaf.utils;
import java.util.Map;
import com.google.common.collect.Maps;
import eu.dnetlib.dhp.schema.common.ModelConstants;
public class ModelHardLimits {
private ModelHardLimits() {
@ -12,6 +18,7 @@ public class ModelHardLimits {
public static final int MAX_EXTERNAL_ENTITIES = 50;
public static final int MAX_AUTHORS = 200;
public static final int MAX_RELATED_AUTHORS = 20;
public static final int MAX_AUTHOR_FULLNAME_LENGTH = 1000;
public static final int MAX_TITLE_LENGTH = 5000;
public static final int MAX_TITLES = 10;
@ -19,6 +26,12 @@ public class ModelHardLimits {
public static final int MAX_ABSTRACT_LENGTH = 150000;
public static final int MAX_RELATED_ABSTRACT_LENGTH = 500;
public static final int MAX_INSTANCES = 10;
public static final Map<String, Long> MAX_RELATIONS_BY_RELCLASS = Maps.newHashMap();
static {
MAX_RELATIONS_BY_RELCLASS.put(ModelConstants.PERSON_PERSON_HASCOAUTHORED, 500L);
MAX_RELATIONS_BY_RELCLASS.put(ModelConstants.RESULT_PERSON_HASAUTHORED, 500L);
}
public static String getCollectionName(String format) {
return format + SEPARATOR + LAYOUT + SEPARATOR + INTERPRETATION;

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@ -26,7 +26,7 @@ public class PidCleaner {
String value = Optional
.ofNullable(pidValue)
.map(String::trim)
.orElseThrow(() -> new IllegalArgumentException("PID value cannot be empty"));
.orElseThrow(() -> new IllegalArgumentException("PID (" + pidType + ") value cannot be empty"));
switch (pidType) {

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@ -179,7 +179,7 @@ class OafMapperUtilsTest {
assertEquals(
ModelConstants.DATASET_RESULTTYPE_CLASSID,
((Result) MergeUtils
.merge(p2, d1))
.merge(p2, d1, true))
.getResulttype()
.getClassid());
}

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@ -38,7 +38,7 @@ public class NumAuthorsTitleSuffixPrefixChain extends AbstractClusteringFunction
@Override
protected Collection<String> doApply(Config conf, String s) {
return suffixPrefixChain(cleanup(s), param("mod"));
return suffixPrefixChain(cleanup(s), paramOrDefault("mod", 10));
}
private Collection<String> suffixPrefixChain(String s, int mod) {

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@ -90,7 +90,7 @@ public class AbstractPaceFunctions extends PaceCommonUtils {
inferFrom = normalize(inferFrom);
inferFrom = filterAllStopWords(inferFrom);
Set<String> cities = getCities(inferFrom, 4);
return citiesToCountry(cities).stream().findFirst().orElse("UNKNOWN");
return citiesToCountry(cities).stream().filter(Objects::nonNull).findFirst().orElse("UNKNOWN");
}
public static String cityInference(String original) {

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@ -54,6 +54,22 @@ public class FieldDef implements Serializable {
public FieldDef() {
}
public FieldDef clone() {
FieldDef fieldDef = new FieldDef();
fieldDef.setName(this.name);
fieldDef.setPath(this.path);
fieldDef.setType(this.type);
fieldDef.setOverrideMatch(this.overrideMatch);
fieldDef.setSize(this.size);
fieldDef.setLength(this.length);
fieldDef.setFilter(this.filter);
fieldDef.setSorted(this.sorted);
fieldDef.setClean(this.clean);
fieldDef.setInfer(this.infer);
fieldDef.setInferenceFrom(this.inferenceFrom);
return fieldDef;
}
public String getInferenceFrom() {
return inferenceFrom;
}

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@ -19,48 +19,10 @@ case class SparkDeduper(conf: DedupConfig) extends Serializable {
val model: SparkModel = SparkModel(conf)
val dedup: (Dataset[Row] => Dataset[Row]) = df => {
df.transform(filterAndCleanup)
.transform(generateClustersWithCollect)
df.transform(generateClustersWithCollect)
.transform(processBlocks)
}
val filterAndCleanup: (Dataset[Row] => Dataset[Row]) = df => {
val df_with_filters = conf.getPace.getModel.asScala.foldLeft(df)((res, fdef) => {
if (conf.blacklists.containsKey(fdef.getName)) {
res.withColumn(
fdef.getName + "_filtered",
filterColumnUDF(fdef).apply(new Column(fdef.getName))
)
} else {
res
}
})
df_with_filters
}
def filterColumnUDF(fdef: FieldDef): UserDefinedFunction = {
val blacklist: Predicate[String] = conf.blacklists().get(fdef.getName)
if (blacklist == null) {
throw new IllegalArgumentException("Column: " + fdef.getName + " does not have any filter")
} else {
fdef.getType match {
case Type.List | Type.JSON =>
udf[Array[String], Array[String]](values => {
values.filter((v: String) => !blacklist.test(v))
})
case _ =>
udf[String, String](v => {
if (blacklist.test(v)) ""
else v
})
}
}
}
val generateClustersWithCollect: (Dataset[Row] => Dataset[Row]) = df_with_filters => {
var df_with_clustering_keys: Dataset[Row] = null

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@ -5,12 +5,12 @@ import eu.dnetlib.pace.common.AbstractPaceFunctions
import eu.dnetlib.pace.config.{DedupConfig, Type}
import eu.dnetlib.pace.util.{MapDocumentUtil, SparkCompatUtils}
import org.apache.commons.lang3.StringUtils
import org.apache.spark.sql.catalyst.encoders.RowEncoder
import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema
import org.apache.spark.sql.types.{DataTypes, Metadata, StructField, StructType}
import org.apache.spark.sql.{Dataset, Row}
import java.util.Locale
import java.util.function.Predicate
import java.util.regex.Pattern
import scala.collection.JavaConverters._
@ -29,8 +29,20 @@ case class SparkModel(conf: DedupConfig) {
identifier.setName(identifierFieldName)
identifier.setType(Type.String)
// create fields for blacklist
val filtered = conf.getPace.getModel.asScala.flatMap(fdef => {
if (conf.blacklists().containsKey(fdef.getName)) {
val fdef_filtered = fdef.clone()
fdef_filtered.setName(fdef.getName + "_filtered")
Seq(fdef, fdef_filtered)
}
else {
Seq(fdef)
}
})
// Construct a Spark StructType representing the schema of the model
(Seq(identifier) ++ conf.getPace.getModel.asScala)
(Seq(identifier) ++ filtered)
.foldLeft(
new StructType()
)((resType, fieldDef) => {
@ -44,7 +56,6 @@ case class SparkModel(conf: DedupConfig) {
})
})
}
val identityFieldPosition: Int = schema.fieldIndex(identifierFieldName)
@ -52,7 +63,8 @@ case class SparkModel(conf: DedupConfig) {
val orderingFieldPosition: Int = schema.fieldIndex(orderingFieldName)
val parseJsonDataset: (Dataset[String] => Dataset[Row]) = df => {
df.map(r => rowFromJson(r))(SparkCompatUtils.encoderFor(schema))
df
.map(r => rowFromJson(r))(SparkCompatUtils.encoderFor(schema))
}
def rowFromJson(json: String): Row = {
@ -64,41 +76,63 @@ case class SparkModel(conf: DedupConfig) {
schema.fieldNames.zipWithIndex.foldLeft(values) {
case ((res, (fname, index))) =>
val fdef = conf.getPace.getModelMap.get(fname)
val fdef = conf.getPace.getModelMap.get(fname.split("_filtered")(0))
if (fdef != null) {
res(index) = fdef.getType match {
case Type.String | Type.Int =>
MapDocumentUtil.truncateValue(
MapDocumentUtil.getJPathString(fdef.getPath, documentContext),
fdef.getLength
)
if (!fname.contains("_filtered")) { //process fields with no blacklist
res(index) = fdef.getType match {
case Type.String | Type.Int =>
MapDocumentUtil.truncateValue(
MapDocumentUtil.getJPathString(fdef.getPath, documentContext),
fdef.getLength
)
case Type.URL =>
var uv = MapDocumentUtil.getJPathString(fdef.getPath, documentContext)
if (!URL_REGEX.matcher(uv).matches)
uv = ""
uv
case Type.URL =>
var uv = MapDocumentUtil.getJPathString(fdef.getPath, documentContext)
if (!URL_REGEX.matcher(uv).matches)
uv = ""
uv
case Type.List | Type.JSON =>
MapDocumentUtil.truncateList(
MapDocumentUtil.getJPathList(fdef.getPath, documentContext, fdef.getType),
fdef.getSize
).asScala
case Type.List | Type.JSON =>
MapDocumentUtil.truncateList(
MapDocumentUtil.getJPathList(fdef.getPath, documentContext, fdef.getType),
fdef.getSize
).asScala
case Type.StringConcat =>
val jpaths = CONCAT_REGEX.split(fdef.getPath)
case Type.StringConcat =>
val jpaths = CONCAT_REGEX.split(fdef.getPath)
MapDocumentUtil.truncateValue(
jpaths
.map(jpath => MapDocumentUtil.getJPathString(jpath, documentContext))
.mkString(" "),
fdef.getLength
)
MapDocumentUtil.truncateValue(
jpaths
.map(jpath => MapDocumentUtil.getJPathString(jpath, documentContext))
.mkString(" "),
fdef.getLength
)
case Type.DoubleArray =>
MapDocumentUtil.getJPathArray(fdef.getPath, json)
case Type.DoubleArray =>
MapDocumentUtil.getJPathArray(fdef.getPath, json)
}
}
else { //process fields with blacklist
val blacklist: Predicate[String] = conf.blacklists().get(fdef.getName)
res(index) = fdef.getType match {
case Type.List | Type.JSON =>
MapDocumentUtil.truncateList(
MapDocumentUtil.getJPathList(fdef.getPath, documentContext, fdef.getType),
fdef.getSize
).asScala.filter((v: String) => !blacklist.test(v))
case _ =>
val value: String = MapDocumentUtil.truncateValue(
MapDocumentUtil.getJPathString(fdef.getPath, documentContext),
fdef.getLength
)
if (blacklist.test(value)) "" else value
}
}
val filter = fdef.getFilter
@ -125,13 +159,12 @@ case class SparkModel(conf: DedupConfig) {
}
if (StringUtils.isNotBlank(fdef.getInfer)) {
val inferFrom : String = if (StringUtils.isNotBlank(fdef.getInferenceFrom)) fdef.getInferenceFrom else fdef.getPath
val inferFrom: String = if (StringUtils.isNotBlank(fdef.getInferenceFrom)) fdef.getInferenceFrom else fdef.getPath
res(index) = res(index) match {
case x: Seq[String] => x.map(inference(_, MapDocumentUtil.getJPathString(inferFrom, documentContext), fdef.getInfer))
case _ => inference(res(index).toString, MapDocumentUtil.getJPathString(inferFrom, documentContext), fdef.getInfer)
}
}
}
res
@ -139,6 +172,7 @@ case class SparkModel(conf: DedupConfig) {
}
new GenericRowWithSchema(values, schema)
}
def clean(value: String, cleantype: String) : String = {

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@ -227,4 +227,17 @@ public class ClusteringFunctionTest extends AbstractPaceTest {
System.out.println(cf.apply(conf, Lists.newArrayList(s)));
}
@Test
public void testNumAuthorsTitleSuffixPrefixChain() {
final ClusteringFunction cf = new NumAuthorsTitleSuffixPrefixChain(params);
params.put("mod", 10);
final String title = "PARP-2 Regulates SIRT1 Expression and Whole-Body Energy Expenditure";
final String num_authors = "10";
System.out.println("title = " + title);
System.out.println("num_authors = " + num_authors);
System.out.println(cf.apply(conf, Lists.newArrayList(num_authors, title)));
}
}

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@ -1,8 +1,7 @@
package eu.dnetlib.pace.common;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
import static org.junit.jupiter.api.Assertions.*;
import org.junit.jupiter.api.*;
@ -54,8 +53,17 @@ public class PaceFunctionTest extends AbstractPaceFunctions {
System.out.println("Fixed aliases : " + fixAliases(TEST_STRING));
}
@Test()
public void countryInferenceTest_NPE() {
assertThrows(
NullPointerException.class,
() -> countryInference("UNKNOWN", null),
"Expected countryInference() to throw an NPE");
}
@Test
public void countryInferenceTest() {
assertEquals("UNKNOWN", countryInference("UNKNOWN", ""));
assertEquals("IT", countryInference("UNKNOWN", "Università di Bologna"));
assertEquals("UK", countryInference("UK", "Università di Bologna"));
assertEquals("IT", countryInference("UNKNOWN", "Universiteé de Naples"));

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@ -367,7 +367,18 @@ public class ComparatorTest extends AbstractPaceTest {
result = dateRange.distance("invalid date", "2021-05-02", conf);
assertEquals(-1.0, result);
}
@Test
public void titleVersionMatchTest() {
TitleVersionMatch titleVersionMatch = new TitleVersionMatch(params);
double result = titleVersionMatch
.compare(
"parp 2 regulates sirt 1 expression and whole body energy expenditure",
"parp 2 regulates sirt 1 expression and whole body energy expenditure", conf);
assertEquals(1.0, result);
}
}

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@ -11,7 +11,6 @@ import org.junit.jupiter.api.Disabled;
import org.junit.jupiter.api.Test;
import eu.dnetlib.pace.model.Person;
import jdk.nashorn.internal.ir.annotations.Ignore;
public class UtilTest {

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@ -151,12 +151,17 @@ public class PromoteActionPayloadForGraphTableJob {
SparkSession spark, String path, Class<G> rowClazz) {
logger.info("Reading graph table from path: {}", path);
return spark
.read()
.textFile(path)
.map(
(MapFunction<String, G>) value -> OBJECT_MAPPER.readValue(value, rowClazz),
Encoders.bean(rowClazz));
if (HdfsSupport.exists(path, spark.sparkContext().hadoopConfiguration())) {
return spark
.read()
.textFile(path)
.map(
(MapFunction<String, G>) value -> OBJECT_MAPPER.readValue(value, rowClazz),
Encoders.bean(rowClazz));
} else {
logger.info("Found empty graph table from path: {}", path);
return spark.emptyDataset(Encoders.bean(rowClazz));
}
}
private static <A extends Oaf> Dataset<A> readActionPayload(
@ -223,7 +228,7 @@ public class PromoteActionPayloadForGraphTableJob {
rowClazz,
actionPayloadClazz);
if (shouldGroupById) {
if (Boolean.TRUE.equals(shouldGroupById)) {
return PromoteActionPayloadFunctions
.groupGraphTableByIdAndMerge(
joinedAndMerged, rowIdFn, mergeRowsAndGetFn, zeroFn, isNotZeroFn, rowClazz);
@ -250,6 +255,8 @@ public class PromoteActionPayloadForGraphTableJob {
return () -> clazz.cast(new eu.dnetlib.dhp.schema.oaf.Relation());
case "eu.dnetlib.dhp.schema.oaf.Software":
return () -> clazz.cast(new eu.dnetlib.dhp.schema.oaf.Software());
case "eu.dnetlib.dhp.schema.oaf.Person":
return () -> clazz.cast(new eu.dnetlib.dhp.schema.oaf.Person());
default:
throw new RuntimeException("unknown class: " + clazz.getCanonicalName());
}

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@ -50,7 +50,7 @@ public class PromoteActionPayloadFunctions {
PromoteAction.Strategy promoteActionStrategy,
Class<G> rowClazz,
Class<A> actionPayloadClazz) {
if (!isSubClass(rowClazz, actionPayloadClazz)) {
if (Boolean.FALSE.equals(isSubClass(rowClazz, actionPayloadClazz))) {
throw new RuntimeException(
"action payload type must be the same or be a super type of table row type");
}

View File

@ -7,3 +7,4 @@ promote_action_payload_for_project_table classpath eu/dnetlib/dhp/actionmanager/
promote_action_payload_for_publication_table classpath eu/dnetlib/dhp/actionmanager/wf/publication/oozie_app
promote_action_payload_for_relation_table classpath eu/dnetlib/dhp/actionmanager/wf/relation/oozie_app
promote_action_payload_for_software_table classpath eu/dnetlib/dhp/actionmanager/wf/software/oozie_app
promote_action_payload_for_person_table classpath eu/dnetlib/dhp/actionmanager/wf/person/oozie_app

View File

@ -148,6 +148,7 @@
<path start="PromoteActionPayloadForPublicationTable"/>
<path start="PromoteActionPayloadForRelationTable"/>
<path start="PromoteActionPayloadForSoftwareTable"/>
<path start="PromoteActionPayloadForPersonTable"/>
</fork>
<action name="PromoteActionPayloadForDatasetTable">
@ -270,6 +271,21 @@
<error to="Kill"/>
</action>
<action name="PromoteActionPayloadForPersonTable">
<sub-workflow>
<app-path>${wf:appPath()}/promote_action_payload_for_person_table</app-path>
<propagate-configuration/>
<configuration>
<property>
<name>inputActionPayloadRootPath</name>
<value>${workingDir}/action_payload_by_type</value>
</property>
</configuration>
</sub-workflow>
<ok to="JoinPromote"/>
<error to="Kill"/>
</action>
<join name="JoinPromote" to="End"/>
<end name="End"/>

View File

@ -0,0 +1,129 @@
<workflow-app name="promote_action_payload_for_person_table" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>activePromotePersonActionPayload</name>
<description>when true will promote actions with eu.dnetlib.dhp.schema.oaf.Person payload</description>
</property>
<property>
<name>inputGraphRootPath</name>
<description>root location of input materialized graph</description>
</property>
<property>
<name>inputActionPayloadRootPath</name>
<description>root location of action payloads to promote</description>
</property>
<property>
<name>outputGraphRootPath</name>
<description>root location for output materialized graph</description>
</property>
<property>
<name>mergeAndGetStrategy</name>
<description>strategy for merging graph table objects with action payload instances, MERGE_FROM_AND_GET or SELECT_NEWER_AND_GET</description>
</property>
<property>
<name>sparkDriverMemory</name>
<description>memory for driver process</description>
</property>
<property>
<name>sparkExecutorMemory</name>
<description>memory for individual executor</description>
</property>
<property>
<name>sparkExecutorCores</name>
<description>number of cores used by single executor</description>
</property>
<property>
<name>oozieActionShareLibForSpark2</name>
<description>oozie action sharelib for spark 2.*</description>
</property>
<property>
<name>spark2ExtraListeners</name>
<value>com.cloudera.spark.lineage.NavigatorAppListener</value>
<description>spark 2.* extra listeners classname</description>
</property>
<property>
<name>spark2SqlQueryExecutionListeners</name>
<value>com.cloudera.spark.lineage.NavigatorQueryListener</value>
<description>spark 2.* sql query execution listeners classname</description>
</property>
<property>
<name>spark2YarnHistoryServerAddress</name>
<description>spark 2.* yarn history server address</description>
</property>
<property>
<name>spark2EventLogDir</name>
<description>spark 2.* event log dir location</description>
</property>
</parameters>
<global>
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<configuration>
<property>
<name>oozie.action.sharelib.for.spark</name>
<value>${oozieActionShareLibForSpark2}</value>
</property>
</configuration>
</global>
<start to="DecisionPromotePersonActionPayload"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<decision name="DecisionPromotePersonActionPayload">
<switch>
<case to="PromotePersonActionPayloadForPersonTable">
${(activePromotePersonActionPayload eq "true") and
(fs:exists(concat(concat(concat(concat(wf:conf('nameNode'),'/'),wf:conf('inputActionPayloadRootPath')),'/'),'clazz=eu.dnetlib.dhp.schema.oaf.Person')) eq "true")}
</case>
<default to="SkipPromotePersonActionPayloadForPersonTable"/>
</switch>
</decision>
<action name="PromotePersonActionPayloadForPersonTable">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>PromotePersonActionPayloadForPersonTable</name>
<class>eu.dnetlib.dhp.actionmanager.promote.PromoteActionPayloadForGraphTableJob</class>
<jar>dhp-actionmanager-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.executor.memoryOverhead=${sparkExecutorMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<arg>--inputGraphTablePath</arg><arg>${inputGraphRootPath}/person</arg>
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--inputActionPayloadPath</arg><arg>${inputActionPayloadRootPath}/clazz=eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--actionPayloadClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--outputGraphTablePath</arg><arg>${outputGraphRootPath}/person</arg>
<arg>--mergeAndGetStrategy</arg><arg>${mergeAndGetStrategy}</arg>
<arg>--promoteActionStrategy</arg><arg>${promoteActionStrategy}</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<action name="SkipPromotePersonActionPayloadForPersonTable">
<distcp xmlns="uri:oozie:distcp-action:0.2">
<prepare>
<delete path="${outputGraphRootPath}/person"/>
</prepare>
<arg>-pb</arg>
<arg>${inputGraphRootPath}/person</arg>
<arg>${outputGraphRootPath}/person</arg>
</distcp>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -34,7 +34,7 @@ import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
import scala.Tuple2;
/**
* Creates action sets for Crossref affiliation relations inferred by BIP!
* Creates action sets for Crossref affiliation relations inferred by OpenAIRE
*/
public class PrepareAffiliationRelations implements Serializable {
@ -104,22 +104,22 @@ public class PrepareAffiliationRelations implements Serializable {
.listKeyValues(OPENAIRE_DATASOURCE_ID, OPENAIRE_DATASOURCE_NAME);
JavaPairRDD<Text, Text> crossrefRelations = prepareAffiliationRelationsNewModel(
spark, crossrefInputPath, collectedfromOpenAIRE);
spark, crossrefInputPath, collectedfromOpenAIRE, BIP_INFERENCE_PROVENANCE + ":crossref");
JavaPairRDD<Text, Text> pubmedRelations = prepareAffiliationRelations(
spark, pubmedInputPath, collectedfromOpenAIRE);
spark, pubmedInputPath, collectedfromOpenAIRE, BIP_INFERENCE_PROVENANCE + ":pubmed");
JavaPairRDD<Text, Text> openAPCRelations = prepareAffiliationRelationsNewModel(
spark, openapcInputPath, collectedfromOpenAIRE);
spark, openapcInputPath, collectedfromOpenAIRE, BIP_INFERENCE_PROVENANCE + ":openapc");
JavaPairRDD<Text, Text> dataciteRelations = prepareAffiliationRelations(
spark, dataciteInputPath, collectedfromOpenAIRE);
JavaPairRDD<Text, Text> dataciteRelations = prepareAffiliationRelationsNewModel(
spark, dataciteInputPath, collectedfromOpenAIRE, BIP_INFERENCE_PROVENANCE + ":datacite");
JavaPairRDD<Text, Text> webCrawlRelations = prepareAffiliationRelations(
spark, webcrawlInputPath, collectedfromOpenAIRE);
JavaPairRDD<Text, Text> webCrawlRelations = prepareAffiliationRelationsNewModel(
spark, webcrawlInputPath, collectedfromOpenAIRE, BIP_INFERENCE_PROVENANCE + ":rawaff");
JavaPairRDD<Text, Text> publisherRelations = prepareAffiliationRelationFromPublisher(
spark, publisherlInputPath, collectedfromOpenAIRE);
JavaPairRDD<Text, Text> publisherRelations = prepareAffiliationRelationFromPublisherNewModel(
spark, publisherlInputPath, collectedfromOpenAIRE, BIP_INFERENCE_PROVENANCE + ":webcrawl");
crossrefRelations
.union(pubmedRelations)
@ -133,7 +133,8 @@ public class PrepareAffiliationRelations implements Serializable {
private static JavaPairRDD<Text, Text> prepareAffiliationRelationFromPublisherNewModel(SparkSession spark,
String inputPath,
List<KeyValue> collectedfrom) {
List<KeyValue> collectedfrom,
String dataprovenance) {
Dataset<Row> df = spark
.read()
@ -142,12 +143,13 @@ public class PrepareAffiliationRelations implements Serializable {
.json(inputPath)
.where("DOI is not null");
return getTextTextJavaPairRDD(collectedfrom, df.selectExpr("DOI", "Organizations as Matchings"));
return getTextTextJavaPairRDDNew(
collectedfrom, df.selectExpr("DOI", "Organizations as Matchings"), dataprovenance);
}
private static JavaPairRDD<Text, Text> prepareAffiliationRelationFromPublisher(SparkSession spark, String inputPath,
List<KeyValue> collectedfrom) {
List<KeyValue> collectedfrom, String dataprovenance) {
Dataset<Row> df = spark
.read()
@ -155,13 +157,14 @@ public class PrepareAffiliationRelations implements Serializable {
.json(inputPath)
.where("DOI is not null");
return getTextTextJavaPairRDD(collectedfrom, df.selectExpr("DOI", "Organizations as Matchings"));
return getTextTextJavaPairRDD(
collectedfrom, df.selectExpr("DOI", "Organizations as Matchings"), dataprovenance);
}
private static <I extends Result> JavaPairRDD<Text, Text> prepareAffiliationRelations(SparkSession spark,
String inputPath,
List<KeyValue> collectedfrom) {
List<KeyValue> collectedfrom, String dataprovenance) {
// load and parse affiliation relations from HDFS
Dataset<Row> df = spark
@ -170,12 +173,12 @@ public class PrepareAffiliationRelations implements Serializable {
.json(inputPath)
.where("DOI is not null");
return getTextTextJavaPairRDD(collectedfrom, df);
return getTextTextJavaPairRDD(collectedfrom, df, dataprovenance);
}
private static <I extends Result> JavaPairRDD<Text, Text> prepareAffiliationRelationsNewModel(SparkSession spark,
String inputPath,
List<KeyValue> collectedfrom) {
List<KeyValue> collectedfrom, String dataprovenance) {
// load and parse affiliation relations from HDFS
Dataset<Row> df = spark
.read()
@ -184,10 +187,11 @@ public class PrepareAffiliationRelations implements Serializable {
.json(inputPath)
.where("DOI is not null");
return getTextTextJavaPairRDDNew(collectedfrom, df);
return getTextTextJavaPairRDDNew(collectedfrom, df, dataprovenance);
}
private static JavaPairRDD<Text, Text> getTextTextJavaPairRDD(List<KeyValue> collectedfrom, Dataset<Row> df) {
private static JavaPairRDD<Text, Text> getTextTextJavaPairRDD(List<KeyValue> collectedfrom, Dataset<Row> df,
String dataprovenance) {
// unroll nested arrays
df = df
.withColumn("matching", functions.explode(new Column("Matchings")))
@ -219,7 +223,7 @@ public class PrepareAffiliationRelations implements Serializable {
DataInfo dataInfo = OafMapperUtils
.dataInfo(
false,
BIP_INFERENCE_PROVENANCE,
dataprovenance,
true,
false,
qualifier,
@ -235,7 +239,8 @@ public class PrepareAffiliationRelations implements Serializable {
new Text(OBJECT_MAPPER.writeValueAsString(aa))));
}
private static JavaPairRDD<Text, Text> getTextTextJavaPairRDDNew(List<KeyValue> collectedfrom, Dataset<Row> df) {
private static JavaPairRDD<Text, Text> getTextTextJavaPairRDDNew(List<KeyValue> collectedfrom, Dataset<Row> df,
String dataprovenance) {
// unroll nested arrays
df = df
.withColumn("matching", functions.explode(new Column("Matchings")))
@ -276,7 +281,7 @@ public class PrepareAffiliationRelations implements Serializable {
DataInfo dataInfo = OafMapperUtils
.dataInfo(
false,
BIP_INFERENCE_PROVENANCE,
dataprovenance,
true,
false,
qualifier,

View File

@ -2,21 +2,31 @@
package eu.dnetlib.dhp.actionmanager.personentity;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import static org.apache.spark.sql.functions.*;
import java.io.BufferedWriter;
import java.io.IOException;
import java.io.OutputStreamWriter;
import java.io.Serializable;
import java.nio.charset.StandardCharsets;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.*;
import java.util.stream.Collectors;
import org.apache.commons.cli.ParseException;
import org.apache.commons.io.IOUtils;
import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.compress.BZip2Codec;
import org.apache.hadoop.mapred.SequenceFileOutputFormat;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.*;
import org.apache.spark.sql.*;
import org.apache.spark.sql.Dataset;
import org.jetbrains.annotations.NotNull;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
@ -28,13 +38,14 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.collection.orcid.model.Author;
import eu.dnetlib.dhp.collection.orcid.model.Employment;
import eu.dnetlib.dhp.collection.orcid.model.Work;
import eu.dnetlib.dhp.common.DbClient;
import eu.dnetlib.dhp.common.HdfsSupport;
import eu.dnetlib.dhp.common.person.CoAuthorshipIterator;
import eu.dnetlib.dhp.common.person.Coauthors;
import eu.dnetlib.dhp.schema.action.AtomicAction;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport;
import eu.dnetlib.dhp.schema.oaf.KeyValue;
import eu.dnetlib.dhp.schema.oaf.Person;
import eu.dnetlib.dhp.schema.oaf.Relation;
import eu.dnetlib.dhp.schema.oaf.*;
import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
import eu.dnetlib.dhp.schema.oaf.utils.PidCleaner;
@ -44,7 +55,7 @@ import scala.Tuple2;
public class ExtractPerson implements Serializable {
private static final Logger log = LoggerFactory.getLogger(ExtractPerson.class);
private static final String QUERY = "SELECT * FROM project_person WHERE pid_type = 'ORCID'";
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
private static final String OPENAIRE_PREFIX = "openaire____";
private static final String SEPARATOR = "::";
@ -58,9 +69,48 @@ public class ExtractPerson implements Serializable {
private static final String PMCID_PREFIX = "50|pmcid_______::";
private static final String ROR_PREFIX = "20|ror_________::";
private static final String PERSON_PREFIX = ModelSupport.getIdPrefix(Person.class) + "|orcid_______";
private static final String PERSON_PREFIX = ModelSupport.getIdPrefix(Person.class)
+ IdentifierFactory.ID_PREFIX_SEPARATOR + ModelConstants.ORCID + "_______";
private static final String PROJECT_ID_PREFIX = ModelSupport.getIdPrefix(Project.class)
+ IdentifierFactory.ID_PREFIX_SEPARATOR;
public static final String ORCID_AUTHORS_CLASSID = "sysimport:crosswalk:orcid";
public static final String ORCID_AUTHORS_CLASSNAME = "Imported from ORCID";
public static final String FUNDER_AUTHORS_CLASSID = "sysimport:crosswalk:funderdatabase";
public static final String FUNDER_AUTHORS_CLASSNAME = "Imported from Funder Database";
public static final String OPENAIRE_DATASOURCE_ID = "10|infrastruct_::f66f1bd369679b5b077dcdf006089556";
public static final String OPENAIRE_DATASOURCE_NAME = "OpenAIRE";
public static List<KeyValue> collectedfromOpenAIRE = OafMapperUtils
.listKeyValues(OPENAIRE_DATASOURCE_ID, OPENAIRE_DATASOURCE_NAME);
public static final DataInfo ORCIDDATAINFO = OafMapperUtils
.dataInfo(
false,
null,
false,
false,
OafMapperUtils
.qualifier(
ORCID_AUTHORS_CLASSID,
ORCID_AUTHORS_CLASSNAME,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91");
public static final DataInfo FUNDERDATAINFO = OafMapperUtils
.dataInfo(
false,
null,
false,
false,
OafMapperUtils
.qualifier(
FUNDER_AUTHORS_CLASSID,
FUNDER_AUTHORS_CLASSNAME,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91");
public static void main(final String[] args) throws IOException, ParseException {
@ -91,19 +141,130 @@ public class ExtractPerson implements Serializable {
final String workingDir = parser.get("workingDir");
log.info("workingDir {}", workingDir);
final String dbUrl = parser.get("postgresUrl");
final String dbUser = parser.get("postgresUser");
final String dbPassword = parser.get("postgresPassword");
final String hdfsNameNode = parser.get("hdfsNameNode");
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
HdfsSupport.remove(outputPath, spark.sparkContext().hadoopConfiguration());
createActionSet(spark, inputPath, outputPath, workingDir);
extractInfoForActionSetFromORCID(spark, inputPath, workingDir);
extractInfoForActionSetFromProjects(
spark, inputPath, workingDir, dbUrl, dbUser, dbPassword, workingDir + "/project", hdfsNameNode);
createActionSet(spark, outputPath, workingDir);
});
}
private static void createActionSet(SparkSession spark, String inputPath, String outputPath, String workingDir) {
private static void extractInfoForActionSetFromProjects(SparkSession spark, String inputPath, String workingDir,
String dbUrl, String dbUser, String dbPassword, String hdfsPath, String hdfsNameNode) throws IOException {
Configuration conf = new Configuration();
conf.set("fs.defaultFS", hdfsNameNode);
FileSystem fileSystem = FileSystem.get(conf);
Path hdfsWritePath = new Path(hdfsPath);
FSDataOutputStream fos = fileSystem.create(hdfsWritePath);
try (DbClient dbClient = new DbClient(dbUrl, dbUser, dbPassword)) {
try (BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(fos, StandardCharsets.UTF_8))) {
dbClient.processResults(QUERY, rs -> writeRelation(getRelationWithProject(rs), writer));
}
} catch (IOException e) {
throw new RuntimeException(e);
}
}
public static Relation getRelationWithProject(ResultSet rs) {
try {
return getProjectRelation(
rs.getString("project"), rs.getString("pid"),
rs.getString("role"));
} catch (final SQLException e) {
throw new RuntimeException(e);
}
}
private static Relation getProjectRelation(String project, String orcid, String role) {
String source = PERSON_PREFIX + "::" + IdentifierFactory.md5(orcid);
String target = PROJECT_ID_PREFIX + StringUtils.substringBefore(project, "::") + "::"
+ IdentifierFactory.md5(StringUtils.substringAfter(project, "::"));
List<KeyValue> properties = new ArrayList<>();
Relation relation = OafMapperUtils
.getRelation(
source, target, ModelConstants.PROJECT_PERSON_RELTYPE, ModelConstants.PROJECT_PERSON_SUBRELTYPE,
ModelConstants.PROJECT_PERSON_PARTICIPATES,
collectedfromOpenAIRE,
FUNDERDATAINFO,
null);
relation.setValidated(true);
if (StringUtil.isNotBlank(role)) {
KeyValue kv = new KeyValue();
kv.setKey("role");
kv.setValue(role);
properties.add(kv);
}
if (!properties.isEmpty())
relation.setProperties(properties);
return relation;
}
protected static void writeRelation(final Relation relation, BufferedWriter writer) {
try {
writer.write(OBJECT_MAPPER.writeValueAsString(relation));
writer.newLine();
} catch (final IOException e) {
throw new RuntimeException(e);
}
}
private static void createActionSet(SparkSession spark, String outputPath, String workingDir) {
Dataset<Person> people;
people = spark
.read()
.textFile(workingDir + "/people")
.map(
(MapFunction<String, Person>) value -> OBJECT_MAPPER
.readValue(value, Person.class),
Encoders.bean(Person.class));
people
.toJavaRDD()
.map(p -> new AtomicAction(p.getClass(), p))
.union(
getRelations(spark, workingDir + "/authorship").toJavaRDD().map(r -> new AtomicAction(r.getClass(), r)))
.union(
getRelations(spark, workingDir + "/coauthorship")
.toJavaRDD()
.map(r -> new AtomicAction(r.getClass(), r)))
.union(
getRelations(spark, workingDir + "/affiliation")
.toJavaRDD()
.map(r -> new AtomicAction(r.getClass(), r)))
.union(
getRelations(spark, workingDir + "/project")
.toJavaRDD()
.map(r -> new AtomicAction(r.getClass(), r)))
.mapToPair(
aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
new Text(OBJECT_MAPPER.writeValueAsString(aa))))
.saveAsHadoopFile(
outputPath, Text.class, Text.class, SequenceFileOutputFormat.class, BZip2Codec.class);
}
private static void extractInfoForActionSetFromORCID(SparkSession spark, String inputPath, String workingDir) {
Dataset<Author> authors = spark
.read()
.parquet(inputPath + "Authors")
@ -129,18 +290,13 @@ public class ExtractPerson implements Serializable {
.parquet(inputPath + "Employments")
.as(Encoders.bean(Employment.class));
Dataset<Author> peopleToMap = authors
.joinWith(works, authors.col("orcid").equalTo(works.col("orcid")))
.map((MapFunction<Tuple2<Author, Work>, Author>) t2 -> t2._1(), Encoders.bean(Author.class))
.groupByKey((MapFunction<Author, String>) a -> a.getOrcid(), Encoders.STRING())
.mapGroups((MapGroupsFunction<String, Author, Author>) (k, it) -> it.next(), Encoders.bean(Author.class));
Dataset<Employment> employment = employmentDataset
.joinWith(peopleToMap, employmentDataset.col("orcid").equalTo(peopleToMap.col("orcid")))
.joinWith(authors, employmentDataset.col("orcid").equalTo(authors.col("orcid")))
.map((MapFunction<Tuple2<Employment, Author>, Employment>) t2 -> t2._1(), Encoders.bean(Employment.class));
Dataset<Person> people;
peopleToMap.map((MapFunction<Author, Person>) op -> {
// Mapping all the orcid profiles even if the profile has no visible works
authors.map((MapFunction<Author, Person>) op -> {
Person person = new Person();
person.setId(DHPUtils.generateIdentifier(op.getOrcid(), PERSON_PREFIX));
person
@ -190,9 +346,19 @@ public class ExtractPerson implements Serializable {
OafMapperUtils
.structuredProperty(
op.getOrcid(), ModelConstants.ORCID, ModelConstants.ORCID_CLASSNAME,
ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES, null));
ModelConstants.DNET_PID_TYPES, ModelConstants.DNET_PID_TYPES,
OafMapperUtils.dataInfo(false,
null,
false,
false,
OafMapperUtils.qualifier(ModelConstants.SYSIMPORT_CROSSWALK_ENTITYREGISTRY,
ModelConstants.SYSIMPORT_CROSSWALK_ENTITYREGISTRY,
ModelConstants.DNET_PID_TYPES,
ModelConstants.DNET_PID_TYPES),
"0.91")));
person.setDateofcollection(op.getLastModifiedDate());
person.setOriginalId(Arrays.asList(op.getOrcid()));
person.setDataInfo(ORCIDDATAINFO);
return person;
}, Encoders.bean(Person.class))
.write()
@ -246,34 +412,6 @@ public class ExtractPerson implements Serializable {
.option("compression", "gzip")
.mode(SaveMode.Overwrite)
.json(workingDir + "/affiliation");
people = spark
.read()
.textFile(workingDir + "/people")
.map(
(MapFunction<String, Person>) value -> OBJECT_MAPPER
.readValue(value, Person.class),
Encoders.bean(Person.class));
people.show(false);
people
.toJavaRDD()
.map(p -> new AtomicAction(p.getClass(), p))
.union(
getRelations(spark, workingDir + "/authorship").toJavaRDD().map(r -> new AtomicAction(r.getClass(), r)))
.union(
getRelations(spark, workingDir + "/coauthorship")
.toJavaRDD()
.map(r -> new AtomicAction(r.getClass(), r)))
.union(
getRelations(spark, workingDir + "/affiliation")
.toJavaRDD()
.map(r -> new AtomicAction(r.getClass(), r)))
.mapToPair(
aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
new Text(OBJECT_MAPPER.writeValueAsString(aa))))
.saveAsHadoopFile(
outputPath, Text.class, Text.class, SequenceFileOutputFormat.class, BZip2Codec.class);
}
private static Dataset<Relation> getRelations(SparkSession spark, String path) {
@ -307,15 +445,9 @@ public class ExtractPerson implements Serializable {
source, target, ModelConstants.ORG_PERSON_RELTYPE, ModelConstants.ORG_PERSON_SUBRELTYPE,
ModelConstants.ORG_PERSON_PARTICIPATES,
Arrays.asList(OafMapperUtils.keyValue(orcidKey, ModelConstants.ORCID_DS)),
OafMapperUtils
.dataInfo(
false, null, false, false,
OafMapperUtils
.qualifier(
ORCID_AUTHORS_CLASSID, ORCID_AUTHORS_CLASSNAME, ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91"),
ORCIDDATAINFO,
null);
relation.setValidated(true);
if (Optional.ofNullable(row.getStartDate()).isPresent() && StringUtil.isNotBlank(row.getStartDate())) {
KeyValue kv = new KeyValue();
@ -336,45 +468,6 @@ public class ExtractPerson implements Serializable {
}
private static Collection<? extends Relation> getCoAuthorshipRelations(String orcid1, String orcid2) {
String source = PERSON_PREFIX + "::" + IdentifierFactory.md5(orcid1);
String target = PERSON_PREFIX + "::" + IdentifierFactory.md5(orcid2);
return Arrays
.asList(
OafMapperUtils
.getRelation(
source, target, ModelConstants.PERSON_PERSON_RELTYPE,
ModelConstants.PERSON_PERSON_SUBRELTYPE,
ModelConstants.PERSON_PERSON_HASCOAUTHORED,
Arrays.asList(OafMapperUtils.keyValue(orcidKey, ModelConstants.ORCID_DS)),
OafMapperUtils
.dataInfo(
false, null, false, false,
OafMapperUtils
.qualifier(
ORCID_AUTHORS_CLASSID, ORCID_AUTHORS_CLASSNAME,
ModelConstants.DNET_PROVENANCE_ACTIONS, ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91"),
null),
OafMapperUtils
.getRelation(
target, source, ModelConstants.PERSON_PERSON_RELTYPE,
ModelConstants.PERSON_PERSON_SUBRELTYPE,
ModelConstants.PERSON_PERSON_HASCOAUTHORED,
Arrays.asList(OafMapperUtils.keyValue(orcidKey, ModelConstants.ORCID_DS)),
OafMapperUtils
.dataInfo(
false, null, false, false,
OafMapperUtils
.qualifier(
ORCID_AUTHORS_CLASSID, ORCID_AUTHORS_CLASSNAME,
ModelConstants.DNET_PROVENANCE_ACTIONS, ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91"),
null));
}
private static @NotNull Iterator<Relation> getAuthorshipRelationIterator(Work w) {
if (Optional.ofNullable(w.getPids()).isPresent())
@ -417,21 +510,15 @@ public class ExtractPerson implements Serializable {
default:
return null;
}
return OafMapperUtils
Relation relation = OafMapperUtils
.getRelation(
source, target, ModelConstants.RESULT_PERSON_RELTYPE,
ModelConstants.RESULT_PERSON_SUBRELTYPE,
ModelConstants.RESULT_PERSON_HASAUTHORED,
Arrays.asList(OafMapperUtils.keyValue(orcidKey, ModelConstants.ORCID_DS)),
OafMapperUtils
.dataInfo(
false, null, false, false,
OafMapperUtils
.qualifier(
ORCID_AUTHORS_CLASSID, ORCID_AUTHORS_CLASSNAME, ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.91"),
ORCIDDATAINFO,
null);
relation.setValidated(true);
return relation;
}
}

View File

@ -31,9 +31,11 @@ spark2SqlQueryExecutionListeners=com.cloudera.spark.lineage.NavigatorQueryListen
# The following is needed as a property of a workflow
oozie.wf.application.path=${oozieTopWfApplicationPath}
crossrefInputPath=/data/bip-affiliations/crossref-data.json
pubmedInputPath=/data/bip-affiliations/pubmed-data.json
openapcInputPath=/data/bip-affiliations/openapc-data.json
dataciteInputPath=/data/bip-affiliations/datacite-data.json
crossrefInputPath=/data/openaire-affiliations/crossref-data.json
pubmedInputPath=/data/openaire-affiliations/pubmed-data-v4.json
openapcInputPath=/data/openaire-affiliations/openapc-data.json
dataciteInputPath=/data/openaire-affiliations/datacite-data.json
webCrawlInputPath=/data/openaire-affiliations/webCrawl
publisherInputPath=/data/openaire-affiliations/publishers
outputPath=/tmp/crossref-affiliations-output-v5
outputPath=/tmp/affRoAS

View File

@ -1,4 +1,4 @@
<workflow-app name="BipAffiliations" xmlns="uri:oozie:workflow:0.5">
<workflow-app name="OpenAIREAffiliations" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
@ -21,6 +21,10 @@
<name>webCrawlInputPath</name>
<description>the path where to find the inferred affiliation relations from webCrawl</description>
</property>
<property>
<name>publisherInputPath</name>
<description>the path where to find the inferred affiliation relations from publisher websites</description>
</property>
<property>
<name>outputPath</name>
<description>the path where to store the actionset</description>
@ -99,7 +103,7 @@
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Produces the atomic action with the inferred by BIP! affiliation relations (from Crossref and Pubmed)</name>
<name>Produces the atomic action with the inferred by OpenAIRE affiliation relations</name>
<class>eu.dnetlib.dhp.actionmanager.bipaffiliations.PrepareAffiliationRelations</class>
<jar>dhp-aggregation-${projectVersion}.jar</jar>
<spark-opts>
@ -117,6 +121,7 @@
<arg>--openapcInputPath</arg><arg>${openapcInputPath}</arg>
<arg>--dataciteInputPath</arg><arg>${dataciteInputPath}</arg>
<arg>--webCrawlInputPath</arg><arg>${webCrawlInputPath}</arg>
<arg>--publisherInputPath</arg><arg>${publisherInputPath}</arg>
<arg>--outputPath</arg><arg>${outputPath}</arg>
</spark>
<ok to="End"/>

View File

@ -21,5 +21,30 @@
"paramLongName": "workingDir",
"paramDescription": "the hdfs name node",
"paramRequired": false
},
{
"paramName": "pu",
"paramLongName": "postgresUrl",
"paramDescription": "the hdfs name node",
"paramRequired": false
},
{
"paramName": "ps",
"paramLongName": "postgresUser",
"paramDescription": "the hdfs name node",
"paramRequired": false
},
{
"paramName": "pp",
"paramLongName": "postgresPassword",
"paramDescription": "the hdfs name node",
"paramRequired": false
},{
"paramName": "nn",
"paramLongName": "hdfsNameNode",
"paramDescription": "the hdfs name node",
"paramRequired": false
}
]

View File

@ -1,2 +1,5 @@
inputPath=/data/orcid_2023/tables/
outputPath=/user/miriam.baglioni/peopleAS
outputPath=/user/miriam.baglioni/peopleAS
postgresUrl=jdbc:postgresql://beta.services.openaire.eu:5432/dnet_openaireplus
postgresUser=dnet
postgresPassword=dnetPwd

View File

@ -9,6 +9,18 @@
<name>outputPath</name>
<description>the path where to store the actionset</description>
</property>
<property>
<name>postgresUrl</name>
<description>the path where to store the actionset</description>
</property>
<property>
<name>postgresUser</name>
<description>the path where to store the actionset</description>
</property>
<property>
<name>postgresPassword</name>
<description>the path where to store the actionset</description>
</property>
<property>
<name>sparkDriverMemory</name>
<description>memory for driver process</description>
@ -102,6 +114,10 @@
<arg>--inputPath</arg><arg>${inputPath}</arg>
<arg>--outputPath</arg><arg>${outputPath}</arg>
<arg>--workingDir</arg><arg>${workingDir}</arg>
<arg>--hdfsNameNode</arg><arg>${nameNode}</arg>
<arg>--postgresUrl</arg><arg>${postgresUrl}</arg>
<arg>--postgresUser</arg><arg>${postgresUser}</arg>
<arg>--postgresPassword</arg><arg>${postgresPassword}</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>

View File

@ -24,7 +24,7 @@
<decision name="resume_from">
<switch>
<case to="download">${wf:conf('resumeFrom') eq 'DownloadDump'}</case>
<case to="reset_workingDir">${wf:conf('resumeFrom') eq 'DownloadDump'}</case>
<default to="create_actionset"/> <!-- first action to be done when downloadDump is to be performed -->
</switch>
</decision>
@ -33,6 +33,14 @@
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="reset_workingDir">
<fs>
<delete path="${workingDir}"/>
<mkdir path="${workingDir}"/>
</fs>
<ok to="download"/>
<error to="Kill"/>
</action>
<action name="download">
<shell xmlns="uri:oozie:shell-action:0.2">
<job-tracker>${jobTracker}</job-tracker>

View File

@ -14,7 +14,7 @@ import eu.dnetlib.dhp.schema.oaf.utils.{
PidType
}
import eu.dnetlib.dhp.utils.DHPUtils
import org.apache.commons.lang.StringUtils
import org.apache.commons.lang3.StringUtils
import org.apache.spark.sql.Row
import org.json4s
import org.json4s.DefaultFormats
@ -673,11 +673,12 @@ case object Crossref2Oaf {
val doi = input.getString(0)
val rorId = input.getString(1)
val pubId = s"50|${PidType.doi.toString.padTo(12, "_")}::${DoiCleaningRule.clean(doi)}"
val pubId = IdentifierFactory.idFromPid("50", "doi", DoiCleaningRule.clean(doi), true)
val affId = GenerateRorActionSetJob.calculateOpenaireId(rorId)
val r: Relation = new Relation
DoiCleaningRule.clean(doi)
r.setSource(pubId)
r.setTarget(affId)
r.setRelType(ModelConstants.RESULT_ORGANIZATION)
@ -978,7 +979,26 @@ case object Crossref2Oaf {
case "10.13039/501100010790" =>
generateSimpleRelationFromAward(funder, "erasmusplus_", a => a)
case _ => logger.debug("no match for " + funder.DOI.get)
//Add for Danish funders
//Independent Research Fund Denmark (IRFD)
case "10.13039/501100004836" =>
generateSimpleRelationFromAward(funder, "irfd________", a => a)
val targetId = getProjectId("irfd________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
//Carlsberg Foundation (CF)
case "10.13039/501100002808" =>
generateSimpleRelationFromAward(funder, "cf__________", a => a)
val targetId = getProjectId("cf__________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
//Novo Nordisk Foundation (NNF)
case "10.13039/501100009708" =>
generateSimpleRelationFromAward(funder, "nnf___________", a => a)
val targetId = getProjectId("nnf_________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
case _ => logger.debug("no match for " + funder.DOI.get)
}
} else {

View File

@ -98,9 +98,9 @@ public class PrepareAffiliationRelationsTest {
"-crossrefInputPath", crossrefAffiliationRelationPathNew,
"-pubmedInputPath", crossrefAffiliationRelationPath,
"-openapcInputPath", crossrefAffiliationRelationPathNew,
"-dataciteInputPath", crossrefAffiliationRelationPath,
"-webCrawlInputPath", crossrefAffiliationRelationPath,
"-publisherInputPath", publisherAffiliationRelationOldPath,
"-dataciteInputPath", crossrefAffiliationRelationPathNew,
"-webCrawlInputPath", crossrefAffiliationRelationPathNew,
"-publisherInputPath", publisherAffiliationRelationPath,
"-outputPath", outputPath
});
@ -112,7 +112,7 @@ public class PrepareAffiliationRelationsTest {
.map(aa -> ((Relation) aa.getPayload()));
// count the number of relations
assertEquals(150, tmp.count());// 18 + 24 *3 + 30 * 2 =
assertEquals(162, tmp.count());// 18 + 24 + 30 * 4 =
Dataset<Relation> dataset = spark.createDataset(tmp.rdd(), Encoders.bean(Relation.class));
dataset.createOrReplaceTempView("result");
@ -123,7 +123,7 @@ public class PrepareAffiliationRelationsTest {
// verify that we have equal number of bi-directional relations
Assertions
.assertEquals(
75, execVerification
81, execVerification
.filter(
"relClass='" + ModelConstants.HAS_AUTHOR_INSTITUTION + "'")
.collectAsList()
@ -131,7 +131,7 @@ public class PrepareAffiliationRelationsTest {
Assertions
.assertEquals(
75, execVerification
81, execVerification
.filter(
"relClass='" + ModelConstants.IS_AUTHOR_INSTITUTION_OF + "'")
.collectAsList()
@ -158,7 +158,7 @@ public class PrepareAffiliationRelationsTest {
Assertions
.assertEquals(
2, execVerification.filter("source = '" + publisherid + "' and target = '" + rorId + "'").count());
4, execVerification.filter("source = '" + publisherid + "' and target = '" + rorId + "'").count());
Assertions
.assertEquals(
@ -173,7 +173,7 @@ public class PrepareAffiliationRelationsTest {
Assertions
.assertEquals(
3, execVerification
1, execVerification
.filter(
"source = '" + ID_PREFIX
+ IdentifierFactory

View File

@ -63,6 +63,7 @@
<path start="copy_software"/>
<path start="copy_datasource"/>
<path start="copy_project"/>
<path start="copy_person"/>
<path start="copy_organization"/>
</fork>
@ -120,6 +121,15 @@
<error to="Kill"/>
</action>
<action name="copy_person">
<distcp xmlns="uri:oozie:distcp-action:0.2">
<arg>${nameNode}/${sourcePath}/person</arg>
<arg>${nameNode}/${outputPath}/person</arg>
</distcp>
<ok to="wait"/>
<error to="Kill"/>
</action>
<action name="copy_datasource">
<distcp xmlns="uri:oozie:distcp-action:0.2">
<arg>${nameNode}/${sourcePath}/datasource</arg>

View File

@ -2,14 +2,13 @@
package eu.dnetlib.dhp.oa.dedup;
import java.util.*;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import org.apache.commons.beanutils.BeanUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.FlatMapGroupsFunction;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.api.java.function.ReduceFunction;
import org.apache.spark.sql.*;
import eu.dnetlib.dhp.oa.dedup.model.Identifier;
@ -107,6 +106,8 @@ public class DedupRecordFactory {
final HashSet<String> acceptanceDate = new HashSet<>();
boolean isVisible = false;
while (it.hasNext()) {
Tuple3<String, String, OafEntity> t = it.next();
OafEntity entity = t._3();
@ -114,6 +115,7 @@ public class DedupRecordFactory {
if (entity == null) {
aliases.add(t._2());
} else {
isVisible = isVisible || !entity.getDataInfo().getInvisible();
cliques.add(entity);
if (acceptanceDate.size() < MAX_ACCEPTANCE_DATE) {
@ -129,13 +131,20 @@ public class DedupRecordFactory {
}
if (acceptanceDate.size() >= MAX_ACCEPTANCE_DATE || cliques.isEmpty()) {
if (!isVisible || acceptanceDate.size() >= MAX_ACCEPTANCE_DATE || cliques.isEmpty()) {
return Collections.emptyIterator();
}
OafEntity mergedEntity = MergeUtils.mergeGroup(dedupId, cliques.iterator());
OafEntity mergedEntity = MergeUtils.mergeGroup(cliques.iterator());
// dedup records do not have date of transformation attribute
mergedEntity.setDateoftransformation(null);
mergedEntity
.setMergedIds(
Stream
.concat(cliques.stream().map(OafEntity::getId), aliases.stream())
.distinct()
.sorted()
.collect(Collectors.toList()));
return Stream
.concat(

View File

@ -91,7 +91,6 @@ public class SparkBlockStats extends AbstractSparkAction {
.read()
.textFile(DedupUtility.createEntityPath(graphBasePath, subEntity))
.transform(deduper.model().parseJsonDataset())
.transform(deduper.filterAndCleanup())
.transform(deduper.generateClustersWithCollect())
.filter(functions.size(new Column("block")).geq(1));

View File

@ -5,11 +5,11 @@ import static eu.dnetlib.dhp.schema.common.ModelConstants.DNET_PROVENANCE_ACTION
import static eu.dnetlib.dhp.schema.common.ModelConstants.PROVENANCE_DEDUP;
import java.io.IOException;
import java.util.Arrays;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.sql.SaveMode;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.*;
import org.dom4j.DocumentException;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
@ -17,6 +17,7 @@ import org.xml.sax.SAXException;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.common.EntityType;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport;
import eu.dnetlib.dhp.schema.oaf.DataInfo;
import eu.dnetlib.dhp.schema.oaf.OafEntity;
@ -25,6 +26,8 @@ import eu.dnetlib.dhp.utils.ISLookupClientFactory;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
import eu.dnetlib.pace.config.DedupConfig;
import scala.collection.JavaConversions;
import scala.collection.JavaConverters;
public class SparkCreateDedupRecord extends AbstractSparkAction {
@ -85,6 +88,36 @@ public class SparkCreateDedupRecord extends AbstractSparkAction {
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath);
log.info("Updating mergerels for: '{}'", subEntity);
final Dataset<Row> dedupIds = spark
.read()
.schema("`id` STRING, `mergedIds` ARRAY<STRING>")
.json(outputPath)
.selectExpr("id as source", "explode(mergedIds) as target");
spark
.read()
.load(mergeRelPath)
.where("relClass == 'merges'")
.join(dedupIds, JavaConversions.asScalaBuffer(Arrays.asList("source", "target")), "left_semi")
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.save(workingPath + "/mergerel_filtered");
final Dataset<Row> validRels = spark.read().load(workingPath + "/mergerel_filtered");
final Dataset<Row> filteredMergeRels = validRels
.union(
validRels
.withColumnRenamed("source", "source_tmp")
.withColumnRenamed("target", "target_tmp")
.withColumn("relClass", functions.lit(ModelConstants.IS_MERGED_IN))
.withColumnRenamed("target_tmp", "source")
.withColumnRenamed("source_tmp", "target"));
saveParquet(filteredMergeRels, mergeRelPath, SaveMode.Overwrite);
removeOutputDir(spark, workingPath + "/mergerel_filtered");
}
}

View File

@ -69,6 +69,7 @@ public class SparkPropagateRelation extends AbstractSparkAction {
Dataset<Relation> mergeRels = spark
.read()
.schema(REL_BEAN_ENC.schema())
.load(DedupUtility.createMergeRelPath(workingPath, "*", "*"))
.as(REL_BEAN_ENC);

View File

@ -46,8 +46,8 @@ class DatasetMergerTest implements Serializable {
}
@Test
void datasetMergerTest() throws InstantiationException, IllegalAccessException, InvocationTargetException {
Dataset pub_merged = MergeUtils.mergeGroup(dedupId, datasets.stream().map(Tuple2::_2).iterator());
void datasetMergerTest() {
Dataset pub_merged = MergeUtils.mergeGroup(datasets.stream().map(Tuple2::_2).iterator());
// verify id
assertEquals(dedupId, pub_merged.getId());

View File

@ -96,7 +96,7 @@
"aggregation": "MAX",
"positive": "layer4",
"negative": "NO_MATCH",
"undefined": "MATCH",
"undefined": "layer4",
"ignoreUndefined": "true"
},
"layer4": {

View File

@ -7,7 +7,7 @@ import eu.dnetlib.dhp.schema.oaf.utils.{GraphCleaningFunctions, IdentifierFactor
import eu.dnetlib.dhp.utils.DHPUtils
import eu.dnetlib.doiboost.DoiBoostMappingUtil
import eu.dnetlib.doiboost.DoiBoostMappingUtil._
import org.apache.commons.lang.StringUtils
import org.apache.commons.lang3.StringUtils
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.JsonAST._
@ -560,9 +560,32 @@ case object Crossref2Oaf {
"10.13039/501100000266" | "10.13039/501100006041" | "10.13039/501100000265" | "10.13039/501100000270" |
"10.13039/501100013589" | "10.13039/501100000271" =>
generateSimpleRelationFromAward(funder, "ukri________", a => a)
//DFG
case "10.13039/501100001659" =>
val targetId = getProjectId("dfgf________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
case _ => logger.debug("no match for " + funder.DOI.get)
//Add for Danish funders
//Independent Research Fund Denmark (IRFD)
case "10.13039/501100004836" =>
generateSimpleRelationFromAward(funder, "irfd________", a => a)
val targetId = getProjectId("irfd________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
//Carlsberg Foundation (CF)
case "10.13039/501100002808" =>
generateSimpleRelationFromAward(funder, "cf__________", a => a)
val targetId = getProjectId("cf__________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
//Novo Nordisk Foundation (NNF)
case "10.13039/501100009708" =>
generateSimpleRelationFromAward(funder, "nnf___________", a => a)
val targetId = getProjectId("nnf_________", "1e5e62235d094afd01cd56e65112fc63")
queue += generateRelation(sourceId, targetId, ModelConstants.IS_PRODUCED_BY)
queue += generateRelation(targetId, sourceId, ModelConstants.PRODUCES)
case _ => logger.debug("no match for " + funder.DOI.get)
}
} else {

View File

@ -6,7 +6,7 @@ import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
import eu.dnetlib.doiboost.DoiBoostMappingUtil
import eu.dnetlib.doiboost.DoiBoostMappingUtil.{createSP, generateDataInfo}
import org.apache.commons.lang.StringUtils
import org.apache.commons.lang3.StringUtils
import org.json4s
import org.json4s.DefaultFormats
import org.json4s.JsonAST._

View File

@ -48,12 +48,7 @@
<groupId>io.github.classgraph</groupId>
<artifactId>classgraph</artifactId>
</dependency>
<dependency>
<groupId>eu.dnetlib.dhp</groupId>
<artifactId>dhp-aggregation</artifactId>
<version>1.2.5-SNAPSHOT</version>
<scope>compile</scope>
</dependency>
</dependencies>

View File

@ -6,11 +6,11 @@ import java.io.Serializable;
import java.util.*;
import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import org.jetbrains.annotations.NotNull;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.amazonaws.util.StringUtils;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.collect.Maps;
@ -81,7 +81,7 @@ public class Utils implements Serializable {
Community c = new Community();
c.setId(cm.getId());
c.setZenodoCommunities(cm.getOtherZenodoCommunities());
if (!StringUtils.isNullOrEmpty(cm.getZenodoCommunity()))
if (StringUtils.isNotBlank(cm.getZenodoCommunity()))
c.getZenodoCommunities().add(cm.getZenodoCommunity());
c.setSubjects(cm.getSubjects());
c.getSubjects().addAll(cm.getFos());

View File

@ -13,13 +13,13 @@ public class CommunityContentprovider {
private String openaireId;
private SelectionConstraints selectioncriteria;
private String enabled;
private Boolean enabled;
public String getEnabled() {
public Boolean getEnabled() {
return enabled;
}
public void setEnabled(String enabled) {
public void setEnabled(Boolean enabled) {
this.enabled = enabled;
}

View File

@ -4,7 +4,7 @@ package eu.dnetlib.dhp.bulktag.community;
import java.io.Serializable;
import java.lang.reflect.InvocationTargetException;
import org.apache.htrace.fasterxml.jackson.annotation.JsonIgnore;
import com.fasterxml.jackson.annotation.JsonIgnore;
import eu.dnetlib.dhp.bulktag.criteria.Selection;
import eu.dnetlib.dhp.bulktag.criteria.VerbResolver;

View File

@ -0,0 +1,302 @@
package eu.dnetlib.dhp.person;
import static com.ibm.icu.text.PluralRules.Operand.w;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.io.Serializable;
import java.util.*;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.function.FilterFunction;
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.*;
import org.apache.spark.sql.Dataset;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.common.person.CoAuthorshipIterator;
import eu.dnetlib.dhp.common.person.Coauthors;
import eu.dnetlib.dhp.countrypropagation.SparkCountryPropagationJob;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport;
import eu.dnetlib.dhp.schema.oaf.*;
import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
import scala.Tuple2;
public class SparkExtractPersonRelations {
private static final Logger log = LoggerFactory.getLogger(SparkCountryPropagationJob.class);
private static final String PERSON_PREFIX = ModelSupport.getIdPrefix(Person.class) + "|orcid_______";
public static final DataInfo DATAINFO = OafMapperUtils
.dataInfo(
false,
"openaire",
true,
false,
OafMapperUtils
.qualifier(
ModelConstants.SYSIMPORT_CROSSWALK_REPOSITORY,
ModelConstants.SYSIMPORT_CROSSWALK_REPOSITORY,
ModelConstants.DNET_PROVENANCE_ACTIONS,
ModelConstants.DNET_PROVENANCE_ACTIONS),
"0.85");
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
SparkCountryPropagationJob.class
.getResourceAsStream(
"/eu/dnetlib/dhp/wf/subworkflows/person/input_personpropagation_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
String sourcePath = parser.get("sourcePath");
log.info("sourcePath: {}", sourcePath);
final String workingPath = parser.get("outputPath");
log.info("workingPath: {}", workingPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
extractRelations(
spark,
sourcePath,
workingPath);
removeIsolatedPerson(spark, sourcePath, workingPath);
});
}
private static void removeIsolatedPerson(SparkSession spark, String sourcePath, String workingPath) {
Dataset<Person> personDataset = spark
.read()
.schema(Encoders.bean(Person.class).schema())
.json(sourcePath + "person")
.as(Encoders.bean(Person.class));
Dataset<Relation> relationDataset = spark
.read()
.schema(Encoders.bean(Relation.class).schema())
.json(sourcePath + "relation")
.as(Encoders.bean(Relation.class));
personDataset
.join(relationDataset, personDataset.col("id").equalTo(relationDataset.col("source")), "left_semi")
.write()
.option("compression", "gzip")
.mode(SaveMode.Overwrite)
.json(workingPath + "person");
spark
.read()
.schema(Encoders.bean(Person.class).schema())
.json(workingPath + "person")
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(sourcePath + "person");
}
private static void extractRelations(SparkSession spark, String sourcePath, String workingPath) {
Dataset<Tuple2<String, Relation>> relationDataset = spark
.read()
.schema(Encoders.bean(Relation.class).schema())
.json(sourcePath + "relation")
.as(Encoders.bean(Relation.class))
.map(
(MapFunction<Relation, Tuple2<String, Relation>>) r -> new Tuple2<>(
r.getSource() + r.getRelClass() + r.getTarget(), r),
Encoders.tuple(Encoders.STRING(), Encoders.bean(Relation.class)));
ModelSupport.entityTypes
.keySet()
.stream()
.filter(ModelSupport::isResult)
.forEach(
e -> {
// 1. search for results having orcid_pending and orcid in the set of pids for the authors
Dataset<Result> resultWithOrcids = spark
.read()
.schema(Encoders.bean(Result.class).schema())
.json(sourcePath + e.name())
.as(Encoders.bean(Result.class))
.filter(
(FilterFunction<Result>) r -> !r.getDataInfo().getDeletedbyinference() &&
!r.getDataInfo().getInvisible() &&
Optional
.ofNullable(r.getAuthor())
.isPresent())
.filter(
(FilterFunction<Result>) r -> r
.getAuthor()
.stream()
.anyMatch(
a -> Optional
.ofNullable(
a
.getPid())
.isPresent() &&
a
.getPid()
.stream()
.anyMatch(
p -> Arrays
.asList("orcid", "orcid_pending")
.contains(p.getQualifier().getClassid().toLowerCase()))));
// 2. create authorship relations between the result identifier and the person entity with
// orcid_pending.
Dataset<Tuple2<String, Relation>> newRelations = resultWithOrcids
.flatMap(
(FlatMapFunction<Result, Relation>) r -> getAuthorshipRelations(r),
Encoders.bean(Relation.class))
// .groupByKey((MapFunction<Relation, String>) r-> r.getSource()+r.getTarget(), Encoders.STRING() )
// .mapGroups((MapGroupsFunction<String, Relation, Relation>) (k,it) -> it.next(), Encoders.bean(Relation.class) )
.map(
(MapFunction<Relation, Tuple2<String, Relation>>) r -> new Tuple2<>(
r.getSource() + r.getRelClass() + r.getTarget(), r),
Encoders.tuple(Encoders.STRING(), Encoders.bean(Relation.class)));
newRelations
.joinWith(relationDataset, newRelations.col("_1").equalTo(relationDataset.col("_1")), "left")
.map((MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, Relation>>, Relation>) t2 -> {
if (t2._2() == null)
return t2._1()._2();
return null;
}, Encoders.bean(Relation.class))
.filter((FilterFunction<Relation>) r -> r != null)
.write()
.mode(SaveMode.Append)
.option("compression", "gzip")
.json(workingPath);
// 2.1 store in a separate location the relation between the person and the pids for the result?
// 3. create co_authorship relations between the pairs of authors with orcid/orcid_pending pids
newRelations = resultWithOrcids
.map((MapFunction<Result, Coauthors>) r -> getAuthorsPidList(r), Encoders.bean(Coauthors.class))
.flatMap(
(FlatMapFunction<Coauthors, Relation>) c -> new CoAuthorshipIterator(c.getCoauthors()),
Encoders.bean(Relation.class))
.groupByKey(
(MapFunction<Relation, String>) r -> r.getSource() + r.getTarget(), Encoders.STRING())
.mapGroups(
(MapGroupsFunction<String, Relation, Relation>) (k, it) -> it.next(),
Encoders.bean(Relation.class))
.map(
(MapFunction<Relation, Tuple2<String, Relation>>) r -> new Tuple2<>(
r.getSource() + r.getRelClass() + r.getTarget(), r),
Encoders.tuple(Encoders.STRING(), Encoders.bean(Relation.class)));
newRelations
.joinWith(relationDataset, newRelations.col("_1").equalTo(relationDataset.col("_1")), "left")
.map((MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, Relation>>, Relation>) t2 -> {
if (t2._2() == null)
return t2._1()._2();
return null;
}, Encoders.bean(Relation.class))
.filter((FilterFunction<Relation>) r -> r != null)
.write()
.mode(SaveMode.Append)
.option("compression", "gzip")
.json(workingPath);
});
spark
.read()
.schema(Encoders.bean(Relation.class).schema())
.json(workingPath)
.write()
.mode(SaveMode.Append)
.option("compression", "gzip")
.json(sourcePath + "relation");
}
private static Coauthors getAuthorsPidList(Result r) {
Coauthors coauth = new Coauthors();
coauth
.setCoauthors(
r
.getAuthor()
.stream()
.filter(
a -> a
.getPid()
.stream()
.anyMatch(
p -> Arrays.asList("orcid", "orcid_pending").contains(p.getQualifier().getClassid())))
.map(a -> {
Optional<StructuredProperty> tmp = a
.getPid()
.stream()
.filter(p -> p.getQualifier().getClassid().equalsIgnoreCase("orcid"))
.findFirst();
if (tmp.isPresent())
return tmp.get().getValue();
tmp = a
.getPid()
.stream()
.filter(p -> p.getQualifier().getClassid().equalsIgnoreCase("orcid_pending"))
.findFirst();
if (tmp.isPresent())
return tmp.get().getValue();
return null;
})
.filter(Objects::nonNull)
.collect(Collectors.toList()));
return coauth;
}
private static Iterator<Relation> getAuthorshipRelations(Result r) {
List<Relation> relationList = new ArrayList<>();
for (Author a : r.getAuthor())
relationList.addAll(a.getPid().stream().map(p -> {
if (p.getQualifier().getClassid().equalsIgnoreCase("orcid_pending"))
return getRelation(p.getValue(), r.getId());
return null;
})
.filter(Objects::nonNull)
.collect(Collectors.toList()));
return relationList.iterator();
}
private static Relation getRelation(String orcid, String resultId) {
String source = PERSON_PREFIX + "::" + IdentifierFactory.md5(orcid);
Relation relation = OafMapperUtils
.getRelation(
source, resultId, ModelConstants.RESULT_PERSON_RELTYPE,
ModelConstants.RESULT_PERSON_SUBRELTYPE,
ModelConstants.RESULT_PERSON_HASAUTHORED,
null, // collectedfrom = null
DATAINFO,
null);
return relation;
}
}

View File

@ -7,4 +7,5 @@ community_organization classpath eu/dnetlib/dhp/wf/subworkflows/resulttocommunit
result_project classpath eu/dnetlib/dhp/wf/subworkflows/projecttoresult/oozie_app
community_project classpath eu/dnetlib/dhp/wf/subworkflows/resulttocommunityfromproject/oozie_app
community_sem_rel classpath eu/dnetlib/dhp/wf/subworkflows/resulttocommunityfromsemrel/oozie_app
country_propagation classpath eu/dnetlib/dhp/wf/subworkflows/countrypropagation/oozie_app
country_propagation classpath eu/dnetlib/dhp/wf/subworkflows/countrypropagation/oozie_app
person_propagation classpath eu/dnetlib/dhp/wf/subworkflows/person/oozie_app

View File

@ -122,6 +122,7 @@
<case to="community_project">${wf:conf('resumeFrom') eq 'CommunityProject'}</case>
<case to="community_sem_rel">${wf:conf('resumeFrom') eq 'CommunitySemanticRelation'}</case>
<case to="country_propagation">${wf:conf('resumeFrom') eq 'CountryPropagation'}</case>
<case to="person_propagation">${wf:conf('resumeFrom') eq 'PersonPropagation'}</case>
<default to="orcid_propagation"/>
</switch>
</decision>
@ -291,10 +292,24 @@
</property>
</configuration>
</sub-workflow>
<ok to="person_propagation" />
<error to="Kill" />
</action>
<action name="person_propagation">
<sub-workflow>
<app-path>${wf:appPath()}/person_propagation
</app-path>
<propagate-configuration/>
<configuration>
<property>
<name>sourcePath</name>
<value>${outputPath}</value>
</property>
</configuration>
</sub-workflow>
<ok to="country_propagation" />
<error to="Kill" />
</action>
<action name="country_propagation">
<sub-workflow>
<app-path>${wf:appPath()}/country_propagation
@ -319,6 +334,8 @@
<error to="Kill" />
</action>
<end name="End"/>
</workflow-app>

View File

@ -34,6 +34,7 @@
<path start="copy_organization"/>
<path start="copy_projects"/>
<path start="copy_datasources"/>
<path start="copy_persons"/>
</fork>
<action name="copy_relation">
@ -80,6 +81,17 @@
<error to="Kill"/>
</action>
<action name="copy_persons">
<distcp xmlns="uri:oozie:distcp-action:0.2">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<arg>${nameNode}/${sourcePath}/person</arg>
<arg>${nameNode}/${outputPath}/person</arg>
</distcp>
<ok to="copy_wait"/>
<error to="Kill"/>
</action>
<join name="copy_wait" to="fork_prepare_assoc_step1"/>
<fork name="fork_prepare_assoc_step1">

View File

@ -0,0 +1,21 @@
[
{
"paramName":"s",
"paramLongName":"sourcePath",
"paramDescription": "the path of the sequencial file to read",
"paramRequired": true
},
{
"paramName": "out",
"paramLongName": "outputPath",
"paramDescription": "the path used to store temporary output files",
"paramRequired": true
},
{
"paramName": "ssm",
"paramLongName": "isSparkSessionManaged",
"paramDescription": "true if the spark session is managed, false otherwise",
"paramRequired": false
}
]

View File

@ -0,0 +1 @@
sourcePath=/tmp/miriam/13_graph_copy

View File

@ -0,0 +1,58 @@
<configuration>
<property>
<name>jobTracker</name>
<value>yarnRM</value>
</property>
<property>
<name>nameNode</name>
<value>hdfs://nameservice1</value>
</property>
<property>
<name>oozie.use.system.libpath</name>
<value>true</value>
</property>
<property>
<name>oozie.action.sharelib.for.spark</name>
<value>spark2</value>
</property>
<property>
<name>hive_metastore_uris</name>
<value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
</property>
<property>
<name>spark2YarnHistoryServerAddress</name>
<value>http://iis-cdh5-test-gw.ocean.icm.edu.pl:18089</value>
</property>
<property>
<name>spark2EventLogDir</name>
<value>/user/spark/spark2ApplicationHistory</value>
</property>
<property>
<name>spark2ExtraListeners</name>
<value>com.cloudera.spark.lineage.NavigatorAppListener</value>
</property>
<property>
<name>spark2SqlQueryExecutionListeners</name>
<value>com.cloudera.spark.lineage.NavigatorQueryListener</value>
</property>
<property>
<name>sparkExecutorNumber</name>
<value>4</value>
</property>
<property>
<name>sparkDriverMemory</name>
<value>15G</value>
</property>
<property>
<name>sparkExecutorMemory</name>
<value>5G</value>
</property>
<property>
<name>sparkExecutorCores</name>
<value>4</value>
</property>
<property>
<name>spark2MaxExecutors</name>
<value>50</value>
</property>
</configuration>

View File

@ -0,0 +1,68 @@
<workflow-app name="person_propagation" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>sourcePath</name>
<description>the source path</description>
</property>
</parameters>
<global>
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<configuration>
<property>
<name>oozie.action.sharelib.for.spark</name>
<value>${oozieActionShareLibForSpark2}</value>
</property>
</configuration>
</global>
<start to="reset_outputpath"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="reset_outputpath">
<fs>
<delete path="${workingDir}"/>
<mkdir path="${workingDir}"/>
</fs>
<ok to="extract_person_relation_from_graph"/>
<error to="Kill"/>
</action>
<action name="extract_person_relation_from_graph">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>personPropagation</name>
<class>eu.dnetlib.dhp.person.SparkExtractPersonRelations</class>
<jar>dhp-enrichment-${projectVersion}.jar</jar>
<spark-opts>
--executor-cores=${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}${spark2EventLogDir}
--conf spark.speculation=false
--conf spark.hadoop.mapreduce.map.speculative=false
--conf spark.hadoop.mapreduce.reduce.speculative=false
--conf spark.sql.shuffle.partitions=7680
</spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}/</arg>
<arg>--outputPath</arg><arg>${workingDir}/relation</arg>
</spark>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

View File

@ -0,0 +1,93 @@
package eu.dnetlib.dhp.person;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.io.FileUtils;
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.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 com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.countrypropagation.SparkCountryPropagationJob;
import eu.dnetlib.dhp.schema.oaf.*;
import scala.Tuple2;
public class PersonPropagationJobTest {
private static final Logger log = LoggerFactory.getLogger(PersonPropagationJobTest.class);
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
private static SparkSession spark;
private static Path workingDir;
@BeforeAll
public static void beforeAll() throws IOException {
workingDir = Files.createTempDirectory(PersonPropagationJobTest.class.getSimpleName());
log.info("using work dir {}", workingDir);
SparkConf conf = new SparkConf();
conf.setAppName(PersonPropagationJobTest.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(PersonPropagationJobTest.class.getSimpleName())
.config(conf)
.getOrCreate();
}
@AfterAll
public static void afterAll() throws IOException {
FileUtils.deleteDirectory(workingDir.toFile());
spark.stop();
}
@Test
void testPersonPropagation() throws Exception {
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/personpropagation/graph")
.getPath();
SparkExtractPersonRelations
.main(
new String[] {
"--isSparkSessionManaged", Boolean.FALSE.toString(),
"--sourcePath", sourcePath,
"--outputPath", workingDir.toString()
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<Relation> tmp = sc
.textFile(workingDir.toString() + "/relation")
.map(item -> OBJECT_MAPPER.readValue(item, Relation.class));
// TODO write assertions and find relevant information for hte resource files
}
}

File diff suppressed because one or more lines are too long

View File

@ -72,9 +72,9 @@ public class GraphHiveTableImporterJob {
final Encoder<T> clazzEncoder = Encoders.bean(clazz);
Dataset<Row> dataset = spark
.read()
.schema(clazzEncoder.schema())
.json(inputPath);
.read()
.schema(clazzEncoder.schema())
.json(inputPath);
if (numPartitions > 0) {
log.info("repartitioning {} to {} partitions", clazz.getSimpleName(), numPartitions);

View File

@ -153,34 +153,40 @@ public abstract class AbstractMdRecordToOafMapper {
final DataInfo entityInfo = prepareDataInfo(doc, this.invisible);
final long lastUpdateTimestamp = new Date().getTime();
final List<Instance> instances = prepareInstances(doc, entityInfo, collectedFrom, hostedBy);
final Instance instance = prepareInstances(doc, entityInfo, collectedFrom, hostedBy);
final String type = getResultType(doc, instances);
if (!Optional
.ofNullable(instance.getInstancetype())
.map(Qualifier::getClassid)
.filter(StringUtils::isNotBlank)
.isPresent()) {
return Lists.newArrayList();
}
return createOafs(doc, type, instances, collectedFrom, entityInfo, lastUpdateTimestamp);
final String type = getResultType(instance);
return createOafs(doc, type, instance, collectedFrom, entityInfo, lastUpdateTimestamp);
} catch (final DocumentException e) {
log.error("Error with record:\n" + xml);
return Lists.newArrayList();
}
}
protected String getResultType(final Document doc, final List<Instance> instances) {
final String type = doc.valueOf("//dr:CobjCategory/@type");
if (StringUtils.isBlank(type) && this.vocs.vocabularyExists(ModelConstants.DNET_RESULT_TYPOLOGIES)) {
final String instanceType = instances
.stream()
.map(i -> i.getInstancetype().getClassid())
.findFirst()
.filter(s -> !UNKNOWN.equalsIgnoreCase(s))
.orElse("0000"); // Unknown
protected String getResultType(final Instance instance) {
if (this.vocs.vocabularyExists(ModelConstants.DNET_RESULT_TYPOLOGIES)) {
return Optional
.ofNullable(this.vocs.getSynonymAsQualifier(ModelConstants.DNET_RESULT_TYPOLOGIES, instanceType))
.ofNullable(instance.getInstancetype())
.map(Qualifier::getClassid)
.map(
instanceType -> Optional
.ofNullable(
this.vocs.getSynonymAsQualifier(ModelConstants.DNET_RESULT_TYPOLOGIES, instanceType))
.map(Qualifier::getClassid)
.orElse("0000"))
.orElse("0000");
} else {
throw new IllegalStateException("Missing vocabulary: " + ModelConstants.DNET_RESULT_TYPOLOGIES);
}
return type;
}
private KeyValue getProvenanceDatasource(final Document doc, final String xpathId, final String xpathName) {
@ -197,12 +203,12 @@ public abstract class AbstractMdRecordToOafMapper {
protected List<Oaf> createOafs(
final Document doc,
final String type,
final List<Instance> instances,
final Instance instance,
final KeyValue collectedFrom,
final DataInfo info,
final long lastUpdateTimestamp) {
final OafEntity entity = createEntity(doc, type, instances, collectedFrom, info, lastUpdateTimestamp);
final OafEntity entity = createEntity(doc, type, instance, collectedFrom, info, lastUpdateTimestamp);
final Set<String> originalId = Sets.newHashSet(entity.getOriginalId());
originalId.add(entity.getId());
@ -235,19 +241,19 @@ public abstract class AbstractMdRecordToOafMapper {
private OafEntity createEntity(final Document doc,
final String type,
final List<Instance> instances,
final Instance instance,
final KeyValue collectedFrom,
final DataInfo info,
final long lastUpdateTimestamp) {
switch (type.toLowerCase()) {
case "publication":
final Publication p = new Publication();
populateResultFields(p, doc, instances, collectedFrom, info, lastUpdateTimestamp);
populateResultFields(p, doc, instance, collectedFrom, info, lastUpdateTimestamp);
p.setJournal(prepareJournal(doc, info));
return p;
case "dataset":
final Dataset d = new Dataset();
populateResultFields(d, doc, instances, collectedFrom, info, lastUpdateTimestamp);
populateResultFields(d, doc, instance, collectedFrom, info, lastUpdateTimestamp);
d.setStoragedate(prepareDatasetStorageDate(doc, info));
d.setDevice(prepareDatasetDevice(doc, info));
d.setSize(prepareDatasetSize(doc, info));
@ -258,7 +264,7 @@ public abstract class AbstractMdRecordToOafMapper {
return d;
case "software":
final Software s = new Software();
populateResultFields(s, doc, instances, collectedFrom, info, lastUpdateTimestamp);
populateResultFields(s, doc, instance, collectedFrom, info, lastUpdateTimestamp);
s.setDocumentationUrl(prepareSoftwareDocumentationUrls(doc, info));
s.setLicense(prepareSoftwareLicenses(doc, info));
s.setCodeRepositoryUrl(prepareSoftwareCodeRepositoryUrl(doc, info));
@ -268,7 +274,7 @@ public abstract class AbstractMdRecordToOafMapper {
case "otherresearchproducts":
default:
final OtherResearchProduct o = new OtherResearchProduct();
populateResultFields(o, doc, instances, collectedFrom, info, lastUpdateTimestamp);
populateResultFields(o, doc, instance, collectedFrom, info, lastUpdateTimestamp);
o.setContactperson(prepareOtherResearchProductContactPersons(doc, info));
o.setContactgroup(prepareOtherResearchProductContactGroups(doc, info));
o.setTool(prepareOtherResearchProductTools(doc, info));
@ -415,7 +421,7 @@ public abstract class AbstractMdRecordToOafMapper {
private void populateResultFields(
final Result r,
final Document doc,
final List<Instance> instances,
final Instance instance,
final KeyValue collectedFrom,
final DataInfo info,
final long lastUpdateTimestamp) {
@ -449,8 +455,8 @@ public abstract class AbstractMdRecordToOafMapper {
r.setExternalReference(new ArrayList<>()); // NOT PRESENT IN MDSTORES
r.setProcessingchargeamount(field(doc.valueOf("//oaf:processingchargeamount"), info));
r.setProcessingchargecurrency(field(doc.valueOf("//oaf:processingchargeamount/@currency"), info));
r.setInstance(instances);
r.setBestaccessright(OafMapperUtils.createBestAccessRights(instances));
r.setInstance(Arrays.asList(instance));
r.setBestaccessright(OafMapperUtils.createBestAccessRights(Arrays.asList(instance)));
r.setEoscifguidelines(prepareEOSCIfGuidelines(doc, info));
}
@ -509,7 +515,7 @@ public abstract class AbstractMdRecordToOafMapper {
protected abstract Qualifier prepareResourceType(Document doc, DataInfo info);
protected abstract List<Instance> prepareInstances(
protected abstract Instance prepareInstances(
Document doc,
DataInfo info,
KeyValue collectedfrom,
@ -657,13 +663,21 @@ public abstract class AbstractMdRecordToOafMapper {
final Node n = (Node) o;
final String classId = n.valueOf(xpathClassId).trim();
if (this.vocs.termExists(schemeId, classId)) {
res
.add(
HashableStructuredProperty
.newInstance(n.getText(), this.vocs.getTermAsQualifier(schemeId, classId), info));
final String value = n.getText();
if (StringUtils.isNotBlank(value)) {
res
.add(
HashableStructuredProperty
.newInstance(value, this.vocs.getTermAsQualifier(schemeId, classId), info));
}
}
}
return Lists.newArrayList(res);
return res
.stream()
.filter(Objects::nonNull)
.filter(p -> StringUtils.isNotBlank(p.getValue()))
.filter(p -> StringUtils.isNotBlank(p.getValue().trim()))
.collect(Collectors.toList());
}
protected List<StructuredProperty> prepareListStructProps(

View File

@ -133,7 +133,7 @@ public class GenerateEntitiesApplication extends AbstractMigrationApplication {
inputRdd
.keyBy(oaf -> ModelSupport.idFn().apply(oaf))
.groupByKey()
.map(t -> MergeUtils.mergeGroup(t._1, t._2.iterator())),
.map(t -> MergeUtils.mergeGroup(t._2.iterator())),
// .mapToPair(oaf -> new Tuple2<>(ModelSupport.idFn().apply(oaf), oaf))
// .reduceByKey(MergeUtils::merge)
// .map(Tuple2::_2),

View File

@ -519,6 +519,28 @@ public class MigrateDbEntitiesApplication extends AbstractMigrationApplication i
r1 = setRelationSemantic(r1, RESULT_RESULT, PUBLICATION_DATASET, IS_RELATED_TO);
r2 = setRelationSemantic(r2, RESULT_RESULT, PUBLICATION_DATASET, IS_RELATED_TO);
break;
case "resultOrganization_affiliation_isAuthorInstitutionOf":
if (!"organization".equals(sourceType)) {
throw new IllegalStateException(
String
.format(
"invalid claim, sourceId: %s, targetId: %s, semantics: %s", sourceId, targetId,
semantics));
}
r1 = setRelationSemantic(r1, RESULT_ORGANIZATION, AFFILIATION, IS_AUTHOR_INSTITUTION_OF);
r2 = setRelationSemantic(r2, RESULT_ORGANIZATION, AFFILIATION, HAS_AUTHOR_INSTITUTION);
break;
case "resultOrganization_affiliation_hasAuthorInstitution":
if (!"organization".equals(targetType)) {
throw new IllegalStateException(
String
.format(
"invalid claim, sourceId: %s, targetId: %s, semantics: %s", sourceId, targetId,
semantics));
}
r1 = setRelationSemantic(r1, RESULT_ORGANIZATION, AFFILIATION, HAS_AUTHOR_INSTITUTION);
r2 = setRelationSemantic(r2, RESULT_ORGANIZATION, AFFILIATION, IS_AUTHOR_INSTITUTION_OF);
break;
default:
throw new IllegalArgumentException("claim semantics not managed: " + semantics);
}

View File

@ -135,7 +135,7 @@ public class OafToOafMapper extends AbstractMdRecordToOafMapper {
}
@Override
protected List<Instance> prepareInstances(
protected Instance prepareInstances(
final Document doc,
final DataInfo info,
final KeyValue collectedfrom,
@ -197,7 +197,7 @@ public class OafToOafMapper extends AbstractMdRecordToOafMapper {
instance.getUrl().addAll(validUrl);
}
return Lists.newArrayList(instance);
return instance;
}
/**

View File

@ -126,7 +126,7 @@ public class OdfToOafMapper extends AbstractMdRecordToOafMapper {
}
@Override
protected List<Instance> prepareInstances(
protected Instance prepareInstances(
final Document doc,
final DataInfo info,
final KeyValue collectedfrom,
@ -210,7 +210,7 @@ public class OdfToOafMapper extends AbstractMdRecordToOafMapper {
instance.setUrl(new ArrayList<>());
instance.getUrl().addAll(validUrl);
}
return Arrays.asList(instance);
return instance;
}
protected String trimAndDecodeUrl(String url) {

View File

@ -80,9 +80,6 @@ public class PatchRelationsApplication {
final Dataset<Relation> rels = readPath(spark, relationPath, Relation.class);
final Dataset<RelationIdMapping> idMapping = readPath(spark, idMappingPath, RelationIdMapping.class);
log.info("relations: {}", rels.count());
log.info("idMapping: {}", idMapping.count());
final Dataset<Relation> bySource = rels
.joinWith(idMapping, rels.col("source").equalTo(idMapping.col("oldId")), "left")
.map((MapFunction<Tuple2<Relation, RelationIdMapping>, Relation>) t -> {

View File

@ -22,5 +22,11 @@
"paramLongName": "targetPath",
"paramDescription": "the output path of the graph enriched",
"paramRequired": true
},
{
"paramName": "wp",
"paramLongName": "workingDir",
"paramDescription": "the working dir",
"paramRequired": true
}
]

View File

@ -51,6 +51,7 @@
<arg>--orcidPath</arg><arg>${orcidPath}</arg>
<arg>--targetPath</arg><arg>${targetPath}</arg>
<arg>--graphPath</arg><arg>${graphPath}</arg>
<arg>--workingDir</arg><arg>${workingDir}</arg>
<arg>--master</arg><arg>yarn</arg>
</spark>
<ok to="reset_outputpath"/>
@ -89,6 +90,14 @@
<arg>${nameNode}/${graphPath}/project</arg>
<arg>${nameNode}/${targetPath}/project</arg>
</distcp>
<ok to="copy_person"/>
<error to="Kill"/>
</action>
<action name="copy_person">
<distcp xmlns="uri:oozie:distcp-action:0.2">
<arg>${nameNode}/${graphPath}/person</arg>
<arg>${nameNode}/${targetPath}/person</arg>
</distcp>
<ok to="copy_relation"/>
<error to="Kill"/>
</action>

View File

@ -142,6 +142,7 @@
<path start="clean_datasource"/>
<path start="clean_organization"/>
<path start="clean_project"/>
<path start="clean_person"/>
<path start="clean_relation"/>
</fork>
@ -161,6 +162,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=15000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/publication</arg>
@ -196,6 +198,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=8000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/dataset</arg>
@ -231,6 +234,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=5000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/otherresearchproduct</arg>
@ -266,6 +270,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=2000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/software</arg>
@ -301,6 +306,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=1000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/datasource</arg>
@ -336,6 +342,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=1000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/organization</arg>
@ -371,6 +378,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=2000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/project</arg>
@ -390,6 +398,42 @@
<error to="Kill"/>
</action>
<action name="clean_person">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Clean person</name>
<class>eu.dnetlib.dhp.oa.graph.clean.CleanGraphSparkJob</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-cores=${sparkExecutorCores}
--executor-memory=${sparkExecutorMemory}
--driver-memory=${sparkDriverMemory}
--conf spark.executor.memoryOverhead=${sparkExecutorMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=2000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/person</arg>
<arg>--outputPath</arg><arg>${graphOutputPath}/person</arg>
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
<arg>--contextId</arg><arg>${contextId}</arg>
<arg>--verifyParam</arg><arg>${verifyParam}</arg>
<arg>--country</arg><arg>${country}</arg>
<arg>--verifyCountryParam</arg><arg>${verifyCountryParam}</arg>
<arg>--hostedBy</arg><arg>${workingDir}/working/hostedby</arg>
<arg>--collectedfrom</arg><arg>${collectedfrom}</arg>
<arg>--masterDuplicatePath</arg><arg>${workingDir}/masterduplicate</arg>
<arg>--deepClean</arg><arg>${shouldClean}</arg>
</spark>
<ok to="wait_clean"/>
<error to="Kill"/>
</action>
<action name="clean_relation">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
@ -406,6 +450,7 @@
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.autoBroadcastJoinThreshold=-1
--conf spark.sql.shuffle.partitions=20000
</spark-opts>
<arg>--inputPath</arg><arg>${graphInputPath}/relation</arg>

View File

@ -102,6 +102,7 @@
<path start="import_datasource"/>
<path start="import_organization"/>
<path start="import_project"/>
<path start="import_person"/>
<path start="import_relation"/>
</fork>
@ -308,6 +309,35 @@
<error to="Kill"/>
</action>
<action name="import_person">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Import table person</name>
<class>eu.dnetlib.dhp.oa.graph.hive.GraphHiveTableImporterJob</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.executor.memoryOverhead=${sparkExecutorMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
--conf spark.sql.shuffle.partitions=1000
</spark-opts>
<arg>--inputPath</arg><arg>${inputPath}/person</arg>
<arg>--hiveDbName</arg><arg>${hiveDbName}</arg>
<arg>--className</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--hiveMetastoreUris</arg><arg>${hiveMetastoreUris}</arg>
<arg>--numPartitions</arg><arg>1000</arg>
</spark>
<ok to="join_import"/>
<error to="Kill"/>
</action>
<action name="import_relation">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>

View File

@ -68,6 +68,7 @@
<path start="merge_datasource"/>
<path start="merge_organization"/>
<path start="merge_project"/>
<path start="merge_person"/>
<path start="merge_relation"/>
</fork>
@ -260,6 +261,33 @@
<error to="Kill"/>
</action>
<action name="merge_person">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Merge person</name>
<class>eu.dnetlib.dhp.oa.graph.merge.MergeGraphTableSparkJob</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-cores=${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}${spark2EventLogDir}
--conf spark.sql.shuffle.partitions=7680
</spark-opts>
<arg>--betaInputPath</arg><arg>${betaInputGraphPath}/person</arg>
<arg>--prodInputPath</arg><arg>${prodInputGraphPath}/person</arg>
<arg>--outputPath</arg><arg>${graphOutputPath}/person</arg>
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--priority</arg><arg>${priority}</arg>
</spark>
<ok to="wait_merge"/>
<error to="Kill"/>
</action>
<action name="merge_relation">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>

View File

@ -649,6 +649,7 @@
<path start="merge_claims_datasource"/>
<path start="merge_claims_organization"/>
<path start="merge_claims_project"/>
<path start="merge_claims_person"/>
<path start="merge_claims_relation"/>
</fork>
@ -860,6 +861,32 @@
<error to="Kill"/>
</action>
<action name="merge_claims_person">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>MergeClaims_person</name>
<class>eu.dnetlib.dhp.oa.graph.raw.MergeClaimsApplication</class>
<jar>dhp-graph-mapper-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory ${sparkExecutorMemory}
--executor-cores ${sparkExecutorCores}
--driver-memory=${sparkDriverMemory}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.shuffle.partitions=200
</spark-opts>
<arg>--rawGraphPath</arg><arg>${workingDir}/graph_raw</arg>
<arg>--claimsGraphPath</arg><arg>${workingDir}/graph_claims</arg>
<arg>--outputRawGaphPath</arg><arg>${graphOutputPath}</arg>
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
</spark>
<ok to="wait_merge"/>
<error to="Kill"/>
</action>
<join name="wait_merge" to="decisionPatchRelations"/>
<decision name="decisionPatchRelations">

View File

@ -47,13 +47,15 @@ class SparkEnrichGraphWithOrcidAuthors(propertyPath: String, args: Array[String]
log.info(s"orcidPath is '$orcidPath'")
val targetPath = parser.get("targetPath")
log.info(s"targetPath is '$targetPath'")
val workingDir = parser.get("workingDir")
log.info(s"targetPath is '$workingDir'")
createTemporaryData(graphPath, orcidPath, targetPath)
analisys(targetPath)
generateGraph(graphPath, targetPath)
createTemporaryData(graphPath, orcidPath, workingDir)
analisys(workingDir)
generateGraph(graphPath, workingDir, targetPath)
}
private def generateGraph(graphPath: String, targetPath: String): Unit = {
private def generateGraph(graphPath: String, workingDir: String, targetPath: String): Unit = {
ModelSupport.entityTypes.asScala
.filter(e => ModelSupport.isResult(e._1))
@ -63,7 +65,7 @@ class SparkEnrichGraphWithOrcidAuthors(propertyPath: String, args: Array[String]
val matched = spark.read
.schema(Encoders.bean(classOf[ORCIDAuthorEnricherResult]).schema)
.parquet(s"${targetPath}/${resultType}_matched")
.parquet(s"${workingDir}/${resultType}_matched")
.selectExpr("id", "enriched_author")
spark.read

View File

@ -133,7 +133,7 @@ object SparkCreateInputGraph {
val ds: Dataset[T] = spark.read.load(sourcePath).as[T]
ds.groupByKey(_.getId)
.mapGroups { (id, it) => MergeUtils.mergeGroup(id, it.asJava).asInstanceOf[T] }
.mapGroups { (id, it) => MergeUtils.mergeGroup(it.asJava).asInstanceOf[T] }
// .reduceGroups { (x: T, y: T) => MergeUtils.merge(x, y).asInstanceOf[T] }
// .map(_)
.write

View File

@ -30,6 +30,8 @@ import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup;
import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport;
import eu.dnetlib.dhp.schema.common.RelationInverse;
import eu.dnetlib.dhp.schema.oaf.*;
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
@ -365,6 +367,40 @@ class MigrateDbEntitiesApplicationTest {
assertValidId(r2.getCollectedfrom().get(0).getKey());
}
@Test
void testProcessClaims_affiliation() throws Exception {
final List<TypedField> fields = prepareMocks("claimsrel_resultset_affiliation.json");
final List<Oaf> list = app.processClaims(rs);
assertEquals(2, list.size());
verifyMocks(fields);
assertTrue(list.get(0) instanceof Relation);
assertTrue(list.get(1) instanceof Relation);
final Relation r1 = (Relation) list.get(0);
final Relation r2 = (Relation) list.get(1);
assertValidId(r1.getSource());
assertValidId(r1.getTarget());
assertValidId(r2.getSource());
assertValidId(r2.getTarget());
assertNotNull(r1.getDataInfo());
assertNotNull(r2.getDataInfo());
assertNotNull(r1.getDataInfo().getTrust());
assertNotNull(r2.getDataInfo().getTrust());
assertEquals(r1.getSource(), r2.getTarget());
assertEquals(r2.getSource(), r1.getTarget());
assertTrue(StringUtils.isNotBlank(r1.getRelClass()));
assertTrue(StringUtils.isNotBlank(r2.getRelClass()));
assertTrue(StringUtils.isNotBlank(r1.getRelType()));
assertTrue(StringUtils.isNotBlank(r2.getRelType()));
assertValidId(r1.getCollectedfrom().get(0).getKey());
assertValidId(r2.getCollectedfrom().get(0).getKey());
}
private List<TypedField> prepareMocks(final String jsonFile) throws IOException, SQLException {
final String json = IOUtils.toString(getClass().getResourceAsStream(jsonFile));
final ObjectMapper mapper = new ObjectMapper();

View File

@ -0,0 +1,27 @@
[
{
"field": "source_type",
"type": "string",
"value": "organization"
},
{
"field": "source_id",
"type": "string",
"value": "openorgs____::b5ca9d4340e26454e367e2908ef3872f"
},
{
"field": "target_type",
"type": "string",
"value": "software"
},
{
"field": "target_id",
"type": "string",
"value": "userclaim___::bde53826d07c8cf47c99222a375cd2e8"
},
{
"field": "semantics",
"type": "string",
"value": "resultOrganization_affiliation_isAuthorInstitutionOf"
}
]

View File

@ -31,6 +31,7 @@ class ORCIDAuthorMatchersTest {
assertTrue(matchOrderedTokenAndAbbreviations("孙林 Sun Lin", "Sun Lin"))
// assertTrue(AuthorsMatchRevised.compare("孙林 Sun Lin", "孙林")); // not yet implemented
}
@Test def testDocumentationNames(): Unit = {
assertTrue(matchOrderedTokenAndAbbreviations("James C. A. Miller-Jones", "James Antony Miller-Jones"))
}

View File

@ -3,6 +3,7 @@ package eu.dnetlib.dhp.oa.provision;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.util.Comparator;
import java.util.List;
import java.util.Objects;
import java.util.Optional;
@ -167,8 +168,9 @@ public class CreateRelatedEntitiesJob_phase1 {
result
.getDescription()
.stream()
.findFirst()
.filter(d -> Objects.nonNull(d.getValue()))
.map(Field::getValue)
.max(Comparator.comparingInt(String::length))
.ifPresent(
d -> re.setDescription(StringUtils.left(d, ModelHardLimits.MAX_RELATED_ABSTRACT_LENGTH)));
}
@ -231,6 +233,14 @@ public class CreateRelatedEntitiesJob_phase1 {
if (!f.isEmpty()) {
re.setFundingtree(f.stream().map(Field::getValue).collect(Collectors.toList()));
}
break;
case person:
final Person person = (Person) entity;
re.setGivenName(person.getGivenName());
re.setFamilyName(person.getFamilyName());
re.setAlternativeNames(person.getAlternativeNames());
break;
}
return re;

View File

@ -2,10 +2,12 @@
package eu.dnetlib.dhp.oa.provision;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import static eu.dnetlib.dhp.schema.oaf.utils.ModelHardLimits.MAX_RELATIONS_BY_RELCLASS;
import static eu.dnetlib.dhp.utils.DHPUtils.toSeq;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
@ -15,11 +17,13 @@ import org.apache.spark.api.java.function.FilterFunction;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.sql.*;
import org.apache.spark.util.LongAccumulator;
import org.jetbrains.annotations.NotNull;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.collect.Lists;
import com.google.common.collect.Maps;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
@ -27,11 +31,13 @@ import eu.dnetlib.dhp.common.HdfsSupport;
import eu.dnetlib.dhp.common.vocabulary.VocabularyGroup;
import eu.dnetlib.dhp.oa.provision.model.JoinedEntity;
import eu.dnetlib.dhp.oa.provision.model.ProvisionModelSupport;
import eu.dnetlib.dhp.oa.provision.model.RelatedEntityWrapper;
import eu.dnetlib.dhp.oa.provision.model.TupleWrapper;
import eu.dnetlib.dhp.oa.provision.utils.ContextMapper;
import eu.dnetlib.dhp.oa.provision.utils.XmlRecordFactory;
import eu.dnetlib.dhp.schema.oaf.DataInfo;
import eu.dnetlib.dhp.schema.oaf.Oaf;
import eu.dnetlib.dhp.schema.oaf.utils.ModelHardLimits;
import eu.dnetlib.dhp.schema.solr.SolrRecord;
import eu.dnetlib.dhp.utils.ISLookupClientFactory;
import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
@ -124,6 +130,9 @@ public class PayloadConverterJob {
.map(Oaf::getDataInfo)
.map(DataInfo::getDeletedbyinference)
.orElse(false))
.map(
(MapFunction<JoinedEntity, JoinedEntity>) PayloadConverterJob::pruneRelatedEntities,
Encoders.kryo(JoinedEntity.class))
.map(
(MapFunction<JoinedEntity, Tuple2<String, SolrRecord>>) je -> new Tuple2<>(
recordFactory.build(je, validateXML),
@ -139,6 +148,32 @@ public class PayloadConverterJob {
.json(outputPath);
}
/**
* This function iterates through the RelatedEntityWrapper(s) associated to the JoinedEntity and rules out
* those exceeding the maximum allowed frequency defined in eu.dnetlib.dhp.schema.oaf.utils.ModelHardLimits#MAX_RELATIONS_BY_RELCLASS
*/
private static JoinedEntity pruneRelatedEntities(JoinedEntity je) {
Map<String, Long> freqs = Maps.newHashMap();
List<RelatedEntityWrapper> rew = Lists.newArrayList();
if (je.getLinks() != null) {
je.getLinks().forEach(link -> {
final String relClass = link.getRelation().getRelClass();
final Long count = freqs.getOrDefault(relClass, 0L);
final Long max = MAX_RELATIONS_BY_RELCLASS.getOrDefault(relClass, Long.MAX_VALUE);
if (count <= max) {
rew.add(link);
freqs.put(relClass, freqs.getOrDefault(relClass, 0L) + 1);
}
});
je.setLinks(rew);
}
return je;
}
private static void removeOutputDir(final SparkSession spark, final String path) {
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
}

View File

@ -23,6 +23,7 @@ import eu.dnetlib.dhp.schema.common.ModelConstants;
import eu.dnetlib.dhp.schema.common.ModelSupport;
import eu.dnetlib.dhp.schema.oaf.*;
import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
import eu.dnetlib.dhp.schema.oaf.utils.ModelHardLimits;
import eu.dnetlib.dhp.schema.solr.*;
import eu.dnetlib.dhp.schema.solr.AccessRight;
import eu.dnetlib.dhp.schema.solr.Author;
@ -37,6 +38,8 @@ import eu.dnetlib.dhp.schema.solr.Measure;
import eu.dnetlib.dhp.schema.solr.OpenAccessColor;
import eu.dnetlib.dhp.schema.solr.OpenAccessRoute;
import eu.dnetlib.dhp.schema.solr.Organization;
import eu.dnetlib.dhp.schema.solr.Person;
import eu.dnetlib.dhp.schema.solr.PersonTopic;
import eu.dnetlib.dhp.schema.solr.Pid;
import eu.dnetlib.dhp.schema.solr.Project;
import eu.dnetlib.dhp.schema.solr.Result;
@ -89,6 +92,8 @@ public class ProvisionModelSupport {
r.setOrganization(mapOrganization((eu.dnetlib.dhp.schema.oaf.Organization) e));
} else if (e instanceof eu.dnetlib.dhp.schema.oaf.Project) {
r.setProject(mapProject((eu.dnetlib.dhp.schema.oaf.Project) e, vocs));
} else if (e instanceof eu.dnetlib.dhp.schema.oaf.Person) {
r.setPerson(mapPerson((eu.dnetlib.dhp.schema.oaf.Person) e));
}
r
.setLinks(
@ -108,7 +113,7 @@ public class ProvisionModelSupport {
RelatedRecord rr = new RelatedRecord();
final RelatedEntity re = rew.getTarget();
final RecordType relatedRecordType = RecordType.valueOf(re.getType());
final RecordType relatedRecordType = RecordType.fromString(re.getType());
final Relation relation = rew.getRelation();
final String relationProvenance = Optional
.ofNullable(relation.getDataInfo())
@ -150,6 +155,17 @@ public class ProvisionModelSupport {
rr.setPublisher(re.getPublisher());
rr.setResulttype(mapQualifier(re.getResulttype()));
rr.setTitle(Optional.ofNullable(re.getTitle()).map(StructuredProperty::getValue).orElse(null));
rr.setDescription(StringUtils.left(re.getDescription(), ModelHardLimits.MAX_RELATED_ABSTRACT_LENGTH));
rr
.setAuthor(
Optional
.ofNullable(re.getAuthor())
.map(
aa -> aa
.stream()
.limit(ModelHardLimits.MAX_RELATED_AUTHORS)
.collect(Collectors.toList()))
.orElse(null));
if (relation.getValidated() == null) {
relation.setValidated(false);
@ -185,6 +201,18 @@ public class ProvisionModelSupport {
return ps;
}
private static Person mapPerson(eu.dnetlib.dhp.schema.oaf.Person p) {
Person ps = new Person();
ps.setFamilyName(p.getFamilyName());
ps.setGivenName(p.getGivenName());
ps.setAlternativeNames(p.getAlternativeNames());
ps.setBiography(p.getBiography());
ps.setConsent(p.getConsent());
// ps.setSubject(...));
return ps;
}
private static Funding mapFunding(List<String> fundingtree, VocabularyGroup vocs) {
SAXReader reader = new SAXReader();
return Optional
@ -378,6 +406,7 @@ public class ProvisionModelSupport {
rs.setPubliclyFunded(r.getPubliclyFunded());
rs.setTransformativeAgreement(r.getTransformativeAgreement());
rs.setExternalReference(mapExternalReference(r.getExternalReference()));
rs.setBestinstancetype(mapQualifier(r.getBestInstancetype()));
rs.setInstance(mapInstances(r.getInstance()));
if (r instanceof Publication) {
@ -667,14 +696,23 @@ public class ProvisionModelSupport {
}
private static List<Author> asAuthor(List<eu.dnetlib.dhp.schema.oaf.Author> authorList) {
return asAuthor(authorList, ModelHardLimits.MAX_AUTHORS);
}
private static List<Author> asAuthor(List<eu.dnetlib.dhp.schema.oaf.Author> authorList, int maxAuthors) {
return Optional
.ofNullable(authorList)
.map(
authors -> authors
.stream()
.limit(maxAuthors)
.map(
a -> Author
.newInstance(a.getFullname(), a.getName(), a.getSurname(), a.getRank(), asPid(a.getPid())))
.newInstance(
StringUtils.left(a.getFullname(), ModelHardLimits.MAX_AUTHOR_FULLNAME_LENGTH),
a.getName(),
a.getSurname(),
a.getRank(), asPid(a.getPid())))
.collect(Collectors.toList()))
.orElse(null);
}

View File

@ -51,6 +51,11 @@ public class RelatedEntity implements Serializable {
private Qualifier contracttype;
private List<String> fundingtree;
// person
private String givenName;
private String familyName;
private List<String> alternativeNames;
public String getId() {
return id;
}
@ -251,6 +256,30 @@ public class RelatedEntity implements Serializable {
this.fundingtree = fundingtree;
}
public String getGivenName() {
return givenName;
}
public void setGivenName(String givenName) {
this.givenName = givenName;
}
public String getFamilyName() {
return familyName;
}
public void setFamilyName(String familyName) {
this.familyName = familyName;
}
public List<String> getAlternativeNames() {
return alternativeNames;
}
public void setAlternativeNames(List<String> alternativeNames) {
this.alternativeNames = alternativeNames;
}
@Override
public boolean equals(Object o) {
if (this == o)
@ -280,7 +309,10 @@ public class RelatedEntity implements Serializable {
&& Objects.equal(code, that.code)
&& Objects.equal(acronym, that.acronym)
&& Objects.equal(contracttype, that.contracttype)
&& Objects.equal(fundingtree, that.fundingtree);
&& Objects.equal(fundingtree, that.fundingtree)
&& Objects.equal(givenName, that.givenName)
&& Objects.equal(familyName, that.familyName)
&& Objects.equal(alternativeNames, that.alternativeNames);
}
@Override
@ -309,6 +341,9 @@ public class RelatedEntity implements Serializable {
code,
acronym,
contracttype,
fundingtree);
fundingtree,
familyName,
givenName,
alternativeNames);
}
}

View File

@ -1035,6 +1035,48 @@ public class XmlRecordFactory implements Serializable {
.collect(Collectors.toList()));
}
break;
case person:
final Person person = (Person) entity;
if (person.getGivenName() != null) {
metadata.add(XmlSerializationUtils.asXmlElement("givenname", person.getGivenName()));
}
if (person.getFamilyName() != null) {
metadata.add(XmlSerializationUtils.asXmlElement("familyname", person.getFamilyName()));
}
if (person.getAlternativeNames() != null) {
metadata
.addAll(
person
.getAlternativeNames()
.stream()
.map(altName -> XmlSerializationUtils.asXmlElement("alternativename", altName))
.collect(Collectors.toList()));
}
if (person.getBiography() != null) {
metadata.add(XmlSerializationUtils.asXmlElement("biography", person.getBiography()));
}
if (person.getSubject() != null) {
metadata
.addAll(
person
.getSubject()
.stream()
.map(pt -> {
List<Tuple2<String, String>> attrs = Lists.newArrayList();
attrs.add(new Tuple2<>("schema", pt.getSchema()));
attrs.add(new Tuple2<>("value", pt.getValue()));
attrs.add(new Tuple2<>("fromYear", String.valueOf(pt.getFromYear())));
attrs.add(new Tuple2<>("toYear", String.valueOf(pt.getToYear())));
return XmlSerializationUtils.asXmlElement("subject", attrs);
})
.collect(Collectors.toList()));
}
if (person.getConsent() != null) {
metadata.add(XmlSerializationUtils.asXmlElement("consent", String.valueOf(person.getConsent())));
}
break;
default:
throw new IllegalArgumentException("invalid entity type: " + type);
@ -1240,6 +1282,25 @@ public class XmlRecordFactory implements Serializable {
.collect(Collectors.toList()));
}
break;
case person:
if (isNotBlank(re.getGivenName())) {
metadata.add(XmlSerializationUtils.asXmlElement("givenname", re.getGivenName()));
}
if (isNotBlank(re.getFamilyName())) {
metadata.add(XmlSerializationUtils.asXmlElement("familyname", re.getFamilyName()));
}
if (re.getAlternativeNames() != null && !re.getAlternativeNames().isEmpty()) {
metadata
.addAll(
re
.getAlternativeNames()
.stream()
.map(name -> XmlSerializationUtils.asXmlElement("alternativename", name))
.collect(Collectors.toList()));
}
break;
default:
throw new IllegalArgumentException("invalid target type: " + targetType);
}

View File

@ -180,6 +180,7 @@
<path start="join_relation_datasource"/>
<path start="join_relation_organization"/>
<path start="join_relation_project"/>
<path start="join_relation_person"/>
</fork>
<action name="join_relation_publication">
@ -378,6 +379,34 @@
<error to="Kill"/>
</action>
<action name="join_relation_person">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Join[relation.target = person.id]</name>
<class>eu.dnetlib.dhp.oa.provision.CreateRelatedEntitiesJob_phase1</class>
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
<spark-opts>
--executor-cores=${sparkExecutorCoresForJoining}
--executor-memory=${sparkExecutorMemoryForJoining}
--driver-memory=${sparkDriverMemoryForJoining}
--conf spark.executor.memoryOverhead=${sparkExecutorMemoryForJoining}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.shuffle.partitions=5000
--conf spark.network.timeout=${sparkNetworkTimeout}
</spark-opts>
<arg>--inputRelationsPath</arg><arg>${workingDir}/relation</arg>
<arg>--inputEntityPath</arg><arg>${inputGraphRootPath}/person</arg>
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--outputPath</arg><arg>${workingDir}/join_partial/person</arg>
</spark>
<ok to="wait_joins"/>
<error to="Kill"/>
</action>
<join name="wait_joins" to="fork_join_all_entities"/>
<fork name="fork_join_all_entities">
@ -388,6 +417,7 @@
<path start="join_datasource_relations"/>
<path start="join_organization_relations"/>
<path start="join_project_relations"/>
<path start="join_person_relations"/>
</fork>
<action name="join_publication_relations">
@ -593,6 +623,35 @@
<error to="Kill"/>
</action>
<action name="join_person_relations">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Join[person.id = relatedEntity.source]</name>
<class>eu.dnetlib.dhp.oa.provision.CreateRelatedEntitiesJob_phase2</class>
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
<spark-opts>
--executor-cores=${sparkExecutorCoresForJoining}
--executor-memory=${sparkExecutorMemoryForJoining}
--driver-memory=${sparkDriverMemoryForJoining}
--conf spark.executor.memoryOverhead=${sparkExecutorMemoryForJoining}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
--conf spark.sql.shuffle.partitions=5000
--conf spark.network.timeout=${sparkNetworkTimeout}
</spark-opts>
<arg>--inputEntityPath</arg><arg>${inputGraphRootPath}/person</arg>
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Person</arg>
<arg>--inputRelatedEntitiesPath</arg><arg>${workingDir}/join_partial</arg>
<arg>--outputPath</arg><arg>${workingDir}/join_entities/person</arg>
<arg>--numPartitions</arg><arg>10000</arg>
</spark>
<ok to="wait_join_phase2"/>
<error to="Kill"/>
</action>
<join name="wait_join_phase2" to="create_payloads"/>
<action name="create_payloads">

View File

@ -1,63 +0,0 @@
#/usr/bin/bash
# Read log files from ranking scripts and create a two-line file
# with score limits for the various measures. To be used by Kleanthis
attrank_file=$(ls *attrank*.log);
pr_file=$(ls *pagerank*.log)
ram_file=$(ls *ram*.log);
cc_file=$(ls *cc*.log);
impulse_file=$(ls *impulse*.log);
echo
echo "-----------------------------"
echo "Attrank file:${attrank_file}";
echo "PageRank file:${pr_file}";
echo "RAM file:${ram_file}";
echo "CC file:${cc_file}";
echo "Impulse file:${impulse_file}";
echo "-----------------------------"
echo
echo
# output file will be called score_limits.csv
echo -e "influence_top001\tinfluence_top01\tinfluence_top1\tinfluence_top10\tpopularity_top001\tpopularity_top01\tpopularity_top1\tpopularity_top10\timpulse_top001\timpulse_top01\timpulse_top1\timpulse_top10\tcc_top001\tcc_top01\tcc_top1\tcc_top10" > score_limits.csv
# ---------------------------------------------------- #
# Get respective score limits (we don't need RAM)
inf_001=$(grep "^0.01%" ${pr_file} | cut -f 2);
inf_01=$(grep "^0.1%" ${pr_file} | cut -f 2);
inf_1=$(grep "^1%" ${pr_file} | cut -f 2);
inf_10=$(grep "^10%" ${pr_file} | cut -f 2);
echo "Influnence limits:"
echo -e "${inf_001}\t${inf_01}\t${inf_1}\t${inf_10}";
# ---------------------------------------------------- #
pop_001=$(grep "^0.01%" ${attrank_file} | cut -f 2);
pop_01=$(grep "^0.1%" ${attrank_file} | cut -f 2);
pop_1=$(grep "^1%" ${attrank_file} | cut -f 2);
pop_10=$(grep "^10%" ${attrank_file} | cut -f 2);
echo "Popularity limits:";
echo -e "${pop_001}\t${pop_01}\t${pop_1}\t${pop_10}";
# ---------------------------------------------------- #
imp_001=$(grep "^0.01%" ${impulse_file} | cut -f 2);
imp_01=$(grep "^0.1%" ${impulse_file} | cut -f 2);
imp_1=$(grep "^1%" ${impulse_file} | cut -f 2);
imp_10=$(grep "^10%" ${impulse_file} | cut -f 2);
echo "Popularity limits:";
echo -e "${imp_001}\t${imp_01}\t${imp_1}\t${imp_10}";
# ---------------------------------------------------- #
cc_001=$(grep "^0.01%" ${cc_file} | cut -f 2);
cc_01=$(grep "^0.1%" ${cc_file} | cut -f 2);
cc_1=$(grep "^1%" ${cc_file} | cut -f 2);
cc_10=$(grep "^10%" ${cc_file} | cut -f 2);
echo "Popularity limits:";
echo -e "${cc_001}\t${cc_01}\t${cc_1}\t${cc_10}";
# ---------------------------------------------------- #
echo -e "${inf_001}\t${inf_01}\t${inf_1}\t${inf_10}\t${pop_001}\t${pop_01}\t${pop_1}\t${pop_10}\t${imp_001}\t${imp_01}\t${imp_1}\t${imp_10}\t${cc_001}\t${cc_01}\t${cc_1}\t${cc_10}" >> score_limits.csv
echo
echo "score_limits.csv contents:"
cat score_limits.csv
echo;
echo;

View File

@ -1,60 +0,0 @@
import json
import sys
from pyspark.sql import SparkSession
from pyspark import SparkConf, SparkContext
if len(sys.argv) != 3:
print("Usage: map_openaire_ids_to_dois.py <hdfs_src_dir> <hdfs_output_dir>")
sys.exit(-1)
conf = SparkConf().setAppName('BIP!: Map OpenAIRE IDs to DOIs')
sc = SparkContext(conf = conf)
spark = SparkSession.builder.appName('BIP!: Map OpenAIRE IDs to DOIs').getOrCreate()
sc.setLogLevel('OFF')
src_dir = sys.argv[1]
output = sys.argv[2]
# src_dir = "/tmp/beta_provision/graph/21_graph_cleaned/"
# output = '/tmp/openaireid_to_dois/'
def transform(doc):
# get publication year from 'doc.dateofacceptance.value'
dateofacceptance = doc.get('dateofacceptance', {}).get('value')
year = 0
if (dateofacceptance is not None):
year = dateofacceptance.split('-')[0]
# for each pid get 'pid.value' if 'pid.qualifier.classid' equals to 'doi'
dois = [ pid['value'] for pid in doc.get('pid', []) if (pid.get('qualifier', {}).get('classid') == 'doi' and pid['value'] is not None)]
num_dois = len(dois)
# exlcude openaire ids that do not correspond to DOIs
if (num_dois == 0):
return None
fields = [ doc['id'], str(num_dois), chr(0x02).join(dois), str(year) ]
return '\t'.join([ v.encode('utf-8') for v in fields ])
docs = None
for result_type in ["publication", "dataset", "software", "otherresearchproduct"]:
tmp = sc.textFile(src_dir + result_type).map(json.loads)
if (docs is None):
docs = tmp
else:
# append all result types in one RDD
docs = docs.union(tmp)
docs = docs.filter(lambda d: d.get('dataInfo', {}).get('deletedbyinference') == False and d.get('dataInfo', {}).get('invisible') == False)
docs = docs.map(transform).filter(lambda d: d is not None)
docs.saveAsTextFile(output)

View File

@ -1,168 +0,0 @@
#!/usr/bin/python
# This program reads the openaire to doi mapping from the ${synonymFolder} of the workflow
# and uses this mapping to create doi-based score files in the format required by BiP! DB.
# This is done by reading each openaire-id based ranking file and joining the openaire based
# score and classes to all the corresponding dois.
#################################################################################################
# Imports
import sys
# Sparksession lib to communicate with cluster via session object
from pyspark.sql import SparkSession
# Import sql types to define schemas
from pyspark.sql.types import *
# Import sql functions with shorthand alias
import pyspark.sql.functions as F
from pyspark.sql.functions import max
# from pyspark.sql.functions import udf
#################################################################################################
#################################################################################################
# Clean up directory name - no longer needed in final workflow version
'''
def clean_directory_name(dir_name):
# We have a name with the form *_bip_universe<digits>_* or *_graph_universe<digits>_*
# and we need to keep the parts in *
dir_name_parts = dir_name.split('_')
dir_name_parts = [part for part in dir_name_parts if ('bip' not in part and 'graph' not in part and 'universe' not in part and 'from' not in part)]
dir_name = dir_name.replace("openaire_id_graph", "openaire_ids")
clean_name = dir_name + ".txt.gz"
# clean_name = '_'.join(dir_name_parts)
# if '_ids' not in clean_name:
# clean_name = clean_name.replace('id_', 'ids_')
# clean_name = clean_name.replace('.txt', '')
# clean_name = clean_name.replace('.gz', '')
# if 'openaire_ids_' in clean_name:
# clean_name = clean_name.replace('openaire_ids_', '')
# clean_name = clean_name + '.txt.gz'
# else:
# clean_name = clean_name + '.txt.gz'
return clean_name
'''
#################################################################################################
if len(sys.argv) < 3:
print ("Usage: ./map_scores_to_dois.py <synonym_folder> <num_partitions> <score_file_1> <score_file_2> <...etc...>")
sys.exit(-1)
# Read arguments
synonyms_folder = sys.argv[1]
num_partitions = int(sys.argv[2])
input_file_list = [argument.replace("_openaire_id_graph", "").replace("_openaire_id_graph_", "") + "_openaire_ids.txt.gz" for argument in sys.argv[3:]]
# input_file_list = [clean_directory_name(item) for item in input_file_list]
# Prepare output specific variables
output_file_list = [item.replace("_openaire_ids", "") for item in input_file_list]
output_file_list = [item + ".txt.gz" if not item.endswith(".txt.gz") else item for item in output_file_list]
# --- INFO MESSAGES --- #
print ("\n\n----------------------------")
print ("Mpping openaire ids to DOIs")
print ("Reading input from: " + synonyms_folder)
print ("Num partitions: " + str(num_partitions))
print ("Input files:" + " -- ".join(input_file_list))
print ("Output files: " + " -- ".join(output_file_list))
print ("----------------------------\n\n")
#######################################################################################
# We weill define the following schemas:
# --> the schema of the openaire - doi mapping file [string - int - doi_list] (the separator of the doi-list is a non printable character)
# --> a schema for floating point ranking scores [string - float - string] (the latter string is the class)
# --> a schema for integer ranking scores [string - int - string] (the latter string is the class)
float_schema = StructType([
StructField('id', StringType(), False),
StructField('score', FloatType(), False),
StructField('class', StringType(), False)
])
int_schema = StructType([
StructField('id', StringType(), False),
StructField('score', IntegerType(), False),
StructField('class', StringType(), False)
])
# This schema concerns the output of the file
# containing the number of references of each doi
synonyms_schema = StructType([
StructField('id', StringType(), False),
StructField('num_synonyms', IntegerType(), False),
StructField('doi_list', StringType(), False),
])
#######################################################################################
# Start spark session
spark = SparkSession.builder.appName('Map openaire scores to DOIs').getOrCreate()
# Set Log Level for spark session
spark.sparkContext.setLogLevel('WARN')
#######################################################################################
# MAIN Program
# Read and repartition the synonym folder - also cache it since we will need to perform multiple joins
synonym_df = spark.read.schema(synonyms_schema).option('delimiter', '\t').csv(synonyms_folder)
synonym_df = synonym_df.select('id', F.split(F.col('doi_list'), chr(0x02)).alias('doi_list'))
synonym_df = synonym_df.select('id', F.explode('doi_list').alias('doi')).repartition(num_partitions, 'id').cache()
# TESTING
# print ("Synonyms: " + str(synonym_df.count()))
# print ("DF looks like this:" )
# synonym_df.show(1000, False)
print ("\n\n-----------------------------")
# Now we need to join the score files on the openaire-id with the synonyms and then keep
# only doi - score - class and write this to the output
for offset, input_file in enumerate(input_file_list):
print ("Mapping scores from " + input_file)
# Select correct schema
schema = int_schema
if "attrank" in input_file.lower() or "pr" in input_file.lower() or "ram" in input_file.lower():
schema = float_schema
# Load file to dataframe
ranking_df = spark.read.schema(schema).option('delimiter', '\t').csv(input_file).repartition(num_partitions, 'id')
# Get max score
max_score = ranking_df.select(max('score').alias('max')).collect()[0]['max']
print ("Max Score for " + str(input_file) + " is " + str(max_score))
# TESTING
# print ("Loaded df sample:")
# ranking_df.show(1000, False)
# Join scores to synonyms and keep required fields
doi_score_df = synonym_df.join(ranking_df, ['id']).select('doi', 'score', 'class').repartition(num_partitions, 'doi').cache()
# Write output
output_file = output_file_list[offset]
print ("Writing to: " + output_file)
doi_score_df.write.mode('overwrite').option('delimiter','\t').option('header',False).csv(output_file, compression='gzip')
# Creata another file for the bip update process
ranking_df = ranking_df.select('id', 'score', F.lit(F.col('score')/max_score).alias('normalized_score'), 'class', F.col('class').alias('class_dup'))
doi_score_df = synonym_df.join(ranking_df, ['id']).select('doi', 'score', 'normalized_score', 'class', 'class_dup').repartition(num_partitions, 'doi').cache()
output_file = output_file.replace(".txt.gz", "_for_bip_update.txt.gz")
print ("Writing bip update to: " + output_file)
doi_score_df.write.mode('overwrite').option('delimiter','\t').option('header',False).csv(output_file, compression='gzip')
# Free memory?
ranking_df.unpersist(True)
print ("-----------------------------")
print ("\n\nFinished!\n\n")

View File

@ -17,10 +17,6 @@
<name>openaireGraphInputPath</name>
<value>${nameNode}/${workingDir}/openaire_id_graph</value>
</property>
<property>
<name>synonymFolder</name>
<value>${nameNode}/${workingDir}/openaireid_to_dois/</value>
</property>
<property>
<name>checkpointDir</name>
<value>${nameNode}/${workingDir}/check/</value>
@ -32,29 +28,34 @@
</configuration>
</global>
<!-- start using a decision node, so as to determine from which point onwards a job will continue -->
<!-- Start using a decision node, to determine from which point onwards a job will continue -->
<start to="entry-point-decision" />
<decision name="entry-point-decision">
<switch>
<!-- The default will be set as the normal start, a.k.a. get-doi-synonyms -->
<!-- If any different condition is set, go to the corresponding start -->
<!-- Start from creating the citation network (i.e., normal execution should start from here) -->
<case to="create-openaire-ranking-graph">${wf:conf('resume') eq "start"}</case>
<!-- Different citation-based impact indicators are computed -->
<case to="spark-cc">${wf:conf('resume') eq "cc"}</case>
<case to="spark-ram">${wf:conf('resume') eq "ram"}</case>
<case to="spark-impulse">${wf:conf('resume') eq "impulse"}</case>
<case to="spark-pagerank">${wf:conf('resume') eq "pagerank"}</case>
<case to="spark-attrank">${wf:conf('resume') eq "attrank"}</case>
<!-- <case to="iterative-rankings">${wf:conf('resume') eq "rankings-iterative"}</case> -->
<case to="get-file-names">${wf:conf('resume') eq "format-results"}</case>
<case to="map-openaire-to-doi">${wf:conf('resume') eq "map-ids"}</case>
<case to="map-scores-to-dois">${wf:conf('resume') eq "map-scores"}</case>
<case to="create-openaire-ranking-graph">${wf:conf('resume') eq "start"}</case>
<!-- Aggregation of impact scores on the project level -->
<!-- Format the results appropriately before transforming them to action sets -->
<case to="get-file-names">${wf:conf('resume') eq "format-results"}</case>
<!-- Aggregation of impact scores on the project level -->
<case to="project-impact-indicators">${wf:conf('resume') eq "projects-impact"}</case>
<!-- Create action sets -->
<case to="create-actionset">${wf:conf('resume') eq "create-actionset"}</case>
<!-- The default will be set as the normal start, a.k.a. create-openaire-ranking-graph -->
<default to="create-openaire-ranking-graph" />
</switch>
</decision>
@ -295,18 +296,11 @@
<capture-output/>
</shell>
<ok to="format-result-files" />
<ok to="format-json-files" />
<error to="filename-getting-error" />
</action>
<!-- Now we will run in parallel the formatting of ranking files for BiP! DB and openaire (json files) -->
<fork name="format-result-files">
<path start="format-bip-files"/>
<path start="format-json-files"/>
</fork>
<!-- Format json files -->
<!-- Two parts: a) format files b) make the file endings .json.gz -->
<action name="format-json-files">
@ -345,139 +339,8 @@
<file>${wfAppPath}/format_ranking_results.py#format_ranking_results.py</file>
</spark>
<ok to="join-file-formatting" />
<error to="json-formatting-fail" />
</action>
<!-- This is the second line of parallel workflow execution where we create the BiP! DB files -->
<action name="format-bip-files">
<!-- This is required as a tag for spark jobs, regardless of programming language -->
<spark xmlns="uri:oozie:spark-action:0.2">
<!-- using configs from an example on openaire -->
<master>yarn-cluster</master>
<mode>cluster</mode>
<!-- This is the name of our job -->
<name>Format Ranking Results BiP! DB</name>
<!-- Script name goes here -->
<jar>format_ranking_results.py</jar>
<!-- spark configuration options: I've taken most of them from an example from dhp workflows / Master value stolen from sandro -->
<spark-opts>
--executor-memory=${sparkNormalExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkNormalDriverMemory}
--conf spark.executor.memoryOverhead=${sparkNormalExecutorMemory}
--conf spark.sql.shuffle.partitions=${sparkShufflePartitions}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<!-- Script arguments here -->
<arg>zenodo</arg>
<!-- Input files must be identified dynamically -->
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['pr_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['attrank_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['cc_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['impulse_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['ram_file']}</arg>
<!-- Num partitions -->
<arg>${sparkShufflePartitions}</arg>
<!-- Type of data to be produced [bip (dois) / openaire (openaire-ids) ] -->
<arg>openaire</arg>
<!-- This needs to point to the file on the hdfs i think -->
<file>${wfAppPath}/format_ranking_results.py#format_ranking_results.py</file>
</spark>
<ok to="join-file-formatting" />
<error to="bip-formatting-fail" />
</action>
<!-- Finish formatting jobs -->
<join name="join-file-formatting" to="map-openaire-to-doi"/>
<!-- maps openaire ids to DOIs -->
<action name="map-openaire-to-doi">
<spark xmlns="uri:oozie:spark-action:0.2">
<!-- Delete previously created doi synonym folder -->
<prepare>
<delete path="${synonymFolder}"/>
</prepare>
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Openaire-DOI synonym collection</name>
<jar>map_openaire_ids_to_dois.py</jar>
<spark-opts>
--executor-memory=${sparkHighExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkHighDriverMemory}
--conf spark.executor.memoryOverhead=${sparkHighExecutorMemory}
--conf spark.sql.shuffle.partitions=${sparkShufflePartitions}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<!-- Script arguments here -->
<arg>${openaireDataInput}/</arg>
<!-- number of partitions to be used on joins -->
<arg>${synonymFolder}</arg>
<file>${wfAppPath}/map_openaire_ids_to_dois.py#map_openaire_ids_to_dois.py</file>
</spark>
<ok to="map-scores-to-dois" />
<error to="synonym-collection-fail" />
</action>
<!-- mapping openaire scores to DOIs -->
<action name="map-scores-to-dois">
<!-- This is required as a tag for spark jobs, regardless of programming language -->
<spark xmlns="uri:oozie:spark-action:0.2">
<!-- using configs from an example on openaire -->
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Mapping Openaire Scores to DOIs</name>
<jar>map_scores_to_dois.py</jar>
<spark-opts>
--executor-memory=${sparkHighExecutorMemory}
--executor-cores=${sparkExecutorCores}
--driver-memory=${sparkHighDriverMemory}
--conf spark.executor.memoryOverhead=${sparkHighExecutorMemory}
--conf spark.sql.shuffle.partitions=${sparkShufflePartitions}
--conf spark.extraListeners=${spark2ExtraListeners}
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
</spark-opts>
<!-- Script arguments here -->
<arg>${synonymFolder}</arg>
<!-- Number of partitions -->
<arg>${sparkShufflePartitions}</arg>
<!-- The remaining input are the ranking files fproduced for bip db-->
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['pr_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['attrank_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['cc_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['impulse_file']}</arg>
<arg>${nameNode}/${workingDir}/${wf:actionData('get-file-names')['ram_file']}</arg>
<file>${wfAppPath}/map_scores_to_dois.py#map_scores_to_dois.py</file>
</spark>
<ok to="project-impact-indicators" />
<error to="map-scores-fail" />
<error to="json-formatting-fail" />
</action>
<action name="project-impact-indicators">
@ -594,18 +457,6 @@
<message>Error formatting json files, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<kill name="bip-formatting-fail">
<message>Error formatting BIP files, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<kill name="synonym-collection-fail">
<message>Synonym collection failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<kill name="map-scores-fail">
<message>Mapping scores to DOIs failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<kill name="actionset-delete-fail">
<message>Deleting output path for actionsets failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>

View File

@ -3,8 +3,8 @@ package eu.dnetlib.dhp.swh.models;
import java.io.Serializable;
import com.cloudera.com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonProperty;
@JsonIgnoreProperties(ignoreUnknown = true)
public class LastVisitData implements Serializable {

View File

@ -937,7 +937,7 @@
<commons.logging.version>1.1.3</commons.logging.version>
<commons-validator.version>1.7</commons-validator.version>
<dateparser.version>1.0.7</dateparser.version>
<dhp-schemas.version>[8.0.1]</dhp-schemas.version>
<dhp-schemas.version>[9.0.0]</dhp-schemas.version>
<dhp.cdh.version>cdh5.9.2</dhp.cdh.version>
<dhp.commons.lang.version>3.5</dhp.commons.lang.version>
<dhp.guava.version>11.0.2</dhp.guava.version>