254 lines
9.0 KiB
Java
254 lines
9.0 KiB
Java
|
|
package eu.dnetlib.dhp.oa.provision;
|
|
|
|
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
|
|
|
import java.util.List;
|
|
import java.util.Objects;
|
|
import java.util.Optional;
|
|
import java.util.stream.Collectors;
|
|
|
|
import org.apache.commons.io.IOUtils;
|
|
import org.apache.commons.lang3.StringUtils;
|
|
import org.apache.spark.SparkConf;
|
|
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.SaveMode;
|
|
import org.apache.spark.sql.SparkSession;
|
|
import org.slf4j.Logger;
|
|
import org.slf4j.LoggerFactory;
|
|
|
|
import com.fasterxml.jackson.databind.ObjectMapper;
|
|
|
|
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
|
import eu.dnetlib.dhp.common.HdfsSupport;
|
|
import eu.dnetlib.dhp.oa.provision.model.ProvisionModelSupport;
|
|
import eu.dnetlib.dhp.oa.provision.model.RelatedEntity;
|
|
import eu.dnetlib.dhp.oa.provision.model.RelatedEntityWrapper;
|
|
import eu.dnetlib.dhp.schema.common.EntityType;
|
|
import eu.dnetlib.dhp.schema.oaf.*;
|
|
import scala.Tuple2;
|
|
|
|
/**
|
|
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects. The
|
|
* operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization, and
|
|
* all the possible relationships (similarity links produced by the Dedup process are excluded).
|
|
* <p>
|
|
* The operation is implemented by sequentially joining one entity type at time (E) with the relationships (R), and
|
|
* again by E, finally grouped by E.id;
|
|
* <p>
|
|
* The workflow is organized in different parts aimed to to reduce the complexity of the operation 1)
|
|
* PrepareRelationsJob: only consider relationships that are not virtually deleted ($.dataInfo.deletedbyinference ==
|
|
* false), each entity can be linked at most to 100 other objects
|
|
* <p>
|
|
* 2) JoinRelationEntityByTargetJob: (phase 1): prepare tuples [relation - target entity] (R - T): for each entity type
|
|
* E_i map E_i as RelatedEntity T_i to simplify the model and extracting only the necessary information join (R.target =
|
|
* T_i.id) save the tuples (R_i, T_i) (phase 2): create the union of all the entity types E, hash by id read the tuples
|
|
* (R, T), hash by R.source join E.id = (R, T).source, where E becomes the Source Entity S save the tuples (S, R, T)
|
|
* <p>
|
|
* 3) AdjacencyListBuilderJob: given the tuple (S - R - T) we need to group by S.id -> List [ R - T ], mapping the
|
|
* result as JoinedEntity
|
|
* <p>
|
|
* 4) XmlConverterJob: convert the JoinedEntities as XML records
|
|
*/
|
|
public class CreateRelatedEntitiesJob_phase1 {
|
|
|
|
private static final Logger log = LoggerFactory.getLogger(CreateRelatedEntitiesJob_phase1.class);
|
|
|
|
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
|
|
|
public static void main(String[] args) throws Exception {
|
|
|
|
String jsonConfiguration = IOUtils
|
|
.toString(
|
|
PrepareRelationsJob.class
|
|
.getResourceAsStream(
|
|
"/eu/dnetlib/dhp/oa/provision/input_params_related_entities_pahase1.json"));
|
|
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
|
|
parser.parseArgument(args);
|
|
|
|
Boolean isSparkSessionManaged = Optional
|
|
.ofNullable(parser.get("isSparkSessionManaged"))
|
|
.map(Boolean::valueOf)
|
|
.orElse(Boolean.TRUE);
|
|
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
|
|
|
|
String inputRelationsPath = parser.get("inputRelationsPath");
|
|
log.info("inputRelationsPath: {}", inputRelationsPath);
|
|
|
|
String inputEntityPath = parser.get("inputEntityPath");
|
|
log.info("inputEntityPath: {}", inputEntityPath);
|
|
|
|
String outputPath = parser.get("outputPath");
|
|
log.info("outputPath: {}", outputPath);
|
|
|
|
String graphTableClassName = parser.get("graphTableClassName");
|
|
log.info("graphTableClassName: {}", graphTableClassName);
|
|
|
|
Class<? extends OafEntity> entityClazz = (Class<? extends OafEntity>) Class.forName(graphTableClassName);
|
|
|
|
SparkConf conf = new SparkConf();
|
|
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
|
|
conf.registerKryoClasses(ProvisionModelSupport.getModelClasses());
|
|
|
|
runWithSparkSession(
|
|
conf,
|
|
isSparkSessionManaged,
|
|
spark -> {
|
|
removeOutputDir(spark, outputPath);
|
|
joinRelationEntity(spark, inputRelationsPath, inputEntityPath, entityClazz, outputPath);
|
|
});
|
|
}
|
|
|
|
private static <E extends OafEntity> void joinRelationEntity(
|
|
SparkSession spark,
|
|
String inputRelationsPath,
|
|
String inputEntityPath,
|
|
Class<E> clazz,
|
|
String outputPath) {
|
|
|
|
Dataset<Tuple2<String, Relation>> relsByTarget = readPathRelation(spark, inputRelationsPath)
|
|
.filter("dataInfo.deletedbyinference == false")
|
|
.map(
|
|
(MapFunction<Relation, Tuple2<String, Relation>>) r -> new Tuple2<>(r.getTarget(),
|
|
r),
|
|
Encoders.tuple(Encoders.STRING(), Encoders.kryo(Relation.class)))
|
|
.cache();
|
|
|
|
Dataset<Tuple2<String, RelatedEntity>> entities = readPathEntity(spark, inputEntityPath, clazz)
|
|
.filter("dataInfo.invisible == false")
|
|
.map(
|
|
(MapFunction<E, Tuple2<String, RelatedEntity>>) e -> new Tuple2<>(e.getId(), asRelatedEntity(e, clazz)),
|
|
Encoders.tuple(Encoders.STRING(), Encoders.kryo(RelatedEntity.class)))
|
|
.cache();
|
|
|
|
relsByTarget
|
|
.joinWith(entities, entities.col("_1").equalTo(relsByTarget.col("_1")), "inner")
|
|
.map(
|
|
(MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, RelatedEntity>>, RelatedEntityWrapper>) t -> new RelatedEntityWrapper(
|
|
t._1()._2(), t._2()._2()),
|
|
Encoders.kryo(RelatedEntityWrapper.class))
|
|
.write()
|
|
.mode(SaveMode.Overwrite)
|
|
.parquet(outputPath);
|
|
}
|
|
|
|
private static <E extends OafEntity> Dataset<E> readPathEntity(
|
|
SparkSession spark, String inputEntityPath, Class<E> entityClazz) {
|
|
|
|
log.info("Reading Graph table from: {}", inputEntityPath);
|
|
return spark
|
|
.read()
|
|
.textFile(inputEntityPath)
|
|
.map(
|
|
(MapFunction<String, E>) value -> OBJECT_MAPPER.readValue(value, entityClazz),
|
|
Encoders.bean(entityClazz));
|
|
}
|
|
|
|
public static <E extends OafEntity> RelatedEntity asRelatedEntity(E entity, Class<E> clazz) {
|
|
|
|
final RelatedEntity re = new RelatedEntity();
|
|
re.setId(entity.getId());
|
|
re.setType(EntityType.fromClass(clazz).name());
|
|
|
|
re.setPid(entity.getPid());
|
|
re.setCollectedfrom(entity.getCollectedfrom());
|
|
|
|
switch (EntityType.fromClass(clazz)) {
|
|
case publication:
|
|
case dataset:
|
|
case otherresearchproduct:
|
|
case software:
|
|
Result result = (Result) entity;
|
|
|
|
if (result.getTitle() != null && !result.getTitle().isEmpty()) {
|
|
final StructuredProperty title = result.getTitle().stream().findFirst().get();
|
|
title.setValue(StringUtils.left(title.getValue(), ModelHardLimits.MAX_TITLE_LENGTH));
|
|
re.setTitle(title);
|
|
}
|
|
|
|
re.setDateofacceptance(getValue(result.getDateofacceptance()));
|
|
re.setPublisher(getValue(result.getPublisher()));
|
|
re.setResulttype(result.getResulttype());
|
|
if (Objects.nonNull(result.getInstance())) {
|
|
re
|
|
.setInstances(
|
|
result
|
|
.getInstance()
|
|
.stream()
|
|
.filter(Objects::nonNull)
|
|
.limit(ModelHardLimits.MAX_INSTANCES)
|
|
.collect(Collectors.toList()));
|
|
}
|
|
|
|
// TODO still to be mapped
|
|
// re.setCodeRepositoryUrl(j.read("$.coderepositoryurl"));
|
|
|
|
break;
|
|
case datasource:
|
|
Datasource d = (Datasource) entity;
|
|
|
|
re.setOfficialname(getValue(d.getOfficialname()));
|
|
re.setWebsiteurl(getValue(d.getWebsiteurl()));
|
|
re.setDatasourcetype(d.getDatasourcetype());
|
|
re.setOpenairecompatibility(d.getOpenairecompatibility());
|
|
|
|
break;
|
|
case organization:
|
|
Organization o = (Organization) entity;
|
|
|
|
re.setLegalname(getValue(o.getLegalname()));
|
|
re.setLegalshortname(getValue(o.getLegalshortname()));
|
|
re.setCountry(o.getCountry());
|
|
re.setWebsiteurl(getValue(o.getWebsiteurl()));
|
|
break;
|
|
case project:
|
|
Project p = (Project) entity;
|
|
|
|
re.setProjectTitle(getValue(p.getTitle()));
|
|
re.setCode(getValue(p.getCode()));
|
|
re.setAcronym(getValue(p.getAcronym()));
|
|
re.setContracttype(p.getContracttype());
|
|
|
|
List<Field<String>> f = p.getFundingtree();
|
|
if (!f.isEmpty()) {
|
|
re.setFundingtree(f.stream().map(s -> s.getValue()).collect(Collectors.toList()));
|
|
}
|
|
break;
|
|
}
|
|
return re;
|
|
}
|
|
|
|
private static String getValue(Field<String> field) {
|
|
return getFieldValueWithDefault(field, "");
|
|
}
|
|
|
|
private static <T> T getFieldValueWithDefault(Field<T> f, T defaultValue) {
|
|
return Optional
|
|
.ofNullable(f)
|
|
.filter(Objects::nonNull)
|
|
.map(x -> x.getValue())
|
|
.orElse(defaultValue);
|
|
}
|
|
|
|
/**
|
|
* Reads a Dataset of eu.dnetlib.dhp.oa.provision.model.SortableRelation objects from a newline delimited json text
|
|
* file,
|
|
*
|
|
* @param spark
|
|
* @param relationPath
|
|
* @return the Dataset<SortableRelation> containing all the relationships
|
|
*/
|
|
private static Dataset<Relation> readPathRelation(
|
|
SparkSession spark, final String relationPath) {
|
|
|
|
log.info("Reading relations from: {}", relationPath);
|
|
return spark.read().load(relationPath).as(Encoders.bean(Relation.class));
|
|
}
|
|
|
|
private static void removeOutputDir(SparkSession spark, String path) {
|
|
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
|
|
}
|
|
}
|