forked from D-Net/dnet-hadoop
Merge branch '8172_impact_indicators_workflow' of https://code-repo.d4science.org/D-Net/dnet-hadoop into 8172_impact_indicators_workflow
This commit is contained in:
commit
a98da54896
|
|
@ -9,6 +9,7 @@ import java.util.List;
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import java.util.Optional;
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import java.util.stream.Collectors;
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import eu.dnetlib.dhp.actionmanager.bipmodel.score.deserializers.BipProjectModel;
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import org.apache.commons.io.IOUtils;
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import org.apache.hadoop.io.Text;
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import org.apache.hadoop.mapred.SequenceFileOutputFormat;
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|
|
@ -24,7 +25,7 @@ import org.slf4j.LoggerFactory;
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||||
import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.actionmanager.bipmodel.BipDeserialize;
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import eu.dnetlib.dhp.actionmanager.bipmodel.score.deserializers.BipResultModel;
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import eu.dnetlib.dhp.actionmanager.bipmodel.BipScore;
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import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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import eu.dnetlib.dhp.common.HdfsSupport;
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|
|
@ -40,7 +41,8 @@ import scala.Tuple2;
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*/
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public class SparkAtomicActionScoreJob implements Serializable {
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private static final String DOI = "doi";
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private static final String RESULT = "result";
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private static final String PROJECT = "project";
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private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionScoreJob.class);
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private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
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@ -56,18 +58,17 @@ public class SparkAtomicActionScoreJob implements Serializable {
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parser.parseArgument(args);
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Boolean isSparkSessionManaged = Optional
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.ofNullable(parser.get("isSparkSessionManaged"))
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.map(Boolean::valueOf)
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.orElse(Boolean.TRUE);
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Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
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log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
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final String inputPath = parser.get("inputPath");
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log.info("inputPath {}: ", inputPath);
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log.info("inputPath: {}", inputPath);
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final String outputPath = parser.get("outputPath");
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log.info("outputPath {}: ", outputPath);
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log.info("outputPath: {}", outputPath);
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final String targetEntity = parser.get("targetEntity");
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log.info("targetEntity: {}", targetEntity);
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SparkConf conf = new SparkConf();
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@ -76,17 +77,48 @@ public class SparkAtomicActionScoreJob implements Serializable {
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isSparkSessionManaged,
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spark -> {
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removeOutputDir(spark, outputPath);
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// follow different procedures for different target entities
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switch (targetEntity) {
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case RESULT:
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prepareResults(spark, inputPath, outputPath);
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});
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break;
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case PROJECT:
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prepareProjects(spark, inputPath, outputPath);
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break;
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default:
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throw new RuntimeException("Unknown target entity: " + targetEntity);
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}
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}
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);
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}
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private static <I extends Project> void prepareProjects(SparkSession spark, String inputPath, String outputPath) {
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// read input bip project scores
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Dataset<BipProjectModel> projectScores = readPath(spark, inputPath, BipProjectModel.class);
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projectScores.map( (MapFunction<BipProjectModel, Project>) bipProjectScores -> {
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Project project = new Project();
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project.setId(bipProjectScores.getProjectId());
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project.setMeasures(bipProjectScores.toMeasures());
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return project;
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}, Encoders.bean(Project.class))
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.toJavaRDD()
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.map(p -> new AtomicAction(Project.class, p))
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.mapToPair( aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
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new Text(OBJECT_MAPPER.writeValueAsString(aa))))
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.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class);
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|
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}
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private static <I extends Result> void prepareResults(SparkSession spark, String bipScorePath, String outputPath) {
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final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
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JavaRDD<BipDeserialize> bipDeserializeJavaRDD = sc
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JavaRDD<BipResultModel> bipDeserializeJavaRDD = sc
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.textFile(bipScorePath)
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.map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class));
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.map(item -> OBJECT_MAPPER.readValue(item, BipResultModel.class));
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|
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Dataset<BipScore> bipScores = spark
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.createDataset(bipDeserializeJavaRDD.flatMap(entry -> entry.keySet().stream().map(key -> {
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|
|
@ -159,12 +191,4 @@ public class SparkAtomicActionScoreJob implements Serializable {
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HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
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}
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public static <R> Dataset<R> readPath(
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SparkSession spark, String inputPath, Class<R> clazz) {
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return spark
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.read()
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.textFile(inputPath)
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.map((MapFunction<String, R>) value -> OBJECT_MAPPER.readValue(value, clazz), Encoders.bean(clazz));
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}
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||||
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||||
}
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|
|
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|
|
@ -0,0 +1,69 @@
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package eu.dnetlib.dhp.actionmanager.bipmodel.score.deserializers;
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||||
import com.opencsv.bean.CsvBindByPosition;
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||||
import eu.dnetlib.dhp.schema.common.ModelConstants;
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||||
import eu.dnetlib.dhp.schema.oaf.KeyValue;
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||||
import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
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||||
import lombok.AllArgsConstructor;
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||||
import lombok.Getter;
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||||
import lombok.NoArgsConstructor;
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||||
import lombok.Setter;
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||||
import eu.dnetlib.dhp.schema.oaf.Measure;
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||||
import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.Collections;
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import java.util.List;
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import static eu.dnetlib.dhp.actionmanager.Constants.*;
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@NoArgsConstructor
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@AllArgsConstructor
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@Getter
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@Setter
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public class BipProjectModel {
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String projectId;
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String numOfInfluentialResults;
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String numOfPopularResults;
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String totalImpulse;
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String totalCitationCount;
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// each project bip measure has exactly one value, hence one key-value pair
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private Measure createMeasure(String measureId, String measureValue) {
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KeyValue kv = new KeyValue();
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kv.setKey("score");
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kv.setValue(measureValue);
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kv.setDataInfo(
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||||
OafMapperUtils.dataInfo(
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||||
false,
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||||
UPDATE_DATA_INFO_TYPE,
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||||
true,
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||||
false,
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||||
OafMapperUtils.qualifier(
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UPDATE_MEASURE_BIP_CLASS_ID,
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||||
UPDATE_CLASS_NAME,
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||||
ModelConstants.DNET_PROVENANCE_ACTIONS,
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||||
ModelConstants.DNET_PROVENANCE_ACTIONS),
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||||
"")
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||||
);
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||||
|
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Measure measure = new Measure();
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measure.setId(measureId);
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measure.setUnit(Collections.singletonList(kv));
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return measure;
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||||
}
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public List<Measure> toMeasures() {
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return Arrays.asList(
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createMeasure("numOfInfluentialResults", numOfInfluentialResults),
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createMeasure("numOfPopularResults", numOfPopularResults),
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||||
createMeasure("totalImpulse", totalImpulse),
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||||
createMeasure("totalCitationCount", totalCitationCount)
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||||
);
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||||
}
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||||
|
||||
}
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||||
|
|
@ -1,5 +1,7 @@
|
|||
|
||||
package eu.dnetlib.dhp.actionmanager.bipmodel;
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||||
package eu.dnetlib.dhp.actionmanager.bipmodel.score.deserializers;
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||||
|
||||
import eu.dnetlib.dhp.actionmanager.bipmodel.Score;
|
||||
|
||||
import java.io.Serializable;
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||||
import java.util.ArrayList;
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||||
|
|
@ -11,9 +13,9 @@ import java.util.List;
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|||
* Only needed for deserialization purposes
|
||||
*/
|
||||
|
||||
public class BipDeserialize extends HashMap<String, List<Score>> implements Serializable {
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||||
public class BipResultModel extends HashMap<String, List<Score>> implements Serializable {
|
||||
|
||||
public BipDeserialize() {
|
||||
public BipResultModel() {
|
||||
super();
|
||||
}
|
||||
|
||||
|
|
@ -24,7 +24,7 @@ import org.slf4j.LoggerFactory;
|
|||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import eu.dnetlib.dhp.actionmanager.bipmodel.BipDeserialize;
|
||||
import eu.dnetlib.dhp.actionmanager.bipmodel.score.deserializers.BipResultModel;
|
||||
import eu.dnetlib.dhp.actionmanager.bipmodel.BipScore;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
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||||
import eu.dnetlib.dhp.common.HdfsSupport;
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||||
|
|
@ -82,9 +82,9 @@ public class PrepareBipFinder implements Serializable {
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|||
|
||||
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
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||||
|
||||
JavaRDD<BipDeserialize> bipDeserializeJavaRDD = sc
|
||||
JavaRDD<BipResultModel> bipDeserializeJavaRDD = sc
|
||||
.textFile(inputPath)
|
||||
.map(item -> OBJECT_MAPPER.readValue(item, BipDeserialize.class));
|
||||
.map(item -> OBJECT_MAPPER.readValue(item, BipResultModel.class));
|
||||
|
||||
spark
|
||||
.createDataset(bipDeserializeJavaRDD.flatMap(entry -> entry.keySet().stream().map(key -> {
|
||||
|
|
|
|||
|
|
@ -16,5 +16,11 @@
|
|||
"paramLongName": "outputPath",
|
||||
"paramDescription": "the path of the new ActionSet",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "te",
|
||||
"paramLongName": "targetEntity",
|
||||
"paramDescription": "the type of target entity to be enriched; currently supported one of { 'result', 'project' }",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -6,8 +6,9 @@ import static org.junit.jupiter.api.Assertions.*;
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|||
import java.io.IOException;
|
||||
import java.nio.file.Files;
|
||||
import java.nio.file.Path;
|
||||
import java.util.List;
|
||||
|
||||
import eu.dnetlib.dhp.schema.oaf.KeyValue;
|
||||
import eu.dnetlib.dhp.schema.oaf.Project;
|
||||
import org.apache.commons.io.FileUtils;
|
||||
import org.apache.hadoop.io.Text;
|
||||
import org.apache.spark.SparkConf;
|
||||
|
|
@ -27,7 +28,6 @@ import org.slf4j.LoggerFactory;
|
|||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
|
||||
import eu.dnetlib.dhp.schema.action.AtomicAction;
|
||||
import eu.dnetlib.dhp.schema.oaf.Publication;
|
||||
import eu.dnetlib.dhp.schema.oaf.Result;
|
||||
|
||||
public class SparkAtomicActionScoreJobTest {
|
||||
|
|
@ -37,8 +37,11 @@ public class SparkAtomicActionScoreJobTest {
|
|||
private static SparkSession spark;
|
||||
|
||||
private static Path workingDir;
|
||||
private static final Logger log = LoggerFactory
|
||||
.getLogger(SparkAtomicActionScoreJobTest.class);
|
||||
|
||||
private final static String RESULT = "result";
|
||||
private final static String PROJECT = "project";
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(SparkAtomicActionScoreJobTest.class);
|
||||
|
||||
@BeforeAll
|
||||
public static void beforeAll() throws IOException {
|
||||
|
|
@ -69,29 +72,31 @@ public class SparkAtomicActionScoreJobTest {
|
|||
spark.stop();
|
||||
}
|
||||
|
||||
@Test
|
||||
void testMatch() throws Exception {
|
||||
String bipScoresPath = getClass()
|
||||
.getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/bip_scores_oid.json")
|
||||
.getPath();
|
||||
|
||||
SparkAtomicActionScoreJob
|
||||
.main(
|
||||
private void runJob(String inputPath, String outputPath, String targetEntity) throws Exception {
|
||||
SparkAtomicActionScoreJob.main(
|
||||
new String[] {
|
||||
"-isSparkSessionManaged",
|
||||
Boolean.FALSE.toString(),
|
||||
"-inputPath",
|
||||
"-isSparkSessionManaged", Boolean.FALSE.toString(),
|
||||
"-inputPath", inputPath,
|
||||
"-outputPath", outputPath,
|
||||
"-targetEntity", targetEntity,
|
||||
}
|
||||
);
|
||||
}
|
||||
@Test
|
||||
void testResultScores() throws Exception {
|
||||
final String targetEntity = RESULT;
|
||||
String inputResultScores = getClass()
|
||||
.getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/result_bip_scores.json")
|
||||
.getPath();
|
||||
String outputPath = workingDir.toString() + "/" + targetEntity + "/actionSet";
|
||||
|
||||
bipScoresPath,
|
||||
|
||||
"-outputPath",
|
||||
workingDir.toString() + "/actionSet"
|
||||
});
|
||||
// execute the job to generate the action sets for result scores
|
||||
runJob(inputResultScores, outputPath, targetEntity);
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Result> tmp = sc
|
||||
.sequenceFile(workingDir.toString() + "/actionSet", Text.class, Text.class)
|
||||
.sequenceFile(outputPath, Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Result) aa.getPayload()));
|
||||
|
||||
|
|
@ -140,4 +145,61 @@ public class SparkAtomicActionScoreJobTest {
|
|||
|
||||
}
|
||||
|
||||
@Test
|
||||
void testProjectScores() throws Exception {
|
||||
String targetEntity = PROJECT;
|
||||
String inputResultScores = getClass()
|
||||
.getResource("/eu/dnetlib/dhp/actionmanager/bipfinder/project_bip_scores.json")
|
||||
.getPath();
|
||||
String outputPath = workingDir.toString() + "/" + targetEntity + "/actionSet";
|
||||
|
||||
// execute the job to generate the action sets for project scores
|
||||
runJob(inputResultScores, outputPath, PROJECT);
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
|
||||
JavaRDD<Project> projects = sc
|
||||
.sequenceFile(outputPath, Text.class, Text.class)
|
||||
.map(value -> OBJECT_MAPPER.readValue(value._2().toString(), AtomicAction.class))
|
||||
.map(aa -> ((Project) aa.getPayload()));
|
||||
|
||||
// test the number of projects
|
||||
assertEquals(4, projects.count());
|
||||
|
||||
String testProjectId = "40|nih_________::c02a8233e9b60f05bb418f0c9b714833";
|
||||
|
||||
// count that the project with id testProjectId is present
|
||||
assertEquals(1, projects.filter(row -> row.getId().equals(testProjectId)).count());
|
||||
|
||||
projects.filter(row -> row.getId().equals(testProjectId))
|
||||
.flatMap(r -> r.getMeasures().iterator())
|
||||
.foreach(m -> {
|
||||
log.info(m.getId() + " " + m.getUnit());
|
||||
|
||||
// ensure that only one score is present for each bip impact measure
|
||||
assertEquals(1, m.getUnit().size());
|
||||
|
||||
KeyValue kv = m.getUnit().get(0);
|
||||
|
||||
// ensure that the correct key is provided, i.e. score
|
||||
assertEquals("score", kv.getKey());
|
||||
|
||||
switch(m.getId()) {
|
||||
case "numOfInfluentialResults":
|
||||
assertEquals("0", kv.getValue());
|
||||
break;
|
||||
case "numOfPopularResults":
|
||||
assertEquals("1", kv.getValue());
|
||||
break;
|
||||
case "totalImpulse":
|
||||
assertEquals("25", kv.getValue());
|
||||
break;
|
||||
case "totalCitationCount":
|
||||
assertEquals("43", kv.getValue());
|
||||
break;
|
||||
default:
|
||||
fail("Unknown measure id in the context of projects");
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,4 @@
|
|||
{"projectId":"40|nsf_________::d93e50d22374a1cf59f6a232413ea027","numOfInfluentialResults":0,"numOfPopularResults":10,"totalImpulse":181,"totalCitationCount":235}
|
||||
{"projectId":"40|nih_________::1c93debc7085e440f245fbe70b2e8b21","numOfInfluentialResults":14,"numOfPopularResults":17,"totalImpulse":1558,"totalCitationCount":4226}
|
||||
{"projectId":"40|nih_________::c02a8233e9b60f05bb418f0c9b714833","numOfInfluentialResults":0,"numOfPopularResults":1,"totalImpulse":25,"totalCitationCount":43}
|
||||
{"projectId":"40|corda_______::d91dcf3a87dd7f72248fab0b8a4ba273","numOfInfluentialResults":2,"numOfPopularResults":3,"totalImpulse":78,"totalCitationCount":178}
|
||||
|
|
@ -1,4 +1,4 @@
|
|||
# Ranking Workflow for Openaire Publications
|
||||
# Ranking Workflow for OpenAIRE Publications
|
||||
|
||||
This project contains the files for running a paper ranking workflow on the openaire graph using apache oozie.
|
||||
All scripts are written in python and the project setup follows the typical oozie workflow structure:
|
||||
|
|
@ -7,17 +7,15 @@ All scripts are written in python and the project setup follows the typical oozi
|
|||
- a job.properties file specifying parameter values for the parameters used by the workflow
|
||||
- a set of python scripts used by the workflow
|
||||
|
||||
**NOTE**: the workflow depends on the external library of ranking scripts called BiP! Ranker.
|
||||
**NOTE**: the workflow depends on the external library of ranking scripts called [BiP! Ranker](https://github.com/athenarc/Bip-Ranker).
|
||||
You can check out a specific tag/release of BIP! Ranker using maven, as described in the following section.
|
||||
|
||||
## Check out a specific tag/release of BIP-Ranker
|
||||
## Build and deploy
|
||||
|
||||
* Edit the `scmVersion` of the maven-scm-plugin in the pom.xml to point to the tag/release version you want to check out.
|
||||
|
||||
* Then, use maven to perform the checkout:
|
||||
Use the following command for packaging:
|
||||
|
||||
```
|
||||
mvn scm:checkout
|
||||
mvn package -Poozie-package -Dworkflow.source.dir=eu/dnetlib/dhp/oa/graph/impact_indicators -DskipTests
|
||||
```
|
||||
|
||||
* The code should be visible under `src/main/bip-ranker` folder.
|
||||
Note: edit the property `bip.ranker.tag` of the `pom.xml` file to specify the tag of [BIP-Ranker](https://github.com/athenarc/Bip-Ranker) that you want to use.
|
||||
|
|
|
|||
|
|
@ -5,9 +5,8 @@
|
|||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>eu.dnetlib.dhp</groupId>
|
||||
<artifactId>dhp</artifactId>
|
||||
<artifactId>dhp-workflows</artifactId>
|
||||
<version>1.2.5-SNAPSHOT</version>
|
||||
<relativePath>../pom.xml</relativePath>
|
||||
</parent>
|
||||
|
||||
<artifactId>dhp-impact-indicators</artifactId>
|
||||
|
|
@ -16,6 +15,9 @@
|
|||
<maven.compiler.source>8</maven.compiler.source>
|
||||
<maven.compiler.target>8</maven.compiler.target>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
|
||||
<!-- Use this property to fetch a specific tag -->
|
||||
<bip.ranker.tag>v1.0.0</bip.ranker.tag>
|
||||
</properties>
|
||||
|
||||
<scm>
|
||||
|
|
@ -32,10 +34,29 @@
|
|||
<configuration>
|
||||
<connectionType>connection</connectionType>
|
||||
<scmVersionType>tag</scmVersionType><!-- 'branch' can also be provided here -->
|
||||
<scmVersion>v1.0.0</scmVersion><!-- in case of scmVersionType == 'branch', this field points to the branch name -->
|
||||
<checkoutDirectory>${project.build.directory}/../src/main/bip-ranker</checkoutDirectory>
|
||||
<scmVersion>${bip.ranker.tag}</scmVersion><!-- in case of scmVersionType == 'branch', this field points to the branch name -->
|
||||
<checkoutDirectory>${project.build.directory}/${oozie.package.file.name}/${oozieAppDir}/bip-ranker</checkoutDirectory>
|
||||
</configuration>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>checkout-bip-ranker</id>
|
||||
<phase>prepare-package</phase>
|
||||
<goals>
|
||||
<goal>checkout</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>eu.dnetlib.dhp</groupId>
|
||||
<artifactId>dhp-aggregation</artifactId>
|
||||
<version>${projectVersion}</version>
|
||||
<scope>compile</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
</project>
|
||||
|
|
@ -90,3 +90,6 @@ oozie.wf.application.path=${wfAppPath}
|
|||
# Path where the final output should be?
|
||||
actionSetOutputPath=${workflowDataDir}/bip_actionsets/
|
||||
|
||||
# The directory to store project impact indicators
|
||||
projectImpactIndicatorsOutput=${workflowDataDir}/project_indicators
|
||||
|
||||
|
|
@ -0,0 +1,108 @@
|
|||
import sys
|
||||
from pyspark.sql import SparkSession
|
||||
from pyspark import SparkConf, SparkContext
|
||||
import pyspark.sql.functions as F
|
||||
from pyspark.sql.types import StringType, IntegerType, StructType, StructField
|
||||
|
||||
if len(sys.argv) < 8:
|
||||
print("Usage: projects_impact.py <relations_folder> <influence_file> <popularity_file> <cc_file> <impulse_file> <num_partitions> <output_dir>")
|
||||
sys.exit(-1)
|
||||
|
||||
appName = 'Project Impact Indicators'
|
||||
conf = SparkConf().setAppName(appName)
|
||||
sc = SparkContext(conf = conf)
|
||||
spark = SparkSession.builder.appName(appName).getOrCreate()
|
||||
sc.setLogLevel('OFF')
|
||||
|
||||
# input parameters
|
||||
relations_fd = sys.argv[1]
|
||||
influence_fd = sys.argv[2]
|
||||
popularity_fd = sys.argv[3]
|
||||
cc_fd = sys.argv[4]
|
||||
impulse_fd = sys.argv[5]
|
||||
num_partitions = int(sys.argv[6])
|
||||
output_dir = sys.argv[7]
|
||||
|
||||
# schema for impact indicator files
|
||||
impact_files_schema = StructType([
|
||||
StructField('resultId', StringType(), False),
|
||||
StructField('score', IntegerType(), False),
|
||||
StructField('class', StringType(), False),
|
||||
])
|
||||
|
||||
# list of impact indicators
|
||||
impact_indicators = [
|
||||
('influence', influence_fd, 'class'),
|
||||
('popularity', popularity_fd, 'class'),
|
||||
('impulse', impulse_fd, 'score'),
|
||||
('citation_count', cc_fd, 'score')
|
||||
]
|
||||
|
||||
'''
|
||||
* Read impact indicator file and return a dataframe with the following schema:
|
||||
* resultId: String
|
||||
* indicator_name: Integer
|
||||
'''
|
||||
def read_df(fd, indicator_name, column_name):
|
||||
return spark.read.schema(impact_files_schema)\
|
||||
.option('delimiter', '\t')\
|
||||
.option('header', False)\
|
||||
.csv(fd)\
|
||||
.select('resultId', F.col(column_name).alias(indicator_name))\
|
||||
.repartition(num_partitions, 'resultId')
|
||||
|
||||
# Print dataframe schema, first 5 rows, and count
|
||||
def print_df(df):
|
||||
df.show(50)
|
||||
df.printSchema()
|
||||
print(df.count())
|
||||
|
||||
# Sets a null value to the column if the value is equal to the given value
|
||||
def set_class_value_to_null(column, value):
|
||||
return F.when(column != value, column).otherwise(F.lit(None))
|
||||
|
||||
# load and filter Project-to-Result relations
|
||||
print("Reading relations")
|
||||
relations = spark.read.json(relations_fd)\
|
||||
.select(F.col('source').alias('projectId'), F.col('target').alias('resultId'), 'relClass', 'dataInfo.deletedbyinference', 'dataInfo.invisible')\
|
||||
.where( (F.col('relClass') == 'produces') \
|
||||
& (F.col('deletedbyinference') == "false")\
|
||||
& (F.col('invisible') == "false"))\
|
||||
.drop('deletedbyinference')\
|
||||
.drop('invisible')\
|
||||
.drop('relClass')\
|
||||
.repartition(num_partitions, 'resultId')
|
||||
|
||||
for indicator_name, fd, column_name in impact_indicators:
|
||||
|
||||
print("Reading {} '{}' field from file".format(indicator_name, column_name))
|
||||
df = read_df(fd, indicator_name, column_name)
|
||||
|
||||
# sets a zero value to the indicator column if the value is C5
|
||||
if (column_name == 'class'):
|
||||
df = df.withColumn(indicator_name, F.when(F.col(indicator_name).isin("C5"), 0).otherwise(1))
|
||||
|
||||
# print_df(df)
|
||||
|
||||
print("Joining {} to relations".format(indicator_name))
|
||||
|
||||
# NOTE: we use inner join because we want to keep only the results that have an impact score
|
||||
# also note that all impact scores have the same set of results
|
||||
relations = relations.join(df, 'resultId', 'inner')\
|
||||
.repartition(num_partitions, 'resultId')
|
||||
|
||||
# uncomment to print non-null values count for each indicator
|
||||
# for indicator_name, fd, column_name in impact_indicators:
|
||||
# print("Counting non null values for {}".format(indicator_name))
|
||||
# print(relations.filter(F.col(indicator_name).isNotNull()).count())
|
||||
|
||||
# sum the impact indicator values for each project
|
||||
relations.groupBy('projectId')\
|
||||
.agg(\
|
||||
F.sum('influence').alias('numOfInfluentialResults'),\
|
||||
F.sum('popularity').alias('numOfPopularResults'),\
|
||||
F.sum('impulse').alias('totalImpulse'),\
|
||||
F.sum('citation_count').alias('totalCitationCount')\
|
||||
)\
|
||||
.write.mode("overwrite")\
|
||||
.json(output_dir, compression="gzip")
|
||||
|
|
@ -15,6 +15,8 @@
|
|||
<case to="map-openaire-to-doi">${resume eq "map-ids"}</case>
|
||||
<case to="map-scores-to-dois">${resume eq "map-scores"}</case>
|
||||
<case to="create-openaire-ranking-graph">${resume eq "start"}</case>
|
||||
<case to="project-impact-indicators">${resume eq "projects-impact"}</case>
|
||||
|
||||
<!-- TODO: add action set creation here -->
|
||||
<default to="create-openaire-ranking-graph" />
|
||||
</switch>
|
||||
|
|
@ -33,7 +35,6 @@
|
|||
<delete path="${synonymFolder}"/>
|
||||
</prepare>
|
||||
|
||||
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -88,7 +89,6 @@
|
|||
<!-- This should give the machine/root of the hdfs, serafeim has provided a link with the required job properties -->
|
||||
<name-node>${nameNode}</name-node>
|
||||
|
||||
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -130,7 +130,6 @@
|
|||
<!-- This should give the machine/root of the hdfs, serafeim has provided a link with the required job properties -->
|
||||
<name-node>${nameNode}</name-node>
|
||||
|
||||
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -179,7 +178,6 @@
|
|||
<!-- This should give the machine/root of the hdfs, serafeim has provided a link with the required job properties -->
|
||||
<name-node>${nameNode}</name-node>
|
||||
|
||||
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -334,7 +332,7 @@
|
|||
<!-- This should give the machine/root of the hdfs -->
|
||||
<name-node>${nameNode}</name-node>
|
||||
|
||||
<!-- Exec is needed foor shell comands - points to type of shell command -->
|
||||
<!-- Exec is needed for shell commands - points to type of shell command -->
|
||||
<exec>/usr/bin/bash</exec>
|
||||
<!-- name of script to run -->
|
||||
<argument>get_ranking_files.sh</argument>
|
||||
|
|
@ -475,7 +473,6 @@
|
|||
<delete path="${synonymFolder}"/>
|
||||
</prepare>
|
||||
|
||||
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -518,7 +515,6 @@
|
|||
<!-- This should give the machine/root of the hdfs, serafeim has provided a link with the required job properties -->
|
||||
<name-node>${nameNode}</name-node>
|
||||
|
||||
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -560,19 +556,17 @@
|
|||
|
||||
<action name="deleteOutputPathForActionSet">
|
||||
<fs>
|
||||
<delete path="${actionSetOutputPath}"/>
|
||||
<mkdir path="${actionSetOutputPath}"/>
|
||||
<!--
|
||||
<delete path="${workingDir}"/>
|
||||
<mkdir path="${workingDir}"/>
|
||||
-->
|
||||
<delete path="${actionSetOutputPath}/results/"/>
|
||||
<delete path="${actionSetOutputPath}/projects/"/>
|
||||
|
||||
<mkdir path="${actionSetOutputPath}/results/"/>
|
||||
<mkdir path="${actionSetOutputPath}/projects/"/>
|
||||
</fs>
|
||||
<ok to="createActionSet"/>
|
||||
<ok to="createActionSetForResults"/>
|
||||
<error to="actionset-delete-fail"/>
|
||||
</action>
|
||||
|
||||
|
||||
<action name="createActionSet">
|
||||
<action name="createActionSetForResults">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
|
|
@ -590,13 +584,90 @@
|
|||
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
|
||||
</spark-opts>
|
||||
<arg>--inputPath</arg><arg>${bipScorePath}</arg>
|
||||
<arg>--outputPath</arg><arg>${actionSetOutputPath}</arg>
|
||||
<arg>--outputPath</arg><arg>${actionSetOutputPath}/results/</arg>
|
||||
<arg>--targetEntity</arg><arg>result</arg>
|
||||
</spark>
|
||||
<ok to="end"/>
|
||||
<ok to="project-impact-indicators"/>
|
||||
<error to="actionset-creation-fail"/>
|
||||
</action>
|
||||
|
||||
<action name="project-impact-indicators">
|
||||
<!-- This is required as a tag for spark jobs, regardless of programming language -->
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<!-- Is this yarn? Probably the answers are at the link serafeim sent me -->
|
||||
<job-tracker>${jobTracker}</job-tracker>
|
||||
<!-- This should give the machine/root of the hdfs, serafeim has provided a link with the required job properties -->
|
||||
<name-node>${nameNode}</name-node>
|
||||
<!-- using configs from an example on openaire -->
|
||||
<master>yarn-cluster</master>
|
||||
<mode>cluster</mode>
|
||||
|
||||
<!-- This is the name of our job -->
|
||||
<name>Project Impact Indicators</name>
|
||||
<!-- Script name goes here -->
|
||||
<jar>projects_impact.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 18G --executor-cores 4 --driver-memory 10G
|
||||
--master yarn
|
||||
--deploy-mode cluster
|
||||
--conf spark.sql.shuffle.partitions=7680
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}</spark-opts>
|
||||
|
||||
<!-- Script arguments here -->
|
||||
|
||||
<!-- graph data folder from which to read relations -->
|
||||
<arg>${openaireDataInput}/relations</arg>
|
||||
|
||||
<!-- input files with impact indicators for results -->
|
||||
<arg>${nameNode}/${workflowDataDir}/${wf:actionData('get-file-names')['pr_file']}</arg>
|
||||
<arg>${nameNode}/${workflowDataDir}/${wf:actionData('get-file-names')['attrank_file']}</arg>
|
||||
<arg>${nameNode}/${workflowDataDir}/${wf:actionData('get-file-names')['cc_file']}</arg>
|
||||
<arg>${nameNode}/${workflowDataDir}/${wf:actionData('get-file-names')['impulse_file']}</arg>
|
||||
|
||||
<!-- number of partitions to be used on joins -->
|
||||
<arg>7680</arg>
|
||||
|
||||
<arg>${projectImpactIndicatorsOutput}</arg>
|
||||
|
||||
<!-- This needs to point to the file on the hdfs i think -->
|
||||
<file>${wfAppPath}/projects_impact.py#projects_impact.py</file>
|
||||
</spark>
|
||||
|
||||
<!-- Do this after finishing okay -->
|
||||
<ok to="createActionSetForProjects" />
|
||||
|
||||
<!-- Go there if we have an error -->
|
||||
<error to="project-impact-indicators-fail" />
|
||||
|
||||
</action>
|
||||
|
||||
<action name="createActionSetForProjects">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Produces the atomic action with the bip finder scores for projects</name>
|
||||
<class>eu.dnetlib.dhp.actionmanager.bipfinder.SparkAtomicActionScoreJob</class>
|
||||
<jar>dhp-aggregation-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-memory=${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}${spark2EventLogDir}
|
||||
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
|
||||
</spark-opts>
|
||||
<arg>--inputPath</arg><arg>${projectImpactIndicatorsOutput}</arg>
|
||||
<arg>--outputPath</arg><arg>${actionSetOutputPath}/projects/</arg>
|
||||
<arg>--targetEntity</arg><arg>project</arg>
|
||||
</spark>
|
||||
<ok to="end"/>
|
||||
<error to="actionset-project-creation-fail"/>
|
||||
</action>
|
||||
|
||||
<!-- TODO: end the workflow-->
|
||||
|
||||
|
|
@ -641,7 +712,14 @@
|
|||
</kill>
|
||||
|
||||
<kill name="actionset-creation-fail">
|
||||
<message>ActionSet creation failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
<message>ActionSet creation for results failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
|
||||
<kill name="project-impact-indicators-fail">
|
||||
<message>Calculating project impact indicators failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
|
||||
<kill name="actionset-project-creation-fail">
|
||||
<message>ActionSet creation for projects failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
</workflow-app>
|
||||
|
|
@ -38,6 +38,7 @@
|
|||
<module>dhp-usage-raw-data-update</module>
|
||||
<module>dhp-broker-events</module>
|
||||
<module>dhp-doiboost</module>
|
||||
<module>dhp-impact-indicators</module>
|
||||
</modules>
|
||||
|
||||
<pluginRepositories>
|
||||
|
|
|
|||
Loading…
Reference in New Issue