[Graph Dump] New funded products dump #222

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claudio.atzori merged 5 commits from dump_new_funded_products into master 2022-07-01 10:51:37 +02:00
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package eu.dnetlib.dhp.oa.graph.dump.projectssubset;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
import java.io.Serializable;
import java.util.Objects;
import java.util.Optional;
import org.apache.commons.io.IOUtils;
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 eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.oa.graph.dump.Utils;
import eu.dnetlib.dhp.schema.dump.oaf.graph.Project;
import scala.Tuple2;
public class ProjectsSubsetSparkJob implements Serializable {
private static final Logger log = LoggerFactory.getLogger(ProjectsSubsetSparkJob.class);
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
ProjectsSubsetSparkJob.class
.getResourceAsStream(
"/eu/dnetlib/dhp/oa/graph/dump/project_subset_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = Optional
.ofNullable(parser.get("isSparkSessionManaged"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
final String inputPath = parser.get("sourcePath");
log.info("inputPath: {}", inputPath);
final String outputPath = parser.get("outputPath");
log.info("outputPath: {}", outputPath);
final String projectListPath = parser.get("projectListPath");
log.info("projectListPath: {}", projectListPath);
SparkConf conf = new SparkConf();
runWithSparkSession(
conf,
isSparkSessionManaged,
spark -> {
Utils.removeOutputDir(spark, outputPath);
getNewProjectList(spark, inputPath, outputPath, projectListPath);
});
}
private static void getNewProjectList(SparkSession spark, String inputPath, String outputPath,
String projectListPath) {
Dataset<String> projectList = spark.read().textFile(projectListPath);
Dataset<Project> projects;
projects = Utils.readPath(spark, inputPath, Project.class);
projects
.joinWith(projectList, projects.col("id").equalTo(projectList.col("value")), "left")
.map((MapFunction<Tuple2<Project, String>, Project>) t2 -> {
if (Optional.ofNullable(t2._2()).isPresent())
return null;
return t2._1();
}, Encoders.bean(Project.class))
.filter(Objects::nonNull)
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.json(outputPath);
Utils
.readPath(spark, outputPath, Project.class)
.map((MapFunction<Project, String>) p -> p.getId(), Encoders.STRING())
.write()
.mode(SaveMode.Append)
.option("compression", "gzip")
.text(projectListPath);
}
}

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[
{
"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
},
{
"paramName": "pl",
"paramLongName": "projectListPath",
"paramDescription": "the path of the association result projectlist",
"paramRequired": true
}
]

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<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>hiveMetastoreUris</name>
<value>thrift://iis-cdh5-test-m3.ocean.icm.edu.pl:9083</value>
</property>
<property>
<name>hiveJdbcUrl</name>
<value>jdbc:hive2://iis-cdh5-test-m3.ocean.icm.edu.pl:10000</value>
</property>
<property>
<name>hiveDbName</name>
<value>openaire</value>
</property>
<property>
<name>oozie.launcher.mapreduce.user.classpath.first</name>
<value>true</value>
</property>
</configuration>

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<workflow-app name="dump_graph" xmlns="uri:oozie:workflow:0.5">
<parameters>
<property>
<name>sourcePath</name>
<description>the source path</description>
</property>
<property>
<name>projectListPath</name>
<description>the path to the project list</description>
</property>
<property>
<name>outputPath</name>
<description>the output path</description>
</property>
<property>
<name>accessToken</name>
<description>the access token used for the deposition in Zenodo</description>
</property>
<property>
<name>connectionUrl</name>
<description>the connection url for Zenodo</description>
</property>
<property>
<name>metadata</name>
<description> the metadata associated to the deposition</description>
</property>
<property>
<name>depositionType</name>
<description>the type of deposition we want to perform. "new" for brand new deposition, "version" for a new version of a published deposition (in this case the concept record id must be provided), "upload" to upload content to an open deposition for which we already have the deposition id (in this case the deposition id should be provided)</description>
</property>
<property>
<name>conceptRecordId</name>
<description>for new version, the id of the record for the old deposition</description>
</property>
<property>
<name>depositionId</name>
<description>the depositionId of a deposition open that has to be added content</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>mapreduce.job.queuename</name>
<value>${queueName}</value>
</property>
<property>
<name>oozie.launcher.mapred.job.queue.name</name>
<value>${oozieLauncherQueueName}</value>
</property>
<property>
<name>oozie.action.sharelib.for.spark</name>
<value>${oozieActionShareLibForSpark2}</value>
</property>
</configuration>
</global>
<start to="dump_project"/>
<kill name="Kill">
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<action name="dump_project">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Dump table project </name>
<class>eu.dnetlib.dhp.oa.graph.dump.complete.SparkDumpEntitiesJob</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}${spark2EventLogDir}
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${sourcePath}/project</arg>
<arg>--resultTableName</arg><arg>eu.dnetlib.dhp.schema.oaf.Project</arg>
<arg>--outputPath</arg><arg>${workingDir}/project</arg>
<arg>--communityMapPath</arg><arg>noneed</arg>
</spark>
<ok to="get_new_projects"/>
<error to="Kill"/>
</action>
<action name="get_new_projects">
<spark xmlns="uri:oozie:spark-action:0.2">
<master>yarn</master>
<mode>cluster</mode>
<name>Dump table project </name>
<class>eu.dnetlib.dhp.oa.graph.dump.projectssubset.ProjectsSubsetSparkJob</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}${spark2EventLogDir}
--conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
</spark-opts>
<arg>--sourcePath</arg><arg>${workingDir}/project</arg>
<arg>--outputPath</arg><arg>${workingDir}/tar/project</arg>
<arg>--projectListPath</arg><arg>${projectListPath}</arg>
</spark>
<ok to="make_archive"/>
<error to="Kill"/>
</action>
<action name="make_archive">
<java>
<main-class>eu.dnetlib.dhp.oa.graph.dump.MakeTar</main-class>
<arg>--hdfsPath</arg><arg>${outputPath}</arg>
<arg>--nameNode</arg><arg>${nameNode}</arg>
<arg>--sourcePath</arg><arg>${workingDir}/tar</arg>
</java>
<ok to="send_zenodo"/>
<error to="Kill"/>
</action>
<action name="send_zenodo">
<java>
<main-class>eu.dnetlib.dhp.oa.graph.dump.SendToZenodoHDFS</main-class>
<arg>--hdfsPath</arg><arg>${outputPath}</arg>
<arg>--nameNode</arg><arg>${nameNode}</arg>
<arg>--accessToken</arg><arg>${accessToken}</arg>
<arg>--connectionUrl</arg><arg>${connectionUrl}</arg>
<arg>--metadata</arg><arg>${metadata}</arg>
<arg>--conceptRecordId</arg><arg>${conceptRecordId}</arg>
<arg>--depositionType</arg><arg>${depositionType}</arg>
<arg>--depositionId</arg><arg>${depositionId}</arg>
</java>
<ok to="End"/>
<error to="Kill"/>
</action>
<end name="End"/>
</workflow-app>

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package eu.dnetlib.dhp.oa.graph.dump.projectssubset;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.HashMap;
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.sql.SaveMode;
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.schema.dump.oaf.graph.Project;
public class ProjectSubsetTest {
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
private static SparkSession spark;
private static Path workingDir;
private static final Logger log = LoggerFactory
.getLogger(eu.dnetlib.dhp.oa.graph.dump.projectssubset.ProjectSubsetTest.class);
@BeforeAll
public static void beforeAll() throws IOException {
workingDir = Files
.createTempDirectory(
eu.dnetlib.dhp.oa.graph.dump.projectssubset.ProjectSubsetTest.class.getSimpleName());
log.info("using work dir {}", workingDir);
SparkConf conf = new SparkConf();
conf.setAppName(eu.dnetlib.dhp.oa.graph.dump.projectssubset.ProjectSubsetTest.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(eu.dnetlib.dhp.oa.graph.dump.projectssubset.ProjectSubsetTest.class.getSimpleName())
.config(conf)
.getOrCreate();
}
@AfterAll
public static void afterAll() throws IOException {
FileUtils.deleteDirectory(workingDir.toFile());
spark.stop();
}
@Test
void testAllNew() throws Exception {
final String projectListPath = getClass()
.getResource("/eu/dnetlib/dhp/oa/graph/dump/projectsubset/projectId")
.getPath();
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/oa/graph/dump/projectsubset/allnew/projects")
.getPath();
spark
.read()
.textFile(projectListPath)
.write()
.mode(SaveMode.Overwrite)
.text(workingDir.toString() + "/projectIds");
ProjectsSubsetSparkJob.main(new String[] {
"-isSparkSessionManaged", Boolean.FALSE.toString(),
"-outputPath", workingDir.toString() + "/projects",
"-sourcePath", sourcePath,
"-projectListPath", workingDir.toString() + "/projectIds"
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<Project> tmp = sc
.textFile(workingDir.toString() + "/projects")
.map(item -> OBJECT_MAPPER.readValue(item, Project.class));
Assertions.assertEquals(12, tmp.count());
Assertions.assertEquals(2, tmp.filter(p -> p.getId().substring(3, 15).equals("aka_________")).count());
Assertions.assertEquals(2, tmp.filter(p -> p.getId().substring(3, 15).equals("anr_________")).count());
Assertions.assertEquals(4, tmp.filter(p -> p.getId().substring(3, 15).equals("arc_________")).count());
Assertions.assertEquals(3, tmp.filter(p -> p.getId().substring(3, 15).equals("conicytf____")).count());
Assertions.assertEquals(1, tmp.filter(p -> p.getId().substring(3, 15).equals("corda_______")).count());
Assertions.assertEquals(40, sc.textFile(workingDir.toString() + "/projectIds").count());
}
@Test
void testMatchOne() throws Exception {
final String projectListPath = getClass()
.getResource("/eu/dnetlib/dhp/oa/graph/dump/projectsubset/projectId")
.getPath();
final String sourcePath = getClass()
.getResource("/eu/dnetlib/dhp/oa/graph/dump/projectsubset/matchOne/projects")
.getPath();
spark
.read()
.textFile(projectListPath)
.write()
.mode(SaveMode.Overwrite)
.text(workingDir.toString() + "/projectIds");
ProjectsSubsetSparkJob.main(new String[] {
"-isSparkSessionManaged", Boolean.FALSE.toString(),
"-outputPath", workingDir.toString() + "/projects",
"-sourcePath", sourcePath,
"-projectListPath", workingDir.toString() + "/projectIds"
});
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
JavaRDD<Project> tmp = sc
.textFile(workingDir.toString() + "/projects")
.map(item -> OBJECT_MAPPER.readValue(item, Project.class));
Assertions.assertEquals(11, tmp.count());
Assertions.assertEquals(2, tmp.filter(p -> p.getId().substring(3, 15).equals("aka_________")).count());
Assertions.assertEquals(2, tmp.filter(p -> p.getId().substring(3, 15).equals("anr_________")).count());
Assertions.assertEquals(4, tmp.filter(p -> p.getId().substring(3, 15).equals("arc_________")).count());
Assertions.assertEquals(3, tmp.filter(p -> p.getId().substring(3, 15).equals("conicytf____")).count());
Assertions.assertEquals(0, tmp.filter(p -> p.getId().substring(3, 15).equals("corda__h2020")).count());
Assertions.assertEquals(39, sc.textFile(workingDir.toString() + "/projectIds").count());
}
}

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{"id":"40|aka_________::01bb7b48e29d732a1c7bc5150b9195c4","websiteurl":null,"code":"135027","acronym":null,"title":"Dynamic 3D resolution-enhanced low-coherence interferometric imaging / Consortium: Hi-Lo","startdate":null,"enddate":null,"callidentifier":"Fotoniikka ja modernit kuvantamismenetelmät LT","keywords":null,"openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"AKA","name":"Academy of Finland","jurisdiction":"FI","funding_stream":null}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|aka_________::9d1af21dbd0f5bc719f71553d19a6b3a","websiteurl":null,"code":"316061","acronym":null,"title":"Finnish Imaging of Degenerative Shoulder Study (FIMAGE): A study on the prevalence of degenerative imaging changes of the shoulder and their relevance to clinical symptoms in the general population.","startdate":null,"enddate":null,"callidentifier":"Academy Project Funding TT","keywords":null,"openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"AKA","name":"Academy of Finland","jurisdiction":"FI","funding_stream":null}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|anr_________::1f21edc5c902be305ee47148955c6e50","websiteurl":null,"code":"ANR-17-CE05-0033","acronym":"MOISE","title":"METAL OXIDES AS LOW LOADED NANO-IRIDIUM SUPPORT FOR COMPETITIVE WATER ELECTROLYSIS","startdate":null,"enddate":null,"callidentifier":null,"keywords":null,"openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"ANR","name":"French National Research Agency (ANR)","jurisdiction":"FR","funding_stream":null}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|anr_________::547e78ffdcb7d72a1ef31058dede3a33","websiteurl":null,"code":"ANR-09-SEGI-0005","acronym":"GALAXY","title":"DEVELOPPEMENT COLLABORATIF DE SYSTEMES COMPLEXES SELON UNE APPROCHE GUIDEE PAR LES MODELES","startdate":null,"enddate":null,"callidentifier":null,"keywords":null,"openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"ANR","name":"French National Research Agency (ANR)","jurisdiction":"FR","funding_stream":null}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|arc_________::838e781a8d479e27a11101421fd8b296","websiteurl":"http://purl.org/au-research/grants/arc/LE0347462","code":"LE0347462","acronym":null,"title":"Femtosecond laser micromachining facility","startdate":"2003-01-01","enddate":"2003-12-31","callidentifier":null,"keywords":"biomedical nanostructures,femtosecond laser machining,laser manufacturing,laser micromachining,microphotonics,photonic bandgap structures","openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"ARC","name":"Australian Research Council (ARC)","jurisdiction":"AU","funding_stream":{"id":"ARC::Linkage Infrastructure, Equipment and Facilities","description":"Linkage Infrastructure, Equipment and Facilities"}}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|arc_________::a461f180f7b6700c0499d4d3d53e58c7","websiteurl":"http://purl.org/au-research/grants/arc/LP140100567","code":"LP140100567","acronym":null,"title":"Linkage Projects - Grant ID: LP140100567","startdate":"2014-01-01","enddate":"2017-12-31","callidentifier":null,"keywords":"EDUCATIONAL MEASUREMENT; EDUCATIONAL MEASUREMENT; HIGH-STAKES TESTING; HIGH-STAKES TESTING; PERFORMANCE ASSESSMENT; PERFORMANCE ASSESSMENT; PERFORMANCE ASSESSMENT","openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"ARC","name":"Australian Research Council (ARC)","jurisdiction":"AU","funding_stream":{"id":"ARC::Linkage Projects","description":"Linkage Projects"}}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|arc_________::b46b9e07d4cea67ccf497520a75ad0c8","websiteurl":"http://purl.org/au-research/grants/arc/DP180101235","code":"DP180101235","acronym":null,"title":"Discovery Projects - Grant ID: DP180101235","startdate":"2018-01-01","enddate":"2023-12-31","callidentifier":null,"keywords":null,"openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"ARC","name":"Australian Research Council (ARC)","jurisdiction":"AU","funding_stream":{"id":"ARC::Discovery Projects","description":"Discovery Projects"}}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|arc_________::c5f86314ce288f91a7f31c219b128fab","websiteurl":"http://purl.org/au-research/grants/arc/LE0989831","code":"LE0989831","acronym":null,"title":"The Australian Music Navigator: research infrastructure for discovering, accessing and analysing Australia's musical landscape","startdate":"2009-01-01","enddate":"2009-12-31","callidentifier":null,"keywords":"database metadata,digital sound,electroacoustic music,film music,music,music information retrieval","openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"ARC","name":"Australian Research Council (ARC)","jurisdiction":"AU","funding_stream":{"id":"ARC::Linkage Infrastructure, Equipment and Facilities","description":"Linkage Infrastructure, Equipment and Facilities"}}],"summary":null,"granted":null,"h2020programme":[]}
{"id":"40|conicytf____::05539f3427ad605d7c1de0168f3e337f","websiteurl":"http://repositorio.conicyt.cl/handle/10533/183109","code":"3120023","acronym":null,"title":"SYNTHESIS AND STRUCTURE-ACTIVITY RELATIONSHIPS OF HETEROARYLISOQUINOLINE- AND PHENANTHRIDINEQUINONES AS ANTITUMOR AGENTS","startdate":"2011-01-01","enddate":"2014-01-28","callidentifier":null,"keywords":null,"openaccessmandateforpublications":false,"openaccessmandatefordataset":false,"subject":[],"funding":[{"shortName":"CONICYT","name":"Comisión Nacional de Investigación Científica y Tecnológica","jurisdiction":"CL","funding_stream":{"id":"CONICYT::FONDECYT::POSTDOCTORADO","description":"Fondecyt fundings - Fondecyt stream, POSTDOCTORADO"}}],"summary":null,"granted":null,"h2020programme":[]}
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