forked from D-Net/dnet-hadoop
imported more diffs from master branch; code formatting
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1eaad89a3c
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d9532446eb
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@ -7,6 +7,10 @@ import eu.dnetlib.dhp.schema.oaf.Qualifier;
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public class ModelConstants {
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public static final String ORCID = "orcid";
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public static final String ORCID_PENDING = "orcid_pending";
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public static final String ORCID_CLASSNAME = "Open Researcher and Contributor ID";
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public static String CROSSREF_ID = "10|openaire____::081b82f96300b6a6e3d282bad31cb6e2";
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public static String DATACITE_ID = "10|openaire____::9e3be59865b2c1c335d32dae2fe7b254";
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@ -9,8 +9,8 @@ import java.util.List;
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*/
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public class BipScore implements Serializable {
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private String id; //doi
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private List<Score> scoreList; //unit as given in the inputfile
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private String id; // doi
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private List<Score> scoreList; // unit as given in the inputfile
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public String getId() {
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return id;
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@ -144,7 +144,6 @@ public class SparkAtomicActionScoreJob implements Serializable {
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}
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private static List<Measure> getMeasure(BipScore value) {
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return value
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.getScoreList()
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@ -10,7 +10,6 @@ import java.util.Objects;
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import java.util.Optional;
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import java.util.stream.Collectors;
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import com.fasterxml.jackson.databind.DeserializationFeature;
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import org.apache.commons.io.IOUtils;
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import org.apache.commons.lang3.StringUtils;
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import org.apache.spark.SparkConf;
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@ -22,6 +21,7 @@ import org.apache.spark.sql.expressions.Aggregator;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import com.fasterxml.jackson.databind.DeserializationFeature;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.jayway.jsonpath.Configuration;
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import com.jayway.jsonpath.DocumentContext;
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@ -44,7 +44,7 @@ public class GroupEntitiesSparkJob {
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private final static String ID_JPATH = "$.id";
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private static ObjectMapper OBJECT_MAPPER = new ObjectMapper()
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.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
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.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
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public static void main(String[] args) throws Exception {
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@ -1,7 +1,7 @@
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package eu.dnetlib.doiboost.orcid
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import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory
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import eu.dnetlib.dhp.schema.oaf.{Author, Publication}
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import eu.dnetlib.dhp.schema.oaf.{Author, DataInfo, Publication}
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import eu.dnetlib.dhp.schema.orcid.OrcidDOI
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import eu.dnetlib.doiboost.DoiBoostMappingUtil
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import eu.dnetlib.doiboost.DoiBoostMappingUtil.{ORCID, PID_TYPES, createSP, generateDataInfo, generateIdentifier}
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import org.apache.commons.lang.StringUtils
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@ -44,23 +44,19 @@ object ORCIDToOAF {
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}
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def convertTOOAF(input:ORCIDElement) :Publication = {
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val doi = input.doi
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def convertTOOAF(input:OrcidDOI) :Publication = {
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val doi = input.getDoi
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val pub:Publication = new Publication
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pub.setPid(List(createSP(doi, "doi", PID_TYPES)).asJava)
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pub.setPid(List(createSP(doi.toLowerCase, "doi", PID_TYPES)).asJava)
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pub.setDataInfo(generateDataInfo())
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//IMPORTANT
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//The old method pub.setId(IdentifierFactory.createIdentifier(pub))
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//will be replaced using IdentifierFactory
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pub.setId(generateIdentifier(pub, doi.toLowerCase))
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pub.setId(IdentifierFactory.createIdentifier(pub))
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try{
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pub.setAuthor(input.authors.map(a=> {
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generateAuthor(a.name, a.surname, a.creditName, a.oid)
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}).asJava)
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val l:List[Author]= input.getAuthors.asScala.map(a=> {
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generateAuthor(a.getName, a.getSurname, a.getCreditName, a.getOid)
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})(collection.breakOut)
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pub.setAuthor(l.asJava)
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pub.setCollectedfrom(List(DoiBoostMappingUtil.createORIDCollectedFrom()).asJava)
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pub.setDataInfo(DoiBoostMappingUtil.generateDataInfo())
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pub
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@ -71,6 +67,13 @@ object ORCIDToOAF {
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}
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}
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def generateOricPIDDatainfo():DataInfo = {
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val di =DoiBoostMappingUtil.generateDataInfo("0.91")
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di.getProvenanceaction.setClassid("sysimport:crosswalk:entityregistry")
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di.getProvenanceaction.setClassname("Harvested")
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di
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}
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def generateAuthor(given: String, family: String, fullName:String, orcid: String): Author = {
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val a = new Author
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a.setName(given)
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@ -80,7 +83,7 @@ object ORCIDToOAF {
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else
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a.setFullname(s"$given $family")
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if (StringUtils.isNotBlank(orcid))
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a.setPid(List(createSP(orcid, ORCID, PID_TYPES)).asJava)
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a.setPid(List(createSP(orcid, ORCID, PID_TYPES, generateOricPIDDatainfo())).asJava)
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a
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}
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@ -45,24 +45,24 @@ object SparkConvertORCIDToOAF {
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Encoders.kryo(classOf[Publication])
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}
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def run(spark:SparkSession,sourcePath:String, targetPath:String):Unit = {
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implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
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implicit val mapOrcid: Encoder[OrcidDOI] = Encoders.kryo[OrcidDOI]
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implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
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def run(spark:SparkSession,sourcePath:String, targetPath:String):Unit = {
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implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
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implicit val mapOrcid: Encoder[OrcidDOI] = Encoders.kryo[OrcidDOI]
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implicit val tupleForJoinEncoder: Encoder[(String, Publication)] = Encoders.tuple(Encoders.STRING, mapEncoderPubs)
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val mapper = new ObjectMapper()
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mapper.getDeserializationConfig.withFeatures(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES)
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val mapper = new ObjectMapper()
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mapper.getDeserializationConfig.withFeatures(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES)
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val dataset:Dataset[OrcidDOI] = spark.createDataset(spark.sparkContext.textFile(sourcePath).map(s => mapper.readValue(s,classOf[OrcidDOI])))
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val dataset:Dataset[OrcidDOI] = spark.createDataset(spark.sparkContext.textFile(sourcePath).map(s => mapper.readValue(s,classOf[OrcidDOI])))
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logger.info("Converting ORCID to OAF")
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dataset.map(o => ORCIDToOAF.convertTOOAF(o)).filter(p=>p!=null)
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.map(d => (d.getId, d))
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.groupByKey(_._1)(Encoders.STRING)
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.agg(getPublicationAggregator().toColumn)
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.map(p => p._2)
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.write.mode(SaveMode.Overwrite).save(targetPath)
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}
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logger.info("Converting ORCID to OAF")
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dataset.map(o => ORCIDToOAF.convertTOOAF(o)).filter(p=>p!=null)
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.map(d => (d.getId, d))
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.groupByKey(_._1)(Encoders.STRING)
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.agg(getPublicationAggregator().toColumn)
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.map(p => p._2)
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.write.mode(SaveMode.Overwrite).save(targetPath)
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}
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def main(args: Array[String]): Unit = {
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@ -10,6 +10,7 @@ import java.text.SimpleDateFormat;
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import java.util.Date;
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import java.util.Optional;
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import javax.swing.text.html.Option;
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import javax.xml.transform.Transformer;
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import javax.xml.transform.TransformerException;
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import javax.xml.transform.stream.StreamResult;
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@ -42,6 +43,10 @@ public class XmlIndexingJob {
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private static final Logger log = LoggerFactory.getLogger(XmlIndexingJob.class);
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public enum OutputFormat {
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SOLR, HDFS
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}
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private static final Integer DEFAULT_BATCH_SIZE = 1000;
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protected static final String DATE_FORMAT = "yyyy-MM-dd'T'hh:mm:ss'Z'";
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@ -52,6 +57,8 @@ public class XmlIndexingJob {
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private int batchSize;
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private OutputFormat outputFormat;
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private String outputPath;
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private SparkSession spark;
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@ -80,14 +87,22 @@ public class XmlIndexingJob {
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final String outputPath = Optional
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.ofNullable(parser.get("outputPath"))
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.map(StringUtils::trim)
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.orElse(null);
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log.info("outputPath: {}", outputPath);
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final Integer batchSize = parser.getObjectMap().containsKey("batchSize")
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? Integer.valueOf(parser.get("batchSize"))
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: DEFAULT_BATCH_SIZE;
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final Integer batchSize = Optional
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.ofNullable(parser.get("batchSize"))
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.map(Integer::valueOf)
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.orElse(DEFAULT_BATCH_SIZE);
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log.info("batchSize: {}", batchSize);
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final OutputFormat outputFormat = Optional
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.ofNullable(parser.get("outputFormat"))
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.map(OutputFormat::valueOf)
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.orElse(OutputFormat.SOLR);
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log.info("outputFormat: {}", outputFormat);
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final SparkConf conf = new SparkConf();
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conf.registerKryoClasses(new Class[] {
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SerializableSolrInputDocument.class
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@ -100,15 +115,18 @@ public class XmlIndexingJob {
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final String isLookupUrl = parser.get("isLookupUrl");
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log.info("isLookupUrl: {}", isLookupUrl);
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final ISLookupClient isLookup = new ISLookupClient(ISLookupClientFactory.getLookUpService(isLookupUrl));
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new XmlIndexingJob(spark, inputPath, format, batchSize, outputPath).run(isLookup);
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new XmlIndexingJob(spark, inputPath, format, batchSize, outputFormat, outputPath).run(isLookup);
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});
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}
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public XmlIndexingJob(SparkSession spark, String inputPath, String format, Integer batchSize, String outputPath) {
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public XmlIndexingJob(SparkSession spark, String inputPath, String format, Integer batchSize,
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OutputFormat outputFormat,
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String outputPath) {
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this.spark = spark;
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this.inputPath = inputPath;
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this.format = format;
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this.batchSize = batchSize;
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this.outputFormat = outputFormat;
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this.outputPath = outputPath;
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}
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@ -137,17 +155,22 @@ public class XmlIndexingJob {
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.map(s -> toIndexRecord(SaxonTransformerFactory.newInstance(indexRecordXslt), s))
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.map(s -> new StreamingInputDocumentFactory(version, dsId).parseDocument(s));
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if (StringUtils.isNotBlank(outputPath)) {
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spark
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.createDataset(
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docs.map(s -> new SerializableSolrInputDocument(s)).rdd(),
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Encoders.kryo(SerializableSolrInputDocument.class))
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.write()
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.mode(SaveMode.Overwrite)
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.parquet(outputPath);
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} else {
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final String collection = ProvisionConstants.getCollectionName(format);
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SolrSupport.indexDocs(zkHost, collection, batchSize, docs.rdd());
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switch (outputFormat) {
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case SOLR:
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final String collection = ProvisionConstants.getCollectionName(format);
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SolrSupport.indexDocs(zkHost, collection, batchSize, docs.rdd());
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break;
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case HDFS:
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spark
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.createDataset(
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docs.map(s -> new SerializableSolrInputDocument(s)).rdd(),
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Encoders.kryo(SerializableSolrInputDocument.class))
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.write()
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.mode(SaveMode.Overwrite)
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.parquet(outputPath);
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break;
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default:
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throw new IllegalArgumentException("invalid outputFormat: " + outputFormat);
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}
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}
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