Implemented workflow for updating table , added step to check if the new generated table is valid
This commit is contained in:
Sandro La Bruzzo
parent
0386f36385
commit
b32a9d1994
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@ -23,6 +23,7 @@ import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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import org.apache.hadoop.io.SequenceFile;
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import org.apache.hadoop.io.Text;
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import org.apache.spark.sql.SparkSession;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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@ -50,6 +51,9 @@ public class OrcidGetUpdatesFile {
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final String namenode = parser.get("namenode");
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log.info("got variable namenode: {}", namenode);
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final String master = parser.get("master");
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log.info("got variable master: {}", master);
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final String targetPath = parser.get("targetPath");
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log.info("got variable targetPath: {}", targetPath);
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@ -59,11 +63,27 @@ public class OrcidGetUpdatesFile {
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final String accessToken = parser.get("accessToken");
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log.info("got variable accessToken: {}", accessToken);
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System.out.println("namenode = " + namenode);
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final String graphPath = parser.get("graphPath");
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log.info("got variable graphPath: {}", graphPath);
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final SparkSession spark = SparkSession
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.builder()
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.appName(OrcidGetUpdatesFile.class.getName())
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.master(master)
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.getOrCreate();
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final String latestDate = spark
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.read()
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.load(graphPath + "/Authors")
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.selectExpr("max(lastModifiedDate)")
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.first()
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.getString(0);
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log.info("latest date is {}", latestDate);
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final FileSystem fileSystem = FileSystem.get(getHadoopConfiguration(namenode));
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new OrcidGetUpdatesFile().readTar(fileSystem, accessToken, apiURL, targetPath, "2023-09-30");
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new OrcidGetUpdatesFile().readTar(fileSystem, accessToken, apiURL, targetPath, latestDate);
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}
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@ -102,6 +122,8 @@ public class OrcidGetUpdatesFile {
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Path hdfsWritePath = new Path("/tmp/orcid_updates.tar.gz");
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final FSDataOutputStream fsDataOutputStream = fileSystem.create(hdfsWritePath, true);
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IOUtils.copy(input, fsDataOutputStream);
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fsDataOutputStream.flush();
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fsDataOutputStream.close();
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FSDataInputStream updateFile = fileSystem.open(hdfsWritePath);
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TarArchiveInputStream tais = new TarArchiveInputStream(new GzipCompressorInputStream(
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new BufferedInputStream(
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@ -4,6 +4,12 @@
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"paramDescription": "the Name Node URI",
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"paramRequired": true
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},
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{
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"paramName": "m",
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"paramLongName": "master",
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"paramDescription": "the master name",
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"paramRequired": true
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},
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{
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"paramName": "t",
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"paramLongName": "targetPath",
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@ -16,6 +22,12 @@
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"paramDescription": "the URL to download the tar file",
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"paramRequired": true
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},
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{
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"paramName": "g",
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"paramLongName": "graphPath",
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"paramDescription": "the path of the input graph",
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"paramRequired": true
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},
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{
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"paramName": "at",
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"paramLongName": "accessToken",
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@ -28,23 +28,35 @@
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</kill>
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<action name="startUpdate">
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<java>
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<configuration>
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<property>
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<name>oozie.launcher.mapreduce.user.classpath.first</name>
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<value>true</value>
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</property>
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</configuration>
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<main-class>eu.dnetlib.dhp.collection.orcid.OrcidGetUpdatesFile</main-class>
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn</master>
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<mode>cluster</mode>
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<name>Check Latest Orcid and Download updates</name>
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<class>eu.dnetlib.dhp.collection.orcid.OrcidGetUpdatesFile</class>
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<jar>dhp-aggregation-${projectVersion}.jar</jar>
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<spark-opts>
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--executor-memory=${sparkExecutorMemory}
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--executor-cores=${sparkExecutorCores}
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--driver-memory=${sparkDriverMemory}
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--conf spark.executor.memoryOverhead=2g
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--conf spark.sql.shuffle.partitions=3000
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--conf spark.extraListeners=${spark2ExtraListeners}
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--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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</spark-opts>
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<arg>--master</arg><arg>yarn</arg>
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<arg>--namenode</arg><arg>${nameNode}</arg>
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<arg>--graphPath</arg><arg>${graphPath}</arg>
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<arg>--targetPath</arg><arg>${targetPath}</arg>
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<arg>--apiURL</arg><arg>${apiURL}</arg>
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<arg>--accessToken</arg><arg>${accessToken}</arg>
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</java>
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</spark>
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<ok to="generateTables"/>
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<error to="Kill"/>
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</action>
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<action name="generateTables">
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<spark xmlns="uri:oozie:spark-action:0.2">
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<master>yarn</master>
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@ -90,7 +102,7 @@
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--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
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--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
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</spark-opts>
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<arg>--graphPath</arg><arg>graphPath</arg>
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<arg>--graphPath</arg><arg>${graphPath}</arg>
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<arg>--updatePath</arg><arg>${targetPath}/updateTable</arg>
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<arg>--targetPath</arg><arg>${targetPath}/newTable</arg>
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<arg>--master</arg><arg>yarn</arg>
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@ -19,10 +19,34 @@ class SparkApplyUpdate(propertyPath: String, args: Array[String], log: Logger)
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val targetPath: String = parser.get("targetPath")
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log.info("found parameters targetPath: {}", targetPath)
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applyTableUpdate(spark, graphPath, updatePath, targetPath)
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checkUpdate(spark, graphPath, targetPath)
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moveTable(spark, graphPath, targetPath)
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}
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def updateDataset(
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private def moveTable(spark: SparkSession, graphPath: String, updatePath: String): Unit = {
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spark.read
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.load(s"$updatePath/Authors")
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.repartition(1000)
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$graphPath/Authors")
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spark.read
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.load(s"$updatePath/Works")
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.repartition(1000)
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$graphPath/Works")
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spark.read
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.load(s"$updatePath/Employments")
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.repartition(1000)
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.write
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.mode(SaveMode.Overwrite)
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.save(s"$graphPath/Employments")
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}
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private def updateDataset(
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inputDataset: DataFrame,
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idUpdate: DataFrame,
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updateDataframe: DataFrame,
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@ -37,7 +61,28 @@ class SparkApplyUpdate(propertyPath: String, args: Array[String], log: Logger)
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.save(targetPath)
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}
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def applyTableUpdate(spark: SparkSession, graphPath: String, updatePath: String, targetPath: String) = {
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private def checkUpdate(spark: SparkSession, graphPath: String, updatePath: String): Unit = {
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val totalOriginalAuthors = spark.read.load(s"$graphPath/Authors").count
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val totalOriginalWorks = spark.read.load(s"$graphPath/Works").count
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val totalOriginalEmployments = spark.read.load(s"$graphPath/Employments").count
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val totalUpdateAuthors = spark.read.load(s"$updatePath/Authors").count
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val totalUpdateWorks = spark.read.load(s"$updatePath/Works").count
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val totalUpdateEmployments = spark.read.load(s"$updatePath/Employments").count
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log.info("totalOriginalAuthors: {}", totalOriginalAuthors)
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log.info("totalOriginalWorks: {}", totalOriginalWorks)
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log.info("totalOriginalEmployments: {}", totalOriginalEmployments)
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log.info("totalUpdateAuthors: {}", totalUpdateAuthors)
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log.info("totalUpdateWorks: {}", totalUpdateWorks)
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log.info("totalUpdateEmployments: {}", totalUpdateEmployments)
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if (
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totalUpdateAuthors < totalOriginalAuthors || totalUpdateEmployments < totalOriginalEmployments || totalUpdateWorks < totalOriginalWorks
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)
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throw new RuntimeException("The updated Graph contains less elements of the original one")
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}
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private def applyTableUpdate(spark: SparkSession, graphPath: String, updatePath: String, targetPath: String): Unit = {
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val orcidIDUpdate = spark.read.load(s"$updatePath/Authors").select("orcid")
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updateDataset(
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spark.read.load(s"$graphPath/Authors"),
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