cleanup and refinements

Reviewed-on: D-Net/dnet-hadoop#333

.gitignore

@@ -26,4 +26,3 @@ spark-warehouse
 /**/*.log
 /**/.factorypath
 /**/.scalafmt.conf
-/.java-version

README.md

@@ -1,128 +1,2 @@
 # dnet-hadoop
-
+Dnet-hadoop is the project that defined all the OOZIE workflows for the OpenAIRE Graph construction, processing, provisioning.
-Dnet-hadoop is the project that defined all the [OOZIE workflows](https://oozie.apache.org/) for the OpenAIRE Graph construction, processing, provisioning.
-
-How to build, package and run oozie workflows
-====================
-
-Oozie-installer is a utility allowing building, uploading and running oozie workflows. In practice, it creates a `*.tar.gz` 
-package that contains resources that define a workflow and some helper scripts.
-
-This module is automatically executed when running:
-
-`mvn package -Poozie-package -Dworkflow.source.dir=classpath/to/parent/directory/of/oozie_app`
-
-on module having set:
-
-```
-<parent>
-    <groupId>eu.dnetlib.dhp</groupId>
-    <artifactId>dhp-workflows</artifactId>
-</parent>
-```
-
-in `pom.xml` file. `oozie-package` profile initializes oozie workflow packaging, `workflow.source.dir` property points to 
-a workflow (notice: this is not a relative path but a classpath to directory usually holding `oozie_app` subdirectory).
-
-The outcome of this packaging is `oozie-package.tar.gz` file containing inside all the resources required to run Oozie workflow:
-
-- jar packages
-- workflow definitions
-- job properties
-- maintenance scripts
-
-Required properties
-====================
-
-In order to include proper workflow within package, `workflow.source.dir` property has to be set. It could be provided 
-by setting `-Dworkflow.source.dir=some/job/dir` maven parameter.
-
-In oder to define full set of cluster environment properties one should create `~/.dhp/application.properties` file with 
-the following properties:
-
-- `dhp.hadoop.frontend.user.name` - your user name on hadoop cluster and frontend machine
-- `dhp.hadoop.frontend.host.name` - frontend host name
-- `dhp.hadoop.frontend.temp.dir` - frontend directory for temporary files
-- `dhp.hadoop.frontend.port.ssh` - frontend machine ssh port
-- `oozieServiceLoc` - oozie service location required by run_workflow.sh script executing oozie job
-- `nameNode` - name node address
-- `jobTracker` - job tracker address
-- `oozie.execution.log.file.location` - location of file that will be created when executing oozie job, it contains output 
-produced by `run_workflow.sh` script (needed to obtain oozie job id)
-- `maven.executable` - mvn command location, requires parameterization due to a different setup of CI cluster
-- `sparkDriverMemory` - amount of memory assigned to spark jobs driver
-- `sparkExecutorMemory` - amount of memory assigned to spark jobs executors
-- `sparkExecutorCores` - number of cores assigned to spark jobs executors
-
-All values will be overriden with the ones from `job.properties` and eventually `job-override.properties` stored in module's 
-main folder.
-
-When overriding properties from `job.properties`, `job-override.properties` file can be created in main module directory 
-(the one containing `pom.xml` file) and define all new properties which will override existing properties. 
-One can provide those properties one by one as command line `-D` arguments.
-
-Properties overriding order is the following:
-
-1. `pom.xml` defined properties (located in the project root dir)
-2. `~/.dhp/application.properties` defined properties
-3. `${workflow.source.dir}/job.properties`
-4. `job-override.properties` (located in the project root dir)
-5. `maven -Dparam=value`
-
-where the maven `-Dparam` property is overriding all the other ones.
-
-Workflow definition requirements
-====================
-
-`workflow.source.dir` property should point to the following directory structure:
-
-	[${workflow.source.dir}]
-		|
-		|-job.properties (optional)
-		|
-		\-[oozie_app]
-			|
-			\-workflow.xml
-
-This property can be set using maven `-D` switch.
-
-`[oozie_app]` is the default directory name however it can be set to any value as soon as `oozieAppDir` property is 
-provided with directory name as value.
-
-Sub-workflows are supported as well and sub-workflow directories should be nested within `[oozie_app]` directory.
-
-Creating oozie installer step-by-step
-=====================================
-
-Automated oozie-installer steps are the following:
-
-1. creating jar packages:  `*.jar` and `*tests.jar` along with copying all dependencies in `target/dependencies`
-2. reading properties from maven, `~/.dhp/application.properties`, `job.properties`, `job-override.properties`
-3. invoking priming mechanism linking resources from import.txt file (currently resolving subworkflow resources)
-4. assembling shell scripts for preparing Hadoop filesystem, uploading Oozie application and starting workflow
-5. copying whole `${workflow.source.dir}` content to `target/${oozie.package.file.name}`
-6. generating updated `job.properties` file in `target/${oozie.package.file.name}` based on maven, 
-`~/.dhp/application.properties`, `job.properties` and `job-override.properties`
-7. creating `lib` directory (or multiple directories for sub-workflows for each nested directory) and copying jar packages 
-created at step (1) to each one of them
-8. bundling whole `${oozie.package.file.name}` directory into single tar.gz package
-
-Uploading oozie package and running workflow on cluster
-=======================================================
-
-In order to simplify deployment and execution process two dedicated profiles were introduced:
-
-- `deploy`
-- `run`
-
-to be used along with `oozie-package` profile e.g. by providing `-Poozie-package,deploy,run` maven parameters.
-
-The `deploy` profile supplements packaging process with:
-1) uploading oozie-package via scp to `/home/${user.name}/oozie-packages` directory on `${dhp.hadoop.frontend.host.name}` machine
-2) extracting uploaded package
-3) uploading oozie content to hadoop cluster HDFS location defined in `oozie.wf.application.path` property (generated dynamically by maven build process, based on `${dhp.hadoop.frontend.user.name}` and `workflow.source.dir` properties)
-
-The `run` profile introduces:
-1) executing oozie application uploaded to HDFS cluster using `deploy` command. Triggers `run_workflow.sh` script providing runtime properties defined in `job.properties` file.
-
-Notice: ssh access to frontend machine has to be configured on system level and it is preferable to set key-based authentication in order to simplify remote operations.

dhp-common/src/main/java/eu/dnetlib/dhp/oa/merge/DispatchEntitiesSparkJob.java

@@ -1,97 +0,0 @@
-
-package eu.dnetlib.dhp.oa.merge;
-
-import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
-
-import java.util.Objects;
-import java.util.Optional;
-
-import org.apache.commons.io.IOUtils;
-import org.apache.commons.lang3.StringUtils;
-import org.apache.spark.SparkConf;
-import org.apache.spark.api.java.function.FilterFunction;
-import org.apache.spark.api.java.function.MapFunction;
-import org.apache.spark.sql.*;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-
-import eu.dnetlib.dhp.application.ArgumentApplicationParser;
-import eu.dnetlib.dhp.common.HdfsSupport;
-import eu.dnetlib.dhp.schema.common.ModelSupport;
-
-public class DispatchEntitiesSparkJob {
-
-	private static final Logger log = LoggerFactory.getLogger(DispatchEntitiesSparkJob.class);
-
-	public static void main(String[] args) throws Exception {
-
-		String jsonConfiguration = IOUtils
-			.toString(
-				Objects
-					.requireNonNull(
-						DispatchEntitiesSparkJob.class
-							.getResourceAsStream(
-								"/eu/dnetlib/dhp/oa/merge/dispatch_entities_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);
-
-		String inputPath = parser.get("inputPath");
-		log.info("inputPath: {}", inputPath);
-
-		String outputPath = parser.get("outputPath");
-		log.info("outputPath: {}", outputPath);
-
-		boolean filterInvisible = Boolean.parseBoolean(parser.get("filterInvisible"));
-		log.info("filterInvisible: {}", filterInvisible);
-
-		SparkConf conf = new SparkConf();
-		runWithSparkSession(
-			conf,
-			isSparkSessionManaged,
-			spark -> dispatchEntities(spark, inputPath, outputPath, filterInvisible));
-	}
-
-	private static void dispatchEntities(
-		SparkSession spark,
-		String inputPath,
-		String outputPath,
-		boolean filterInvisible) {
-
-		Dataset<String> df = spark.read().textFile(inputPath);
-
-		ModelSupport.oafTypes.entrySet().parallelStream().forEach(entry -> {
-			String entityType = entry.getKey();
-			Class<?> clazz = entry.getValue();
-
-			final String entityPath = outputPath + "/" + entityType;
-			if (!entityType.equalsIgnoreCase("relation")) {
-				HdfsSupport.remove(entityPath, spark.sparkContext().hadoopConfiguration());
-				Dataset<Row> entityDF = spark
-					.read()
-					.schema(Encoders.bean(clazz).schema())
-					.json(
-						df
-							.filter((FilterFunction<String>) s -> s.startsWith(clazz.getName()))
-							.map(
-								(MapFunction<String, String>) s -> StringUtils.substringAfter(s, "|"),
-								Encoders.STRING()));
-
-				if (filterInvisible) {
-					entityDF = entityDF.filter("dataInfo.invisible != true");
-				}
-
-				entityDF
-					.write()
-					.mode(SaveMode.Overwrite)
-					.option("compression", "gzip")
-					.json(entityPath);
-			}
-		});
-	}
-}

dhp-common/src/main/java/eu/dnetlib/dhp/oa/merge/GroupEntitiesSparkJob.java

@@ -2,36 +2,28 @@
 package eu.dnetlib.dhp.oa.merge;
 
 import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
-import static eu.dnetlib.dhp.utils.DHPUtils.toSeq;
+import static org.apache.spark.sql.functions.col;
+import static org.apache.spark.sql.functions.when;
 
-import java.io.IOException;
+import java.util.Map;
-import java.util.List;
-import java.util.Objects;
 import java.util.Optional;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.ForkJoinPool;
 import java.util.stream.Collectors;
 
 import org.apache.commons.io.IOUtils;
-import org.apache.commons.lang3.StringUtils;
 import org.apache.spark.SparkConf;
-import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.api.java.function.FilterFunction;
 import org.apache.spark.api.java.function.MapFunction;
+import org.apache.spark.api.java.function.ReduceFunction;
 import org.apache.spark.sql.*;
-import org.apache.spark.sql.expressions.Aggregator;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import com.fasterxml.jackson.databind.DeserializationFeature;
-import com.fasterxml.jackson.databind.ObjectMapper;
-import com.jayway.jsonpath.Configuration;
-import com.jayway.jsonpath.DocumentContext;
-import com.jayway.jsonpath.JsonPath;
-import com.jayway.jsonpath.Option;
-
 import eu.dnetlib.dhp.application.ArgumentApplicationParser;
 import eu.dnetlib.dhp.common.HdfsSupport;
+import eu.dnetlib.dhp.schema.common.EntityType;
 import eu.dnetlib.dhp.schema.common.ModelSupport;
-import eu.dnetlib.dhp.schema.oaf.*;
+import eu.dnetlib.dhp.schema.oaf.OafEntity;
 import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
 import scala.Tuple2;
 
@@ -39,13 +31,9 @@ import scala.Tuple2;
  * Groups the graph content by entity identifier to ensure ID uniqueness
  */
 public class GroupEntitiesSparkJob {
-
 	private static final Logger log = LoggerFactory.getLogger(GroupEntitiesSparkJob.class);
 
-	private static final String ID_JPATH = "$.id";
+	private static final Encoder<OafEntity> OAFENTITY_KRYO_ENC =  Encoders.kryo(OafEntity.class);
-
-	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper()
-		.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
 
 	public static void main(String[] args) throws Exception {
 
@@ -66,9 +54,15 @@ public class GroupEntitiesSparkJob {
 		String graphInputPath = parser.get("graphInputPath");
 		log.info("graphInputPath: {}", graphInputPath);
 
+		String checkpointPath = parser.get("checkpointPath");
+		log.info("checkpointPath: {}", checkpointPath);
+
 		String outputPath = parser.get("outputPath");
 		log.info("outputPath: {}", outputPath);
 
+		boolean filterInvisible = Boolean.valueOf(parser.get("filterInvisible"));
+		log.info("filterInvisible: {}", filterInvisible);
+
 		SparkConf conf = new SparkConf();
 		conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
 		conf.registerKryoClasses(ModelSupport.getOafModelClasses());
@@ -78,126 +72,95 @@ public class GroupEntitiesSparkJob {
 			isSparkSessionManaged,
 			spark -> {
 				HdfsSupport.remove(outputPath, spark.sparkContext().hadoopConfiguration());
-				groupEntities(spark, graphInputPath, outputPath);
+				groupEntities(spark, graphInputPath, checkpointPath, outputPath, filterInvisible);
 			});
 	}
 
 	private static void groupEntities(
 		SparkSession spark,
 		String inputPath,
-		String outputPath) {
+		String checkpointPath,
+		String outputPath,
+		boolean filterInvisible) {
 
-		final TypedColumn<OafEntity, OafEntity> aggregator = new GroupingAggregator().toColumn();
+		Dataset<OafEntity> allEntities = spark.emptyDataset(OAFENTITY_KRYO_ENC);
-		final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+
-		spark
+		for (Map.Entry<EntityType, Class> e : ModelSupport.entityTypes.entrySet()) {
-			.read()
+			String entity = e.getKey().name();
-			.textFile(toSeq(listEntityPaths(inputPath, sc)))
+			Class<? extends OafEntity> entityClass = e.getValue();
-			.map((MapFunction<String, OafEntity>) GroupEntitiesSparkJob::parseOaf, Encoders.kryo(OafEntity.class))
+			String entityInputPath = inputPath + "/" + entity;
-			.filter((FilterFunction<OafEntity>) e -> StringUtils.isNotBlank(ModelSupport.idFn().apply(e)))
+
-			.groupByKey((MapFunction<OafEntity, String>) oaf -> ModelSupport.idFn().apply(oaf), Encoders.STRING())
+			if (!HdfsSupport.exists(entityInputPath, spark.sparkContext().hadoopConfiguration())) {
-			.agg(aggregator)
+				continue;
+			}
+
+			allEntities = allEntities
+				.union(
+					((Dataset<OafEntity>) spark
+						.read()
+						.schema(Encoders.bean(entityClass).schema())
+						.json(entityInputPath)
+						.filter("length(id) > 0")
+						.as(Encoders.bean(entityClass)))
+							.map((MapFunction<OafEntity, OafEntity>) r -> r, OAFENTITY_KRYO_ENC));
+		}
+
+		Dataset<?> groupedEntities = allEntities
+			.groupByKey((MapFunction<OafEntity, String>) OafEntity::getId, Encoders.STRING())
+			.reduceGroups((ReduceFunction<OafEntity>) (b, a) -> OafMapperUtils.mergeEntities(b, a))
 			.map(
-				(MapFunction<Tuple2<String, OafEntity>, String>) t -> t._2().getClass().getName() +
+				(MapFunction<Tuple2<String, OafEntity>, Tuple2<String, OafEntity>>) t -> new Tuple2(
-					"|" + OBJECT_MAPPER.writeValueAsString(t._2()),
+					t._2().getClass().getName(), t._2()),
-				Encoders.STRING())
+				Encoders.tuple(Encoders.STRING(), OAFENTITY_KRYO_ENC));
+
+		// pivot on "_1" (classname of the entity)
+		// created columns  containing only entities of the same class
+		for (Map.Entry<EntityType, Class> e : ModelSupport.entityTypes.entrySet()) {
+			String entity = e.getKey().name();
+			Class<? extends OafEntity> entityClass = e.getValue();
+
+			groupedEntities = groupedEntities
+				.withColumn(
+					entity,
+					when(col("_1").equalTo(entityClass.getName()), col("_2")));
+		}
+
+		groupedEntities
+			.drop("_1", "_2")
 			.write()
-			.option("compression", "gzip")
 			.mode(SaveMode.Overwrite)
-			.text(outputPath);
+			.option("compression", "gzip")
-	}
+			.save(checkpointPath);
 
-	public static class GroupingAggregator extends Aggregator<OafEntity, OafEntity, OafEntity> {
+		ForkJoinPool parPool = new ForkJoinPool(ModelSupport.entityTypes.size());
 
-		@Override
+		ModelSupport.entityTypes
-		public OafEntity zero() {
+			.entrySet()
-			return null;
-		}
-
-		@Override
-		public OafEntity reduce(OafEntity b, OafEntity a) {
-			return mergeAndGet(b, a);
-		}
-
-		private OafEntity mergeAndGet(OafEntity b, OafEntity a) {
-			if (Objects.nonNull(a) && Objects.nonNull(b)) {
-				return OafMapperUtils.mergeEntities(b, a);
-			}
-			return Objects.isNull(a) ? b : a;
-		}
-
-		@Override
-		public OafEntity merge(OafEntity b, OafEntity a) {
-			return mergeAndGet(b, a);
-		}
-
-		@Override
-		public OafEntity finish(OafEntity j) {
-			return j;
-		}
-
-		@Override
-		public Encoder<OafEntity> bufferEncoder() {
-			return Encoders.kryo(OafEntity.class);
-		}
-
-		@Override
-		public Encoder<OafEntity> outputEncoder() {
-			return Encoders.kryo(OafEntity.class);
-		}
-
-	}
-
-	private static OafEntity parseOaf(String s) {
-
-		DocumentContext dc = JsonPath
-			.parse(s, Configuration.defaultConfiguration().addOptions(Option.SUPPRESS_EXCEPTIONS));
-		final String id = dc.read(ID_JPATH);
-		if (StringUtils.isNotBlank(id)) {
-
-			String prefix = StringUtils.substringBefore(id, "|");
-			switch (prefix) {
-				case "10":
-					return parse(s, Datasource.class);
-				case "20":
-					return parse(s, Organization.class);
-				case "40":
-					return parse(s, Project.class);
-				case "50":
-					String resultType = dc.read("$.resulttype.classid");
-					switch (resultType) {
-						case "publication":
-							return parse(s, Publication.class);
-						case "dataset":
-							return parse(s, eu.dnetlib.dhp.schema.oaf.Dataset.class);
-						case "software":
-							return parse(s, Software.class);
-						case "other":
-							return parse(s, OtherResearchProduct.class);
-						default:
-							throw new IllegalArgumentException(String.format("invalid resultType: '%s'", resultType));
-					}
-				default:
-					throw new IllegalArgumentException(String.format("invalid id prefix: '%s'", prefix));
-			}
-		} else {
-			throw new IllegalArgumentException(String.format("invalid oaf: '%s'", s));
-		}
-	}
-
-	private static <T extends OafEntity> OafEntity parse(String s, Class<T> clazz) {
-		try {
-			return OBJECT_MAPPER.readValue(s, clazz);
-		} catch (IOException e) {
-			throw new IllegalArgumentException(e);
-		}
-	}
-
-	private static List<String> listEntityPaths(String inputPath, JavaSparkContext sc) {
-		return HdfsSupport
-			.listFiles(inputPath, sc.hadoopConfiguration())
 			.stream()
-			.filter(f -> !f.toLowerCase().contains("relation"))
+			.map(e -> parPool.submit(() -> {
-			.collect(Collectors.toList());
+				String entity = e.getKey().name();
-	}
+				Class<? extends OafEntity> entityClass = e.getValue();
 
+				spark
+					.read()
+					.load(checkpointPath)
+					.select(col(entity).as("value"))
+					.filter("value IS NOT NULL")
+					.as(OAFENTITY_KRYO_ENC)
+					.map((MapFunction<OafEntity, OafEntity>) r -> r, (Encoder<OafEntity>) Encoders.bean(entityClass))
+					.filter(filterInvisible ? "dataInfo.invisible != TRUE" : "TRUE")
+					.write()
+					.mode(SaveMode.Overwrite)
+					.option("compression", "gzip")
+					.json(outputPath + "/" + entity);
+			}))
+			.collect(Collectors.toList())
+			.forEach(t -> {
+				try {
+					t.get();
+				} catch (InterruptedException | ExecutionException e) {
+					throw new RuntimeException(e);
+				}
+			});
+	}
 }

dhp-common/src/main/java/eu/dnetlib/dhp/schema/oaf/utils/PmidCleaningRule.java

@@ -7,7 +7,7 @@ import java.util.regex.Pattern;
 // https://researchguides.stevens.edu/c.php?g=442331&p=6577176
 public class PmidCleaningRule {
 
-	public static final Pattern PATTERN = Pattern.compile("0*(\\d{1,8})");
+	public static final Pattern PATTERN = Pattern.compile("[1-9]{1,8}");
 
 	public static String clean(String pmid) {
 		String s = pmid
@@ -17,7 +17,7 @@ public class PmidCleaningRule {
 		final Matcher m = PATTERN.matcher(s);
 
 		if (m.find()) {
-			return m.group(1);
+			return m.group();
 		}
 		return "";
 	}

dhp-common/src/main/resources/eu/dnetlib/dhp/oa/merge/dispatch_entities_parameters.json

@@ -1,26 +0,0 @@
-[
-  {
-    "paramName": "issm",
-    "paramLongName": "isSparkSessionManaged",
-    "paramDescription": "when true will stop SparkSession after job execution",
-    "paramRequired": false
-  },
-  {
-    "paramName": "i",
-    "paramLongName": "inputPath",
-    "paramDescription": "the source path",
-    "paramRequired": true
-  },
-  {
-    "paramName": "o",
-    "paramLongName": "outputPath",
-    "paramDescription": "path of the output graph",
-    "paramRequired": true
-  },
-  {
-    "paramName": "fi",
-    "paramLongName": "filterInvisible",
-    "paramDescription": "if true filters out invisible entities",
-    "paramRequired": true
-  }
-]

dhp-common/src/main/resources/eu/dnetlib/dhp/oa/merge/group_graph_entities_parameters.json

@@ -8,13 +8,25 @@
   {
     "paramName": "gin",
     "paramLongName": "graphInputPath",
-    "paramDescription": "the graph root path",
+    "paramDescription": "the input graph root path",
+    "paramRequired": true
+  },
+  {
+    "paramName": "cp",
+    "paramLongName": "checkpointPath",
+    "paramDescription": "checkpoint directory",
     "paramRequired": true
   },
   {
     "paramName": "out",
     "paramLongName": "outputPath",
-    "paramDescription": "the output merged graph root path",
+    "paramDescription": "the output graph root path",
+    "paramRequired": true
+  },
+  {
+    "paramName": "fi",
+    "paramLongName": "filterInvisible",
+    "paramDescription": "if true filters out invisible entities",
     "paramRequired": true
   }
 ]

dhp-common/src/test/java/eu/dnetlib/dhp/schema/oaf/utils/PmidCleaningRuleTest.java

@@ -9,16 +9,10 @@ class PmidCleaningRuleTest {
 
 	@Test
 	void testCleaning() {
-		// leading zeros are removed
 		assertEquals("1234", PmidCleaningRule.clean("01234"));
-		// tolerant to spaces in the middle
 		assertEquals("1234567", PmidCleaningRule.clean("0123 4567"));
-		// stop parsing at first not numerical char
 		assertEquals("123", PmidCleaningRule.clean("0123x4567"));
-		// invalid id leading to empty result
 		assertEquals("", PmidCleaningRule.clean("abc"));
-		// valid id with zeroes in the number
-		assertEquals("20794075", PmidCleaningRule.clean("20794075"));
 	}
 
 }

dhp-pace-core/src/main/java/eu/dnetlib/pace/util/DiffPatchMatch.java

@@ -18,7 +18,6 @@ package eu.dnetlib.pace.util;
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-
 /*
  * Diff Match and Patch
  * Copyright 2018 The diff-match-patch Authors.

dhp-workflows/dhp-actionmanager/README.md

@@ -1,72 +0,0 @@
-# Action Management Framework
-
-This module implements the oozie workflow for the integration of pre-built contents into the OpenAIRE Graph.
-
-Such contents can be 
-
-* brand new, non-existing records to be introduced as nodes of the graph
-* updates (or enrichment) for records that does exist in the graph (e.g. a new subject term for a publication)
-* relations among existing nodes
-
-The actionset contents are organised into logical containers, each of them can contain multiple versions contents and is characterised by
-
-* a name
-* an identifier
-* the paths on HDFS where each version of the contents is stored
-
-Each version is then characterised by 
-
-* the creation date
-* the last update date
-* the indication where it is the latest one or it is an expired version, candidate for garbage collection
-
-## ActionSet serialization
-
-Each actionset version contains records compliant to the graph internal data model, i.e. subclasses of `eu.dnetlib.dhp.schema.oaf.Oaf`,
-defined in the external schemas module
-
-```
-<dependency>
-    <groupId>eu.dnetlib.dhp</groupId>
-    <artifactId>${dhp-schemas.artifact}</artifactId>
-    <version>${dhp-schemas.version}</version>
-</dependency>
-```
-
-When the actionset contains a relationship, the model class to use is `eu.dnetlib.dhp.schema.oaf.Relation`, otherwise 
-when the actionset contains an entity, it is a `eu.dnetlib.dhp.schema.oaf.OafEntity` or one of its subclasses 
-`Datasource`, `Organization`, `Project`, `Result` (or one of its subclasses `Publication`, `Dataset`, etc...). 
-
-Then, each OpenAIRE Graph model class instance must be wrapped using the class `eu.dnetlib.dhp.schema.action.AtomicAction`, a generic 
-container that defines two attributes
-
-* `T payload` the OpenAIRE Graph class instance containing the data;
-* `Class<T> clazz` must contain the class whose instance is contained in the payload.
-
-Each AtomicAction can be then serialised in JSON format using `com.fasterxml.jackson.databind.ObjectMapper` from
-
-```
-<dependency>
-    <groupId>com.fasterxml.jackson.core</groupId>
-    <artifactId>jackson-databind</artifactId>
-    <version>${dhp.jackson.version}</version>
-</dependency>
-```
-
-Then, the JSON serialization must be stored as a GZip compressed sequence file (`org.apache.hadoop.mapred.SequenceFileOutputFormat`). 
-As such, it contains a set of tuples, a key and a value defined as `org.apache.hadoop.io.Text` where
-
-* the `key` must be set to the class canonical name contained in the `AtomicAction`;
-* the `value` must be set to the AtomicAction JSON serialization.
-
-The following snippet provides an example of how create an actionset version of Relation records:
-
-```
-  rels // JavaRDD<Relation>
-    .map(relation -> new AtomicAction<Relation>(Relation.class, relation))
-    .mapToPair(
-        aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
-            new Text(OBJECT_MAPPER.writeValueAsString(aa))))
-    .saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class, GzipCodec.class);
-```
-

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/opencitations/CreateActionSetSparkJob.java

@@ -12,6 +12,7 @@ import org.apache.commons.io.IOUtils;
 import org.apache.hadoop.io.Text;
 import org.apache.hadoop.mapred.SequenceFileOutputFormat;
 import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaPairRDD;
 import org.apache.spark.api.java.function.FilterFunction;
 import org.apache.spark.api.java.function.FlatMapFunction;
 import org.apache.spark.api.java.function.MapFunction;
@@ -30,15 +31,29 @@ import eu.dnetlib.dhp.schema.common.ModelSupport;
 import eu.dnetlib.dhp.schema.oaf.*;
 import eu.dnetlib.dhp.schema.oaf.utils.CleaningFunctions;
 import eu.dnetlib.dhp.schema.oaf.utils.IdentifierFactory;
+import eu.dnetlib.dhp.schema.oaf.utils.OafMapperUtils;
+import eu.dnetlib.dhp.schema.oaf.utils.PidType;
+import eu.dnetlib.dhp.utils.DHPUtils;
 import scala.Tuple2;
 
 public class CreateActionSetSparkJob implements Serializable {
 	public static final String OPENCITATIONS_CLASSID = "sysimport:crosswalk:opencitations";
 	public static final String OPENCITATIONS_CLASSNAME = "Imported from OpenCitations";
-	private static final String ID_PREFIX = "50|doi_________::";
+
+	// DOI-to-DOI citations
+	public static final String COCI = "COCI";
+
+	// PMID-to-PMID citations
+	public static final String POCI = "POCI";
+
+	private static final String DOI_PREFIX = "50|doi_________::";
+
+	private static final String PMID_PREFIX = "50|pmid________::";
+
 	private static final String TRUST = "0.91";
 
 	private static final Logger log = LoggerFactory.getLogger(CreateActionSetSparkJob.class);
+
 	private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
 
 	public static void main(final String[] args) throws IOException, ParseException {
@@ -62,7 +77,7 @@ public class CreateActionSetSparkJob implements Serializable {
 		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
 
 		final String inputPath = parser.get("inputPath");
-		log.info("inputPath {}", inputPath.toString());
+		log.info("inputPath {}", inputPath);
 
 		final String outputPath = parser.get("outputPath");
 		log.info("outputPath {}", outputPath);
@@ -76,41 +91,68 @@ public class CreateActionSetSparkJob implements Serializable {
 		runWithSparkSession(
 			conf,
 			isSparkSessionManaged,
-			spark -> {
+			spark -> extractContent(spark, inputPath, outputPath, shouldDuplicateRels));
-				extractContent(spark, inputPath, outputPath, shouldDuplicateRels);
-			});
 
 	}
 
 	private static void extractContent(SparkSession spark, String inputPath, String outputPath,
 		boolean shouldDuplicateRels) {
-		spark
+
+		getTextTextJavaPairRDD(spark, inputPath, shouldDuplicateRels, COCI)
+			.union(getTextTextJavaPairRDD(spark, inputPath, shouldDuplicateRels, POCI))
+			.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class);
+	}
+
+	private static JavaPairRDD<Text, Text> getTextTextJavaPairRDD(SparkSession spark, String inputPath,
+		boolean shouldDuplicateRels, String prefix) {
+		return spark
 			.read()
-			.textFile(inputPath + "/*")
+			.textFile(inputPath + "/" + prefix + "/" + prefix + "_JSON/*")
 			.map(
 				(MapFunction<String, COCI>) value -> OBJECT_MAPPER.readValue(value, COCI.class),
 				Encoders.bean(COCI.class))
 			.flatMap(
-				(FlatMapFunction<COCI, Relation>) value -> createRelation(value, shouldDuplicateRels).iterator(),
+				(FlatMapFunction<COCI, Relation>) value -> createRelation(
+					value, shouldDuplicateRels, prefix)
+						.iterator(),
 				Encoders.bean(Relation.class))
-			.filter((FilterFunction<Relation>) value -> value != null)
+			.filter((FilterFunction<Relation>) Objects::nonNull)
 			.toJavaRDD()
 			.map(p -> new AtomicAction(p.getClass(), p))
 			.mapToPair(
 				aa -> new Tuple2<>(new Text(aa.getClazz().getCanonicalName()),
-					new Text(OBJECT_MAPPER.writeValueAsString(aa))))
+					new Text(OBJECT_MAPPER.writeValueAsString(aa))));
-			.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class);
-
 	}
 
-	private static List<Relation> createRelation(COCI value, boolean duplicate) {
+	private static List<Relation> createRelation(COCI value, boolean duplicate, String p) {
 
 		List<Relation> relationList = new ArrayList<>();
+		String prefix;
+		String citing;
+		String cited;
 
-		String citing = ID_PREFIX
+		switch (p) {
-			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", value.getCiting()));
+			case COCI:
-		final String cited = ID_PREFIX
+				prefix = DOI_PREFIX;
-			+ IdentifierFactory.md5(CleaningFunctions.normalizePidValue("doi", value.getCited()));
+				citing = prefix
+					+ IdentifierFactory
+						.md5(CleaningFunctions.normalizePidValue(PidType.doi.toString(), value.getCiting()));
+				cited = prefix
+					+ IdentifierFactory
+						.md5(CleaningFunctions.normalizePidValue(PidType.doi.toString(), value.getCited()));
+				break;
+			case POCI:
+				prefix = PMID_PREFIX;
+				citing = prefix
+					+ IdentifierFactory
+						.md5(CleaningFunctions.normalizePidValue(PidType.pmid.toString(), value.getCiting()));
+				cited = prefix
+					+ IdentifierFactory
+						.md5(CleaningFunctions.normalizePidValue(PidType.pmid.toString(), value.getCited()));
+				break;
+			default:
+				throw new IllegalStateException("Invalid prefix: " + p);
+		}
 
 		if (!citing.equals(cited)) {
 			relationList
@@ -120,7 +162,7 @@ public class CreateActionSetSparkJob implements Serializable {
 						cited, ModelConstants.CITES));
 
 			if (duplicate && value.getCiting().endsWith(".refs")) {
-				citing = ID_PREFIX + IdentifierFactory
+				citing = prefix + IdentifierFactory
 					.md5(
 						CleaningFunctions
 							.normalizePidValue(
@@ -132,59 +174,30 @@ public class CreateActionSetSparkJob implements Serializable {
 		return relationList;
 	}
 
-	private static Collection<Relation> getRelations(String citing, String cited) {
-
-		return Arrays
-			.asList(
-				getRelation(citing, cited, ModelConstants.CITES),
-				getRelation(cited, citing, ModelConstants.IS_CITED_BY));
-	}
-
 	public static Relation getRelation(
 		String source,
 		String target,
-		String relclass) {
+		String relClass) {
-		Relation r = new Relation();
-		r.setCollectedfrom(getCollectedFrom());
-		r.setSource(source);
-		r.setTarget(target);
-		r.setRelClass(relclass);
-		r.setRelType(ModelConstants.RESULT_RESULT);
-		r.setSubRelType(ModelConstants.CITATION);
-		r
-			.setDataInfo(
-				getDataInfo());
-		return r;
-	}
 
-	public static List<KeyValue> getCollectedFrom() {
+		return OafMapperUtils
-		KeyValue kv = new KeyValue();
+			.getRelation(
-		kv.setKey(ModelConstants.OPENOCITATIONS_ID);
+				source,
-		kv.setValue(ModelConstants.OPENOCITATIONS_NAME);
+				target,
-
+				ModelConstants.RESULT_RESULT,
-		return Arrays.asList(kv);
+				ModelConstants.CITATION,
-	}
+				relClass,
-
+				Arrays
-	public static DataInfo getDataInfo() {
+					.asList(
-		DataInfo di = new DataInfo();
+						OafMapperUtils.keyValue(ModelConstants.OPENOCITATIONS_ID, ModelConstants.OPENOCITATIONS_NAME)),
-		di.setInferred(false);
+				OafMapperUtils
-		di.setDeletedbyinference(false);
+					.dataInfo(
-		di.setTrust(TRUST);
+						false, null, false, false,
-
+						OafMapperUtils
-		di
+							.qualifier(
-			.setProvenanceaction(
+								OPENCITATIONS_CLASSID, OPENCITATIONS_CLASSNAME,
-				getQualifier(OPENCITATIONS_CLASSID, OPENCITATIONS_CLASSNAME, ModelConstants.DNET_PROVENANCE_ACTIONS));
+								ModelConstants.DNET_PROVENANCE_ACTIONS, ModelConstants.DNET_PROVENANCE_ACTIONS),
-		return di;
+						TRUST),
-	}
+				null);
-
-	public static Qualifier getQualifier(String class_id, String class_name,
-		String qualifierSchema) {
-		Qualifier pa = new Qualifier();
-		pa.setClassid(class_id);
-		pa.setClassname(class_name);
-		pa.setSchemeid(qualifierSchema);
-		pa.setSchemename(qualifierSchema);
-		return pa;
 	}
 
 }

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/opencitations/GetOpenCitationsRefs.java

@@ -3,6 +3,7 @@ package eu.dnetlib.dhp.actionmanager.opencitations;
 
 import java.io.*;
 import java.io.Serializable;
+import java.util.Arrays;
 import java.util.Objects;
 import java.util.zip.GZIPOutputStream;
 import java.util.zip.ZipEntry;
@@ -37,7 +38,7 @@ public class GetOpenCitationsRefs implements Serializable {
 		parser.parseArgument(args);
 
 		final String[] inputFile = parser.get("inputFile").split(";");
-		log.info("inputFile {}", inputFile.toString());
+		log.info("inputFile {}", Arrays.asList(inputFile));
 
 		final String workingPath = parser.get("workingPath");
 		log.info("workingPath {}", workingPath);
@@ -45,6 +46,9 @@ public class GetOpenCitationsRefs implements Serializable {
 		final String hdfsNameNode = parser.get("hdfsNameNode");
 		log.info("hdfsNameNode {}", hdfsNameNode);
 
+		final String prefix = parser.get("prefix");
+		log.info("prefix {}", prefix);
+
 		Configuration conf = new Configuration();
 		conf.set("fs.defaultFS", hdfsNameNode);
 
@@ -53,30 +57,31 @@ public class GetOpenCitationsRefs implements Serializable {
 		GetOpenCitationsRefs ocr = new GetOpenCitationsRefs();
 
 		for (String file : inputFile) {
-			ocr.doExtract(workingPath + "/Original/" + file, workingPath, fileSystem);
+			ocr.doExtract(workingPath + "/Original/" + file, workingPath, fileSystem, prefix);
 		}
 
 	}
 
-	private void doExtract(String inputFile, String workingPath, FileSystem fileSystem)
+	private void doExtract(String inputFile, String workingPath, FileSystem fileSystem, String prefix)
 		throws IOException {
 
 		final Path path = new Path(inputFile);
 
 		FSDataInputStream oc_zip = fileSystem.open(path);
 
-		int count = 1;
+		// int count = 1;
 		try (ZipInputStream zis = new ZipInputStream(oc_zip)) {
 			ZipEntry entry = null;
 			while ((entry = zis.getNextEntry()) != null) {
 
 				if (!entry.isDirectory()) {
 					String fileName = entry.getName();
-					fileName = fileName.substring(0, fileName.indexOf("T")) + "_" + count;
+					// fileName = fileName.substring(0, fileName.indexOf("T")) + "_" + count;
-					count++;
+					fileName = fileName.substring(0, fileName.lastIndexOf("."));
+					// count++;
 					try (
 						FSDataOutputStream out = fileSystem
-							.create(new Path(workingPath + "/COCI/" + fileName + ".gz"));
+							.create(new Path(workingPath + "/" + prefix + "/" + fileName + ".gz"));
 						GZIPOutputStream gzipOs = new GZIPOutputStream(new BufferedOutputStream(out))) {
 
 						IOUtils.copy(zis, gzipOs);

dhp-workflows/dhp-aggregation/src/main/java/eu/dnetlib/dhp/actionmanager/opencitations/ReadCOCI.java

@@ -7,6 +7,7 @@ import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
 
 import java.io.IOException;
 import java.io.Serializable;
+import java.util.Arrays;
 import java.util.Optional;
 
 import org.apache.commons.io.IOUtils;
@@ -42,13 +43,16 @@ public class ReadCOCI implements Serializable {
 		log.info("outputPath: {}", outputPath);
 
 		final String[] inputFile = parser.get("inputFile").split(";");
-		log.info("inputFile {}", inputFile.toString());
+		log.info("inputFile {}", Arrays.asList(inputFile));
 		Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
 		log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
 
 		final String workingPath = parser.get("workingPath");
 		log.info("workingPath {}", workingPath);
 
+		final String format = parser.get("format");
+		log.info("format {}", format);
+
 		SparkConf sconf = new SparkConf();
 
 		final String delimiter = Optional
@@ -64,16 +68,17 @@ public class ReadCOCI implements Serializable {
 					workingPath,
 					inputFile,
 					outputPath,
-					delimiter);
+					delimiter,
+					format);
 			});
 	}
 
 	private static void doRead(SparkSession spark, String workingPath, String[] inputFiles,
 		String outputPath,
-		String delimiter) throws IOException {
+		String delimiter, String format) {
 
 		for (String inputFile : inputFiles) {
-			String p_string = workingPath + "/" + inputFile + ".gz";
+			String pString = workingPath + "/" + inputFile + ".gz";
 
 			Dataset<Row> cociData = spark
 				.read()
@@ -82,14 +87,20 @@ public class ReadCOCI implements Serializable {
 				.option("inferSchema", "true")
 				.option("header", "true")
 				.option("quotes", "\"")
-				.load(p_string)
+				.load(pString)
 				.repartition(100);
 
 			cociData.map((MapFunction<Row, COCI>) row -> {
 				COCI coci = new COCI();
+				if (format.equals("COCI")) {
+					coci.setCiting(row.getString(1));
+					coci.setCited(row.getString(2));
+				} else {
+					coci.setCiting(String.valueOf(row.getInt(1)));
+					coci.setCited(String.valueOf(row.getInt(2)));
+				}
 				coci.setOci(row.getString(0));
-				coci.setCiting(row.getString(1));
+
-				coci.setCited(row.getString(2));
 				return coci;
 			}, Encoders.bean(COCI.class))
 				.write()

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/as_parameters.json

@@ -16,10 +16,11 @@
     "paramLongName": "isSparkSessionManaged",
     "paramDescription": "the hdfs name node",
     "paramRequired": false
-  },  {
+  },
-  "paramName": "sdr",
+  {
-  "paramLongName": "shouldDuplicateRels",
+    "paramName": "sdr",
-  "paramDescription": "the hdfs name node",
+    "paramLongName": "shouldDuplicateRels",
-  "paramRequired": false
+    "paramDescription": "activates/deactivates the construction of bidirectional relations Cites/IsCitedBy",
-}
+    "paramRequired": false
+  }
 ]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/input_parameters.json

@@ -16,5 +16,11 @@
     "paramLongName": "hdfsNameNode",
     "paramDescription": "the hdfs name node",
     "paramRequired": true
+  },
+  {
+    "paramName": "p",
+    "paramLongName": "prefix",
+    "paramDescription": "COCI or POCI",
+    "paramRequired": true
   }
 ]

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/input_readcoci_parameters.json

@@ -30,7 +30,12 @@
     "paramLongName": "inputFile",
     "paramDescription": "the hdfs name node",
     "paramRequired": true
-  }
+  }, {
+  "paramName": "f",
+  "paramLongName": "format",
+  "paramDescription": "the hdfs name node",
+  "paramRequired": true
+}
 ]
 
 

dhp-workflows/dhp-aggregation/src/main/resources/eu/dnetlib/dhp/actionmanager/opencitations/oozie_app/workflow.xml

@@ -34,6 +34,7 @@
     <kill name="Kill">
         <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
     </kill>
+
     <action name="download">
         <shell xmlns="uri:oozie:shell-action:0.2">
             <job-tracker>${jobTracker}</job-tracker>
@@ -46,7 +47,7 @@
             </configuration>
             <exec>download.sh</exec>
             <argument>${filelist}</argument>
-            <argument>${workingPath}/Original</argument>
+            <argument>${workingPath}/${prefix}/Original</argument>
             <env-var>HADOOP_USER_NAME=${wf:user()}</env-var>
             <file>download.sh</file>
             <capture-output/>
@@ -54,12 +55,14 @@
         <ok to="extract"/>
         <error to="Kill"/>
     </action>
+
     <action name="extract">
         <java>
             <main-class>eu.dnetlib.dhp.actionmanager.opencitations.GetOpenCitationsRefs</main-class>
             <arg>--hdfsNameNode</arg><arg>${nameNode}</arg>
             <arg>--inputFile</arg><arg>${inputFile}</arg>
-            <arg>--workingPath</arg><arg>${workingPath}</arg>
+            <arg>--workingPath</arg><arg>${workingPath}/${prefix}</arg>
+            <arg>--prefix</arg><arg>${prefix}</arg>
         </java>
         <ok to="read"/>
         <error to="Kill"/>
@@ -82,10 +85,11 @@
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
                 --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
             </spark-opts>
-            <arg>--workingPath</arg><arg>${workingPath}/COCI</arg>
+            <arg>--workingPath</arg><arg>${workingPath}/${prefix}/${prefix}</arg>
-            <arg>--outputPath</arg><arg>${workingPath}/COCI_JSON/</arg>
+            <arg>--outputPath</arg><arg>${workingPath}/${prefix}/${prefix}_JSON/</arg>
             <arg>--delimiter</arg><arg>${delimiter}</arg>
             <arg>--inputFile</arg><arg>${inputFileCoci}</arg>
+            <arg>--format</arg><arg>${prefix}</arg>
         </spark>
         <ok to="create_actionset"/>
         <error to="Kill"/>
@@ -108,7 +112,7 @@
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
                 --conf spark.sql.warehouse.dir=${sparkSqlWarehouseDir}
             </spark-opts>
-            <arg>--inputPath</arg><arg>${workingPath}/COCI_JSON</arg>
+            <arg>--inputPath</arg><arg>${workingPath}</arg>
             <arg>--outputPath</arg><arg>${outputPath}</arg>
         </spark>
         <ok to="End"/>

dhp-workflows/dhp-aggregation/src/main/scala/eu/dnetlib/dhp/sx/bio/BioDBToOAF.scala

@@ -222,7 +222,7 @@ object BioDBToOAF {
   def uniprotToOAF(input: String): List[Oaf] = {
     implicit lazy val formats: DefaultFormats.type = org.json4s.DefaultFormats
     lazy val json = parse(input)
-    val pid = (json \ "pid").extract[String].trim()
+    val pid = (json \ "pid").extract[String]
 
     val d = new Dataset
 

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/sx/graph/bio/pdb_dump

@@ -1,44 +1,15 @@
-{"classification": "Signaling protein", "pdb": "5NM4", "deposition_date": "2017-04-05", "title": "A2a adenosine receptor room-temperature structure determined by serial Femtosecond crystallography", "Keywords": ["Oom-temperature", " serial crystallography", " signaling protein"], "authors": ["T.weinert", "R.cheng", "D.james", "D.gashi", "P.nogly", "K.jaeger", "M.hennig", "", "J.standfuss"], "pmid": "28912485", "doi": "10.1038/S41467-017-00630-4"}
+{"pdb": "1CW0", "title": "crystal structure analysis of very short patch repair (vsr) endonuclease in complex with a duplex dna", "authors": ["S.E.Tsutakawa", "H.Jingami", "K.Morikawa"], "doi": "10.1016/S0092-8674(00)81550-0", "pmid": "10612397"}
-{"classification": "Oxidoreductase/oxidoreductase inhibitor", "pdb": "4KN3", "deposition_date": "2013-05-08", "title": "Structure of the y34ns91g double mutant of dehaloperoxidase from Amphitrite ornata with 2,4,6-trichlorophenol", "Keywords": ["Lobin", " oxygen storage", " peroxidase", " oxidoreductase", " oxidoreductase-", "Oxidoreductase inhibitor complex"], "authors": ["C.wang", "L.lovelace", "L.lebioda"], "pmid": "23952341", "doi": "10.1021/BI400627W"}
+{"pdb": "2CWW", "title": "crystal structure of thermus thermophilus ttha1280, a putative sam- dependent rna methyltransferase, in complex with s-adenosyl-l- homocysteine", "authors": ["A.A.Pioszak", "K.Murayama", "N.Nakagawa", "A.Ebihara", "S.Kuramitsu", "M.Shirouzu", "S.Yokoyama", "Riken Structural Genomics/proteomics Initiative (Rsgi)"], "doi": "10.1107/S1744309105029842", "pmid": "16511182"}
-{"classification": "Transport protein", "pdb": "8HKM", "deposition_date": "2022-11-27", "title": "Ion channel", "Keywords": ["On channel", " transport protein"], "authors": ["D.h.jiang", "J.t.zhang"], "pmid": "37494189", "doi": "10.1016/J.CELREP.2023.112858"}
+{"pdb": "6CWE", "title": "structure of alpha-gsa[8,6p] bound by cd1d and in complex with the va14vb8.2 tcr", "authors": ["J.Wang", "D.Zajonc"], "doi": null, "pmid": null}
-{"classification": "Signaling protein", "pdb": "6JT1", "deposition_date": "2019-04-08", "title": "Structure of human soluble guanylate cyclase in the heme oxidised State", "Keywords": ["Oluble guanylate cyclase", " signaling protein"], "authors": ["L.chen", "Y.kang", "R.liu", "J.-x.wu"], "pmid": "31514202", "doi": "10.1038/S41586-019-1584-6"}
+{"pdb": "5CWS", "title": "crystal structure of the intact chaetomium thermophilum nsp1-nup49- nup57 channel nucleoporin heterotrimer bound to its nic96 nuclear pore complex attachment site", "authors": ["C.J.Bley", "S.Petrovic", "M.Paduch", "V.Lu", "A.A.Kossiakoff", "A.Hoelz"], "doi": "10.1126/SCIENCE.AAC9176", "pmid": "26316600"}
-{"classification": "Immune system", "pdb": "7OW6", "deposition_date": "2021-06-16", "title": "Crystal structure of a tcr in complex with hla-a*11:01 bound to kras G12d peptide (vvvgadgvgk)", "Keywords": ["La", " kras", " tcr", " immune system"], "authors": ["V.karuppiah", "R.a.robinson"], "doi": "10.1038/S41467-022-32811-1"}
+{"pdb": "5CWE", "title": "structure of cyp107l2 from streptomyces avermitilis with lauric acid", "authors": ["T.-V.Pham", "S.-H.Han", "J.-H.Kim", "D.-H.Kim", "L.-W.Kang"], "doi": null, "pmid": null}
-{"classification": "Biosynthetic protein", "pdb": "5EQ8", "deposition_date": "2015-11-12", "title": "Crystal structure of medicago truncatula histidinol-phosphate Phosphatase (mthpp) in complex with l-histidinol", "Keywords": ["Istidine biosynthesis", " metabolic pathways", " dimer", " plant", "", "Biosynthetic protein"], "authors": ["M.ruszkowski", "Z.dauter"], "pmid": "26994138", "doi": "10.1074/JBC.M115.708727"}
+{"pdb": "7CW4", "title": "acetyl-coa acetyltransferase from bacillus cereus atcc 14579", "authors": ["J.Hong", "K.J.Kim"], "doi": "10.1016/J.BBRC.2020.09.048", "pmid": "32972748"}
-{"classification": "De novo protein", "pdb": "8CWA", "deposition_date": "2022-05-18", "title": "Solution nmr structure of 8-residue rosetta-designed cyclic peptide D8.21 in cdcl3 with cis/trans switching (tc conformation, 53%)", "Keywords": ["Yclic peptide", " non natural amino acids", " cis/trans", " switch peptides", "", "De novo design", "Membrane permeability", "De novo protein"], "authors": ["T.a.ramelot", "R.tejero", "G.t.montelione"], "pmid": "36041435", "doi": "10.1016/J.CELL.2022.07.019"}
+{"pdb": "2CWP", "title": "crystal structure of metrs related protein from pyrococcus horikoshii", "authors": ["K.Murayama", "M.Kato-Murayama", "M.Shirouzu", "S.Yokoyama", "Riken StructuralGenomics/proteomics Initiative (Rsgi)"], "doi": null, "pmid": null}
-{"classification": "Hydrolase", "pdb": "3R6M", "deposition_date": "2011-03-21", "title": "Crystal structure of vibrio parahaemolyticus yeaz", "Keywords": ["Ctin/hsp70 nucleotide-binding fold", " bacterial resuscitation", " viable", "But non-culturable state", "Resuscitation promoting factor", "Ygjd", "", "Yjee", "Vibrio parahaemolyticus", "Hydrolase"], "authors": ["A.roujeinikova", "I.aydin"], "pmid": "21858042", "doi": "10.1371/JOURNAL.PONE.0023245"}
+{"pdb": "2CW7", "title": "crystal structure of intein homing endonuclease ii", "authors": ["H.Matsumura", "H.Takahashi", "T.Inoue", "H.Hashimoto", "M.Nishioka", "S.Fujiwara", "M.Takagi", "T.Imanaka", "Y.Kai"], "doi": "10.1002/PROT.20858", "pmid": "16493661"}
-{"classification": "Hydrolase", "pdb": "2W5J", "deposition_date": "2008-12-10", "title": "Structure of the c14-rotor ring of the proton translocating Chloroplast atp synthase", "Keywords": ["Ydrolase", " chloroplast", " atp synthase", " lipid-binding", " cf(0)", " membrane", "", "Transport", "Formylation", "Energy transduction", "Hydrogen ion transport", "", "Ion transport", "Transmembrane", "Membrane protein"], "authors": ["M.vollmar", "D.schlieper", "M.winn", "C.buechner", "G.groth"], "pmid": "19423706", "doi": "10.1074/JBC.M109.006916"}
+{"pdb": "1CWU", "title": "brassica napus enoyl acp reductase a138g mutant complexed with nad+ and thienodiazaborine", "authors": ["A.Roujeinikova", "J.B.Rafferty", "D.W.Rice"], "doi": "10.1074/JBC.274.43.30811", "pmid": "10521472"}
-{"classification": "De novo protein", "pdb": "4GLU", "deposition_date": "2012-08-14", "title": "Crystal structure of the mirror image form of vegf-a", "Keywords": ["-protein", " covalent dimer", " cysteine knot protein", " growth factor", " de", "Novo protein"], "authors": ["K.mandal", "M.uppalapati", "D.ault-riche", "J.kenney", "J.lowitz", "S.sidhu", "", "S.b.h.kent"], "pmid": "22927390", "doi": "10.1073/PNAS.1210483109"}
+{"pdb": "3CWN", "title": "escherichia coli transaldolase b mutant f178y", "authors": ["T.Sandalova", "G.Schneider", "A.Samland"], "doi": "10.1074/JBC.M803184200", "pmid": "18687684"}
-{"classification": "Hydrolase/hydrolase inhibitor", "pdb": "3WYL", "deposition_date": "2014-09-01", "title": "Crystal structure of the catalytic domain of pde10a complexed with 5- Methoxy-3-(1-phenyl-1h-pyrazol-5-yl)-1-(3-(trifluoromethyl)phenyl) Pyridazin-4(1h)-one", "Keywords": ["Ydrolase-hydrolase inhibitor complex"], "authors": ["H.oki", "Y.hayano"], "pmid": "25384088", "doi": "10.1021/JM5013648"}
+{"pdb": "1CWL", "title": "human cyclophilin a complexed with 4 4-hydroxy-meleu cyclosporin", "authors": ["V.Mikol", "J.Kallen", "P.Taylor", "M.D.Walkinshaw"], "doi": "10.1006/JMBI.1998.2108", "pmid": "9769216"}
-{"classification": "Isomerase", "pdb": "5BOR", "deposition_date": "2015-05-27", "title": "Structure of acetobacter aceti pure-s57c, sulfonate form", "Keywords": ["Cidophile", " pure", " purine biosynthesis", " isomerase"], "authors": ["K.l.sullivan", "T.j.kappock"]}
+{"pdb": "3CW2", "title": "crystal structure of the intact archaeal translation initiation factor 2 from sulfolobus solfataricus .", "authors": ["E.A.Stolboushkina", "S.V.Nikonov", "A.D.Nikulin", "U.Blaesi", "D.J.Manstein", "R.V.Fedorov", "M.B.Garber", "O.S.Nikonov"], "doi": "10.1016/J.JMB.2008.07.039", "pmid": "18675278"}
-{"classification": "Hydrolase", "pdb": "1X0C", "deposition_date": "2005-03-17", "title": "Improved crystal structure of isopullulanase from aspergillus niger Atcc 9642", "Keywords": ["Ullulan", " glycoside hydrolase family 49", " glycoprotein", " hydrolase"], "authors": ["M.mizuno", "T.tonozuka", "A.yamamura", "Y.miyasaka", "H.akeboshi", "S.kamitori", "", "A.nishikawa", "Y.sakano"], "pmid": "18155243", "doi": "10.1016/J.JMB.2007.11.098"}
+{"pdb": "3CW9", "title": "4-chlorobenzoyl-coa ligase/synthetase in the thioester-forming conformation, bound to 4-chlorophenacyl-coa", "authors": ["A.S.Reger", "J.Cao", "R.Wu", "D.Dunaway-Mariano", "A.M.Gulick"], "doi": "10.1021/BI800696Y", "pmid": "18620418"}
-{"classification": "Oxidoreductase", "pdb": "7CUP", "deposition_date": "2020-08-23", "title": "Structure of 2,5-dihydroxypridine dioxygenase from pseudomonas putida Kt2440", "Keywords": ["On-heme dioxygenase", " oxidoreductase"], "authors": ["G.q.liu", "H.z.tang"]}
+{"pdb": "3CWU", "title": "crystal structure of an alka host/guest complex 2'-fluoro-2'-deoxy-1, n6-ethenoadenine:thymine base pair", "authors": ["B.R.Bowman", "S.Lee", "S.Wang", "G.L.Verdine"], "doi": "10.1016/J.STR.2008.04.012", "pmid": "18682218"}
-{"classification": "Ligase", "pdb": "1VCN", "deposition_date": "2004-03-10", "title": "Crystal structure of t.th. hb8 ctp synthetase complex with sulfate Anion", "Keywords": ["Etramer", " riken structural genomics/proteomics initiative", " rsgi", "", "Structural genomics", "Ligase"], "authors": ["M.goto", "Riken structural genomics/proteomics initiative (rsgi)"], "pmid": "15296735", "doi": "10.1016/J.STR.2004.05.013"}
+{"pdb": "5CWF", "title": "crystal structure of de novo designed helical repeat protein dhr8", "authors": ["G.Bhabha", "D.C.Ekiert"], "doi": "10.1038/NATURE16162", "pmid": "26675729"}
-{"classification": "Transferase/transferase inhibitor", "pdb": "6C9V", "deposition_date": "2018-01-28", "title": "Mycobacterium tuberculosis adenosine kinase bound to (2r,3s,4r,5r)-2- (hydroxymethyl)-5-(6-(4-phenylpiperazin-1-yl)-9h-purin-9-yl) Tetrahydrofuran-3,4-diol", "Keywords": ["Ucleoside analog", " complex", " inhibitor", " structural genomics", " psi-2", "", "Protein structure initiative", "Tb structural genomics consortium", "", "Tbsgc", "Transferase-transferase inhibitor complex"], "authors": ["R.a.crespo", "Tb structural genomics consortium (tbsgc)"], "pmid": "31002508", "doi": "10.1021/ACS.JMEDCHEM.9B00020"}
-{"classification": "De novo protein", "pdb": "4LPY", "deposition_date": "2013-07-16", "title": "Crystal structure of tencon variant g10", "Keywords": ["Ibronectin type iii fold", " alternate scaffold", " de novo protein"], "authors": ["A.teplyakov", "G.obmolova", "G.l.gilliland"], "pmid": "24375666", "doi": "10.1002/PROT.24502"}
-{"classification": "Isomerase", "pdb": "2Y88", "deposition_date": "2011-02-03", "title": "Crystal structure of mycobacterium tuberculosis phosphoribosyl Isomerase (variant d11n) with bound prfar", "Keywords": ["Romatic amino acid biosynthesis", " isomerase", " tim-barrel", " histidine", "Biosynthesis", "Tryptophan biosynthesis"], "authors": ["J.kuper", "A.v.due", "A.geerlof", "M.wilmanns"], "pmid": "21321225", "doi": "10.1073/PNAS.1015996108"}
-{"classification": "Unknown function", "pdb": "1SR0", "deposition_date": "2004-03-22", "title": "Crystal structure of signalling protein from sheep(sps-40) at 3.0a Resolution using crystal grown in the presence of polysaccharides", "Keywords": ["Ignalling protein", " involution", " unknown function"], "authors": ["D.b.srivastava", "A.s.ethayathulla", "N.singh", "J.kumar", "S.sharma", "T.p.singh"]}
-{"classification": "Dna binding protein", "pdb": "3RH2", "deposition_date": "2011-04-11", "title": "Crystal structure of a tetr-like transcriptional regulator (sama_0099) From shewanella amazonensis sb2b at 2.42 a resolution", "Keywords": ["Na/rna-binding 3-helical bundle", " structural genomics", " joint center", "For structural genomics", "Jcsg", "Protein structure initiative", "Psi-", "Biology", "Dna binding protein"], "authors": ["Joint center for structural genomics (jcsg)"]}
-{"classification": "Transferase", "pdb": "2WK5", "deposition_date": "2009-06-05", "title": "Structural features of native human thymidine phosphorylase And in complex with 5-iodouracil", "Keywords": ["Lycosyltransferase", " developmental protein", " angiogenesis", "", "5-iodouracil", "Growth factor", "Enzyme kinetics", "", "Differentiation", "Disease mutation", "Thymidine", "Phosphorylase", "Chemotaxis", "Transferase", "Mutagenesis", "", "Polymorphism"], "authors": ["E.mitsiki", "A.c.papageorgiou", "S.iyer", "N.thiyagarajan", "S.h.prior", "", "D.sleep", "C.finnis", "K.r.acharya"], "pmid": "19555658", "doi": "10.1016/J.BBRC.2009.06.104"}
-{"classification": "Hydrolase", "pdb": "3P9Y", "deposition_date": "2010-10-18", "title": "Crystal structure of the drosophila melanogaster ssu72-pctd complex", "Keywords": ["Hosphatase", " cis proline", " lmw ptp-like fold", " rna polymerase ii ctd", "", "Hydrolase"], "authors": ["J.w.werner-allen", "P.zhou"], "pmid": "21159777", "doi": "10.1074/JBC.M110.197129"}
-{"classification": "Recombination/dna", "pdb": "6OEO", "deposition_date": "2019-03-27", "title": "Cryo-em structure of mouse rag1/2 nfc complex (dna1)", "Keywords": ["(d)j recombination", " dna transposition", " rag", " scid", " recombination", "", "Recombination-dna complex"], "authors": ["X.chen", "Y.cui", "Z.h.zhou", "W.yang", "M.gellert"], "pmid": "32015552", "doi": "10.1038/S41594-019-0363-2"}
-{"classification": "Hydrolase", "pdb": "4ECA", "deposition_date": "1997-02-21", "title": "Asparaginase from e. coli, mutant t89v with covalently bound aspartate", "Keywords": ["Ydrolase", " acyl-enzyme intermediate", " threonine amidohydrolase"], "authors": ["G.j.palm", "J.lubkowski", "A.wlodawer"], "pmid": "8706862", "doi": "10.1016/0014-5793(96)00660-6"}
-{"classification": "Transcription/protein binding", "pdb": "3UVX", "deposition_date": "2011-11-30", "title": "Crystal structure of the first bromodomain of human brd4 in complex With a diacetylated histone 4 peptide (h4k12ack16ac)", "Keywords": ["Romodomain", " bromodomain containing protein 4", " cap", " hunk1", " mcap", "", "Mitotic chromosome associated protein", "Peptide complex", "Structural", "Genomics consortium", "Sgc", "Transcription-protein binding complex"], "authors": ["P.filippakopoulos", "S.picaud", "T.keates", "E.ugochukwu", "F.von delft", "", "C.h.arrowsmith", "A.m.edwards", "J.weigelt", "C.bountra", "S.knapp", "Structural", "Genomics consortium (sgc)"], "pmid": "22464331", "doi": "10.1016/J.CELL.2012.02.013"}
-{"classification": "Membrane protein", "pdb": "1TLZ", "deposition_date": "2004-06-10", "title": "Tsx structure complexed with uridine", "Keywords": ["Ucleoside transporter", " beta barrel", " uridine", " membrane", "Protein"], "authors": ["J.ye", "B.van den berg"], "pmid": "15272310", "doi": "10.1038/SJ.EMBOJ.7600330"}
-{"classification": "Dna binding protein", "pdb": "7AZD", "deposition_date": "2020-11-16", "title": "Dna polymerase sliding clamp from escherichia coli with peptide 20 Bound", "Keywords": ["Ntibacterial drug", " dna binding protein"], "authors": ["C.monsarrat", "G.compain", "C.andre", "I.martiel", "S.engilberge", "V.olieric", "", "P.wolff", "K.brillet", "M.landolfo", "C.silva da veiga", "J.wagner", "G.guichard", "", "D.y.burnouf"], "pmid": "34806883", "doi": "10.1021/ACS.JMEDCHEM.1C00918"}
-{"classification": "Transferase", "pdb": "5N3K", "deposition_date": "2017-02-08", "title": "Camp-dependent protein kinase a from cricetulus griseus in complex With fragment like molecule o-guanidino-l-homoserine", "Keywords": ["Ragment", " complex", " transferase", " serine threonine kinase", " camp", "", "Kinase", "Pka"], "authors": ["C.siefker", "A.heine", "G.klebe"]}
-{"classification": "Biosynthetic protein", "pdb": "8H52", "deposition_date": "2022-10-11", "title": "Crystal structure of helicobacter pylori carboxyspermidine Dehydrogenase in complex with nadp", "Keywords": ["Arboxyspermidine dehydrogenase", " biosynthetic protein"], "authors": ["K.y.ko", "S.c.park", "S.y.cho", "S.i.yoon"], "pmid": "36283333", "doi": "10.1016/J.BBRC.2022.10.049"}
-{"classification": "Metal binding protein", "pdb": "6DYC", "deposition_date": "2018-07-01", "title": "Co(ii)-bound structure of the engineered cyt cb562 variant, ch3", "Keywords": ["Esigned protein", " 4-helix bundle", " electron transport", " metal binding", "Protein"], "authors": ["F.a.tezcan", "J.rittle"], "pmid": "30778140", "doi": "10.1038/S41557-019-0218-9"}
-{"classification": "Protein fibril", "pdb": "6A6B", "deposition_date": "2018-06-27", "title": "Cryo-em structure of alpha-synuclein fiber", "Keywords": ["Lpha-syn fiber", " parkinson disease", " protein fibril"], "authors": ["Y.w.li", "C.y.zhao", "F.luo", "Z.liu", "X.gui", "Z.luo", "X.zhang", "D.li", "C.liu", "X.li"], "pmid": "30065316", "doi": "10.1038/S41422-018-0075-X"}
-{"classification": "Dna", "pdb": "7D5E", "deposition_date": "2020-09-25", "title": "Left-handed g-quadruplex containing two bulges", "Keywords": ["-quadruplex", " bulge", " dna", " left-handed"], "authors": ["P.das", "A.maity", "K.h.ngo", "F.r.winnerdy", "B.bakalar", "Y.mechulam", "E.schmitt", "", "A.t.phan"], "pmid": "33503265", "doi": "10.1093/NAR/GKAA1259"}
-{"classification": "Transferase", "pdb": "3RSY", "deposition_date": "2011-05-02", "title": "Cellobiose phosphorylase from cellulomonas uda in complex with sulfate And glycerol", "Keywords": ["H94", " alpha barrel", " cellobiose phosphorylase", " disaccharide", "Phosphorylase", "Transferase"], "authors": ["A.van hoorebeke", "J.stout", "W.soetaert", "J.van beeumen", "T.desmet", "S.savvides"]}
-{"classification": "Oxidoreductase", "pdb": "7MCI", "deposition_date": "2021-04-02", "title": "Mofe protein from azotobacter vinelandii with a sulfur-replenished Cofactor", "Keywords": ["Zotobacter vinelandii", " mofe-protein", " nitrogenase", " oxidoreductase"], "authors": ["W.kang", "C.lee", "Y.hu", "M.w.ribbe"], "doi": "10.1038/S41929-022-00782-7"}
-{"classification": "Dna", "pdb": "1XUW", "deposition_date": "2004-10-26", "title": "Structural rationalization of a large difference in rna affinity Despite a small difference in chemistry between two 2'-o-modified Nucleic acid analogs", "Keywords": ["Na mimetic methylcarbamate amide analog", " dna"], "authors": ["R.pattanayek", "L.sethaphong", "C.pan", "M.prhavc", "T.p.prakash", "M.manoharan", "", "M.egli"], "pmid": "15547979", "doi": "10.1021/JA044637K"}
-{"classification": "Lyase", "pdb": "7C0D", "deposition_date": "2020-05-01", "title": "Crystal structure of azospirillum brasilense l-2-keto-3-deoxyarabonate Dehydratase (hydroxypyruvate-bound form)", "Keywords": ["-2-keto-3-deoxyarabonate dehydratase", " lyase"], "authors": ["Y.watanabe", "S.watanabe"], "pmid": "32697085", "doi": "10.1021/ACS.BIOCHEM.0C00515"}
-{"classification": "Signaling protein", "pdb": "5LYK", "deposition_date": "2016-09-28", "title": "Crystal structure of intracellular b30.2 domain of btn3a1 bound to Citrate", "Keywords": ["30.2", " butyrophilin", " signaling protein"], "authors": ["F.mohammed", "A.t.baker", "M.salim", "B.e.willcox"], "pmid": "28862425", "doi": "10.1021/ACSCHEMBIO.7B00694"}
-{"classification": "Toxin", "pdb": "4IZL", "deposition_date": "2013-01-30", "title": "Structure of the n248a mutant of the panton-valentine leucocidin s Component from staphylococcus aureus", "Keywords": ["I-component leucotoxin", " staphylococcus aureus", " s component", "Leucocidin", "Beta-barrel pore forming toxin", "Toxin"], "authors": ["L.maveyraud", "B.j.laventie", "G.prevost", "L.mourey"], "pmid": "24643034", "doi": "10.1371/JOURNAL.PONE.0092094"}
-{"classification": "Dna", "pdb": "6F3C", "deposition_date": "2017-11-28", "title": "The cytotoxic [pt(h2bapbpy)] platinum complex interacting with the Cgtacg hexamer", "Keywords": ["Rug-dna complex", " four-way junction", " dna"], "authors": ["M.ferraroni", "C.bazzicalupi", "P.gratteri", "F.papi"], "pmid": "31046177", "doi": "10.1002/ANIE.201814532"}
-{"classification": "Signaling protein/inhibitor", "pdb": "4L5M", "deposition_date": "2013-06-11", "title": "Complexe of arno sec7 domain with the protein-protein interaction Inhibitor n-(4-hydroxy-2,6-dimethylphenyl)benzenesulfonamide at ph6.5", "Keywords": ["Ec-7domain", " signaling protein-inhibitor complex"], "authors": ["F.hoh", "J.rouhana"], "pmid": "24112024", "doi": "10.1021/JM4009357"}
-{"classification": "Signaling protein", "pdb": "5I6J", "deposition_date": "2016-02-16", "title": "Crystal structure of srgap2 f-barx", "Keywords": ["Rgap2", " f-bar", " fx", " signaling protein"], "authors": ["M.sporny", "J.guez-haddad", "M.n.isupov", "Y.opatowsky"], "pmid": "28333212", "doi": "10.1093/MOLBEV/MSX094"}
-{"classification": "Metal binding protein", "pdb": "1Q80", "deposition_date": "2003-08-20", "title": "Solution structure and dynamics of nereis sarcoplasmic calcium binding Protein", "Keywords": ["Ll-alpha", " metal binding protein"], "authors": ["G.rabah", "R.popescu", "J.a.cox", "Y.engelborghs", "C.t.craescu"], "pmid": "15819893", "doi": "10.1111/J.1742-4658.2005.04629.X"}
-{"classification": "Transferase", "pdb": "1TW1", "deposition_date": "2004-06-30", "title": "Beta-1,4-galactosyltransferase mutant met344his (m344h-gal-t1) complex With udp-galactose and magnesium", "Keywords": ["Et344his mutation; closed conformation; mn binding", " transferase"], "authors": ["B.ramakrishnan", "E.boeggeman", "P.k.qasba"], "pmid": "15449940", "doi": "10.1021/BI049007+"}
-{"classification": "Rna", "pdb": "2PN4", "deposition_date": "2007-04-23", "title": "Crystal structure of hepatitis c virus ires subdomain iia", "Keywords": ["Cv", " ires", " subdoamin iia", " rna", " strontium", " hepatitis"], "authors": ["Q.zhao", "Q.han", "C.r.kissinger", "P.a.thompson"], "pmid": "18391410", "doi": "10.1107/S0907444908002011"}

dhp-workflows/dhp-aggregation/src/test/resources/eu/dnetlib/dhp/sx/graph/bio/uniprot_dump

@@ -1,36 +1,6 @@
-{"pid": " Q6GZX4", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 43"}], "title": "Putative transcription factor 001R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
+{"pid": "Q6GZX4", "dates": [{"date": "28-JUN-2011", "date_info": " integrated into UniProtKB/Swiss-Prot."}, {"date": "19-JUL-2004", "date_info": " sequence version 1."}, {"date": "12-AUG-2020", "date_info": " entry version 41."}], "title": "Putative transcription factor 001R;", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3).", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus."], "references": [{"PubMed": "15165820"}, {" DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZX3", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 45"}], "title": "Uncharacterized protein 002L", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
+{"pid": "Q6GZX3", "dates": [{"date": "28-JUN-2011", "date_info": " integrated into UniProtKB/Swiss-Prot."}, {"date": "19-JUL-2004", "date_info": " sequence version 1."}, {"date": "12-AUG-2020", "date_info": " entry version 42."}], "title": "Uncharacterized protein 002L;", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3).", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus."], "references": [{"PubMed": "15165820"}, {" DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197F8", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2022-02-23", "date_info": "entry version 29"}], "title": "Uncharacterized protein 002R", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
+{"pid": "Q197F8", "dates": [{"date": "16-JUN-2009", "date_info": " integrated into UniProtKB/Swiss-Prot."}, {"date": "11-JUL-2006", "date_info": " sequence version 1."}, {"date": "12-AUG-2020", "date_info": " entry version 27."}], "title": "Uncharacterized protein 002R;", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus).", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus."], "references": [{"PubMed": "16912294"}, {" DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q197F7", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2020-08-12", "date_info": "entry version 23"}], "title": "Uncharacterized protein 003L", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
+{"pid": "Q197F7", "dates": [{"date": "16-JUN-2009", "date_info": " integrated into UniProtKB/Swiss-Prot."}, {"date": "11-JUL-2006", "date_info": " sequence version 1."}, {"date": "12-AUG-2020", "date_info": " entry version 23."}], "title": "Uncharacterized protein 003L;", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus).", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus."], "references": [{"PubMed": "16912294"}, {" DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZX2", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 37"}], "title": "Uncharacterized protein 3R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
+{"pid": "Q6GZX2", "dates": [{"date": "28-JUN-2011", "date_info": " integrated into UniProtKB/Swiss-Prot."}, {"date": "19-JUL-2004", "date_info": " sequence version 1."}, {"date": "12-AUG-2020", "date_info": " entry version 36."}], "title": "Uncharacterized protein 3R;", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3).", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus."], "references": [{"PubMed": "15165820"}, {" DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZX1", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 38"}], "title": "Uncharacterized protein 004R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
+{"pid": "Q6GZX1", "dates": [{"date": "28-JUN-2011", "date_info": " integrated into UniProtKB/Swiss-Prot."}, {"date": "19-JUL-2004", "date_info": " sequence version 1."}, {"date": "12-AUG-2020", "date_info": " entry version 34."}], "title": "Uncharacterized protein 004R;", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3).", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus."], "references": [{"PubMed": "15165820"}, {" DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197F5", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2022-10-12", "date_info": "entry version 32"}], "title": "Uncharacterized protein 005L", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZX0", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 47"}], "title": "Uncharacterized protein 005R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q91G88", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2001-12-01", "date_info": "sequence version 1"}, {"date": "2023-06-28", "date_info": "entry version 53"}], "title": "Putative KilA-N domain-containing protein 006L", "organism_species": "Invertebrate iridescent virus 6 (IIV-6) (Chilo iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Iridovirus"], "references": [{"PubMed": "17239238"}, {"DOI": "10.1186/1743-422x-4-11"}]}
-{"pid": " Q6GZW9", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 34"}], "title": "Uncharacterized protein 006R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZW8", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 32"}], "title": "Uncharacterized protein 007R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197F3", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2023-02-22", "date_info": "entry version 28"}], "title": "Uncharacterized protein 007R", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q197F2", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2022-02-23", "date_info": "entry version 22"}], "title": "Uncharacterized protein 008L", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZW6", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 67"}], "title": "Putative helicase 009L", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q91G85", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2001-12-01", "date_info": "sequence version 1"}, {"date": "2023-02-22", "date_info": "entry version 38"}], "title": "Uncharacterized protein 009R", "organism_species": "Invertebrate iridescent virus 6 (IIV-6) (Chilo iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Iridovirus"], "references": [{"PubMed": "17239238"}, {"DOI": "10.1186/1743-422x-4-11"}]}
-{"pid": " Q6GZW5", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 37"}], "title": "Uncharacterized protein 010R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197E9", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2023-02-22", "date_info": "entry version 28"}], "title": "Uncharacterized protein 011L", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZW4", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 37"}], "title": "Uncharacterized protein 011R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZW3", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 35"}], "title": "Uncharacterized protein 012L", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197E7", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2023-02-22", "date_info": "entry version 37"}], "title": "Uncharacterized protein IIV3-013L", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZW2", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 30"}], "title": "Uncharacterized protein 013R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZW1", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 35"}], "title": "Uncharacterized protein 014R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZW0", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 50"}], "title": "Uncharacterized protein 015R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZV8", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 35"}], "title": "Uncharacterized protein 017L", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZV7", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 33"}], "title": "Uncharacterized protein 018L", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZV6", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 87"}], "title": "Putative serine/threonine-protein kinase 019R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZV5", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 40"}], "title": "Uncharacterized protein 020R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZV4", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 35"}], "title": "Uncharacterized protein 021L", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197D8", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2022-12-14", "date_info": "entry version 35"}], "title": "Transmembrane protein 022L", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZV2", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 33"}], "title": "Uncharacterized protein 023R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197D7", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2023-02-22", "date_info": "entry version 25"}], "title": "Uncharacterized protein 023R", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q6GZV1", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 37"}], "title": "Uncharacterized protein 024R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q197D5", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2006-07-11", "date_info": "sequence version 1"}, {"date": "2022-10-12", "date_info": "entry version 24"}], "title": "Uncharacterized protein 025R", "organism_species": "Invertebrate iridescent virus 3 (IIV-3) (Mosquito iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Chloriridovirus"], "references": [{"PubMed": "16912294"}, {"DOI": "10.1128/jvi.00464-06"}]}
-{"pid": " Q91G70", "dates": [{"date": "2009-06-16", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2001-12-01", "date_info": "sequence version 1"}, {"date": "2020-08-12", "date_info": "entry version 32"}], "title": "Uncharacterized protein 026R", "organism_species": "Invertebrate iridescent virus 6 (IIV-6) (Chilo iridescent virus)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Betairidovirinae", "Iridovirus"], "references": [{"PubMed": "17239238"}, {"DOI": "10.1186/1743-422x-4-11"}]}
-{"pid": " Q6GZU9", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 49"}], "title": "Uncharacterized protein 027R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}
-{"pid": " Q6GZU8", "dates": [{"date": "2011-06-28", "date_info": "integrated into UniProtKB/Swiss-Prot"}, {"date": "2004-07-19", "date_info": "sequence version 1"}, {"date": "2023-09-13", "date_info": "entry version 55"}], "title": "Uncharacterized protein 028R", "organism_species": "Frog virus 3 (isolate Goorha) (FV-3)", "subjects": ["Viruses", "Varidnaviria", "Bamfordvirae", "Nucleocytoviricota", "Megaviricetes", "Pimascovirales", "Iridoviridae", "Alphairidovirinae", "Ranavirus"], "references": [{"PubMed": "15165820"}, {"DOI": "10.1016/j.virol.2004.02.019"}]}

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/RelationAggregator.java

@@ -1,57 +0,0 @@
-
-package eu.dnetlib.dhp.oa.dedup;
-
-import java.util.Objects;
-
-import org.apache.spark.sql.Encoder;
-import org.apache.spark.sql.Encoders;
-import org.apache.spark.sql.expressions.Aggregator;
-
-import eu.dnetlib.dhp.schema.oaf.Relation;
-
-public class RelationAggregator extends Aggregator<Relation, Relation, Relation> {
-
-	private static final Relation ZERO = new Relation();
-
-	@Override
-	public Relation zero() {
-		return ZERO;
-	}
-
-	@Override
-	public Relation reduce(Relation b, Relation a) {
-		return mergeRel(b, a);
-	}
-
-	@Override
-	public Relation merge(Relation b, Relation a) {
-		return mergeRel(b, a);
-	}
-
-	@Override
-	public Relation finish(Relation r) {
-		return r;
-	}
-
-	private Relation mergeRel(Relation b, Relation a) {
-		if (Objects.equals(b, ZERO)) {
-			return a;
-		}
-		if (Objects.equals(a, ZERO)) {
-			return b;
-		}
-
-		b.mergeFrom(a);
-		return b;
-	}
-
-	@Override
-	public Encoder<Relation> bufferEncoder() {
-		return Encoders.kryo(Relation.class);
-	}
-
-	@Override
-	public Encoder<Relation> outputEncoder() {
-		return Encoders.kryo(Relation.class);
-	}
-}

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkCleanRelation.scala

@@ -1,78 +0,0 @@
-package eu.dnetlib.dhp.oa.dedup
-
-import eu.dnetlib.dhp.application.ArgumentApplicationParser
-import eu.dnetlib.dhp.common.HdfsSupport
-import eu.dnetlib.dhp.schema.oaf.Relation
-import eu.dnetlib.dhp.utils.ISLookupClientFactory
-import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService
-import org.apache.commons.io.IOUtils
-import org.apache.spark.SparkConf
-import org.apache.spark.sql._
-import org.apache.spark.sql.functions.col
-import org.apache.spark.sql.types.{DataTypes, StructField, StructType}
-import org.slf4j.LoggerFactory
-
-object SparkCleanRelation {
-  private val log = LoggerFactory.getLogger(classOf[SparkCleanRelation])
-
-  @throws[Exception]
-  def main(args: Array[String]): Unit = {
-    val parser = new ArgumentApplicationParser(
-      IOUtils.toString(
-        classOf[SparkCleanRelation].getResourceAsStream("/eu/dnetlib/dhp/oa/dedup/cleanRelation_parameters.json")
-      )
-    )
-    parser.parseArgument(args)
-    val conf = new SparkConf
-
-    new SparkCleanRelation(parser, AbstractSparkAction.getSparkSession(conf))
-      .run(ISLookupClientFactory.getLookUpService(parser.get("isLookUpUrl")))
-  }
-}
-
-class SparkCleanRelation(parser: ArgumentApplicationParser, spark: SparkSession)
-    extends AbstractSparkAction(parser, spark) {
-  override def run(isLookUpService: ISLookUpService): Unit = {
-    val graphBasePath = parser.get("graphBasePath")
-    val inputPath = parser.get("inputPath")
-    val outputPath = parser.get("outputPath")
-
-    SparkCleanRelation.log.info("graphBasePath: '{}'", graphBasePath)
-    SparkCleanRelation.log.info("inputPath: '{}'", inputPath)
-    SparkCleanRelation.log.info("outputPath: '{}'", outputPath)
-
-    AbstractSparkAction.removeOutputDir(spark, outputPath)
-
-    val entities =
-      Seq("datasource", "project", "organization", "publication", "dataset", "software", "otherresearchproduct")
-
-    val idsSchema = StructType.fromDDL("`id` STRING, `dataInfo` STRUCT<`deletedbyinference`:BOOLEAN,`invisible`:BOOLEAN>")
-
-    val emptyIds = spark.createDataFrame(spark.sparkContext.emptyRDD[Row].setName("empty"),
-      idsSchema)
-
-    val ids = entities
-      .foldLeft(emptyIds)((ds, entity) => {
-        val entityPath = graphBasePath + '/' + entity
-        if (HdfsSupport.exists(entityPath, spark.sparkContext.hadoopConfiguration)) {
-          ds.union(spark.read.schema(idsSchema).json(entityPath))
-        } else {
-          ds
-        }
-      })
-      .filter("dataInfo.deletedbyinference != true AND dataInfo.invisible != true")
-      .select("id")
-      .distinct()
-
-    val relations = spark.read.schema(Encoders.bean(classOf[Relation]).schema).json(inputPath)
-      .filter("dataInfo.deletedbyinference != true AND dataInfo.invisible != true")
-
-    AbstractSparkAction.save(
-      relations
-        .join(ids, col("source") === ids("id"), "leftsemi")
-        .join(ids, col("target") === ids("id"), "leftsemi"),
-      outputPath,
-      SaveMode.Overwrite
-    )
-  }
-}

dhp-workflows/dhp-dedup-openaire/src/main/java/eu/dnetlib/dhp/oa/dedup/SparkPropagateRelation.java

@@ -3,23 +3,19 @@ package eu.dnetlib.dhp.oa.dedup;
 
 import static org.apache.spark.sql.functions.col;
 
-import java.util.Arrays;
-import java.util.Collections;
-import java.util.Iterator;
-import java.util.Objects;
-
-import org.apache.commons.beanutils.BeanUtils;
 import org.apache.commons.io.IOUtils;
-import org.apache.commons.lang3.StringUtils;
 import org.apache.spark.SparkConf;
-import org.apache.spark.api.java.function.FilterFunction;
 import org.apache.spark.api.java.function.MapFunction;
 import org.apache.spark.api.java.function.ReduceFunction;
 import org.apache.spark.sql.*;
+import org.apache.spark.sql.catalyst.encoders.RowEncoder;
+import org.apache.spark.sql.types.StructType;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import eu.dnetlib.dhp.application.ArgumentApplicationParser;
+import eu.dnetlib.dhp.common.HdfsSupport;
+import eu.dnetlib.dhp.schema.common.EntityType;
 import eu.dnetlib.dhp.schema.common.ModelConstants;
 import eu.dnetlib.dhp.schema.common.ModelSupport;
 import eu.dnetlib.dhp.schema.oaf.DataInfo;
@@ -70,73 +66,63 @@ public class SparkPropagateRelation extends AbstractSparkAction {
 		log.info("workingPath: '{}'", workingPath);
 		log.info("graphOutputPath: '{}'", graphOutputPath);
 
-		final String outputRelationPath = DedupUtility.createEntityPath(graphOutputPath, "relation");
-		removeOutputDir(spark, outputRelationPath);
-
 		Dataset<Relation> mergeRels = spark
-			.read()
+				.read()
-			.load(DedupUtility.createMergeRelPath(workingPath, "*", "*"))
+				.load(DedupUtility.createMergeRelPath(workingPath, "*", "*"))
-			.as(REL_BEAN_ENC);
+				.as(REL_BEAN_ENC);
 
 		// <mergedObjectID, dedupID>
-		Dataset<Row> mergedIds = mergeRels
+		Dataset<Row> idsToMerge = mergeRels
-			.where(col("relClass").equalTo(ModelConstants.MERGES))
+				.where(col("relClass").equalTo(ModelConstants.MERGES))
-			.select(col("source").as("dedupID"), col("target").as("mergedObjectID"))
+				.select(col("source").as("dedupID"), col("target").as("mergedObjectID"))
-			.distinct()
+				.distinct();
-			.cache();
 
 		Dataset<Row> allRels = spark
-			.read()
+				.read()
-			.schema(REL_BEAN_ENC.schema())
+				.schema(REL_BEAN_ENC.schema())
-			.json(DedupUtility.createEntityPath(graphBasePath, "relation"));
+				.json(graphBasePath + "/relation");
 
 		Dataset<Relation> dedupedRels = allRels
-			.joinWith(mergedIds, allRels.col("source").equalTo(mergedIds.col("mergedObjectID")), "left_outer")
+				.joinWith(idsToMerge, allRels.col("source").equalTo(idsToMerge.col("mergedObjectID")), "left_outer")
-			.joinWith(mergedIds, col("_1.target").equalTo(mergedIds.col("mergedObjectID")), "left_outer")
+				.joinWith(idsToMerge, col("_1.target").equalTo(idsToMerge.col("mergedObjectID")), "left_outer")
-			.select("_1._1", "_1._2.dedupID", "_2.dedupID")
+				.select("_1._1", "_1._2.dedupID", "_2.dedupID")
-			.as(Encoders.tuple(REL_BEAN_ENC, Encoders.STRING(), Encoders.STRING()))
+				.as(Encoders.tuple(REL_BEAN_ENC, Encoders.STRING(), Encoders.STRING()))
-			.flatMap(SparkPropagateRelation::addInferredRelations, REL_KRYO_ENC);
+				.map((MapFunction<Tuple3<Relation, String, String>, Relation>) t -> {
+					Relation rel = t._1();
+					String newSource = t._2();
+					String newTarget = t._3();
 
-		Dataset<Relation> processedRelations = distinctRelations(
+					if (rel.getDataInfo() == null) {
-			dedupedRels.union(mergeRels.map((MapFunction<Relation, Relation>) r -> r, REL_KRYO_ENC)))
+						rel.setDataInfo(new DataInfo());
-				.filter((FilterFunction<Relation>) r -> !Objects.equals(r.getSource(), r.getTarget()));
+					}
 
-		save(processedRelations, outputRelationPath, SaveMode.Overwrite);
+					if (newSource != null || newTarget != null) {
-	}
+						rel.getDataInfo().setDeletedbyinference(false);
 
-	private static Iterator<Relation> addInferredRelations(Tuple3<Relation, String, String> t) throws Exception {
+						if (newSource != null)
-		Relation existingRel = t._1();
+							rel.setSource(newSource);
-		String newSource = t._2();
-		String newTarget = t._3();
 
-		if (newSource == null && newTarget == null) {
+						if (newTarget != null)
-			return Collections.singleton(t._1()).iterator();
+							rel.setTarget(newTarget);
-		}
+					}
 
-		// update existing relation
+					return rel;
-		if (existingRel.getDataInfo() == null) {
+				}, REL_BEAN_ENC);
-			existingRel.setDataInfo(new DataInfo());
-		}
-		existingRel.getDataInfo().setDeletedbyinference(true);
 
-		// Create new relation inferred by dedupIDs
+		// ids of records that are both not deletedbyinference and not invisible
-		Relation inferredRel = (Relation) BeanUtils.cloneBean(existingRel);
+		Dataset<Row> ids = validIds(spark, graphBasePath);
 
-		inferredRel.setDataInfo((DataInfo) BeanUtils.cloneBean(existingRel.getDataInfo()));
+		// filter relations that point to valid records, can force them to be visible
-		inferredRel.getDataInfo().setDeletedbyinference(false);
+		Dataset<Relation> cleanedRels = dedupedRels
+				.join(ids, col("source").equalTo(ids.col("id")), "leftsemi")
+				.join(ids, col("target").equalTo(ids.col("id")), "leftsemi")
+				.as(REL_BEAN_ENC)
+				.map((MapFunction<Relation, Relation>) r -> {
+					r.getDataInfo().setInvisible(false);
+					return r;
+				}, REL_KRYO_ENC);
 
-		if (newSource != null)
+		Dataset<Relation> distinctRels = cleanedRels
-			inferredRel.setSource(newSource);
-
-		if (newTarget != null)
-			inferredRel.setTarget(newTarget);
-
-		return Arrays.asList(existingRel, inferredRel).iterator();
-	}
-
-	private Dataset<Relation> distinctRelations(Dataset<Relation> rels) {
-		return rels
-			.filter(getRelationFilterFunction())
 			.groupByKey(
 				(MapFunction<Relation, String>) r -> String
 					.join(" ", r.getSource(), r.getTarget(), r.getRelType(), r.getSubRelType(), r.getRelClass()),
@@ -146,13 +132,33 @@ public class SparkPropagateRelation extends AbstractSparkAction {
 				return b;
 			})
 			.map((MapFunction<Tuple2<String, Relation>, Relation>) Tuple2::_2, REL_BEAN_ENC);
+
+		final String outputRelationPath = graphOutputPath + "/relation";
+		removeOutputDir(spark, outputRelationPath);
+		save(
+			distinctRels
+				.union(mergeRels)
+				.filter("source != target AND dataInfo.deletedbyinference != true AND dataInfo.invisible != true"),
+			outputRelationPath,
+			SaveMode.Overwrite);
 	}
 
-	private FilterFunction<Relation> getRelationFilterFunction() {
+	static Dataset<Row> validIds(SparkSession spark, String graphBasePath) {
-		return r -> StringUtils.isNotBlank(r.getSource()) ||
+		StructType idsSchema = StructType
-			StringUtils.isNotBlank(r.getTarget()) ||
+			.fromDDL("`id` STRING, `dataInfo` STRUCT<`deletedbyinference`:BOOLEAN,`invisible`:BOOLEAN>");
-			StringUtils.isNotBlank(r.getRelType()) ||
+
-			StringUtils.isNotBlank(r.getSubRelType()) ||
+		Dataset<Row> allIds = spark.emptyDataset(RowEncoder.apply(idsSchema));
-			StringUtils.isNotBlank(r.getRelClass());
+
+		for (EntityType entityType : ModelSupport.entityTypes.keySet()) {
+			String entityPath = graphBasePath + '/' + entityType.name();
+			if (HdfsSupport.exists(entityPath, spark.sparkContext().hadoopConfiguration())) {
+				allIds = allIds.union(spark.read().schema(idsSchema).json(entityPath));
+			}
+		}
+
+		return allIds
+			.filter("dataInfo.deletedbyinference != true AND dataInfo.invisible != true")
+			.select("id")
+			.distinct();
 	}
 }

dhp-workflows/dhp-dedup-openaire/src/main/resources/eu/dnetlib/dhp/oa/dedup/cleanRelation_parameters.json

@@ -1,20 +0,0 @@
-[
-  {
-    "paramName": "i",
-    "paramLongName": "graphBasePath",
-    "paramDescription": "the base path of raw graph",
-    "paramRequired": true
-  },
-  {
-    "paramName": "w",
-    "paramLongName": "inputPath",
-    "paramDescription": "the path to the input relation to cleanup",
-    "paramRequired": true
-  },
-  {
-    "paramName": "o",
-    "paramLongName": "outputPath",
-    "paramDescription": "the path of the output relation cleaned",
-    "paramRequired": true
-  }
-]

dhp-workflows/dhp-dedup-openaire/src/main/resources/eu/dnetlib/dhp/oa/dedup/consistency/oozie_app/workflow.xml

@@ -100,35 +100,9 @@
                 --conf spark.sql.shuffle.partitions=15000
             </spark-opts>
             <arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
-            <arg>--graphOutputPath</arg><arg>${workingPath}/propagaterelation/</arg>
+            <arg>--graphOutputPath</arg><arg>${graphOutputPath}</arg>
             <arg>--workingPath</arg><arg>${workingPath}</arg>
         </spark>
-        <ok to="CleanRelation"/>
-        <error to="Kill"/>
-    </action>
-
-    <action name="CleanRelation">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn</master>
-            <mode>cluster</mode>
-            <name>Clean Relations</name>
-            <class>eu.dnetlib.dhp.oa.dedup.SparkCleanRelation</class>
-            <jar>dhp-dedup-openaire-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-memory=${sparkExecutorMemory}
-                --conf spark.executor.memoryOverhead=${sparkExecutorMemoryOverhead}
-                --executor-cores=${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.shuffle.partitions=15000
-            </spark-opts>
-            <arg>--graphBasePath</arg><arg>${graphBasePath}</arg>
-            <arg>--inputPath</arg><arg>${workingPath}/propagaterelation/relation</arg>
-            <arg>--outputPath</arg><arg>${graphOutputPath}/relation</arg>
-        </spark>
         <ok to="group_entities"/>
         <error to="Kill"/>
     </action>
@@ -152,31 +126,7 @@
                 --conf spark.sql.shuffle.partitions=15000
             </spark-opts>
             <arg>--graphInputPath</arg><arg>${graphBasePath}</arg>
-            <arg>--outputPath</arg><arg>${workingPath}/grouped_entities</arg>
+            <arg>--checkpointPath</arg><arg>${workingPath}/grouped_entities</arg>
-        </spark>
-        <ok to="dispatch_entities"/>
-        <error to="Kill"/>
-    </action>
-
-    <action name="dispatch_entities">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn</master>
-            <mode>cluster</mode>
-            <name>Dispatch grouped entitities</name>
-            <class>eu.dnetlib.dhp.oa.merge.DispatchEntitiesSparkJob</class>
-            <jar>dhp-dedup-openaire-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-memory=${sparkExecutorMemory}
-                --conf spark.executor.memoryOverhead=${sparkExecutorMemoryOverhead}
-                --executor-cores=${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.shuffle.partitions=7680
-            </spark-opts>
-            <arg>--inputPath</arg><arg>${workingPath}/grouped_entities</arg>
             <arg>--outputPath</arg><arg>${graphOutputPath}</arg>
             <arg>--filterInvisible</arg><arg>${filterInvisible}</arg>
         </spark>

dhp-workflows/dhp-dedup-openaire/src/test/java/eu/dnetlib/dhp/oa/dedup/SparkDedupTest.java

@@ -3,7 +3,6 @@ package eu.dnetlib.dhp.oa.dedup;
 
 import static java.nio.file.Files.createTempDirectory;
 
-import static org.apache.spark.sql.functions.col;
 import static org.apache.spark.sql.functions.count;
 import static org.junit.jupiter.api.Assertions.*;
 import static org.mockito.Mockito.lenient;
@@ -23,14 +22,13 @@ import java.util.stream.Collectors;
 import org.apache.commons.io.FileUtils;
 import org.apache.commons.io.IOUtils;
 import org.apache.spark.SparkConf;
-import org.apache.spark.api.java.JavaPairRDD;
-import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.api.java.function.FilterFunction;
 import org.apache.spark.api.java.function.MapFunction;
-import org.apache.spark.api.java.function.PairFunction;
-import org.apache.spark.sql.*;
 import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Encoders;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.SparkSession;
 import org.junit.jupiter.api.*;
 import org.junit.jupiter.api.extension.ExtendWith;
 import org.mockito.Mock;
@@ -46,8 +44,6 @@ import eu.dnetlib.dhp.schema.common.ModelConstants;
 import eu.dnetlib.dhp.schema.oaf.*;
 import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
 import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
-import eu.dnetlib.pace.util.MapDocumentUtil;
-import scala.Tuple2;
 
 @ExtendWith(MockitoExtension.class)
 @TestMethodOrder(MethodOrderer.OrderAnnotation.class)
@@ -62,6 +58,8 @@ public class SparkDedupTest implements Serializable {
 	private static String testGraphBasePath;
 	private static String testOutputBasePath;
 	private static String testDedupGraphBasePath;
+	private static String testConsistencyGraphBasePath;
+
 	private static final String testActionSetId = "test-orchestrator";
 	private static String whitelistPath;
 	private static List<String> whiteList;
@@ -75,6 +73,7 @@ public class SparkDedupTest implements Serializable {
 			.get(SparkDedupTest.class.getResource("/eu/dnetlib/dhp/dedup/entities").toURI())
 			.toFile()
 			.getAbsolutePath();
+
 		testOutputBasePath = createTempDirectory(SparkDedupTest.class.getSimpleName() + "-")
 			.toAbsolutePath()
 			.toString();
@@ -83,6 +82,10 @@ public class SparkDedupTest implements Serializable {
 			.toAbsolutePath()
 			.toString();
 
+		testConsistencyGraphBasePath = createTempDirectory(SparkDedupTest.class.getSimpleName() + "-")
+			.toAbsolutePath()
+			.toString();
+
 		whitelistPath = Paths
 			.get(SparkDedupTest.class.getResource("/eu/dnetlib/dhp/dedup/whitelist.simrels.txt").toURI())
 			.toFile()
@@ -674,22 +677,45 @@ public class SparkDedupTest implements Serializable {
 		assertEquals(mergedOrp, deletedOrp);
 	}
 
+	@Test
+	@Order(6)
+	void copyRelationsNoOpenorgsTest() throws Exception {
+
+		ArgumentApplicationParser parser = new ArgumentApplicationParser(
+			IOUtils
+				.toString(
+					SparkCopyRelationsNoOpenorgs.class
+						.getResourceAsStream(
+							"/eu/dnetlib/dhp/oa/dedup/updateEntity_parameters.json")));
+		parser
+			.parseArgument(
+				new String[] {
+					"-i", testGraphBasePath, "-w", testOutputBasePath, "-o", testDedupGraphBasePath
+				});
+
+		new SparkCopyRelationsNoOpenorgs(parser, spark).run(isLookUpService);
+
+		final Dataset<Row> outputRels = spark.read().text(testDedupGraphBasePath + "/relation");
+
+		System.out.println(outputRels.count());
+		// assertEquals(2382, outputRels.count());
+	}
+
 	@Test
 	@Order(7)
 	void propagateRelationTest() throws Exception {
 
 		ArgumentApplicationParser parser = new ArgumentApplicationParser(
 			classPathResourceAsString("/eu/dnetlib/dhp/oa/dedup/propagateRelation_parameters.json"));
-		String outputRelPath = testDedupGraphBasePath + "/propagaterelation";
 		parser
 			.parseArgument(
 				new String[] {
-					"-i", testGraphBasePath, "-w", testOutputBasePath, "-o", outputRelPath
+					"-i", testDedupGraphBasePath, "-w", testOutputBasePath, "-o", testConsistencyGraphBasePath
 				});
 
 		new SparkPropagateRelation(parser, spark).run(isLookUpService);
 
-		long relations = jsc.textFile(outputRelPath + "/relation").count();
+		long relations = jsc.textFile(testDedupGraphBasePath + "/relation").count();
 
 //		assertEquals(4860, relations);
 		System.out.println("relations = " + relations);
@@ -699,95 +725,52 @@ public class SparkDedupTest implements Serializable {
 			.read()
 			.load(DedupUtility.createMergeRelPath(testOutputBasePath, "*", "*"))
 			.as(Encoders.bean(Relation.class));
-		final JavaPairRDD<String, String> mergedIds = mergeRels
-			.where("relClass == 'merges'")
-			.select(mergeRels.col("target"))
-			.distinct()
-			.toJavaRDD()
-			.mapToPair(
-				(PairFunction<Row, String, String>) r -> new Tuple2<String, String>(r.getString(0), "d"));
 
-		JavaRDD<String> toCheck = jsc
+		Dataset<Row> inputRels = spark
-			.textFile(outputRelPath + "/relation")
+			.read()
-			.mapToPair(json -> new Tuple2<>(MapDocumentUtil.getJPathString("$.source", json), json))
+			.json(testDedupGraphBasePath + "/relation");
-			.join(mergedIds)
-			.map(t -> t._2()._1())
-			.mapToPair(json -> new Tuple2<>(MapDocumentUtil.getJPathString("$.target", json), json))
-			.join(mergedIds)
-			.map(t -> t._2()._1());
 
-		long deletedbyinference = toCheck.filter(this::isDeletedByInference).count();
+		Dataset<Row> outputRels = spark
-		long updated = toCheck.count();
+			.read()
+			.json(testConsistencyGraphBasePath + "/relation");
 
-		assertEquals(updated, deletedbyinference);
+		assertEquals(
+			0, outputRels
+				.filter("dataInfo.deletedbyinference == true OR dataInfo.invisible == true")
+				.count());
+
+		assertEquals(
+			5, outputRels
+				.filter("relClass NOT IN ('merges', 'isMergedIn')")
+				.count());
+
+		assertEquals(5 + mergeRels.count(), outputRels.count());
 	}
 
 	@Test
 	@Order(8)
-	void testCleanBaseRelations() throws Exception {
+	void testCleanedPropagatedRelations() throws Exception {
-		ArgumentApplicationParser parser = new ArgumentApplicationParser(
-			classPathResourceAsString("/eu/dnetlib/dhp/oa/dedup/cleanRelation_parameters.json"));
-
-		// append dangling relations to be cleaned up
 		Dataset<Row> df_before = spark
 			.read()
 			.schema(Encoders.bean(Relation.class).schema())
-			.json(testGraphBasePath + "/relation");
+			.json(testDedupGraphBasePath + "/relation");
-		Dataset<Row> df_input = df_before
-			.unionByName(df_before.drop("source").withColumn("source", functions.lit("n/a")))
-			.unionByName(df_before.drop("target").withColumn("target", functions.lit("n/a")));
-		df_input.write().mode(SaveMode.Overwrite).json(testOutputBasePath + "_tmp");
-
-		parser
-			.parseArgument(
-				new String[] {
-					"--graphBasePath", testGraphBasePath,
-					"--inputPath", testGraphBasePath + "/relation",
-					"--outputPath", testDedupGraphBasePath + "/relation"
-				});
-
-		new SparkCleanRelation(parser, spark).run(isLookUpService);
 
 		Dataset<Row> df_after = spark
 			.read()
 			.schema(Encoders.bean(Relation.class).schema())
-			.json(testDedupGraphBasePath + "/relation");
+			.json(testConsistencyGraphBasePath + "/relation");
-
-		assertNotEquals(df_before.count(), df_input.count());
-		assertNotEquals(df_input.count(), df_after.count());
-		assertEquals(5, df_after.count());
-	}
-
-	@Test
-	@Order(9)
-	void testCleanDedupedRelations() throws Exception {
-		ArgumentApplicationParser parser = new ArgumentApplicationParser(
-			classPathResourceAsString("/eu/dnetlib/dhp/oa/dedup/cleanRelation_parameters.json"));
-
-		String inputRelPath = testDedupGraphBasePath + "/propagaterelation/relation";
-
-		// append dangling relations to be cleaned up
-		Dataset<Row> df_before = spark.read().schema(Encoders.bean(Relation.class).schema()).json(inputRelPath);
-
-		df_before.filter(col("dataInfo.deletedbyinference").notEqual(true)).show(50, false);
-
-		parser
-			.parseArgument(
-				new String[] {
-					"--graphBasePath", testGraphBasePath,
-					"--inputPath", inputRelPath,
-					"--outputPath", testDedupGraphBasePath + "/relation"
-				});
-
-		new SparkCleanRelation(parser, spark).run(isLookUpService);
-
-		Dataset<Row> df_after = spark
-			.read()
-			.schema(Encoders.bean(Relation.class).schema())
-			.json(testDedupGraphBasePath + "/relation");
 
 		assertNotEquals(df_before.count(), df_after.count());
-		assertEquals(0, df_after.count());
+
+		assertEquals(
+			0, df_after
+				.filter("dataInfo.deletedbyinference == true OR dataInfo.invisible == true")
+				.count());
+
+		assertEquals(
+			5, df_after
+				.filter("relClass NOT IN ('merges', 'isMergedIn')")
+				.count());
 	}
 
 	@Test
@@ -813,6 +796,7 @@ public class SparkDedupTest implements Serializable {
 	public static void finalCleanUp() throws IOException {
 		FileUtils.deleteDirectory(new File(testOutputBasePath));
 		FileUtils.deleteDirectory(new File(testDedupGraphBasePath));
+		FileUtils.deleteDirectory(new File(testConsistencyGraphBasePath));
 	}
 
 	public boolean isDeletedByInference(String s) {

dhp-workflows/dhp-dedup-openaire/src/test/java/eu/dnetlib/dhp/oa/dedup/SparkOpenorgsProvisionTest.java

@@ -3,6 +3,7 @@ package eu.dnetlib.dhp.oa.dedup;
 
 import static java.nio.file.Files.createTempDirectory;
 
+import static org.apache.spark.sql.functions.col;
 import static org.junit.jupiter.api.Assertions.assertEquals;
 import static org.mockito.Mockito.lenient;
 
@@ -15,10 +16,6 @@ import java.nio.file.Paths;
 import org.apache.commons.io.FileUtils;
 import org.apache.commons.io.IOUtils;
 import org.apache.spark.SparkConf;
-import org.apache.spark.api.java.JavaPairRDD;
-import org.apache.spark.api.java.JavaRDD;
-import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.api.java.function.PairFunction;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Encoders;
 import org.apache.spark.sql.Row;
@@ -33,8 +30,6 @@ import eu.dnetlib.dhp.application.ArgumentApplicationParser;
 import eu.dnetlib.dhp.schema.oaf.Relation;
 import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpException;
 import eu.dnetlib.enabling.is.lookup.rmi.ISLookUpService;
-import eu.dnetlib.pace.util.MapDocumentUtil;
-import scala.Tuple2;
 
 @ExtendWith(MockitoExtension.class)
 @TestMethodOrder(MethodOrderer.OrderAnnotation.class)
@@ -44,11 +39,11 @@ public class SparkOpenorgsProvisionTest implements Serializable {
 	ISLookUpService isLookUpService;
 
 	private static SparkSession spark;
-	private static JavaSparkContext jsc;
 
 	private static String testGraphBasePath;
 	private static String testOutputBasePath;
 	private static String testDedupGraphBasePath;
+	private static String testConsistencyGraphBasePath;
 	private static final String testActionSetId = "test-orchestrator";
 
 	@BeforeAll
@@ -64,6 +59,9 @@ public class SparkOpenorgsProvisionTest implements Serializable {
 		testDedupGraphBasePath = createTempDirectory(SparkOpenorgsProvisionTest.class.getSimpleName() + "-")
 			.toAbsolutePath()
 			.toString();
+		testConsistencyGraphBasePath = createTempDirectory(SparkOpenorgsProvisionTest.class.getSimpleName() + "-")
+			.toAbsolutePath()
+			.toString();
 
 		FileUtils.deleteDirectory(new File(testOutputBasePath));
 		FileUtils.deleteDirectory(new File(testDedupGraphBasePath));
@@ -76,8 +74,13 @@ public class SparkOpenorgsProvisionTest implements Serializable {
 			.master("local[*]")
 			.config(conf)
 			.getOrCreate();
+	}
 
-		jsc = JavaSparkContext.fromSparkContext(spark.sparkContext());
+	@AfterAll
+	public static void finalCleanUp() throws IOException {
+		FileUtils.deleteDirectory(new File(testOutputBasePath));
+		FileUtils.deleteDirectory(new File(testDedupGraphBasePath));
+		FileUtils.deleteDirectory(new File(testConsistencyGraphBasePath));
 	}
 
 	@BeforeEach
@@ -186,26 +189,21 @@ public class SparkOpenorgsProvisionTest implements Serializable {
 
 		new SparkUpdateEntity(parser, spark).run(isLookUpService);
 
-		long organizations = jsc.textFile(testDedupGraphBasePath + "/organization").count();
+		Dataset<Row> organizations = spark.read().json(testDedupGraphBasePath + "/organization");
 
-		long mergedOrgs = spark
+		Dataset<Row> mergedOrgs = spark
 			.read()
 			.load(testOutputBasePath + "/" + testActionSetId + "/organization_mergerel")
-			.as(Encoders.bean(Relation.class))
 			.where("relClass=='merges'")
-			.javaRDD()
+			.select("target")
-			.map(Relation::getTarget)
+			.distinct();
-			.distinct()
-			.count();
 
-		assertEquals(80, organizations);
+		assertEquals(80, organizations.count());
 
-		long deletedOrgs = jsc
+		Dataset<Row> deletedOrgs = organizations
-			.textFile(testDedupGraphBasePath + "/organization")
+			.filter("dataInfo.deletedbyinference = TRUE");
-			.filter(this::isDeletedByInference)
-			.count();
 
-		assertEquals(mergedOrgs, deletedOrgs);
+		assertEquals(mergedOrgs.count(), deletedOrgs.count());
 	}
 
 	@Test
@@ -226,10 +224,9 @@ public class SparkOpenorgsProvisionTest implements Serializable {
 
 		new SparkCopyRelationsNoOpenorgs(parser, spark).run(isLookUpService);
 
-		final JavaRDD<String> rels = jsc.textFile(testDedupGraphBasePath + "/relation");
+		final Dataset<Row> outputRels = spark.read().text(testDedupGraphBasePath + "/relation");
-
-		assertEquals(2382, rels.count());
 
+		assertEquals(2382, outputRels.count());
 	}
 
 	@Test
@@ -244,51 +241,41 @@ public class SparkOpenorgsProvisionTest implements Serializable {
 		parser
 			.parseArgument(
 				new String[] {
-					"-i", testGraphBasePath, "-w", testOutputBasePath, "-o", testDedupGraphBasePath
+					"-i", testDedupGraphBasePath, "-w", testOutputBasePath, "-o", testConsistencyGraphBasePath
 				});
 
 		new SparkPropagateRelation(parser, spark).run(isLookUpService);
 
-		long relations = jsc.textFile(testDedupGraphBasePath + "/relation").count();
-
-		assertEquals(4896, relations);
-
-		// check deletedbyinference
 		final Dataset<Relation> mergeRels = spark
 			.read()
 			.load(DedupUtility.createMergeRelPath(testOutputBasePath, "*", "*"))
 			.as(Encoders.bean(Relation.class));
-		final JavaPairRDD<String, String> mergedIds = mergeRels
+
+		Dataset<Row> inputRels = spark
+			.read()
+			.json(testDedupGraphBasePath + "/relation");
+
+		Dataset<Row> outputRels = spark
+			.read()
+			.json(testConsistencyGraphBasePath + "/relation");
+
+		final Dataset<Row> mergedIds = mergeRels
 			.where("relClass == 'merges'")
-			.select(mergeRels.col("target"))
+			.select(col("target").as("id"))
-			.distinct()
+			.distinct();
-			.toJavaRDD()
-			.mapToPair(
-				(PairFunction<Row, String, String>) r -> new Tuple2<String, String>(r.getString(0), "d"));
 
-		JavaRDD<String> toCheck = jsc
+		Dataset<Row> toUpdateRels = inputRels
-			.textFile(testDedupGraphBasePath + "/relation")
+			.as("rel")
-			.mapToPair(json -> new Tuple2<>(MapDocumentUtil.getJPathString("$.source", json), json))
+			.join(mergedIds.as("s"), col("rel.source").equalTo(col("s.id")), "left_outer")
-			.join(mergedIds)
+			.join(mergedIds.as("t"), col("rel.target").equalTo(col("t.id")), "left_outer")
-			.map(t -> t._2()._1())
+			.filter("s.id IS NOT NULL OR t.id IS NOT NULL")
-			.mapToPair(json -> new Tuple2<>(MapDocumentUtil.getJPathString("$.target", json), json))
+			.distinct();
-			.join(mergedIds)
-			.map(t -> t._2()._1());
 
-		long deletedbyinference = toCheck.filter(this::isDeletedByInference).count();
+		Dataset<Row> updatedRels = inputRels
-		long updated = toCheck.count();
+			.select("source", "target", "relClass")
+			.except(outputRels.select("source", "target", "relClass"));
 
-		assertEquals(updated, deletedbyinference);
+		assertEquals(toUpdateRels.count(), updatedRels.count());
+		assertEquals(140, outputRels.count());
 	}
-
-	@AfterAll
-	public static void finalCleanUp() throws IOException {
-		FileUtils.deleteDirectory(new File(testOutputBasePath));
-		FileUtils.deleteDirectory(new File(testDedupGraphBasePath));
-	}
-
-	public boolean isDeletedByInference(String s) {
-		return s.contains("\"deletedbyinference\":true");
-	}
-
 }

dhp-workflows/dhp-distcp/pom.xml

@@ -0,0 +1,13 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <parent>
+        <artifactId>dhp-workflows</artifactId>
+        <groupId>eu.dnetlib.dhp</groupId>
+        <version>1.2.5-SNAPSHOT</version>
+    </parent>
+    <modelVersion>4.0.0</modelVersion>
+
+    <artifactId>dhp-distcp</artifactId>
+
+
+</project>

dhp-workflows/dhp-distcp/src/main/resources/eu/dnetlib/dhp/distcp/oozie_app/config-default.xml

@@ -0,0 +1,18 @@
+<configuration>
+    <property>
+        <name>jobTracker</name>
+        <value>yarnRM</value>
+    </property>
+    <property>
+        <name>nameNode</name>
+        <value>hdfs://nameservice1</value>
+    </property>
+    <property>
+        <name>sourceNN</name>
+        <value>webhdfs://namenode2.hadoop.dm.openaire.eu:50071</value>
+    </property>
+    <property>
+        <name>oozie.use.system.libpath</name>
+        <value>true</value>
+    </property>
+</configuration>

dhp-workflows/dhp-distcp/src/main/resources/eu/dnetlib/dhp/distcp/oozie_app/workflow.xml

@@ -0,0 +1,46 @@
+<workflow-app name="distcp" xmlns="uri:oozie:workflow:0.5">
+    <parameters>
+        <property>
+            <name>sourceNN</name>
+            <description>the source name node</description>
+        </property>
+        <property>
+            <name>sourcePath</name>
+            <description>the source path</description>
+        </property>
+        <property>
+            <name>targetPath</name>
+            <description>the target path</description>
+        </property>
+        <property>
+            <name>hbase_dump_distcp_memory_mb</name>
+            <value>6144</value>
+            <description>memory for distcp action copying InfoSpace dump from remote cluster</description>
+        </property>
+        <property>
+            <name>hbase_dump_distcp_num_maps</name>
+            <value>1</value>
+            <description>maximum number of simultaneous copies of InfoSpace dump from remote location</description>
+        </property>
+    </parameters>
+
+    <start to="distcp"/>
+
+    <kill name="Kill">
+        <message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
+    </kill>
+
+    <action name="distcp">
+        <distcp xmlns="uri:oozie:distcp-action:0.2">
+            <arg>-Dmapreduce.map.memory.mb=${hbase_dump_distcp_memory_mb}</arg>
+            <arg>-pb</arg>
+            <arg>-m ${hbase_dump_distcp_num_maps}</arg>
+            <arg>${sourceNN}/${sourcePath}</arg>
+            <arg>${nameNode}/${targetPath}</arg>
+        </distcp>
+        <ok to="End" />
+        <error to="Kill" />
+    </action>
+
+    <end name="End"/>
+</workflow-app>

dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/PropagationConstant.java

@@ -5,7 +5,6 @@ import java.util.ArrayList;
 import java.util.List;
 import java.util.Optional;
 
-import org.apache.hadoop.conf.Configuration;
 import org.apache.spark.api.java.function.MapFunction;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Encoders;

dhp-workflows/dhp-enrichment/src/main/java/eu/dnetlib/dhp/countrypropagation/SparkCountryPropagationJob.java

@@ -14,7 +14,6 @@ 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.Row;
 import org.apache.spark.sql.SaveMode;
 import org.apache.spark.sql.SparkSession;
 import org.slf4j.Logger;
@@ -85,26 +84,19 @@ public class SparkCountryPropagationJob {
 		Dataset<R> res = readPath(spark, sourcePath, resultClazz);
 
 		log.info("Reading prepared info: {}", preparedInfoPath);
-		final Dataset<Row> preparedInfoRaw = spark
+		Dataset<ResultCountrySet> prepared = spark
 			.read()
-			.json(preparedInfoPath);
+			.json(preparedInfoPath)
+			.as(Encoders.bean(ResultCountrySet.class));
+
+		res
+			.joinWith(prepared, res.col("id").equalTo(prepared.col("resultId")), "left_outer")
+			.map(getCountryMergeFn(), Encoders.bean(resultClazz))
+			.write()
+			.option("compression", "gzip")
+			.mode(SaveMode.Overwrite)
+			.json(outputPath);
 
-		if (!preparedInfoRaw.isEmpty()) {
-			final Dataset<ResultCountrySet> prepared = preparedInfoRaw.as(Encoders.bean(ResultCountrySet.class));
-			res
-				.joinWith(prepared, res.col("id").equalTo(prepared.col("resultId")), "left_outer")
-				.map(getCountryMergeFn(), Encoders.bean(resultClazz))
-				.write()
-				.option("compression", "gzip")
-				.mode(SaveMode.Overwrite)
-				.json(outputPath);
-		} else {
-			res
-				.write()
-				.option("compression", "gzip")
-				.mode(SaveMode.Overwrite)
-				.json(outputPath);
-		}
 	}
 
 	private static <R extends Result> MapFunction<Tuple2<R, ResultCountrySet>, R> getCountryMergeFn() {

dhp-workflows/dhp-enrichment/src/main/resources/eu/dnetlib/dhp/resulttocommunityfromsemrel/oozie_app/workflow.xml

@@ -260,7 +260,6 @@
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
                 --conf spark.dynamicAllocation.enabled=true
                 --conf spark.dynamicAllocation.maxExecutors=${spark2MaxExecutors}
-                --conf spark.sql.shuffle.partitions=10000
             </spark-opts>
             <arg>--preparedInfoPath</arg><arg>${workingDir}/preparedInfo/mergedCommunityAssoc</arg>
             <arg>--sourcePath</arg><arg>${sourcePath}/publication</arg>
@@ -290,7 +289,6 @@
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
                 --conf spark.dynamicAllocation.enabled=true
                 --conf spark.dynamicAllocation.maxExecutors=${spark2MaxExecutors}
-                --conf spark.sql.shuffle.partitions=5000
             </spark-opts>
             <arg>--preparedInfoPath</arg><arg>${workingDir}/preparedInfo/mergedCommunityAssoc</arg>
             <arg>--sourcePath</arg><arg>${sourcePath}/dataset</arg>
@@ -320,7 +318,6 @@
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
                 --conf spark.dynamicAllocation.enabled=true
                 --conf spark.dynamicAllocation.maxExecutors=${spark2MaxExecutors}
-                --conf spark.sql.shuffle.partitions=2000
             </spark-opts>
             <arg>--preparedInfoPath</arg><arg>${workingDir}/preparedInfo/mergedCommunityAssoc</arg>
             <arg>--sourcePath</arg><arg>${sourcePath}/otherresearchproduct</arg>
@@ -350,7 +347,6 @@
                 --conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
                 --conf spark.dynamicAllocation.enabled=true
                 --conf spark.dynamicAllocation.maxExecutors=${spark2MaxExecutors}
-                --conf spark.sql.shuffle.partitions=1000
             </spark-opts>
             <arg>--preparedInfoPath</arg><arg>${workingDir}/preparedInfo/mergedCommunityAssoc</arg>
             <arg>--sourcePath</arg><arg>${sourcePath}/software</arg>

dhp-workflows/dhp-graph-mapper/src/main/resources/eu/dnetlib/dhp/oa/graph/group/oozie_app/workflow.xml

@@ -96,30 +96,7 @@
                 --conf spark.sql.shuffle.partitions=15000
             </spark-opts>
             <arg>--graphInputPath</arg><arg>${graphBasePath}</arg>
-            <arg>--outputPath</arg><arg>${workingPath}/grouped_entities</arg>
+            <arg>--checkpointPath</arg><arg>${workingPath}/grouped_entities</arg>
-        </spark>
-        <ok to="dispatch_entities"/>
-        <error to="Kill"/>
-    </action>
-
-    <action name="dispatch_entities">
-        <spark xmlns="uri:oozie:spark-action:0.2">
-            <master>yarn</master>
-            <mode>cluster</mode>
-            <name>Dispatch grouped entities</name>
-            <class>eu.dnetlib.dhp.oa.merge.DispatchEntitiesSparkJob</class>
-            <jar>dhp-graph-mapper-${projectVersion}.jar</jar>
-            <spark-opts>
-                --executor-cores=${sparkExecutorCores}
-                --executor-memory=${sparkExecutorMemory}
-                --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.shuffle.partitions=7680
-            </spark-opts>
-            <arg>--inputPath</arg><arg>${workingPath}/grouped_entities</arg>
             <arg>--outputPath</arg><arg>${graphOutputPath}</arg>
             <arg>--filterInvisible</arg><arg>${filterInvisible}</arg>
         </spark>

dhp-workflows/dhp-graph-mapper/src/test/java/eu/dnetlib/dhp/oa/graph/group/GroupEntitiesSparkJobTest.java

@@ -1,16 +1,15 @@
 
 package eu.dnetlib.dhp.oa.graph.group;
 
-import static org.junit.jupiter.api.Assertions.assertEquals;
+import com.fasterxml.jackson.databind.DeserializationFeature;
-
+import com.fasterxml.jackson.databind.ObjectMapper;
-import java.io.IOException;
+import eu.dnetlib.dhp.common.HdfsSupport;
-import java.net.URISyntaxException;
+import eu.dnetlib.dhp.oa.merge.GroupEntitiesSparkJob;
-import java.nio.file.Files;
+import eu.dnetlib.dhp.schema.common.ModelSupport;
-import java.nio.file.Path;
+import eu.dnetlib.dhp.schema.oaf.OafEntity;
-import java.nio.file.Paths;
+import eu.dnetlib.dhp.schema.oaf.Result;
-
+import eu.dnetlib.dhp.utils.DHPUtils;
 import org.apache.commons.io.FileUtils;
-import org.apache.commons.lang3.StringUtils;
 import org.apache.spark.SparkConf;
 import org.apache.spark.api.java.function.FilterFunction;
 import org.apache.spark.api.java.function.MapFunction;
@@ -19,118 +18,108 @@ import org.apache.spark.sql.Encoders;
 import org.apache.spark.sql.SparkSession;
 import org.junit.jupiter.api.*;
 
-import com.fasterxml.jackson.databind.DeserializationFeature;
+import java.io.IOException;
-import com.fasterxml.jackson.databind.ObjectMapper;
+import java.net.URISyntaxException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
 
-import eu.dnetlib.dhp.common.HdfsSupport;
+import static org.junit.jupiter.api.Assertions.assertEquals;
-import eu.dnetlib.dhp.oa.merge.DispatchEntitiesSparkJob;
-import eu.dnetlib.dhp.oa.merge.GroupEntitiesSparkJob;
-import eu.dnetlib.dhp.schema.common.ModelSupport;
-import eu.dnetlib.dhp.schema.oaf.Result;
-import eu.dnetlib.dhp.utils.DHPUtils;
 
 @TestMethodOrder(MethodOrderer.OrderAnnotation.class)
 public class GroupEntitiesSparkJobTest {
 
-	private static SparkSession spark;
+    private static SparkSession spark;
 
-	private static ObjectMapper mapper = new ObjectMapper()
+    private static ObjectMapper mapper = new ObjectMapper()
-		.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
+            .configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
 
-	private static Path workingDir;
+    private static Path workingDir;
-	private Path dataInputPath;
+    private Path dataInputPath;
 
-	private Path groupEntityPath;
+    private Path checkpointPath;
-	private Path dispatchEntityPath;
 
-	@BeforeAll
+    private Path outputPath;
-	public static void beforeAll() throws IOException {
-		workingDir = Files.createTempDirectory(GroupEntitiesSparkJob.class.getSimpleName());
 
-		SparkConf conf = new SparkConf();
+    @BeforeAll
-		conf.setAppName(GroupEntitiesSparkJob.class.getSimpleName());
+    public static void beforeAll() throws IOException {
-		conf.setMaster("local");
+        workingDir = Files.createTempDirectory(GroupEntitiesSparkJob.class.getSimpleName());
-		conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
-		conf.registerKryoClasses(ModelSupport.getOafModelClasses());
-		spark = SparkSession.builder().config(conf).getOrCreate();
-	}
 
-	@BeforeEach
+        SparkConf conf = new SparkConf();
-	public void beforeEach() throws IOException, URISyntaxException {
+        conf.setAppName(GroupEntitiesSparkJob.class.getSimpleName());
-		dataInputPath = Paths.get(ClassLoader.getSystemResource("eu/dnetlib/dhp/oa/graph/group").toURI());
+        conf.setMaster("local");
-		groupEntityPath = workingDir.resolve("grouped_entity");
+        conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
-		dispatchEntityPath = workingDir.resolve("dispatched_entity");
+        conf.registerKryoClasses(ModelSupport.getOafModelClasses());
-	}
+        spark = SparkSession.builder().config(conf).getOrCreate();
+    }
 
-	@AfterAll
+    @BeforeEach
-	public static void afterAll() throws IOException {
+    public void beforeEach() throws IOException, URISyntaxException {
-		spark.stop();
+        dataInputPath = Paths.get(ClassLoader.getSystemResource("eu/dnetlib/dhp/oa/graph/group").toURI());
-		FileUtils.deleteDirectory(workingDir.toFile());
+        checkpointPath = workingDir.resolve("grouped_entity");
-	}
+        outputPath = workingDir.resolve("dispatched_entity");
+    }
 
-	@Test
+    @AfterAll
-	@Order(1)
+    public static void afterAll() throws IOException {
-	void testGroupEntities() throws Exception {
+        spark.stop();
-		GroupEntitiesSparkJob.main(new String[] {
+        FileUtils.deleteDirectory(workingDir.toFile());
-			"-isSparkSessionManaged",
+    }
-			Boolean.FALSE.toString(),
-			"-graphInputPath",
-			dataInputPath.toString(),
-			"-outputPath",
-			groupEntityPath.toString()
-		});
 
-		Dataset<Result> output = spark
+    @Test
-			.read()
+    @Order(1)
-			.textFile(groupEntityPath.toString())
+    void testGroupEntities() throws Exception {
-			.map((MapFunction<String, String>) s -> StringUtils.substringAfter(s, "|"), Encoders.STRING())
+        GroupEntitiesSparkJob.main(new String[]{
-			.map((MapFunction<String, Result>) s -> mapper.readValue(s, Result.class), Encoders.bean(Result.class));
+                "-isSparkSessionManaged",
+                Boolean.FALSE.toString(),
+                "-graphInputPath",
+                dataInputPath.toString(),
+                "-checkpointPath",
+                checkpointPath.toString(),
+                "-outputPath",
+                outputPath.toString(),
+                "-filterInvisible",
+                Boolean.FALSE.toString()
+        });
 
-		assertEquals(
+        Dataset<OafEntity> checkpointTable = spark
-			1,
+                .read()
-			output
+                .load(checkpointPath.toString())
-				.filter(
+                .selectExpr("COALESCE(*)")
-					(FilterFunction<Result>) r -> "50|doi_________::09821844208a5cd6300b2bfb13bca1b9"
+                .as(Encoders.kryo(OafEntity.class));
-						.equals(r.getId()) &&
-						r.getCollectedfrom().stream().anyMatch(kv -> kv.getValue().equalsIgnoreCase("zenodo")))
-				.count());
-	}
 
-	@Test
-	@Order(2)
-	void testDispatchEntities() throws Exception {
-		DispatchEntitiesSparkJob.main(new String[] {
-			"-isSparkSessionManaged",
-			Boolean.FALSE.toString(),
-			"-inputPath",
-			groupEntityPath.toString(),
-			"-outputPath",
-			dispatchEntityPath.resolve(".").toString(),
-			"-filterInvisible",
-			Boolean.TRUE.toString()
-		});
 
-		Dataset<Result> output = spark
+        assertEquals(
-			.read()
+                1,
-			.textFile(
+                checkpointTable
-				DHPUtils
+                        .filter(
-					.toSeq(
+                                (FilterFunction<OafEntity>) r -> "50|doi_________::09821844208a5cd6300b2bfb13bca1b9"
-						HdfsSupport
+                                        .equals(r.getId()) &&
-							.listFiles(dispatchEntityPath.toString(), spark.sparkContext().hadoopConfiguration())))
+                                        r.getCollectedfrom().stream().anyMatch(kv -> kv.getValue().equalsIgnoreCase("zenodo")))
-			.map((MapFunction<String, Result>) s -> mapper.readValue(s, Result.class), Encoders.bean(Result.class));
+                        .count());
 
-		assertEquals(3, output.count());
+
-		assertEquals(
+        Dataset<Result> output = spark
-			2,
+                .read()
-			output
+                .textFile(
-				.map((MapFunction<Result, String>) r -> r.getResulttype().getClassid(), Encoders.STRING())
+                        DHPUtils
-				.filter((FilterFunction<String>) s -> s.equals("publication"))
+                                .toSeq(
-				.count());
+                                        HdfsSupport
-		assertEquals(
+                                                .listFiles(outputPath.toString(), spark.sparkContext().hadoopConfiguration())))
-			1,
+                .map((MapFunction<String, Result>) s -> mapper.readValue(s, Result.class), Encoders.bean(Result.class));
-			output
+
-				.map((MapFunction<Result, String>) r -> r.getResulttype().getClassid(), Encoders.STRING())
+        assertEquals(3, output.count());
-				.filter((FilterFunction<String>) s -> s.equals("dataset"))
+        assertEquals(
-				.count());
+                2,
-	}
+                output
-}
+                        .map((MapFunction<Result, String>) r -> r.getResulttype().getClassid(), Encoders.STRING())
+                        .filter((FilterFunction<String>) s -> s.equals("publication"))
+                        .count());
+        assertEquals(
+                1,
+                output
+                        .map((MapFunction<Result, String>) r -> r.getResulttype().getClassid(), Encoders.STRING())
+                        .filter((FilterFunction<String>) s -> s.equals("dataset"))
+                        .count());
+    }
+}

dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/edith-demo/10.1098-rsta.2020.0257.xml

@@ -1,586 +0,0 @@
-<record>
-    <result xmlns:dri="http://www.driver-repository.eu/namespace/dri"
-            xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
-        <header>
-            <dri:objIdentifier>doi_dedup___::e225555a08a082ad8f53f179bc59c5d0</dri:objIdentifier>
-            <dri:dateOfCollection>2023-01-27T05:32:10Z</dri:dateOfCollection>
-        </header>
-        <metadata>
-            <oaf:entity xmlns:oaf="http://namespace.openaire.eu/oaf"
-                        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
-                        xsi:schemaLocation="http://namespace.openaire.eu/oaf http://namespace.openaire.eu/oaf http://www.openaire.eu/schema/0.2/oaf-0.2.xsd">
-
-                <oaf:result>
-                    <collectedfrom name="Crossref" id="openaire____::081b82f96300b6a6e3d282bad31cb6e2"/>
-                    <collectedfrom name="UnpayWall" id="openaire____::8ac8380272269217cb09a928c8caa993"/>
-                    <collectedfrom name="ORCID" id="openaire____::806360c771262b4d6770e7cdf04b5c5a"/>
-                    <collectedfrom name="Microsoft Academic Graph" id="openaire____::5f532a3fc4f1ea403f37070f59a7a53a"/>
-                    <collectedfrom name="Oxford University Research Archive"
-                                   id="opendoar____::2290a7385ed77cc5592dc2153229f082"/>
-                    <collectedfrom name="PubMed Central" id="opendoar____::eda80a3d5b344bc40f3bc04f65b7a357"/>
-                    <collectedfrom name="Europe PubMed Central" id="opendoar____::8b6dd7db9af49e67306feb59a8bdc52c"/>
-                    <originalId>10.1098/rsta.2020.0257</originalId>
-                    <originalId>50|doiboost____::e225555a08a082ad8f53f179bc59c5d0</originalId>
-                    <originalId>3211056089</originalId>
-                    <originalId>50|od______1064::83eb0f76b60445d72bb7428a1b68ef1a</originalId>
-                    <originalId>oai:ora.ox.ac.uk:uuid:9fc4563a-07e1-41d1-8b99-31ce2f8ac027</originalId>
-                    <originalId>50|od_______267::6d978e42c57dfc79d61a84ab5be28cb8</originalId>
-                    <originalId>oai:pubmedcentral.nih.gov:8543046</originalId>
-                    <originalId>od_______267::6d978e42c57dfc79d61a84ab5be28cb8</originalId>
-                    <originalId>34689630</originalId>
-                    <originalId>PMC8543046</originalId>
-                    <pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types"
-                         schemename="dnet:pid_types">10.1098/rsta.2020.0257
-                    </pid>
-                    <pid classid="pmc" classname="PubMed Central ID" schemeid="dnet:pid_types"
-                         schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:crosswalk:repository"
-                         trust="0.9">PMC8543046
-                    </pid>
-                    <pid classid="pmid" classname="PubMed ID" schemeid="dnet:pid_types" schemename="dnet:pid_types"
-                         inferred="false" provenanceaction="sysimport:crosswalk:repository" trust="0.9">34689630
-                    </pid>
-                    <measure id="influence" score="5.534974E-9" class="C"/>
-                    <measure id="popularity" score="2.0811036E-8" class="C"/>
-                    <measure id="influence_alt" score="8" class="C"/>
-                    <measure id="popularity_alt" score="2.736" class="C"/>
-                    <measure id="impulse" score="8" class="C"/>
-                    <measure id="downloads" count="1"/>
-                    <measure id="views" count="4"/>
-                    <title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title"
-                           schemename="dnet:dataCite_title">A completely automated pipeline for 3D reconstruction of
-                        human heart from 2D cine magnetic resonance slices.
-                    </title>
-                    <title classid="main title" classname="main title" schemeid="dnet:dataCite_title"
-                           schemename="dnet:dataCite_title">A completely automated pipeline for 3D reconstruction of
-                        human heart from 2D cine magnetic resonance slices
-                    </title>
-                    <bestaccessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
-                                     schemename="dnet:access_modes"/>
-                    <creator rank="8" URL="https://academic.microsoft.com/#/detail/2103042895">Vicente Grau</creator>
-                    <creator rank="1" orcid="0000-0001-8198-5128"
-                             URL="https://academic.microsoft.com/#/detail/2693349397">Abhirup Banerjee
-                    </creator>
-                    <creator rank="3" URL="https://academic.microsoft.com/#/detail/1425738153">Ernesto Zacur</creator>
-                    <creator rank="6" URL="https://academic.microsoft.com/#/detail/2043191934">Robin P. Choudhury
-                    </creator>
-                    <creator rank="7" URL="https://academic.microsoft.com/#/detail/2166186014">Blanca Rodriguez
-                    </creator>
-                    <creator rank="2" URL="https://academic.microsoft.com/#/detail/2889449215">Julia Camps</creator>
-                    <creator rank="5" URL="https://academic.microsoft.com/#/detail/264390263">Yoram Rudy</creator>
-                    <creator rank="4" URL="https://academic.microsoft.com/#/detail/2713879776">Christopher M. Andrews
-                    </creator>
-                    <country classid="GB" classname="United Kingdom" schemeid="dnet:countries"
-                             schemename="dnet:countries"/>
-                    <dateofacceptance>2021-10-01</dateofacceptance>
-                    <description>Cardiac magnetic resonance (CMR) imaging is a valuable modality in the diagnosis and
-                        characterization of cardiovascular diseases, since it can identify abnormalities in structure
-                        and function of the myocardium non-invasively and without the need for ionizing radiation.
-                        However, in clinical practice, it is commonly acquired as a collection of separated and
-                        independent 2D image planes, which limits its accuracy in 3D analysis. This paper presents a
-                        completely automated pipeline for generating patient-specific 3D biventricular heart models from
-                        cine magnetic resonance (MR) slices. Our pipeline automatically selects the relevant cine MR
-                        images, segments them using a deep learning-based method to extract the heart contours, and
-                        aligns the contours in 3D space correcting possible misalignments due to breathing or subject
-                        motion first using the intensity and contours information from the cine data and next with the
-                        help of a statistical shape model. Finally, the sparse 3D representation of the contours is used
-                        to generate a smooth 3D biventricular mesh. The computational pipeline is applied and evaluated
-                        in a CMR dataset of 20 healthy subjects. Our results show an average reduction of misalignment
-                        artefacts from 1.82 ± 1.60 mm to 0.72 ± 0.73 mm over 20 subjects, in terms of distance from the
-                        final reconstructed mesh. The high-resolution 3D biventricular meshes obtained with our
-                        computational pipeline are used for simulations of electrical activation patterns, showing
-                        agreement with non-invasive electrocardiographic imaging. The automatic methodologies presented
-                        here for patient-specific MR imaging-based 3D biventricular representations contribute to the
-                        efficient realization of precision medicine, enabling the enhanced interpretability of clinical
-                        data, the digital twin vision through patient-specific image-based modelling and simulation, and
-                        augmented reality applications.
-                        This article is part of the theme issue ‘Advanced computation in cardiovascular physiology: new
-                        challenges and opportunities’.
-                    </description>
-                    <subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">General Physics and Astronomy
-                    </subject>
-                    <subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">General Engineering
-                    </subject>
-                    <subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">General Mathematics
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Pipeline (computing)
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Cine mri
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Structure and function
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Cardiac magnetic resonance
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Magnetic resonance imaging
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="false"
-                             provenanceaction="sysimport:actionset" trust="0.5338496">medicine.diagnostic_test
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="false"
-                             provenanceaction="sysimport:actionset" trust="0.5338496">medicine
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Human heart
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Modality (human–computer interaction)
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">3D reconstruction
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Computer science
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Nuclear magnetic resonance
-                    </subject>
-                    <subject classid="SDG" classname="Sustainable Development Goals"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:sdg">3. Good health
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">03 medical and health sciences
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">0302 clinical medicine
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">030218 Nuclear Medicine &amp;
-                        Medical Imaging
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">03021801 Radiology/Image
-                        segmentation
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">03021801 Radiology/Image
-                        segmentation - deep learning/datum
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">030204 Cardiovascular System
-                        &amp; Hematology
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">03020401 Aging-associated
-                        diseases/Heart diseases
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">030217 Neurology &amp;
-                        Neurosurgery
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">03021701 Brain/Neural circuits
-                    </subject>
-
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-                    <description>Background: The concept of digital twins has great potential for transforming the existing health care system by making it more personalized. As a convergence of health care, artificial intelligence, and information and communication technologies, personalized health care services that are developed under the concept of digital twins raise a myriad of ethical issues. Although some of the ethical issues are known to researchers working on digital health and personalized medicine, currently, there is no comprehensive review that maps the major ethical risks of digital twins for personalized health care services.   Objective This study aims to fill the research gap by identifying the major ethical risks of digital twins for personalized health care services. We first propose a working definition for digital twins for personalized health care services to facilitate future discussions on the ethical issues related to these emerging digital health services. We then develop a process-oriented ethical map to identify the major ethical risks in each of the different data processing phases.   MethodsWe resorted to the literature on eHealth, personalized medicine, precision medicine, and information engineering to identify potential issues and developed a process-oriented ethical map to structure the inquiry in a more systematic way. The ethical map allows us to see how each of the major ethical concerns emerges during the process of transforming raw data into valuable information. Developers of a digital twin for personalized health care service may use this map to identify ethical risks during the development stage in a more systematic way and can proactively address them.   ResultsThis paper provides a working definition of digital twins for personalized health care services by identifying 3 features that distinguish the new application from other eHealth services. On the basis of the working definition, this paper further layouts 10 major operational problems and the corresponding ethical risks.   ConclusionsIt is challenging to address all the major ethical risks that a digital twin for a personalized health care service might encounter proactively without a conceptual map at hand. The process-oriented ethical map we propose here can assist the developers of digital twins for personalized health care services in analyzing ethical risks in a more systematic manner. </description>
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-                         provenanceaction="sysimport:crosswalk:datasetarchive" trust="0.9">10.3390/pr9111967
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-                    <title classid="alternative title" classname="alternative title" schemeid="dnet:dataCite_title"
-                           schemename="dnet:dataCite_title">Digital Twins for Continuous mRNA Production
-                    </title>
-                    <bestaccessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes"
-                                     schemename="dnet:access_modes"/>
-                    <dateofacceptance>2021-11-04</dateofacceptance>
-                    <description>The global coronavirus pandemic continues to restrict public life worldwide. An
-                        effective means of limiting the pandemic is vaccination. Messenger ribonucleic acid (mRNA)
-                        vaccines currently available on the market have proven to be a well-tolerated and effective
-                        class of vaccine against coronavirus type 2 (CoV2). Accordingly, demand is presently
-                        outstripping mRNA vaccine production. One way to increase productivity is to switch from the
-                        currently performed batch to continuous in vitro transcription, which has proven to be a crucial
-                        material-consuming step. In this article, a physico-chemical model of in vitro mRNA
-                        transcription in a tubular reactor is presented and compared to classical batch and continuous
-                        in vitro transcription in a stirred tank. The three models are validated based on a distinct and
-                        quantitative validation workflow. Statistically significant parameters are identified as part of
-                        the parameter determination concept. Monte Carlo simulations showed that the model is precise,
-                        with a deviation of less than 1%. The advantages of continuous production are pointed out
-                        compared to batchwise in vitro transcription by optimization of the space–time yield.
-                        Improvements of a factor of 56 (0.011 µM/min) in the case of the continuously stirred tank
-                        reactor (CSTR) and 68 (0.013 µM/min) in the case of the plug flow reactor (PFR) were found.
-                    </description>
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-                    </subject>
-                    <subject classid="keyword" classname="keyword" schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Bioengineering
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Coronavirus
-                    </subject>
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-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="false"
-                             provenanceaction="sysimport:actionset" trust="0.4019353">medicine.disease_cause
-                    </subject>
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-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="false"
-                             provenanceaction="sysimport:actionset" trust="0.4019353">medicine
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-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Continuous production
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Messenger RNA
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Continuous stirred-tank reactor
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies">Plug flow reactor model
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-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
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-                             schemename="dnet:subject_classification_typologies">Mathematics
-                    </subject>
-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
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-                             schemename="dnet:subject_classification_typologies">In vitro transcription
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-                    <subject classid="MAG" classname="Microsoft Academic Graph classification"
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-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">03 medical and health sciences
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">0301 basic medicine
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">030104 Developmental Biology
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">0303 health sciences
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-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">030304 Developmental Biology
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
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-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">0210 nano-technology
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-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
-                             inferenceprovenance="update" provenanceaction="subject:fos">021001 Nanoscience &amp;
-                        Nanotechnology
-                    </subject>
-                    <subject classid="FOS" classname="Fields of Science and Technology classification"
-                             schemeid="dnet:subject_classification_typologies"
-                             schemename="dnet:subject_classification_typologies" inferred="true"
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-                    <journal issn="2227-9717">Processes</journal>
-                    <context id="covid-19" label="COVID-19" type="community"/>
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-                            <dateofacceptance>2021-11-04</dateofacceptance>
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-                    <creator rank="1">Marasco Pier Lorenzo</creator>
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-                    <description>Sentinel-3 NDVI Analysis Ready Data (ARD) (C_GLS_NDVI_20220101_20220701_Lombardia_S3_2.nc) product provided by the Copernicus Global Land Service [3]. The file C_GLS_NDVI_20220101_20220701_Lombardia_S3_2_masked.nc is derived from C_GLS_NDVI_20220101_20220701_Lombardia_S3_2.nc but values have been scaled (raw_value * ( 1/250) - 0.08) and values lower then -0.08 and greater than 0.92 have been removed (set to missing values). The original dataset can also be discovered through the OpenEO API[5] from the CGLS distributor VITO [4]. Access is free of charge but an EGI registration is needed. The file called Italy.geojson has been created using the Global Administrative Unit Layers GAUL G2015_2014 provided by FAO-UN (see Documentation). It only contains information related to Italy. Further info about drought indexes can be found in the Integrated Drought Management Programme [5] [1] Application of vegetation index and brightness temperature for drought detection [2] NDVI [3] Copernicus Global Land Service [4] Vito [5] OpenEO [5] Integrated Drought Management</description>
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-                            <instancetype classid="0021" classname="Dataset" schemeid="dnet:publication_resource" schemename="dnet:publication_resource" />
-                            <pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">10.5281/zenodo.6969999</pid>
-                            <refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels" schemename="dnet:review_levels" />
-                            <license>https://creativecommons.org/licenses/by/4.0/legalcode</license>
-                            <webresource>
-                                <url>https://doi.org/10.5281/zenodo.6969999</url>
-                            </webresource>
-                        </instance>
-                        <instance>
-                            <accessright classid="OPEN" classname="Open Access" schemeid="dnet:access_modes" schemename="dnet:access_modes" />
-                            <collectedfrom name="Datacite" id="openaire____::9e3be59865b2c1c335d32dae2fe7b254" />
-                            <hostedby name="ZENODO" id="opendoar____::358aee4cc897452c00244351e4d91f69" />
-                            <dateofacceptance>2022-08-05</dateofacceptance>
-                            <instancetype classid="0021" classname="Dataset" schemeid="dnet:publication_resource" schemename="dnet:publication_resource" />
-                            <pid classid="doi" classname="Digital Object Identifier" schemeid="dnet:pid_types" schemename="dnet:pid_types" inferred="false" provenanceaction="sysimport:actionset" trust="0.9">10.5281/zenodo.6967372</pid>
-                            <refereed classid="0000" classname="UNKNOWN" schemeid="dnet:review_levels" schemename="dnet:review_levels" />
-                            <license>https://creativecommons.org/licenses/by/4.0/legalcode</license>
-                            <webresource>
-                                <url>https://doi.org/10.5281/zenodo.6967372</url>
-                            </webresource>
-                        </instance>
-                    </children>
-                </oaf:result>
-            </oaf:entity>
-        </metadata>
-    </result>
-</record>

dhp-workflows/dhp-graph-provision/src/test/resources/eu/dnetlib/dhp/oa/provision/publication.json

@@ -1,10 +1,10 @@
 {
   "eoscifguidelines": [
     {
-      "code": "EOSC::Jupyter Notebook",
+      "code" : "EOSC::Jupyter Notebook",
-      "label": "EOSC::Jupyter Notebook",
+      "label" : "EOSC::Jupyter Notebook",
-      "url": "",
+      "url" : "",
-      "semanticRelation": "compliesWith"
+      "semanticRelation" : "compliesWith"
     }
   ],
   "measures": [
@@ -431,26 +431,7 @@
       "value": "VIRTA"
     }
   ],
-  "context": [
+  "context": [],
-    {
-      "id": "eosc",
-      "dataInfo": [
-        {
-          "invisible": false,
-          "inferred": false,
-          "deletedbyinference": false,
-          "trust": "0.9",
-          "inferenceprovenance": "",
-          "provenanceaction": {
-            "classid": "sysimport:crosswalk",
-            "classname": "sysimport:crosswalk",
-            "schemeid": "dnet:provenanceActions",
-            "schemename": "dnet:provenanceActions"
-          }
-        }
-      ]
-    }
-  ],
   "contributor": [],
   "country": [],
   "coverage": [],

dhp-workflows/docs/oozie-installer.markdown

@@ -0,0 +1,111 @@
+General notes
+====================
+
+Oozie-installer is a utility allowing building, uploading and running oozie workflows. In practice, it creates a `*.tar.gz` package that contains resouces that define a workflow and some helper scripts.
+
+This module is automatically executed when running: 
+
+`mvn package -Poozie-package -Dworkflow.source.dir=classpath/to/parent/directory/of/oozie_app` 
+
+on module having set:
+
+	<parent>
+            <groupId>eu.dnetlib.dhp</groupId>
+            <artifactId>dhp-workflows</artifactId>
+	</parent>
+
+in `pom.xml` file. `oozie-package` profile initializes oozie workflow packaging, `workflow.source.dir` property points to a workflow (notice: this is not a relative path but a classpath to directory usually holding `oozie_app` subdirectory). 
+ 
+The outcome of this packaging is `oozie-package.tar.gz` file containing inside all the resources required to run Oozie workflow:
+
+- jar packages
+- workflow definitions
+- job properties
+- maintenance scripts
+
+Required properties
+====================
+
+In order to include proper workflow within package, `workflow.source.dir` property has to be set. It could be provided by setting `-Dworkflow.source.dir=some/job/dir` maven parameter.
+
+In oder to define full set of cluster environment properties one should create `~/.dhp/application.properties` file with the following properties:
+
+- `dhp.hadoop.frontend.user.name` - your user name on hadoop cluster and frontend machine
+- `dhp.hadoop.frontend.host.name` - frontend host name
+- `dhp.hadoop.frontend.temp.dir` - frontend directory for temporary files
+- `dhp.hadoop.frontend.port.ssh` - frontend machine ssh port
+- `oozieServiceLoc` - oozie service location required by run_workflow.sh script executing oozie job
+- `nameNode` - name node address
+- `jobTracker` - job tracker address
+- `oozie.execution.log.file.location` - location of file that will be created when executing oozie job, it contains output produced by `run_workflow.sh` script (needed to obtain oozie job id)
+- `maven.executable` - mvn command location, requires parameterization due to a different setup of CI cluster
+- `sparkDriverMemory` - amount of memory assigned to spark jobs driver
+- `sparkExecutorMemory` - amount of memory assigned to spark jobs executors
+- `sparkExecutorCores` - number of cores assigned to spark jobs executors
+
+All values will be overriden with the ones from `job.properties` and eventually `job-override.properties` stored in module's main folder.
+
+When overriding properties from `job.properties`, `job-override.properties` file can be created in main module directory (the one containing `pom.xml` file) and define all new properties which will override existing properties. One can provide those properties one by one as command line -D arguments.
+
+Properties overriding order is the following:
+
+1. `pom.xml` defined properties (located in the project root dir)
+2. `~/.dhp/application.properties` defined properties
+3. `${workflow.source.dir}/job.properties`
+4. `job-override.properties` (located in the project root dir)
+5. `maven -Dparam=value`
+
+where the maven `-Dparam` property is overriding all the other ones.
+
+Workflow definition requirements
+====================
+
+`workflow.source.dir` property should point to the following directory structure:
+
+	[${workflow.source.dir}]
+		|
+		|-job.properties (optional)
+		|
+		\-[oozie_app]
+			|
+			\-workflow.xml
+
+This property can be set using maven `-D` switch.
+
+`[oozie_app]` is the default directory name however it can be set to any value as soon as `oozieAppDir` property is provided with directory name as value.
+
+Subworkflows are supported as well and subworkflow directories should be nested within `[oozie_app]` directory. 
+
+Creating oozie installer step-by-step
+=====================================
+
+Automated oozie-installer steps are the following:
+
+1. creating jar packages:  `*.jar` and `*tests.jar` along with copying all dependancies in `target/dependencies`
+2. reading properties from maven, `~/.dhp/application.properties`, `job.properties`, `job-override.properties`
+3. invoking priming mechanism linking resources from import.txt file (currently resolving subworkflow resources)
+4. assembling shell scripts for preparing Hadoop filesystem, uploading Oozie application and starting workflow
+5. copying whole `${workflow.source.dir}` content to `target/${oozie.package.file.name}`
+6. generating updated `job.properties` file in `target/${oozie.package.file.name}` based on maven, `~/.dhp/application.properties`, `job.properties` and `job-override.properties`
+7. creating `lib` directory (or multiple directories for subworkflows for each nested directory) and copying jar packages created at step (1) to each one of them
+8. bundling whole `${oozie.package.file.name}` directory into single tar.gz package
+
+Uploading oozie package and running workflow on cluster
+=======================================================
+
+In order to simplify deployment and execution process two dedicated profiles were introduced:
+
+- `deploy`
+- `run`
+
+to be used along with `oozie-package` profile e.g. by providing `-Poozie-package,deploy,run` maven parameters.
+
+`deploy` profile supplements packaging process with:
+1) uploading oozie-package via scp to `/home/${user.name}/oozie-packages` directory on `${dhp.hadoop.frontend.host.name}` machine
+2) extracting uploaded package
+3) uploading oozie content to hadoop cluster HDFS location defined in `oozie.wf.application.path` property (generated dynamically by maven build process, based on `${dhp.hadoop.frontend.user.name}` and `workflow.source.dir` properties)
+
+`run` profile introduces:
+1) executing oozie application uploaded to HDFS cluster using `deploy` command. Triggers `run_workflow.sh` script providing runtime properties defined in `job.properties` file.
+
+Notice: ssh access to frontend machine has to be configured on system level and it is preferable to set key-based authentication in order to simplify remote operations.

dhp-workflows/pom.xml

@@ -25,6 +25,7 @@
     <modules>
         <module>dhp-workflow-profiles</module>
         <module>dhp-aggregation</module>
+        <module>dhp-distcp</module>
         <module>dhp-actionmanager</module>
         <module>dhp-graph-mapper</module>
         <module>dhp-dedup-openaire</module>

pom.xml

@@ -112,6 +112,16 @@
 			<url>https://maven.d4science.org/nexus/content/repositories/dnet-deps</url>
 			<layout>default</layout>
 		</repository>
+		<repository>
+			<id>maven-restlet</id>
+			<name>Restlet repository</name>
+			<url>https://maven.restlet.talend.com</url>
+		</repository>
+		<repository>
+			<id>conjars</id>
+			<name>conjars</name>
+			<url>https://conjars.wensel.net/repo/</url>
+		</repository>
 	</repositories>
 
 	<dependencies>