forked from D-Net/dnet-hadoop
dataset based provision WIP
This commit is contained in:
parent
24b2c9012e
commit
3d1b637cab
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@ -13,6 +13,26 @@
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<packaging>jar</packaging>
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<dependencies>
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<dependency>
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<groupId>eu.dnetlib.dhp</groupId>
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<artifactId>dhp-schemas</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.hadoop</groupId>
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<artifactId>hadoop-common</artifactId>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-core_2.11</artifactId>
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</dependency>
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<dependency>
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<groupId>org.apache.spark</groupId>
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<artifactId>spark-sql_2.11</artifactId>
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</dependency>
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<dependency>
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<groupId>commons-cli</groupId>
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<artifactId>commons-cli</artifactId>
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@ -0,0 +1,56 @@
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package eu.dnetlib.dhp.common;
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import java.io.Serializable;
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import java.util.function.Supplier;
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/**
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* Provides serializable and throwing extensions to standard functional interfaces.
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*/
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public class FunctionalInterfaceSupport {
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private FunctionalInterfaceSupport() {
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}
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/**
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* Serializable supplier of any kind of objects. To be used withing spark processing pipelines when supplying
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* functions externally.
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*
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* @param <T>
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*/
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@FunctionalInterface
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public interface SerializableSupplier<T> extends Supplier<T>, Serializable {
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}
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/**
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* Extension of consumer accepting functions throwing an exception.
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*
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* @param <T>
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* @param <E>
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*/
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@FunctionalInterface
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public interface ThrowingConsumer<T, E extends Exception> {
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void accept(T t) throws E;
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}
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/**
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* Extension of supplier accepting functions throwing an exception.
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*
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* @param <T>
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* @param <E>
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*/
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@FunctionalInterface
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public interface ThrowingSupplier<T, E extends Exception> {
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T get() throws E;
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}
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/**
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* Extension of runnable accepting functions throwing an exception.
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*
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* @param <E>
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*/
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@FunctionalInterface
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public interface ThrowingRunnable<E extends Exception> {
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void run() throws E;
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}
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}
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@ -0,0 +1,57 @@
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package eu.dnetlib.dhp.common;
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import org.apache.hadoop.conf.Configuration;
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import org.apache.hadoop.fs.FileStatus;
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import org.apache.hadoop.fs.FileSystem;
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import org.apache.hadoop.fs.Path;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import java.util.Arrays;
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import java.util.List;
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import java.util.stream.Collectors;
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import static eu.dnetlib.dhp.common.ThrowingSupport.rethrowAsRuntimeException;
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/**
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* HDFS utility methods.
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*/
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public class HdfsSupport {
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private static final Logger logger = LoggerFactory.getLogger(HdfsSupport.class);
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private HdfsSupport() {
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}
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/**
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* Removes a path (file or dir) from HDFS.
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*
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* @param path Path to be removed
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* @param configuration Configuration of hadoop env
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*/
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public static void remove(String path, Configuration configuration) {
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logger.info("Removing path: {}", path);
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rethrowAsRuntimeException(() -> {
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Path f = new Path(path);
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FileSystem fileSystem = FileSystem.get(configuration);
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if (fileSystem.exists(f)) {
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fileSystem.delete(f, true);
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}
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});
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}
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/**
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* Lists hadoop files located below path or alternatively lists subdirs under path.
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*
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* @param path Path to be listed for hadoop files
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* @param configuration Configuration of hadoop env
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* @return List with string locations of hadoop files
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*/
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public static List<String> listFiles(String path, Configuration configuration) {
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logger.info("Listing files in path: {}", path);
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return rethrowAsRuntimeException(() -> Arrays
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.stream(FileSystem.get(configuration).listStatus(new Path(path)))
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.filter(FileStatus::isDirectory)
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.map(x -> x.getPath().toString())
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.collect(Collectors.toList()));
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}
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}
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@ -0,0 +1,57 @@
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package eu.dnetlib.dhp.common;
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import eu.dnetlib.dhp.common.FunctionalInterfaceSupport.ThrowingConsumer;
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import org.apache.spark.SparkConf;
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import org.apache.spark.sql.SparkSession;
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import java.util.Objects;
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import java.util.function.Function;
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/**
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* SparkSession utility methods.
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*/
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public class SparkSessionSupport {
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private SparkSessionSupport() {
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}
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/**
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* Runs a given function using SparkSession created using default builder and supplied SparkConf. Stops SparkSession
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* when SparkSession is managed. Allows to reuse SparkSession created externally.
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*
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* @param conf SparkConf instance
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* @param isSparkSessionManaged When true will stop SparkSession
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* @param fn Consumer to be applied to constructed SparkSession
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*/
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public static void runWithSparkSession(SparkConf conf,
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Boolean isSparkSessionManaged,
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ThrowingConsumer<SparkSession, Exception> fn) {
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runWithSparkSession(c -> SparkSession.builder().config(c).getOrCreate(), conf, isSparkSessionManaged, fn);
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}
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/**
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* Runs a given function using SparkSession created using supplied builder and supplied SparkConf. Stops SparkSession
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* when SparkSession is managed. Allows to reuse SparkSession created externally.
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*
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* @param sparkSessionBuilder Builder of SparkSession
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* @param conf SparkConf instance
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* @param isSparkSessionManaged When true will stop SparkSession
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* @param fn Consumer to be applied to constructed SparkSession
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*/
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public static void runWithSparkSession(Function<SparkConf, SparkSession> sparkSessionBuilder,
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SparkConf conf,
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Boolean isSparkSessionManaged,
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ThrowingConsumer<SparkSession, Exception> fn) {
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SparkSession spark = null;
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try {
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spark = sparkSessionBuilder.apply(conf);
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fn.accept(spark);
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} catch (Exception e) {
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throw new RuntimeException(e);
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} finally {
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if (Objects.nonNull(spark) && isSparkSessionManaged) {
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spark.stop();
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}
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}
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}
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}
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package eu.dnetlib.dhp.common;
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import eu.dnetlib.dhp.common.FunctionalInterfaceSupport.ThrowingRunnable;
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import eu.dnetlib.dhp.common.FunctionalInterfaceSupport.ThrowingSupplier;
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/**
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* Exception handling utility methods.
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*/
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public class ThrowingSupport {
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private ThrowingSupport() {
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}
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/**
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* Executes given runnable and rethrows any exceptions as RuntimeException.
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*
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* @param fn Runnable to be executed
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* @param <E> Type of exception thrown
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*/
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public static <E extends Exception> void rethrowAsRuntimeException(ThrowingRunnable<E> fn) {
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try {
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fn.run();
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} catch (Exception e) {
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throw new RuntimeException(e);
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}
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}
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/**
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* Executes given runnable and rethrows any exceptions as RuntimeException with custom message.
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*
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* @param fn Runnable to be executed
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* @param msg Message to be set for rethrown exception
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* @param <E> Type of exception thrown
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*/
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public static <E extends Exception> void rethrowAsRuntimeException(ThrowingRunnable<E> fn, String msg) {
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try {
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fn.run();
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} catch (Exception e) {
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throw new RuntimeException(msg, e);
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}
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}
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/**
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* Executes given supplier and rethrows any exceptions as RuntimeException.
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*
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* @param fn Supplier to be executed
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* @param <T> Type of returned value
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* @param <E> Type of exception thrown
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* @return Result of supplier execution
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*/
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public static <T, E extends Exception> T rethrowAsRuntimeException(ThrowingSupplier<T, E> fn) {
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try {
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return fn.get();
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} catch (Exception e) {
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throw new RuntimeException(e);
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}
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}
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/**
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* Executes given supplier and rethrows any exceptions as RuntimeException with custom message.
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*
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* @param fn Supplier to be executed
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* @param msg Message to be set for rethrown exception
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* @param <T> Type of returned value
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* @param <E> Type of exception thrown
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* @return Result of supplier execution
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*/
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public static <T, E extends Exception> T rethrowAsRuntimeException(ThrowingSupplier<T, E> fn, String msg) {
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try {
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return fn.get();
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} catch (Exception e) {
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throw new RuntimeException(msg, e);
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}
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}
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}
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@ -0,0 +1,78 @@
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package eu.dnetlib.dhp.common;
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import org.apache.hadoop.conf.Configuration;
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import org.junit.jupiter.api.Nested;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.io.TempDir;
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import java.io.IOException;
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import java.nio.file.Files;
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import java.nio.file.Path;
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import java.util.Arrays;
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import java.util.List;
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import java.util.stream.Collectors;
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import static org.junit.jupiter.api.Assertions.*;
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public class HdfsSupportTest {
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@Nested
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class Remove {
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@Test
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public void shouldThrowARuntimeExceptionOnError() {
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// when
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assertThrows(RuntimeException.class, () ->
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HdfsSupport.remove(null, new Configuration()));
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}
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@Test
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public void shouldRemoveADirFromHDFS(@TempDir Path tempDir) {
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// when
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HdfsSupport.remove(tempDir.toString(), new Configuration());
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// then
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assertFalse(Files.exists(tempDir));
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}
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@Test
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public void shouldRemoveAFileFromHDFS(@TempDir Path tempDir) throws IOException {
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// given
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Path file = Files.createTempFile(tempDir, "p", "s");
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// when
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HdfsSupport.remove(file.toString(), new Configuration());
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// then
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assertFalse(Files.exists(file));
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}
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}
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@Nested
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class ListFiles {
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@Test
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public void shouldThrowARuntimeExceptionOnError() {
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// when
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assertThrows(RuntimeException.class, () ->
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HdfsSupport.listFiles(null, new Configuration()));
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}
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@Test
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public void shouldListFilesLocatedInPath(@TempDir Path tempDir) throws IOException {
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Path subDir1 = Files.createTempDirectory(tempDir, "list_me");
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Path subDir2 = Files.createTempDirectory(tempDir, "list_me");
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// when
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List<String> paths = HdfsSupport.listFiles(tempDir.toString(), new Configuration());
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// then
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assertEquals(2, paths.size());
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List<String> expecteds = Arrays.stream(new String[]{subDir1.toString(), subDir2.toString()})
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.sorted().collect(Collectors.toList());
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List<String> actuals = paths.stream().sorted().collect(Collectors.toList());
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assertTrue(actuals.get(0).contains(expecteds.get(0)));
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assertTrue(actuals.get(1).contains(expecteds.get(1)));
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}
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}
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}
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package eu.dnetlib.dhp.common;
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import eu.dnetlib.dhp.schema.common.ModelSupport;
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import eu.dnetlib.dhp.schema.oaf.OafEntity;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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import eu.dnetlib.dhp.schema.oaf.Result;
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import org.junit.jupiter.api.Nested;
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import org.junit.jupiter.api.Test;
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import static org.junit.jupiter.api.Assertions.assertFalse;
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import static org.junit.jupiter.api.Assertions.assertTrue;
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public class ModelSupportTest {
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@Nested
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class IsSubClass {
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@Test
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public void shouldReturnFalseWhenSubClassDoesNotExtendSuperClass() {
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// when
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Boolean result = ModelSupport.isSubClass(Relation.class, OafEntity.class);
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// then
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assertFalse(result);
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}
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@Test
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public void shouldReturnTrueWhenSubClassExtendsSuperClass() {
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// when
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Boolean result = ModelSupport.isSubClass(Result.class, OafEntity.class);
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// then
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assertTrue(result);
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}
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}
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}
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@ -0,0 +1,54 @@
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package eu.dnetlib.dhp.common;
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import eu.dnetlib.dhp.common.FunctionalInterfaceSupport.ThrowingConsumer;
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import org.apache.spark.SparkConf;
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import org.apache.spark.sql.SparkSession;
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import org.junit.jupiter.api.Nested;
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import org.junit.jupiter.api.Test;
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import java.util.function.Function;
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import static org.mockito.Mockito.*;
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public class SparkSessionSupportTest {
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@Nested
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class RunWithSparkSession {
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@Test
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public void shouldExecuteFunctionAndNotStopSparkSessionWhenSparkSessionIsNotManaged() throws Exception {
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// given
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SparkSession spark = mock(SparkSession.class);
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SparkConf conf = mock(SparkConf.class);
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Function<SparkConf, SparkSession> sparkSessionBuilder = mock(Function.class);
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when(sparkSessionBuilder.apply(conf)).thenReturn(spark);
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ThrowingConsumer<SparkSession, Exception> fn = mock(ThrowingConsumer.class);
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// when
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SparkSessionSupport.runWithSparkSession(sparkSessionBuilder, conf, false, fn);
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// then
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verify(sparkSessionBuilder).apply(conf);
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verify(fn).accept(spark);
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verify(spark, never()).stop();
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}
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@Test
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public void shouldExecuteFunctionAndStopSparkSessionWhenSparkSessionIsManaged() throws Exception {
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// given
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SparkSession spark = mock(SparkSession.class);
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SparkConf conf = mock(SparkConf.class);
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Function<SparkConf, SparkSession> sparkSessionBuilder = mock(Function.class);
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when(sparkSessionBuilder.apply(conf)).thenReturn(spark);
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ThrowingConsumer<SparkSession, Exception> fn = mock(ThrowingConsumer.class);
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// when
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SparkSessionSupport.runWithSparkSession(sparkSessionBuilder, conf, true, fn);
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// then
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verify(sparkSessionBuilder).apply(conf);
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verify(fn).accept(spark);
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verify(spark, times(1)).stop();
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}
|
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}
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}
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|
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@ -0,0 +1,51 @@
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package eu.dnetlib.dhp.schema.common;
|
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|
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import eu.dnetlib.dhp.schema.oaf.Oaf;
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|
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/**
|
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* Inheritance utility methods.
|
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*/
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public class ModelSupport {
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private ModelSupport() {
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}
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|
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/**
|
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* Checks subclass-superclass relationship.
|
||||
*
|
||||
* @param subClazzObject Subclass object instance
|
||||
* @param superClazzObject Superclass object instance
|
||||
* @param <X> Subclass type
|
||||
* @param <Y> Superclass type
|
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* @return True if X is a subclass of Y
|
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*/
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public static <X extends Oaf, Y extends Oaf> Boolean isSubClass(X subClazzObject, Y superClazzObject) {
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return isSubClass(subClazzObject.getClass(), superClazzObject.getClass());
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}
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|
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/**
|
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* Checks subclass-superclass relationship.
|
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*
|
||||
* @param subClazzObject Subclass object instance
|
||||
* @param superClazz Superclass class
|
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* @param <X> Subclass type
|
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* @param <Y> Superclass type
|
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* @return True if X is a subclass of Y
|
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*/
|
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public static <X extends Oaf, Y extends Oaf> Boolean isSubClass(X subClazzObject, Class<Y> superClazz) {
|
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return isSubClass(subClazzObject.getClass(), superClazz);
|
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}
|
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|
||||
/**
|
||||
* Checks subclass-superclass relationship.
|
||||
*
|
||||
* @param subClazz Subclass class
|
||||
* @param superClazz Superclass class
|
||||
* @param <X> Subclass type
|
||||
* @param <Y> Superclass type
|
||||
* @return True if X is a subclass of Y
|
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*/
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public static <X extends Oaf, Y extends Oaf> Boolean isSubClass(Class<X> subClazz, Class<Y> superClazz) {
|
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return superClazz.isAssignableFrom(subClazz);
|
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}
|
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}
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|
@ -92,8 +92,7 @@ public class Relation extends Oaf {
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subRelType.equals(relation.subRelType) &&
|
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relClass.equals(relation.relClass) &&
|
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source.equals(relation.source) &&
|
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target.equals(relation.target) &&
|
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Objects.equals(collectedFrom, relation.collectedFrom);
|
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target.equals(relation.target);
|
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}
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|
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@Override
|
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|
|
|
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@ -0,0 +1,167 @@
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package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.common.HdfsSupport;
|
||||
import eu.dnetlib.dhp.oa.provision.model.*;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.ContextMapper;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.api.java.function.Function;
|
||||
import org.apache.spark.api.java.function.Function2;
|
||||
import org.apache.spark.api.java.function.PairFunction;
|
||||
import org.apache.spark.rdd.RDD;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SaveMode;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import scala.Tuple2;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.Optional;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
import static eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils.*;
|
||||
|
||||
/**
|
||||
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects.
|
||||
* The operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization,
|
||||
* and all the possible relationships (similarity links produced by the Dedup process are excluded).
|
||||
*
|
||||
* The operation is implemented by sequentially joining one entity type at time (E) with the relationships (R), and again
|
||||
* by E, finally grouped by E.id;
|
||||
*
|
||||
* The workflow is organized in different parts aimed to to reduce the complexity of the operation
|
||||
* 1) PrepareRelationsJob:
|
||||
* only consider relationships that are not virtually deleted ($.dataInfo.deletedbyinference == false), each entity
|
||||
* can be linked at most to 100 other objects
|
||||
*
|
||||
* 2) JoinRelationEntityByTargetJob:
|
||||
* prepare tuples [source entity - relation - target entity] (S - R - T):
|
||||
* for each entity type E_i
|
||||
* join (R.target = E_i.id),
|
||||
* map E_i as RelatedEntity T_i, extracting only the necessary information beforehand to produce [R - T_i]
|
||||
* join (E_i.id = [R - T_i].source), where E_i becomes the source entity S
|
||||
*
|
||||
* 3) AdjacencyListBuilderJob:
|
||||
* given the tuple (S - R - T) we need to group by S.id -> List [ R - T ], mappnig the result as JoinedEntity
|
||||
*
|
||||
* 4) XmlConverterJob:
|
||||
* convert the JoinedEntities as XML records
|
||||
*/
|
||||
public class AdjacencyListBuilderJob {
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(AdjacencyListBuilderJob.class);
|
||||
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
|
||||
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
|
||||
IOUtils.toString(
|
||||
AdjacencyListBuilderJob.class
|
||||
.getResourceAsStream("/eu/dnetlib/dhp/oa/provision/input_params_build_adjacency_lists.json")));
|
||||
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);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
|
||||
conf.registerKryoClasses(getKryoClasses());
|
||||
|
||||
runWithSparkSession(conf, isSparkSessionManaged,
|
||||
spark -> {
|
||||
removeOutputDir(spark, outputPath);
|
||||
createAdjacencyLists(spark, inputPath, outputPath);
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
private static void createAdjacencyLists(SparkSession spark, String inputPath, String outputPath) {
|
||||
|
||||
RDD<JoinedEntity> joined = spark.read()
|
||||
.load(inputPath)
|
||||
.as(Encoders.kryo(EntityRelEntity.class))
|
||||
.javaRDD()
|
||||
.map(e -> getJoinedEntity(e))
|
||||
.mapToPair(e -> new Tuple2<>(e.getEntity().getId(), e))
|
||||
.reduceByKey((j1, j2) -> getJoinedEntity(j1, j2))
|
||||
.map(Tuple2::_2)
|
||||
.rdd();
|
||||
|
||||
spark.createDataset(joined, Encoders.bean(JoinedEntity.class))
|
||||
.write()
|
||||
.mode(SaveMode.Overwrite)
|
||||
.parquet(outputPath);
|
||||
|
||||
}
|
||||
|
||||
private static JoinedEntity getJoinedEntity(JoinedEntity j1, JoinedEntity j2) {
|
||||
JoinedEntity je = new JoinedEntity();
|
||||
je.setEntity(je.getEntity());
|
||||
je.setType(j1.getType());
|
||||
|
||||
Links links = new Links();
|
||||
links.addAll(j1.getLinks());
|
||||
links.addAll(j2.getLinks());
|
||||
|
||||
return je;
|
||||
}
|
||||
|
||||
private static JoinedEntity getJoinedEntity(EntityRelEntity e) {
|
||||
JoinedEntity j = new JoinedEntity();
|
||||
j.setEntity(toOafEntity(e.getEntity()));
|
||||
j.setType(EntityType.valueOf(e.getEntity().getType()));
|
||||
Links links = new Links();
|
||||
links.add(new eu.dnetlib.dhp.oa.provision.model.Tuple2(e.getRelation(), e.getTarget()));
|
||||
j.setLinks(links);
|
||||
return j;
|
||||
}
|
||||
|
||||
private static OafEntity toOafEntity(TypedRow typedRow) {
|
||||
return parseOaf(typedRow.getOaf(), typedRow.getType());
|
||||
}
|
||||
|
||||
private static OafEntity parseOaf(final String json, final String type) {
|
||||
try {
|
||||
switch (GraphMappingUtils.EntityType.valueOf(type)) {
|
||||
case publication:
|
||||
return OBJECT_MAPPER.readValue(json, Publication.class);
|
||||
case dataset:
|
||||
return OBJECT_MAPPER.readValue(json, Dataset.class);
|
||||
case otherresearchproduct:
|
||||
return OBJECT_MAPPER.readValue(json, OtherResearchProduct.class);
|
||||
case software:
|
||||
return OBJECT_MAPPER.readValue(json, Software.class);
|
||||
case datasource:
|
||||
return OBJECT_MAPPER.readValue(json, Datasource.class);
|
||||
case organization:
|
||||
return OBJECT_MAPPER.readValue(json, Organization.class);
|
||||
case project:
|
||||
return OBJECT_MAPPER.readValue(json, Project.class);
|
||||
default:
|
||||
throw new IllegalArgumentException("invalid type: " + type);
|
||||
}
|
||||
} catch (IOException e) {
|
||||
throw new IllegalArgumentException(e);
|
||||
}
|
||||
}
|
||||
|
||||
private static void removeOutputDir(SparkSession spark, String path) {
|
||||
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,157 @@
|
|||
package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.common.HdfsSupport;
|
||||
import eu.dnetlib.dhp.oa.provision.model.EntityRelEntity;
|
||||
import eu.dnetlib.dhp.oa.provision.model.SortableRelation;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
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.Dataset;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SaveMode;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import scala.Tuple2;
|
||||
|
||||
import java.util.Optional;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
import static eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils.*;
|
||||
|
||||
/**
|
||||
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects.
|
||||
* The operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization,
|
||||
* and all the possible relationships (similarity links produced by the Dedup process are excluded).
|
||||
*
|
||||
* The operation is implemented by sequentially joining one entity type at time (E) with the relationships (R), and again
|
||||
* by E, finally grouped by E.id;
|
||||
*
|
||||
* The workflow is organized in different parts aimed to to reduce the complexity of the operation
|
||||
* 1) PrepareRelationsJob:
|
||||
* only consider relationships that are not virtually deleted ($.dataInfo.deletedbyinference == false), each entity
|
||||
* can be linked at most to 100 other objects
|
||||
*
|
||||
* 2) CreateRelatedEntitiesJob_phase1:
|
||||
* prepare tuples [relation - target entity] (R - T):
|
||||
* for each entity type E_i
|
||||
* join (R.target = E_i.id),
|
||||
* map E_i as RelatedEntity T_i, extracting only the necessary information beforehand to produce [R - T_i]
|
||||
* save the tuples [R - T_i] in append mode
|
||||
*
|
||||
* 3) CreateRelatedEntitiesJob_phase2:
|
||||
* prepare tuples [source entity - relation - target entity] (S - R - T):
|
||||
* create the union of the each entity type, hash by id (S)
|
||||
* for each [R - T_i] produced in phase1
|
||||
* join S.id = [R - T_i].source to produce (S_i - R - T_i)
|
||||
* save in append mode
|
||||
*
|
||||
* 4) AdjacencyListBuilderJob:
|
||||
* given the tuple (S - R - T) we need to group by S.id -> List [ R - T ], mappnig the result as JoinedEntity
|
||||
*
|
||||
* 5) XmlConverterJob:
|
||||
* convert the JoinedEntities as XML records
|
||||
*/
|
||||
public class CreateRelatedEntitiesJob_phase1 {
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(CreateRelatedEntitiesJob_phase1.class);
|
||||
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
|
||||
String jsonConfiguration = IOUtils.toString(
|
||||
PrepareRelationsJob.class
|
||||
.getResourceAsStream("/eu/dnetlib/dhp/oa/provision/input_params_related_entities_pahase1.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 inputRelationsPath = parser.get("inputRelationsPath");
|
||||
log.info("inputRelationsPath: {}", inputRelationsPath);
|
||||
|
||||
String inputEntityPath = parser.get("inputEntityPath");
|
||||
log.info("inputEntityPath: {}", inputEntityPath);
|
||||
|
||||
String outputPath = parser.get("outputPath");
|
||||
log.info("outputPath: {}", outputPath);
|
||||
|
||||
String graphTableClassName = parser.get("graphTableClassName");
|
||||
log.info("graphTableClassName: {}", graphTableClassName);
|
||||
|
||||
Class<? extends OafEntity> entityClazz = (Class<? extends OafEntity>) Class.forName(graphTableClassName);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
|
||||
conf.registerKryoClasses(getKryoClasses());
|
||||
|
||||
runWithSparkSession(conf, isSparkSessionManaged,
|
||||
spark -> {
|
||||
removeOutputDir(spark, outputPath);
|
||||
joinRelationEntity(spark, inputRelationsPath, inputEntityPath, entityClazz, outputPath);
|
||||
});
|
||||
}
|
||||
|
||||
private static <E extends OafEntity> void joinRelationEntity(SparkSession spark, String inputRelationsPath, String inputEntityPath, Class<E> entityClazz, String outputPath) {
|
||||
|
||||
Dataset<Tuple2<String, SortableRelation>> relsByTarget = readPathRelation(spark, inputRelationsPath)
|
||||
.map((MapFunction<SortableRelation, Tuple2<String, SortableRelation>>) r -> new Tuple2<>(r.getTarget(), r),
|
||||
Encoders.tuple(Encoders.STRING(), Encoders.kryo(SortableRelation.class)));
|
||||
|
||||
Dataset<Tuple2<String, E>> entities = readPathEntity(spark, inputEntityPath, entityClazz)
|
||||
.map((MapFunction<E, Tuple2<String, E>>) e -> new Tuple2<>(e.getId(), e),
|
||||
Encoders.tuple(Encoders.STRING(), Encoders.kryo(entityClazz)))
|
||||
.cache();
|
||||
|
||||
relsByTarget
|
||||
.joinWith(entities, entities.col("_1").equalTo(relsByTarget.col("_1")), "inner")
|
||||
.filter((FilterFunction<Tuple2<Tuple2<String, SortableRelation>, Tuple2<String, E>>>)
|
||||
value -> value._2()._2().getDataInfo().getDeletedbyinference() == false)
|
||||
.map((MapFunction<Tuple2<Tuple2<String, SortableRelation>, Tuple2<String, E>>, EntityRelEntity>)
|
||||
t -> new EntityRelEntity(t._1()._2(), GraphMappingUtils.asRelatedEntity(t._2()._2(), entityClazz)),
|
||||
Encoders.bean(EntityRelEntity.class))
|
||||
.write()
|
||||
.mode(SaveMode.Append)
|
||||
.parquet(outputPath);
|
||||
}
|
||||
|
||||
private static <E extends OafEntity> Dataset<E> readPathEntity(SparkSession spark, String inputEntityPath, Class<E> entityClazz) {
|
||||
|
||||
log.info("Reading Graph table from: {}", inputEntityPath);
|
||||
return spark
|
||||
.read()
|
||||
.textFile(inputEntityPath)
|
||||
.map((MapFunction<String, E>) value -> OBJECT_MAPPER.readValue(value, entityClazz), Encoders.bean(entityClazz));
|
||||
}
|
||||
|
||||
/**
|
||||
* Reads a Dataset of eu.dnetlib.dhp.oa.provision.model.SortableRelation objects from a newline delimited json text file,
|
||||
*
|
||||
* @param spark
|
||||
* @param relationPath
|
||||
* @return the Dataset<SortableRelation> containing all the relationships
|
||||
*/
|
||||
private static Dataset<SortableRelation> readPathRelation(SparkSession spark, final String relationPath) {
|
||||
|
||||
log.info("Reading relations from: {}", relationPath);
|
||||
return spark.read()
|
||||
.load(relationPath)
|
||||
.as(Encoders.bean(SortableRelation.class));
|
||||
}
|
||||
|
||||
private static void removeOutputDir(SparkSession spark, String path) {
|
||||
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,168 @@
|
|||
package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.common.HdfsSupport;
|
||||
import eu.dnetlib.dhp.oa.provision.model.EntityRelEntity;
|
||||
import eu.dnetlib.dhp.oa.provision.model.TypedRow;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.api.java.function.MapFunction;
|
||||
import org.apache.spark.sql.Dataset;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SaveMode;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import scala.Tuple2;
|
||||
|
||||
import java.util.Map;
|
||||
import java.util.Optional;
|
||||
import java.util.function.Function;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
import static eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils.*;
|
||||
|
||||
/**
|
||||
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects.
|
||||
* The operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization,
|
||||
* and all the possible relationships (similarity links produced by the Dedup process are excluded).
|
||||
*
|
||||
* The operation is implemented by sequentially joining one entity type at time (E) with the relationships (R), and again
|
||||
* by E, finally grouped by E.id;
|
||||
*
|
||||
* The workflow is organized in different parts aimed to to reduce the complexity of the operation
|
||||
* 1) PrepareRelationsJob:
|
||||
* only consider relationships that are not virtually deleted ($.dataInfo.deletedbyinference == false), each entity
|
||||
* can be linked at most to 100 other objects
|
||||
*
|
||||
* 2) CreateRelatedEntitiesJob_phase1:
|
||||
* prepare tuples [relation - target entity] (R - T):
|
||||
* for each entity type E_i
|
||||
* join (R.target = E_i.id),
|
||||
* map E_i as RelatedEntity T_i, extracting only the necessary information beforehand to produce [R - T_i]
|
||||
* save the tuples [R - T_i] in append mode
|
||||
*
|
||||
* 3) CreateRelatedEntitiesJob_phase2:
|
||||
* prepare tuples [source entity - relation - target entity] (S - R - T):
|
||||
* create the union of the each entity type, hash by id (S)
|
||||
* for each [R - T_i] produced in phase1
|
||||
* join S.id = [R - T_i].source to produce (S_i - R - T_i)
|
||||
* save in append mode
|
||||
*
|
||||
* 4) AdjacencyListBuilderJob:
|
||||
* given the tuple (S - R - T) we need to group by S.id -> List [ R - T ], mappnig the result as JoinedEntity
|
||||
*
|
||||
* 5) XmlConverterJob:
|
||||
* convert the JoinedEntities as XML records
|
||||
*/
|
||||
public class CreateRelatedEntitiesJob_phase2 {
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(CreateRelatedEntitiesJob_phase2.class);
|
||||
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
|
||||
String jsonConfiguration = IOUtils.toString(
|
||||
PrepareRelationsJob.class
|
||||
.getResourceAsStream("/eu/dnetlib/dhp/oa/provision/input_params_related_entities_pahase1.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 inputRelatedEntitiesPath = parser.get("inputRelatedEntitiesPath");
|
||||
log.info("inputRelatedEntitiesPath: {}", inputRelatedEntitiesPath);
|
||||
|
||||
String inputGraphPath = parser.get("inputGraphPath");
|
||||
log.info("inputGraphPath: {}", inputGraphPath);
|
||||
|
||||
String outputPath = parser.get("outputPath");
|
||||
log.info("outputPath: {}", outputPath);
|
||||
|
||||
String graphTableClassName = parser.get("graphTableClassName");
|
||||
log.info("graphTableClassName: {}", graphTableClassName);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
|
||||
conf.registerKryoClasses(getKryoClasses());
|
||||
|
||||
runWithSparkSession(conf, isSparkSessionManaged,
|
||||
spark -> {
|
||||
removeOutputDir(spark, outputPath);
|
||||
joinAllEntities(spark, inputRelatedEntitiesPath, inputGraphPath, outputPath);
|
||||
});
|
||||
}
|
||||
|
||||
private static void joinAllEntities(SparkSession spark, String inputRelatedEntitiesPath, String inputGraphPath, String outputPath) {
|
||||
|
||||
Dataset<Tuple2<String, EntityRelEntity>> relsBySource = readRelatedEntities(spark, inputRelatedEntitiesPath);
|
||||
Dataset<Tuple2<String, TypedRow>> entities = readAllEntities(spark, inputGraphPath);
|
||||
|
||||
entities
|
||||
.joinWith(relsBySource, entities.col("_1").equalTo(relsBySource.col("_1")), "left_outer")
|
||||
.map((MapFunction<Tuple2<Tuple2<String, TypedRow>, Tuple2<String, EntityRelEntity>>, EntityRelEntity>) value -> {
|
||||
EntityRelEntity re = new EntityRelEntity();
|
||||
re.setEntity(value._1()._2());
|
||||
Optional<EntityRelEntity> related = Optional.ofNullable(value._2()).map(Tuple2::_2);
|
||||
if (related.isPresent()) {
|
||||
re.setRelation(related.get().getRelation());
|
||||
re.setTarget(related.get().getTarget());
|
||||
}
|
||||
return re;
|
||||
}, Encoders.bean(EntityRelEntity.class))
|
||||
.write()
|
||||
.mode(SaveMode.Append)
|
||||
.parquet(outputPath);
|
||||
}
|
||||
|
||||
private static Dataset<Tuple2<String, TypedRow>> readAllEntities(SparkSession spark, String inputGraphPath) {
|
||||
return GraphMappingUtils.entityTypes.entrySet()
|
||||
.stream()
|
||||
.map((Function<Map.Entry<GraphMappingUtils.EntityType, Class>, Dataset<TypedRow>>)
|
||||
e -> readPathEntity(spark, inputGraphPath + "/" + e.getKey().name(), e.getValue())
|
||||
.map((MapFunction<OafEntity, TypedRow>) entity -> {
|
||||
TypedRow t = new TypedRow();
|
||||
t.setType(e.getKey().name());
|
||||
t.setDeleted(entity.getDataInfo().getDeletedbyinference());
|
||||
t.setId(entity.getId());
|
||||
t.setOaf(OBJECT_MAPPER.writeValueAsString(entity));
|
||||
return t;
|
||||
}, Encoders.bean(TypedRow.class)))
|
||||
.reduce(spark.emptyDataset(Encoders.bean(TypedRow.class)), Dataset::union)
|
||||
.map((MapFunction<TypedRow, Tuple2<String, TypedRow>>)
|
||||
value -> new Tuple2<>(value.getId(), value),
|
||||
Encoders.tuple(Encoders.STRING(), Encoders.kryo(TypedRow.class)));
|
||||
}
|
||||
|
||||
private static Dataset<Tuple2<String, EntityRelEntity>> readRelatedEntities(SparkSession spark, String inputRelatedEntitiesPath) {
|
||||
return spark.read()
|
||||
.load(inputRelatedEntitiesPath)
|
||||
.as(Encoders.kryo(EntityRelEntity.class))
|
||||
.map((MapFunction<EntityRelEntity, Tuple2<String, EntityRelEntity>>)
|
||||
value -> new Tuple2<>(value.getRelation().getSource(), value),
|
||||
Encoders.tuple(Encoders.STRING(), Encoders.kryo(EntityRelEntity.class)));
|
||||
}
|
||||
|
||||
|
||||
private static <E extends OafEntity> Dataset<E> readPathEntity(SparkSession spark, String inputEntityPath, Class<E> entityClazz) {
|
||||
|
||||
log.info("Reading Graph table from: {}", inputEntityPath);
|
||||
return spark
|
||||
.read()
|
||||
.textFile(inputEntityPath)
|
||||
.map((MapFunction<String, E>) value -> OBJECT_MAPPER.readValue(value, entityClazz), Encoders.bean(entityClazz));
|
||||
}
|
||||
|
||||
private static void removeOutputDir(SparkSession spark, String path) {
|
||||
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -1,346 +0,0 @@
|
|||
package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import com.fasterxml.jackson.databind.DeserializationFeature;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import com.google.common.collect.Iterators;
|
||||
import com.google.common.collect.Maps;
|
||||
import com.jayway.jsonpath.DocumentContext;
|
||||
import com.jayway.jsonpath.JsonPath;
|
||||
import eu.dnetlib.dhp.oa.provision.model.*;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.*;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import org.apache.spark.SparkContext;
|
||||
import org.apache.spark.api.java.JavaSparkContext;
|
||||
import org.apache.spark.api.java.function.*;
|
||||
import org.apache.spark.rdd.RDD;
|
||||
import org.apache.spark.sql.*;
|
||||
import org.apache.spark.sql.Dataset;
|
||||
import org.apache.spark.sql.types.*;
|
||||
import org.apache.spark.util.LongAccumulator;
|
||||
import scala.Tuple2;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.io.Serializable;
|
||||
import java.util.*;
|
||||
|
||||
import static org.apache.spark.sql.functions.*;
|
||||
|
||||
import static eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils.asRelatedEntity;
|
||||
|
||||
/**
|
||||
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects.
|
||||
* The operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization,
|
||||
* and all the possible relationships (similarity links produced by the Dedup process are excluded).
|
||||
*
|
||||
* The operation is implemented creating the union between the entity types (E), joined by the relationships (R), and again
|
||||
* by E, finally grouped by E.id;
|
||||
*
|
||||
* Different manipulations of the E and R sets are introduced to reduce the complexity of the operation
|
||||
* 1) treat the object payload as string, extracting only the necessary information beforehand using json path,
|
||||
* it seems that deserializing it with jackson's object mapper has higher memory footprint.
|
||||
*
|
||||
* 2) only consider rels that are not virtually deleted ($.dataInfo.deletedbyinference == false)
|
||||
* 3) we only need a subset of fields from the related entities, so we introduce a distinction between E_source = S
|
||||
* and E_target = T. Objects in T are heavily pruned by all the unnecessary information
|
||||
*
|
||||
* 4) perform the join as (((T.id join R.target) union S) groupby S.id) yield S -> [ <T, R> ]
|
||||
*/
|
||||
public class GraphJoiner_v2 implements Serializable {
|
||||
|
||||
private Map<String, LongAccumulator> accumulators = Maps.newHashMap();
|
||||
|
||||
public static final int MAX_RELS = 100;
|
||||
|
||||
public static final String schemaLocation = "https://www.openaire.eu/schema/1.0/oaf-1.0.xsd";
|
||||
|
||||
private SparkSession spark;
|
||||
|
||||
private ContextMapper contextMapper;
|
||||
|
||||
private String inputPath;
|
||||
|
||||
private String outPath;
|
||||
|
||||
private String otherDsTypeId;
|
||||
|
||||
public GraphJoiner_v2(SparkSession spark, ContextMapper contextMapper, String otherDsTypeId, String inputPath, String outPath) {
|
||||
this.spark = spark;
|
||||
this.contextMapper = contextMapper;
|
||||
this.otherDsTypeId = otherDsTypeId;
|
||||
this.inputPath = inputPath;
|
||||
this.outPath = outPath;
|
||||
|
||||
final SparkContext sc = spark.sparkContext();
|
||||
prepareAccumulators(sc);
|
||||
}
|
||||
|
||||
public GraphJoiner_v2 adjacencyLists() throws IOException {
|
||||
|
||||
final JavaSparkContext jsc = JavaSparkContext.fromSparkContext(getSpark().sparkContext());
|
||||
|
||||
// read each entity
|
||||
Dataset<TypedRow> datasource = readPathEntity(jsc, getInputPath(), "datasource");
|
||||
Dataset<TypedRow> organization = readPathEntity(jsc, getInputPath(), "organization");
|
||||
Dataset<TypedRow> project = readPathEntity(jsc, getInputPath(), "project");
|
||||
Dataset<TypedRow> dataset = readPathEntity(jsc, getInputPath(), "dataset");
|
||||
Dataset<TypedRow> otherresearchproduct = readPathEntity(jsc, getInputPath(), "otherresearchproduct");
|
||||
Dataset<TypedRow> software = readPathEntity(jsc, getInputPath(), "software");
|
||||
Dataset<TypedRow> publication = readPathEntity(jsc, getInputPath(), "publication");
|
||||
|
||||
// create the union between all the entities
|
||||
datasource
|
||||
.union(organization)
|
||||
.union(project)
|
||||
.union(dataset)
|
||||
.union(otherresearchproduct)
|
||||
.union(software)
|
||||
.union(publication)
|
||||
.repartition(7000)
|
||||
.write()
|
||||
.partitionBy("id")
|
||||
.parquet(getOutPath() + "/entities");
|
||||
|
||||
Dataset<Tuple2<String, TypedRow>> entities = getSpark()
|
||||
.read()
|
||||
.load(getOutPath() + "/entities")
|
||||
.map((MapFunction<Row, Tuple2<String, TypedRow>>) r -> {
|
||||
TypedRow t = new TypedRow();
|
||||
t.setId(r.getAs("id"));
|
||||
t.setDeleted(r.getAs("deleted"));
|
||||
t.setType(r.getAs("type"));
|
||||
t.setOaf(r.getAs("oaf"));
|
||||
|
||||
return new Tuple2<>(t.getId(), t);
|
||||
}, Encoders.tuple(Encoders.STRING(), Encoders.kryo(TypedRow.class)))
|
||||
.cache();
|
||||
|
||||
System.out.println("Entities, number of partitions: " + entities.rdd().getNumPartitions());
|
||||
System.out.println("Entities schema:");
|
||||
entities.printSchema();
|
||||
System.out.println("Entities count:" + entities.count());
|
||||
|
||||
// reads the relationships
|
||||
readPathRelation(jsc, getInputPath())
|
||||
.groupByKey((MapFunction<Relation, SortableRelationKey>) t -> SortableRelationKey.from(t), Encoders.kryo(SortableRelationKey.class))
|
||||
.flatMapGroups((FlatMapGroupsFunction<SortableRelationKey, Relation, Relation>) (key, values) -> Iterators.limit(values, MAX_RELS), Encoders.kryo(Relation.class))
|
||||
.repartition(3000)
|
||||
.write()
|
||||
.partitionBy("source", "target")
|
||||
.parquet(getOutPath() + "/relations");
|
||||
|
||||
Dataset<Relation> rels = getSpark()
|
||||
.read()
|
||||
.load(getOutPath() + "/relations")
|
||||
.map((MapFunction<Row, Relation>) r -> {
|
||||
Relation rel = new Relation();
|
||||
rel.setSource(r.getAs("source"));
|
||||
rel.setTarget(r.getAs("target"));
|
||||
rel.setRelType(r.getAs("relType"));
|
||||
rel.setSubRelType(r.getAs("subRelType"));
|
||||
rel.setRelClass(r.getAs("relClass"));
|
||||
rel.setDataInfo(r.getAs("dataInfo"));
|
||||
rel.setCollectedFrom(r.getList(r.fieldIndex("collectedFrom")));
|
||||
return rel;
|
||||
}, Encoders.kryo(Relation.class))
|
||||
.cache();
|
||||
|
||||
System.out.println("Relation schema:");
|
||||
System.out.println("Relation, number of partitions: " + rels.rdd().getNumPartitions());
|
||||
System.out.println("Relation schema:");
|
||||
entities.printSchema();
|
||||
System.out.println("Relation count:" + rels.count());
|
||||
|
||||
/*
|
||||
Dataset<Tuple2<String, Relation>> relsByTarget = rels
|
||||
.map((MapFunction<Relation, Tuple2<String, Relation>>) r -> new Tuple2<>(r.getTarget(), r), Encoders.tuple(Encoders.STRING(), Encoders.kryo(Relation.class)));
|
||||
|
||||
|
||||
relsByTarget
|
||||
.joinWith(entities, relsByTarget.col("_1").equalTo(entities.col("_1")), "inner")
|
||||
.filter((FilterFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, TypedRow>>>) value -> value._2()._2().getDeleted() == false)
|
||||
.map((MapFunction<Tuple2<Tuple2<String, Relation>, Tuple2<String, TypedRow>>, EntityRelEntity>) t -> {
|
||||
EntityRelEntity e = new EntityRelEntity();
|
||||
e.setRelation(t._1()._2());
|
||||
e.setTarget(asRelatedEntity(t._2()._2()));
|
||||
return e;
|
||||
}, Encoders.kryo(EntityRelEntity.class))
|
||||
.repartition(20000)
|
||||
.write()
|
||||
.parquet(getOutPath() + "/bySource");
|
||||
|
||||
Dataset<Tuple2<String, EntityRelEntity>> bySource = getSpark()
|
||||
.read()
|
||||
.load(getOutPath() + "/bySource")
|
||||
.map(new MapFunction<Row, EntityRelEntity>() {
|
||||
@Override
|
||||
public EntityRelEntity call(Row value) throws Exception {
|
||||
return null;
|
||||
}
|
||||
}, Encoders.kryo(EntityRelEntity.class))
|
||||
.map((MapFunction<EntityRelEntity, Tuple2<String, EntityRelEntity>>) e -> new Tuple2<>(e.getRelation().getSource(), e),
|
||||
Encoders.tuple(Encoders.STRING(), Encoders.kryo(EntityRelEntity.class)))
|
||||
|
||||
System.out.println("bySource schema");
|
||||
bySource.printSchema();
|
||||
|
||||
|
||||
|
||||
|
||||
Dataset<EntityRelEntity> joined = entities
|
||||
.joinWith(bySource, entities.col("_1").equalTo(bySource.col("_1")), "left")
|
||||
.map((MapFunction<Tuple2<Tuple2<String, TypedRow>, Tuple2<String, EntityRelEntity>>, EntityRelEntity>) value -> {
|
||||
EntityRelEntity re = new EntityRelEntity();
|
||||
re.setEntity(value._1()._2());
|
||||
Optional<EntityRelEntity> related = Optional.ofNullable(value._2()).map(Tuple2::_2);
|
||||
if (related.isPresent()) {
|
||||
re.setRelation(related.get().getRelation());
|
||||
re.setTarget(related.get().getTarget());
|
||||
}
|
||||
return re;
|
||||
}, Encoders.kryo(EntityRelEntity.class));
|
||||
|
||||
System.out.println("joined schema");
|
||||
joined.printSchema();
|
||||
//joined.write().json(getOutPath() + "/joined");
|
||||
|
||||
final Dataset<JoinedEntity> grouped = joined
|
||||
.groupByKey((MapFunction<EntityRelEntity, TypedRow>) e -> e.getEntity(), Encoders.kryo(TypedRow.class))
|
||||
.mapGroups((MapGroupsFunction<TypedRow, EntityRelEntity, JoinedEntity>) (key, values) -> toJoinedEntity(key, values), Encoders.kryo(JoinedEntity.class));
|
||||
|
||||
System.out.println("grouped schema");
|
||||
grouped.printSchema();
|
||||
|
||||
final XmlRecordFactory recordFactory = new XmlRecordFactory(accumulators, contextMapper, false, schemaLocation, otherDsTypeId);
|
||||
grouped
|
||||
.map((MapFunction<JoinedEntity, String>) value -> recordFactory.build(value), Encoders.STRING())
|
||||
.javaRDD()
|
||||
.mapToPair((PairFunction<Tuple2<String, String>, String, String>) t -> new Tuple2<>(t._1(), t._2()))
|
||||
.saveAsHadoopFile(getOutPath() + "/xml", Text.class, Text.class, SequenceFileOutputFormat.class, GzipCodec.class);
|
||||
|
||||
|
||||
*/
|
||||
|
||||
return this;
|
||||
}
|
||||
|
||||
public SparkSession getSpark() {
|
||||
return spark;
|
||||
}
|
||||
|
||||
public String getInputPath() {
|
||||
return inputPath;
|
||||
}
|
||||
|
||||
public String getOutPath() {
|
||||
return outPath;
|
||||
}
|
||||
|
||||
// HELPERS
|
||||
|
||||
private JoinedEntity toJoinedEntity(TypedRow key, Iterator<EntityRelEntity> values) {
|
||||
final ObjectMapper mapper = getObjectMapper();
|
||||
final JoinedEntity j = new JoinedEntity();
|
||||
j.setType(key.getType());
|
||||
j.setEntity(parseOaf(key.getOaf(), key.getType(), mapper));
|
||||
final Links links = new Links();
|
||||
values.forEachRemaining(rel -> links.add(
|
||||
new eu.dnetlib.dhp.oa.provision.model.Tuple2(
|
||||
rel.getRelation(),
|
||||
rel.getTarget()
|
||||
)));
|
||||
j.setLinks(links);
|
||||
return j;
|
||||
}
|
||||
|
||||
private OafEntity parseOaf(final String json, final String type, final ObjectMapper mapper) {
|
||||
try {
|
||||
switch (GraphMappingUtils.EntityType.valueOf(type)) {
|
||||
case publication:
|
||||
return mapper.readValue(json, Publication.class);
|
||||
case dataset:
|
||||
return mapper.readValue(json, eu.dnetlib.dhp.schema.oaf.Dataset.class);
|
||||
case otherresearchproduct:
|
||||
return mapper.readValue(json, OtherResearchProduct.class);
|
||||
case software:
|
||||
return mapper.readValue(json, Software.class);
|
||||
case datasource:
|
||||
return mapper.readValue(json, Datasource.class);
|
||||
case organization:
|
||||
return mapper.readValue(json, Organization.class);
|
||||
case project:
|
||||
return mapper.readValue(json, Project.class);
|
||||
default:
|
||||
throw new IllegalArgumentException("invalid type: " + type);
|
||||
}
|
||||
} catch (IOException e) {
|
||||
throw new IllegalArgumentException(e);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Reads a set of eu.dnetlib.dhp.schema.oaf.OafEntity objects from a new line delimited json file,
|
||||
* extracts necessary information using json path, wraps the oaf object in a eu.dnetlib.dhp.graph.model.TypedRow
|
||||
* @param sc
|
||||
* @param inputPath
|
||||
* @param type
|
||||
* @return the JavaPairRDD<String, TypedRow> indexed by entity identifier
|
||||
*/
|
||||
private Dataset<TypedRow> readPathEntity(final JavaSparkContext sc, final String inputPath, final String type) {
|
||||
RDD<String> rdd = sc.textFile(inputPath + "/" + type)
|
||||
.rdd();
|
||||
|
||||
return getSpark().createDataset(rdd, Encoders.STRING())
|
||||
.map((MapFunction<String, TypedRow>) s -> {
|
||||
final DocumentContext json = JsonPath.parse(s);
|
||||
final TypedRow t = new TypedRow();
|
||||
t.setId(json.read("$.id"));
|
||||
t.setDeleted(json.read("$.dataInfo.deletedbyinference"));
|
||||
t.setType(type);
|
||||
t.setOaf(s);
|
||||
return t;
|
||||
}, Encoders.bean(TypedRow.class));
|
||||
}
|
||||
|
||||
/**
|
||||
* Reads a set of eu.dnetlib.dhp.schema.oaf.Relation objects from a sequence file <className, relation json serialization>,
|
||||
* extracts necessary information using json path, wraps the oaf object in a eu.dnetlib.dhp.graph.model.TypedRow
|
||||
* @param sc
|
||||
* @param inputPath
|
||||
* @return the JavaRDD<TypedRow> containing all the relationships
|
||||
*/
|
||||
private Dataset<Relation> readPathRelation(final JavaSparkContext sc, final String inputPath) {
|
||||
final RDD<String> rdd = sc.textFile(inputPath + "/relation")
|
||||
.rdd();
|
||||
|
||||
return getSpark().createDataset(rdd, Encoders.STRING())
|
||||
.map((MapFunction<String, Relation>) s -> new ObjectMapper().readValue(s, Relation.class), Encoders.bean(Relation.class));
|
||||
}
|
||||
|
||||
private ObjectMapper getObjectMapper() {
|
||||
return new ObjectMapper().configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false);
|
||||
}
|
||||
|
||||
private void prepareAccumulators(SparkContext sc) {
|
||||
accumulators.put("resultResult_similarity_isAmongTopNSimilarDocuments", sc.longAccumulator("resultResult_similarity_isAmongTopNSimilarDocuments"));
|
||||
accumulators.put("resultResult_similarity_hasAmongTopNSimilarDocuments", sc.longAccumulator("resultResult_similarity_hasAmongTopNSimilarDocuments"));
|
||||
accumulators.put("resultResult_supplement_isSupplementTo", sc.longAccumulator("resultResult_supplement_isSupplementTo"));
|
||||
accumulators.put("resultResult_supplement_isSupplementedBy", sc.longAccumulator("resultResult_supplement_isSupplementedBy"));
|
||||
accumulators.put("resultResult_dedup_isMergedIn", sc.longAccumulator("resultResult_dedup_isMergedIn"));
|
||||
accumulators.put("resultResult_dedup_merges", sc.longAccumulator("resultResult_dedup_merges"));
|
||||
|
||||
accumulators.put("resultResult_publicationDataset_isRelatedTo", sc.longAccumulator("resultResult_publicationDataset_isRelatedTo"));
|
||||
accumulators.put("resultResult_relationship_isRelatedTo", sc.longAccumulator("resultResult_relationship_isRelatedTo"));
|
||||
accumulators.put("resultProject_outcome_isProducedBy", sc.longAccumulator("resultProject_outcome_isProducedBy"));
|
||||
accumulators.put("resultProject_outcome_produces", sc.longAccumulator("resultProject_outcome_produces"));
|
||||
accumulators.put("resultOrganization_affiliation_isAuthorInstitutionOf", sc.longAccumulator("resultOrganization_affiliation_isAuthorInstitutionOf"));
|
||||
|
||||
accumulators.put("resultOrganization_affiliation_hasAuthorInstitution", sc.longAccumulator("resultOrganization_affiliation_hasAuthorInstitution"));
|
||||
accumulators.put("projectOrganization_participation_hasParticipant", sc.longAccumulator("projectOrganization_participation_hasParticipant"));
|
||||
accumulators.put("projectOrganization_participation_isParticipant", sc.longAccumulator("projectOrganization_participation_isParticipant"));
|
||||
accumulators.put("organizationOrganization_dedup_isMergedIn", sc.longAccumulator("organizationOrganization_dedup_isMergedIn"));
|
||||
accumulators.put("organizationOrganization_dedup_merges", sc.longAccumulator("resultProject_outcome_produces"));
|
||||
accumulators.put("datasourceOrganization_provision_isProvidedBy", sc.longAccumulator("datasourceOrganization_provision_isProvidedBy"));
|
||||
accumulators.put("datasourceOrganization_provision_provides", sc.longAccumulator("datasourceOrganization_provision_provides"));
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,132 @@
|
|||
package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import com.google.common.collect.Lists;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.common.HdfsSupport;
|
||||
import eu.dnetlib.dhp.oa.provision.model.SortableRelation;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
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.PairFunction;
|
||||
import org.apache.spark.rdd.RDD;
|
||||
import org.apache.spark.sql.Dataset;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SaveMode;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import scala.Tuple2;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Optional;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
|
||||
/**
|
||||
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects.
|
||||
* The operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization,
|
||||
* and all the possible relationships (similarity links produced by the Dedup process are excluded).
|
||||
*
|
||||
* The operation is implemented by sequentially joining one entity type at time (E) with the relationships (R), and again
|
||||
* by E, finally grouped by E.id;
|
||||
*
|
||||
* The workflow is organized in different parts aimed to to reduce the complexity of the operation
|
||||
* 1) PrepareRelationsJob:
|
||||
* only consider relationships that are not virtually deleted ($.dataInfo.deletedbyinference == false), each entity
|
||||
* can be linked at most to 100 other objects
|
||||
*
|
||||
* 2) JoinRelationEntityByTargetJob:
|
||||
* prepare tuples [source entity - relation - target entity] (S - R - T):
|
||||
* for each entity type E_i
|
||||
* join (R.target = E_i.id),
|
||||
* map E_i as RelatedEntity T_i, extracting only the necessary information beforehand to produce [R - T_i]
|
||||
* join (E_i.id = [R - T_i].source), where E_i becomes the source entity S
|
||||
*
|
||||
* 3) AdjacencyListBuilderJob:
|
||||
* given the tuple (S - R - T) we need to group by S.id -> List [ R - T ], mappnig the result as JoinedEntity
|
||||
*
|
||||
* 4) XmlConverterJob:
|
||||
* convert the JoinedEntities as XML records
|
||||
*/
|
||||
public class PrepareRelationsJob {
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(PrepareRelationsJob.class);
|
||||
|
||||
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
|
||||
|
||||
public static final int MAX_RELS = 100;
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
String jsonConfiguration = IOUtils.toString(
|
||||
PrepareRelationsJob.class
|
||||
.getResourceAsStream("/eu/dnetlib/dhp/oa/provision/input_params_prepare_relations.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 inputRelationsPath = parser.get("inputRelationsPath");
|
||||
log.info("inputRelationsPath: {}", inputRelationsPath);
|
||||
|
||||
String outputPath = parser.get("outputPath");
|
||||
log.info("outputPath: {}", outputPath);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
|
||||
runWithSparkSession(conf, isSparkSessionManaged,
|
||||
spark -> {
|
||||
removeOutputDir(spark, outputPath);
|
||||
prepareRelationsFromPaths(spark, inputRelationsPath, outputPath);
|
||||
});
|
||||
}
|
||||
|
||||
private static void prepareRelationsFromPaths(SparkSession spark, String inputRelationsPath, String outputPath) {
|
||||
RDD<SortableRelation> rels = readPathRelation(spark, inputRelationsPath)
|
||||
.filter((FilterFunction<SortableRelation>) r -> r.getDataInfo().getDeletedbyinference() == false)
|
||||
.javaRDD()
|
||||
.mapToPair((PairFunction<SortableRelation, String, List<SortableRelation>>) rel -> new Tuple2<>(
|
||||
rel.getSource(),
|
||||
Lists.newArrayList(rel)))
|
||||
.reduceByKey((v1, v2) -> {
|
||||
v1.addAll(v2);
|
||||
v1.sort(SortableRelation::compareTo);
|
||||
if (v1.size() > MAX_RELS) {
|
||||
return v1.subList(0, MAX_RELS);
|
||||
}
|
||||
return new ArrayList<>(v1.subList(0, MAX_RELS));
|
||||
})
|
||||
.flatMap(r -> r._2().iterator())
|
||||
.rdd();
|
||||
|
||||
spark.createDataset(rels, Encoders.bean(SortableRelation.class))
|
||||
.write()
|
||||
.mode(SaveMode.Overwrite)
|
||||
.parquet(outputPath);
|
||||
}
|
||||
|
||||
/**
|
||||
* Reads a Dataset of eu.dnetlib.dhp.oa.provision.model.SortableRelation objects from a newline delimited json text file,
|
||||
*
|
||||
* @param spark
|
||||
* @param inputPath
|
||||
* @return the Dataset<SortableRelation> containing all the relationships
|
||||
*/
|
||||
private static Dataset<SortableRelation> readPathRelation(SparkSession spark, final String inputPath) {
|
||||
return spark.read()
|
||||
.textFile(inputPath)
|
||||
.map((MapFunction<String, SortableRelation>) s -> OBJECT_MAPPER.readValue(s, SortableRelation.class),
|
||||
Encoders.bean(SortableRelation.class));
|
||||
}
|
||||
|
||||
private static void removeOutputDir(SparkSession spark, String path) {
|
||||
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -2,6 +2,7 @@ package eu.dnetlib.dhp.oa.provision;
|
|||
|
||||
import com.lucidworks.spark.util.SolrSupport;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.ContextMapper;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.StreamingInputDocumentFactory;
|
||||
import eu.dnetlib.dhp.utils.ISLookupClientFactory;
|
||||
import eu.dnetlib.dhp.utils.saxon.SaxonTransformerFactory;
|
||||
|
|
@ -18,6 +19,8 @@ import org.apache.spark.SparkConf;
|
|||
import org.apache.spark.api.java.JavaSparkContext;
|
||||
import org.apache.spark.rdd.RDD;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
|
||||
import javax.xml.transform.Transformer;
|
||||
import javax.xml.transform.TransformerException;
|
||||
|
|
@ -28,14 +31,20 @@ import java.io.StringReader;
|
|||
import java.io.StringWriter;
|
||||
import java.text.SimpleDateFormat;
|
||||
import java.util.Date;
|
||||
import java.util.Optional;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
|
||||
public class SparkXmlIndexingJob {
|
||||
|
||||
private static final Log log = LogFactory.getLog(SparkXmlIndexingJob.class);
|
||||
private static final Logger log = LoggerFactory.getLogger(SparkXmlIndexingJob.class);
|
||||
|
||||
private static final Integer DEFAULT_BATCH_SIZE = 1000;
|
||||
|
||||
private static final String LAYOUT = "index";
|
||||
private static final String INTERPRETATION = "openaire";
|
||||
private static final String SEPARATOR = "-";
|
||||
public static final String DATE_FORMAT = "yyyy-MM-dd'T'hh:mm:ss'Z'";
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
|
||||
|
|
@ -45,30 +54,46 @@ public class SparkXmlIndexingJob {
|
|||
"/eu/dnetlib/dhp/oa/provision/input_params_update_index.json")));
|
||||
parser.parseArgument(args);
|
||||
|
||||
final String inputPath = parser.get("sourcePath");
|
||||
Boolean isSparkSessionManaged = Optional
|
||||
.ofNullable(parser.get("isSparkSessionManaged"))
|
||||
.map(Boolean::valueOf)
|
||||
.orElse(Boolean.TRUE);
|
||||
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
|
||||
|
||||
final String inputPath = parser.get("inputPath");
|
||||
log.info("inputPath: {}", inputPath);
|
||||
|
||||
final String isLookupUrl = parser.get("isLookupUrl");
|
||||
log.info("isLookupUrl: {}", isLookupUrl);
|
||||
|
||||
final String format = parser.get("format");
|
||||
log.info("format: {}", format);
|
||||
|
||||
final Integer batchSize = parser.getObjectMap().containsKey("batchSize") ? Integer.valueOf(parser.get("batchSize")) : DEFAULT_BATCH_SIZE;
|
||||
log.info("batchSize: {}", batchSize);
|
||||
|
||||
final ISLookUpService isLookup = ISLookupClientFactory.getLookUpService(isLookupUrl);
|
||||
final String fields = getLayoutSource(isLookup, format);
|
||||
log.info("fields: {}", fields);
|
||||
|
||||
final String xslt = getLayoutTransformer(isLookup);
|
||||
|
||||
final String dsId = getDsId(format, isLookup);
|
||||
log.info("dsId: {}", dsId);
|
||||
|
||||
final String zkHost = getZkHost(isLookup);
|
||||
log.info("zkHost: {}", zkHost);
|
||||
|
||||
final String version = getRecordDatestamp();
|
||||
|
||||
final String indexRecordXslt = getLayoutTransformer(format, fields, xslt);
|
||||
log.info("indexRecordTransformer {}", indexRecordXslt);
|
||||
|
||||
log.info("indexRecordTransformer: " + indexRecordXslt);
|
||||
final SparkConf conf = new SparkConf();
|
||||
|
||||
final String master = parser.get("master");
|
||||
final SparkConf conf = new SparkConf()
|
||||
.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
|
||||
|
||||
try(SparkSession spark = getSession(conf, master)) {
|
||||
|
||||
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
|
||||
runWithSparkSession(conf, isSparkSessionManaged,
|
||||
spark -> {
|
||||
final JavaSparkContext sc = JavaSparkContext.fromSparkContext(spark.sparkContext());
|
||||
|
||||
RDD<SolrInputDocument> docs = sc.sequenceFile(inputPath, Text.class, Text.class)
|
||||
.map(t -> t._2().toString())
|
||||
|
|
@ -76,17 +101,9 @@ public class SparkXmlIndexingJob {
|
|||
.map(s -> new StreamingInputDocumentFactory(version, dsId).parseDocument(s))
|
||||
.rdd();
|
||||
|
||||
SolrSupport.indexDocs(zkHost, format + "-" + LAYOUT + "-openaire", batchSize, docs);
|
||||
}
|
||||
}
|
||||
|
||||
private static SparkSession getSession(SparkConf conf, String master) {
|
||||
return SparkSession
|
||||
.builder()
|
||||
.config(conf)
|
||||
.appName(SparkXmlIndexingJob.class.getSimpleName())
|
||||
.master(master)
|
||||
.getOrCreate();
|
||||
final String collection = format + SEPARATOR + LAYOUT + SEPARATOR + INTERPRETATION;
|
||||
SolrSupport.indexDocs(zkHost, collection, batchSize, docs);
|
||||
});
|
||||
}
|
||||
|
||||
private static String toIndexRecord(Transformer tr, final String record) {
|
||||
|
|
@ -95,7 +112,7 @@ public class SparkXmlIndexingJob {
|
|||
tr.transform(new StreamSource(new StringReader(record)), res);
|
||||
return res.getWriter().toString();
|
||||
} catch (Throwable e) {
|
||||
System.out.println("XPathException on record:\n" + record);
|
||||
log.error("XPathException on record: \n {}", record, e);
|
||||
throw new IllegalArgumentException(e);
|
||||
}
|
||||
}
|
||||
|
|
@ -127,7 +144,7 @@ public class SparkXmlIndexingJob {
|
|||
* @return the parsed date
|
||||
*/
|
||||
public static String getRecordDatestamp() {
|
||||
return new SimpleDateFormat("yyyy-MM-dd'T'hh:mm:ss'Z'").format(new Date());
|
||||
return new SimpleDateFormat(DATE_FORMAT).format(new Date());
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -1,81 +0,0 @@
|
|||
package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.oa.provision.model.*;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.ContextMapper;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
|
||||
public class SparkXmlRecordBuilderJob_v2 {
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
|
||||
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
|
||||
IOUtils.toString(
|
||||
SparkXmlRecordBuilderJob_v2.class.getResourceAsStream("/eu/dnetlib/dhp/oa/provision/input_params_build_adjacency_lists.json")));
|
||||
parser.parseArgument(args);
|
||||
|
||||
try(SparkSession spark = getSession(parser)) {
|
||||
|
||||
final String inputPath = parser.get("sourcePath");
|
||||
final String outputPath = parser.get("outputPath");
|
||||
final String isLookupUrl = parser.get("isLookupUrl");
|
||||
final String otherDsTypeId = parser.get("otherDsTypeId");
|
||||
|
||||
|
||||
new GraphJoiner_v2(spark, ContextMapper.fromIS(isLookupUrl), otherDsTypeId, inputPath, outputPath)
|
||||
.adjacencyLists();
|
||||
}
|
||||
}
|
||||
|
||||
private static SparkSession getSession(ArgumentApplicationParser parser) {
|
||||
final SparkConf conf = new SparkConf();
|
||||
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
|
||||
conf.set("spark.sql.shuffle.partitions", parser.get("sparkSqlShufflePartitions"));
|
||||
conf.registerKryoClasses(new Class[]{
|
||||
Author.class,
|
||||
Context.class,
|
||||
Country.class,
|
||||
DataInfo.class,
|
||||
eu.dnetlib.dhp.schema.oaf.Dataset.class,
|
||||
Datasource.class,
|
||||
ExternalReference.class,
|
||||
ExtraInfo.class,
|
||||
Field.class,
|
||||
GeoLocation.class,
|
||||
Instance.class,
|
||||
Journal.class,
|
||||
KeyValue.class,
|
||||
Oaf.class,
|
||||
OafEntity.class,
|
||||
OAIProvenance.class,
|
||||
Organization.class,
|
||||
OriginDescription.class,
|
||||
OtherResearchProduct.class,
|
||||
Project.class,
|
||||
Publication.class,
|
||||
Qualifier.class,
|
||||
Relation.class,
|
||||
Result.class,
|
||||
Software.class,
|
||||
StructuredProperty.class,
|
||||
|
||||
TypedRow.class,
|
||||
EntityRelEntity.class,
|
||||
JoinedEntity.class,
|
||||
SortableRelationKey.class,
|
||||
Tuple2.class,
|
||||
Links.class,
|
||||
RelatedEntity.class
|
||||
});
|
||||
return SparkSession
|
||||
.builder()
|
||||
.config(conf)
|
||||
.appName(SparkXmlRecordBuilderJob_v2.class.getSimpleName())
|
||||
.master(parser.get("master"))
|
||||
.getOrCreate();
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,149 @@
|
|||
package eu.dnetlib.dhp.oa.provision;
|
||||
|
||||
import com.google.common.collect.Maps;
|
||||
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
|
||||
import eu.dnetlib.dhp.common.HdfsSupport;
|
||||
import eu.dnetlib.dhp.oa.provision.model.*;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.ContextMapper;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils;
|
||||
import eu.dnetlib.dhp.oa.provision.utils.XmlRecordFactory;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import org.apache.commons.io.IOUtils;
|
||||
import org.apache.hadoop.io.Text;
|
||||
import org.apache.hadoop.io.compress.GzipCodec;
|
||||
import org.apache.hadoop.mapred.SequenceFileOutputFormat;
|
||||
import org.apache.spark.SparkConf;
|
||||
import org.apache.spark.SparkContext;
|
||||
import org.apache.spark.api.java.function.Function;
|
||||
import org.apache.spark.api.java.function.Function2;
|
||||
import org.apache.spark.api.java.function.MapFunction;
|
||||
import org.apache.spark.api.java.function.PairFunction;
|
||||
import org.apache.spark.rdd.RDD;
|
||||
import org.apache.spark.sql.Encoders;
|
||||
import org.apache.spark.sql.SaveMode;
|
||||
import org.apache.spark.sql.SparkSession;
|
||||
import org.apache.spark.util.LongAccumulator;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import scala.Tuple2;
|
||||
|
||||
import java.util.Map;
|
||||
import java.util.Optional;
|
||||
|
||||
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkSession;
|
||||
|
||||
/**
|
||||
* Joins the graph nodes by resolving the links of distance = 1 to create an adjacency list of linked objects.
|
||||
* The operation considers all the entity types (publication, dataset, software, ORP, project, datasource, organization,
|
||||
* and all the possible relationships (similarity links produced by the Dedup process are excluded).
|
||||
*
|
||||
* The operation is implemented by sequentially joining one entity type at time (E) with the relationships (R), and again
|
||||
* by E, finally grouped by E.id;
|
||||
*
|
||||
* The workflow is organized in different parts aimed to to reduce the complexity of the operation
|
||||
* 1) PrepareRelationsJob:
|
||||
* only consider relationships that are not virtually deleted ($.dataInfo.deletedbyinference == false), each entity
|
||||
* can be linked at most to 100 other objects
|
||||
*
|
||||
* 2) JoinRelationEntityByTargetJob:
|
||||
* prepare tuples [source entity - relation - target entity] (S - R - T):
|
||||
* for each entity type E_i
|
||||
* join (R.target = E_i.id),
|
||||
* map E_i as RelatedEntity T_i, extracting only the necessary information beforehand to produce [R - T_i]
|
||||
* join (E_i.id = [R - T_i].source), where E_i becomes the source entity S
|
||||
*
|
||||
* 3) AdjacencyListBuilderJob:
|
||||
* given the tuple (S - R - T) we need to group by S.id -> List [ R - T ], mappnig the result as JoinedEntity
|
||||
*
|
||||
* 4) XmlConverterJob:
|
||||
* convert the JoinedEntities as XML records
|
||||
*/
|
||||
public class XmlConverterJob {
|
||||
|
||||
private static final Logger log = LoggerFactory.getLogger(XmlConverterJob.class);
|
||||
|
||||
public static final String schemaLocation = "https://www.openaire.eu/schema/1.0/oaf-1.0.xsd";
|
||||
|
||||
public static void main(String[] args) throws Exception {
|
||||
|
||||
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
|
||||
IOUtils.toString(
|
||||
XmlConverterJob.class
|
||||
.getResourceAsStream("/eu/dnetlib/dhp/oa/provision/input_params_xml_converter.json")));
|
||||
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);
|
||||
|
||||
String isLookupUrl = parser.get("isLookupUrl");
|
||||
log.info("isLookupUrl: {}", isLookupUrl);
|
||||
|
||||
String otherDsTypeId = parser.get("otherDsTypeId");
|
||||
log.info("otherDsTypeId: {}", otherDsTypeId);
|
||||
|
||||
SparkConf conf = new SparkConf();
|
||||
|
||||
runWithSparkSession(conf, isSparkSessionManaged,
|
||||
spark -> {
|
||||
removeOutputDir(spark, outputPath);
|
||||
convertToXml(spark, inputPath, outputPath, ContextMapper.fromIS(isLookupUrl), otherDsTypeId);
|
||||
});
|
||||
|
||||
}
|
||||
|
||||
private static void convertToXml(SparkSession spark, String inputPath, String outputPath, ContextMapper contextMapper, String otherDsTypeId) {
|
||||
|
||||
final XmlRecordFactory recordFactory = new XmlRecordFactory(prepareAccumulators(spark.sparkContext()), contextMapper, false, schemaLocation, otherDsTypeId);
|
||||
|
||||
spark.read()
|
||||
.load(inputPath)
|
||||
.as(Encoders.bean(JoinedEntity.class))
|
||||
.map((MapFunction<JoinedEntity, Tuple2<String, String>>) je -> new Tuple2<>(
|
||||
je.getEntity().getId(),
|
||||
recordFactory.build(je)
|
||||
), Encoders.tuple(Encoders.STRING(), Encoders.STRING()))
|
||||
.javaRDD()
|
||||
.mapToPair((PairFunction<Tuple2<String, String>, String, String>) t -> t)
|
||||
.saveAsHadoopFile(outputPath, Text.class, Text.class, SequenceFileOutputFormat.class, GzipCodec.class);
|
||||
}
|
||||
|
||||
private static void removeOutputDir(SparkSession spark, String path) {
|
||||
HdfsSupport.remove(path, spark.sparkContext().hadoopConfiguration());
|
||||
}
|
||||
|
||||
private static Map<String, LongAccumulator> prepareAccumulators(SparkContext sc) {
|
||||
Map<String, LongAccumulator> accumulators = Maps.newHashMap();
|
||||
accumulators.put("resultResult_similarity_isAmongTopNSimilarDocuments", sc.longAccumulator("resultResult_similarity_isAmongTopNSimilarDocuments"));
|
||||
accumulators.put("resultResult_similarity_hasAmongTopNSimilarDocuments", sc.longAccumulator("resultResult_similarity_hasAmongTopNSimilarDocuments"));
|
||||
accumulators.put("resultResult_supplement_isSupplementTo", sc.longAccumulator("resultResult_supplement_isSupplementTo"));
|
||||
accumulators.put("resultResult_supplement_isSupplementedBy", sc.longAccumulator("resultResult_supplement_isSupplementedBy"));
|
||||
accumulators.put("resultResult_dedup_isMergedIn", sc.longAccumulator("resultResult_dedup_isMergedIn"));
|
||||
accumulators.put("resultResult_dedup_merges", sc.longAccumulator("resultResult_dedup_merges"));
|
||||
|
||||
accumulators.put("resultResult_publicationDataset_isRelatedTo", sc.longAccumulator("resultResult_publicationDataset_isRelatedTo"));
|
||||
accumulators.put("resultResult_relationship_isRelatedTo", sc.longAccumulator("resultResult_relationship_isRelatedTo"));
|
||||
accumulators.put("resultProject_outcome_isProducedBy", sc.longAccumulator("resultProject_outcome_isProducedBy"));
|
||||
accumulators.put("resultProject_outcome_produces", sc.longAccumulator("resultProject_outcome_produces"));
|
||||
accumulators.put("resultOrganization_affiliation_isAuthorInstitutionOf", sc.longAccumulator("resultOrganization_affiliation_isAuthorInstitutionOf"));
|
||||
|
||||
accumulators.put("resultOrganization_affiliation_hasAuthorInstitution", sc.longAccumulator("resultOrganization_affiliation_hasAuthorInstitution"));
|
||||
accumulators.put("projectOrganization_participation_hasParticipant", sc.longAccumulator("projectOrganization_participation_hasParticipant"));
|
||||
accumulators.put("projectOrganization_participation_isParticipant", sc.longAccumulator("projectOrganization_participation_isParticipant"));
|
||||
accumulators.put("organizationOrganization_dedup_isMergedIn", sc.longAccumulator("organizationOrganization_dedup_isMergedIn"));
|
||||
accumulators.put("organizationOrganization_dedup_merges", sc.longAccumulator("resultProject_outcome_produces"));
|
||||
accumulators.put("datasourceOrganization_provision_isProvidedBy", sc.longAccumulator("datasourceOrganization_provision_isProvidedBy"));
|
||||
accumulators.put("datasourceOrganization_provision_provides", sc.longAccumulator("datasourceOrganization_provision_provides"));
|
||||
|
||||
return accumulators;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
@ -1,15 +1,26 @@
|
|||
package eu.dnetlib.dhp.oa.provision.model;
|
||||
|
||||
import eu.dnetlib.dhp.schema.oaf.Relation;
|
||||
|
||||
import java.io.Serializable;
|
||||
|
||||
public class EntityRelEntity implements Serializable {
|
||||
|
||||
private TypedRow entity;
|
||||
private Relation relation;
|
||||
private SortableRelation relation;
|
||||
private RelatedEntity target;
|
||||
|
||||
public EntityRelEntity() {
|
||||
}
|
||||
|
||||
public EntityRelEntity(SortableRelation relation, RelatedEntity target) {
|
||||
this(null, relation, target);
|
||||
}
|
||||
|
||||
public EntityRelEntity(TypedRow entity, SortableRelation relation, RelatedEntity target) {
|
||||
this.entity = entity;
|
||||
this.relation = relation;
|
||||
this.target = target;
|
||||
}
|
||||
|
||||
public TypedRow getEntity() {
|
||||
return entity;
|
||||
}
|
||||
|
|
@ -18,11 +29,11 @@ public class EntityRelEntity implements Serializable {
|
|||
this.entity = entity;
|
||||
}
|
||||
|
||||
public Relation getRelation() {
|
||||
public SortableRelation getRelation() {
|
||||
return relation;
|
||||
}
|
||||
|
||||
public void setRelation(Relation relation) {
|
||||
public void setRelation(SortableRelation relation) {
|
||||
this.relation = relation;
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -1,22 +1,23 @@
|
|||
package eu.dnetlib.dhp.oa.provision.model;
|
||||
|
||||
import eu.dnetlib.dhp.oa.provision.utils.GraphMappingUtils;
|
||||
import eu.dnetlib.dhp.schema.oaf.OafEntity;
|
||||
|
||||
import java.io.Serializable;
|
||||
|
||||
public class JoinedEntity implements Serializable {
|
||||
|
||||
private String type;
|
||||
private GraphMappingUtils.EntityType type;
|
||||
|
||||
private OafEntity entity;
|
||||
|
||||
private Links links;
|
||||
|
||||
public String getType() {
|
||||
public GraphMappingUtils.EntityType getType() {
|
||||
return type;
|
||||
}
|
||||
|
||||
public void setType(String type) {
|
||||
public void setType(GraphMappingUtils.EntityType type) {
|
||||
this.type = type;
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
package eu.dnetlib.dhp.oa.provision.model;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.HashSet;
|
||||
|
||||
public class Links extends ArrayList<Tuple2> {
|
||||
public class Links extends HashSet<Tuple2> {
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,34 @@
|
|||
package eu.dnetlib.dhp.oa.provision.model;
|
||||
|
||||
import com.google.common.collect.ComparisonChain;
|
||||
import com.google.common.collect.Maps;
|
||||
import eu.dnetlib.dhp.schema.oaf.Relation;
|
||||
|
||||
import java.util.Map;
|
||||
|
||||
public class SortableRelation extends Relation implements Comparable<Relation> {
|
||||
|
||||
private final static Map<String, Integer> weights = Maps.newHashMap();
|
||||
|
||||
static {
|
||||
weights.put("outcome", 0);
|
||||
weights.put("supplement", 1);
|
||||
weights.put("publicationDataset", 2);
|
||||
weights.put("relationship", 3);
|
||||
weights.put("similarity", 4);
|
||||
weights.put("affiliation", 5);
|
||||
|
||||
weights.put("provision", 6);
|
||||
weights.put("participation", 7);
|
||||
weights.put("dedup", 8);
|
||||
}
|
||||
|
||||
@Override
|
||||
public int compareTo(Relation o) {
|
||||
return ComparisonChain.start()
|
||||
.compare(weights.get(getSubRelType()), weights.get(o.getSubRelType()))
|
||||
.compare(getSource(), o.getSource())
|
||||
.compare(getTarget(), o.getTarget())
|
||||
.result();
|
||||
}
|
||||
}
|
||||
|
|
@ -2,7 +2,10 @@ package eu.dnetlib.dhp.oa.provision.model;
|
|||
|
||||
import eu.dnetlib.dhp.schema.oaf.Relation;
|
||||
|
||||
public class Tuple2 {
|
||||
import java.io.Serializable;
|
||||
import java.util.Objects;
|
||||
|
||||
public class Tuple2 implements Serializable {
|
||||
|
||||
private Relation relation;
|
||||
|
||||
|
|
@ -28,4 +31,18 @@ public class Tuple2 {
|
|||
public void setRelatedEntity(RelatedEntity relatedEntity) {
|
||||
this.relatedEntity = relatedEntity;
|
||||
}
|
||||
|
||||
@Override
|
||||
public boolean equals(Object o) {
|
||||
if (this == o) return true;
|
||||
if (o == null || getClass() != o.getClass()) return false;
|
||||
Tuple2 t2 = (Tuple2) o;
|
||||
return getRelation().equals(t2.getRelation());
|
||||
}
|
||||
|
||||
@Override
|
||||
public int hashCode() {
|
||||
return Objects.hash(getRelation().hashCode());
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,30 +1,47 @@
|
|||
package eu.dnetlib.dhp.oa.provision.utils;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonInclude;
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import com.google.common.collect.Maps;
|
||||
import com.google.common.collect.Sets;
|
||||
import com.jayway.jsonpath.DocumentContext;
|
||||
import com.jayway.jsonpath.JsonPath;
|
||||
import eu.dnetlib.dhp.oa.provision.model.*;
|
||||
import eu.dnetlib.dhp.oa.provision.model.RelatedEntity;
|
||||
import eu.dnetlib.dhp.oa.provision.model.SortableRelation;
|
||||
import eu.dnetlib.dhp.schema.oaf.*;
|
||||
import net.minidev.json.JSONArray;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
|
||||
import java.util.LinkedHashMap;
|
||||
import java.util.Map;
|
||||
import java.util.Set;
|
||||
import java.util.*;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
import static org.apache.commons.lang3.StringUtils.*;
|
||||
import static org.apache.commons.lang3.StringUtils.substringAfter;
|
||||
|
||||
public class GraphMappingUtils {
|
||||
|
||||
public static final String SEPARATOR = "_";
|
||||
|
||||
public final static Map<EntityType, Class> entityTypes = Maps.newHashMap();
|
||||
|
||||
static {
|
||||
entityTypes.put(EntityType.datasource, Datasource.class);
|
||||
entityTypes.put(EntityType.organization, Organization.class);
|
||||
entityTypes.put(EntityType.project, Project.class);
|
||||
entityTypes.put(EntityType.dataset, Dataset.class);
|
||||
entityTypes.put(EntityType.otherresearchproduct, OtherResearchProduct.class);
|
||||
entityTypes.put(EntityType.software, Software.class);
|
||||
entityTypes.put(EntityType.publication, Publication.class);
|
||||
}
|
||||
|
||||
public enum EntityType {
|
||||
publication, dataset, otherresearchproduct, software, datasource, organization, project
|
||||
publication, dataset, otherresearchproduct, software, datasource, organization, project;
|
||||
|
||||
public static <T extends OafEntity> EntityType fromClass(Class<T> clazz) {
|
||||
switch (clazz.getName()) {
|
||||
case "eu.dnetlib.dhp.schema.oaf.Publication" : return publication;
|
||||
case "eu.dnetlib.dhp.schema.oaf.Dataset" : return dataset;
|
||||
case "eu.dnetlib.dhp.schema.oaf.OtherResearchProduct" : return otherresearchproduct;
|
||||
case "eu.dnetlib.dhp.schema.oaf.Software" : return software;
|
||||
case "eu.dnetlib.dhp.schema.oaf.Datasource" : return datasource;
|
||||
case "eu.dnetlib.dhp.schema.oaf.Organization" : return organization;
|
||||
case "eu.dnetlib.dhp.schema.oaf.Project" : return project;
|
||||
default: throw new IllegalArgumentException("Unknown OafEntity class: " + clazz.getName());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public enum MainEntityType {
|
||||
|
|
@ -33,8 +50,6 @@ public class GraphMappingUtils {
|
|||
|
||||
public static Set<String> authorPidTypes = Sets.newHashSet("orcid", "magidentifier");
|
||||
|
||||
public static Set<String> instanceFieldFilter = Sets.newHashSet("instancetype", "hostedby", "license", "accessright", "collectedfrom", "dateofacceptance", "distributionlocation");
|
||||
|
||||
private static final String schemeTemplate = "dnet:%s_%s_relations";
|
||||
|
||||
private static Map<EntityType, MainEntityType> entityMapping = Maps.newHashMap();
|
||||
|
|
@ -49,6 +64,38 @@ public class GraphMappingUtils {
|
|||
entityMapping.put(EntityType.project, MainEntityType.project);
|
||||
}
|
||||
|
||||
public static Class[] getKryoClasses() {
|
||||
return new Class[]{
|
||||
Author.class,
|
||||
Context.class,
|
||||
Country.class,
|
||||
DataInfo.class,
|
||||
eu.dnetlib.dhp.schema.oaf.Dataset.class,
|
||||
Datasource.class,
|
||||
ExternalReference.class,
|
||||
ExtraInfo.class,
|
||||
Field.class,
|
||||
GeoLocation.class,
|
||||
Instance.class,
|
||||
Journal.class,
|
||||
KeyValue.class,
|
||||
Oaf.class,
|
||||
OafEntity.class,
|
||||
OAIProvenance.class,
|
||||
Organization.class,
|
||||
OriginDescription.class,
|
||||
OtherResearchProduct.class,
|
||||
Project.class,
|
||||
Publication.class,
|
||||
Qualifier.class,
|
||||
Relation.class,
|
||||
SortableRelation.class, //SUPPORT
|
||||
Result.class,
|
||||
Software.class,
|
||||
StructuredProperty.class
|
||||
};
|
||||
}
|
||||
|
||||
public static String getScheme(final String sourceType, final String targetType) {
|
||||
return String.format(schemeTemplate,
|
||||
entityMapping.get(EntityType.valueOf(sourceType)).name(),
|
||||
|
|
@ -63,152 +110,81 @@ public class GraphMappingUtils {
|
|||
return MainEntityType.result.name().equals(getMainType(type));
|
||||
}
|
||||
|
||||
public static RelatedEntity asRelatedEntity(TypedRow e) {
|
||||
public static <E extends OafEntity> RelatedEntity asRelatedEntity(E entity, Class<E> clazz) {
|
||||
|
||||
final DocumentContext j = JsonPath.parse(e.getOaf());
|
||||
final RelatedEntity re = new RelatedEntity();
|
||||
re.setId(j.read("$.id"));
|
||||
re.setType(e.getType());
|
||||
re.setId(entity.getId());
|
||||
re.setType(clazz.getName());
|
||||
|
||||
switch (EntityType.valueOf(e.getType())) {
|
||||
re.setPid(entity.getPid());
|
||||
re.setCollectedfrom(entity.getCollectedfrom());
|
||||
|
||||
switch (GraphMappingUtils.EntityType.fromClass(clazz)) {
|
||||
case publication:
|
||||
case dataset:
|
||||
case otherresearchproduct:
|
||||
case software:
|
||||
mapTitle(j, re);
|
||||
re.setDateofacceptance(j.read("$.dateofacceptance.value"));
|
||||
re.setPublisher(j.read("$.publisher.value"));
|
||||
|
||||
JSONArray pids = j.read("$.pid");
|
||||
re.setPid(pids.stream()
|
||||
.map(p -> asStructuredProperty((LinkedHashMap<String, Object>) p))
|
||||
.collect(Collectors.toList()));
|
||||
Result r = (Result) entity;
|
||||
|
||||
re.setResulttype(asQualifier(j.read("$.resulttype")));
|
||||
if (r.getTitle() == null && !r.getTitle().isEmpty()) {
|
||||
re.setTitle(r.getTitle().stream().findFirst().get());
|
||||
}
|
||||
|
||||
JSONArray collfrom = j.read("$.collectedfrom");
|
||||
re.setCollectedfrom(collfrom.stream()
|
||||
.map(c -> asKV((LinkedHashMap<String, Object>) c))
|
||||
.collect(Collectors.toList()));
|
||||
|
||||
// will throw exception when the instance is not found
|
||||
JSONArray instances = j.read("$.instance");
|
||||
re.setInstances(instances.stream()
|
||||
.map(i -> {
|
||||
final LinkedHashMap<String, Object> p = (LinkedHashMap<String, Object>) i;
|
||||
final Field<String> license = new Field<String>();
|
||||
license.setValue((String) ((LinkedHashMap<String, Object>) p.get("license")).get("value"));
|
||||
final Instance instance = new Instance();
|
||||
instance.setLicense(license);
|
||||
instance.setAccessright(asQualifier((LinkedHashMap<String, String>) p.get("accessright")));
|
||||
instance.setInstancetype(asQualifier((LinkedHashMap<String, String>) p.get("instancetype")));
|
||||
instance.setHostedby(asKV((LinkedHashMap<String, Object>) p.get("hostedby")));
|
||||
//TODO mapping of distributionlocation
|
||||
instance.setCollectedfrom(asKV((LinkedHashMap<String, Object>) p.get("collectedfrom")));
|
||||
|
||||
Field<String> dateofacceptance = new Field<String>();
|
||||
dateofacceptance.setValue((String) ((LinkedHashMap<String, Object>) p.get("dateofacceptance")).get("value"));
|
||||
instance.setDateofacceptance(dateofacceptance);
|
||||
return instance;
|
||||
}).collect(Collectors.toList()));
|
||||
re.setDateofacceptance(getValue(r.getDateofacceptance()));
|
||||
re.setPublisher(getValue(r.getPublisher()));
|
||||
re.setResulttype(re.getResulttype());
|
||||
re.setInstances(re.getInstances());
|
||||
|
||||
//TODO still to be mapped
|
||||
//re.setCodeRepositoryUrl(j.read("$.coderepositoryurl"));
|
||||
|
||||
break;
|
||||
case datasource:
|
||||
re.setOfficialname(j.read("$.officialname.value"));
|
||||
re.setWebsiteurl(j.read("$.websiteurl.value"));
|
||||
re.setDatasourcetype(asQualifier(j.read("$.datasourcetype")));
|
||||
re.setOpenairecompatibility(asQualifier(j.read("$.openairecompatibility")));
|
||||
Datasource d = (Datasource) entity;
|
||||
|
||||
re.setOfficialname(getValue(d.getOfficialname()));
|
||||
re.setWebsiteurl(getValue(d.getWebsiteurl()));
|
||||
re.setDatasourcetype(d.getDatasourcetype());
|
||||
re.setOpenairecompatibility(d.getOpenairecompatibility());
|
||||
|
||||
break;
|
||||
case organization:
|
||||
re.setLegalname(j.read("$.legalname.value"));
|
||||
re.setLegalshortname(j.read("$.legalshortname.value"));
|
||||
re.setCountry(asQualifier(j.read("$.country")));
|
||||
re.setWebsiteurl(j.read("$.websiteurl.value"));
|
||||
Organization o = (Organization) entity;
|
||||
|
||||
re.setLegalname(getValue(o.getLegalname()));
|
||||
re.setLegalshortname(getValue(o.getLegalshortname()));
|
||||
re.setCountry(o.getCountry());
|
||||
re.setWebsiteurl(getValue(o.getWebsiteurl()));
|
||||
break;
|
||||
case project:
|
||||
re.setProjectTitle(j.read("$.title.value"));
|
||||
re.setCode(j.read("$.code.value"));
|
||||
re.setAcronym(j.read("$.acronym.value"));
|
||||
re.setContracttype(asQualifier(j.read("$.contracttype")));
|
||||
Project p = (Project) entity;
|
||||
|
||||
JSONArray f = j.read("$.fundingtree");
|
||||
re.setProjectTitle(getValue(p.getTitle()));
|
||||
re.setCode(getValue(p.getCode()));
|
||||
re.setAcronym(getValue(p.getAcronym()));
|
||||
re.setContracttype(p.getContracttype());
|
||||
|
||||
List<Field<String>> f = p.getFundingtree();
|
||||
if (!f.isEmpty()) {
|
||||
re.setFundingtree(f.stream()
|
||||
.map(s -> ((LinkedHashMap<String, String>) s).get("value"))
|
||||
.map(s -> s.getValue())
|
||||
.collect(Collectors.toList()));
|
||||
}
|
||||
|
||||
break;
|
||||
}
|
||||
|
||||
return re;
|
||||
}
|
||||
|
||||
|
||||
private static KeyValue asKV(LinkedHashMap<String, Object> j) {
|
||||
final KeyValue kv = new KeyValue();
|
||||
kv.setKey((String) j.get("key"));
|
||||
kv.setValue((String) j.get("value"));
|
||||
return kv;
|
||||
private static String getValue(Field<String> field) {
|
||||
return getFieldValueWithDefault(field, "");
|
||||
}
|
||||
|
||||
private static void mapTitle(DocumentContext j, RelatedEntity re) {
|
||||
final JSONArray a = j.read("$.title");
|
||||
if (!a.isEmpty()) {
|
||||
final StructuredProperty sp = asStructuredProperty((LinkedHashMap<String, Object>) a.get(0));
|
||||
if (StringUtils.isNotBlank(sp.getValue())) {
|
||||
re.setTitle(sp);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private static StructuredProperty asStructuredProperty(LinkedHashMap<String, Object> j) {
|
||||
final StructuredProperty sp = new StructuredProperty();
|
||||
final String value = (String) j.get("value");
|
||||
if (StringUtils.isNotBlank(value)) {
|
||||
sp.setValue((String) j.get("value"));
|
||||
sp.setQualifier(asQualifier((LinkedHashMap<String, String>) j.get("qualifier")));
|
||||
}
|
||||
return sp;
|
||||
}
|
||||
|
||||
public static Qualifier asQualifier(LinkedHashMap<String, String> j) {
|
||||
final Qualifier q = new Qualifier();
|
||||
|
||||
final String classid = j.get("classid");
|
||||
if (StringUtils.isNotBlank(classid)) {
|
||||
q.setClassid(classid);
|
||||
}
|
||||
|
||||
final String classname = j.get("classname");
|
||||
if (StringUtils.isNotBlank(classname)) {
|
||||
q.setClassname(classname);
|
||||
}
|
||||
|
||||
final String schemeid = j.get("schemeid");
|
||||
if (StringUtils.isNotBlank(schemeid)) {
|
||||
q.setSchemeid(schemeid);
|
||||
}
|
||||
|
||||
final String schemename = j.get("schemename");
|
||||
if (StringUtils.isNotBlank(schemename)) {
|
||||
q.setSchemename(schemename);
|
||||
}
|
||||
return q;
|
||||
}
|
||||
|
||||
public static String serialize(final Object o) {
|
||||
try {
|
||||
return new ObjectMapper()
|
||||
.setSerializationInclusion(JsonInclude.Include.NON_NULL)
|
||||
.writeValueAsString(o);
|
||||
} catch (JsonProcessingException e) {
|
||||
throw new IllegalArgumentException("unable to serialize: " + o.toString(), e);
|
||||
}
|
||||
private static <T> T getFieldValueWithDefault(Field<T> f, T defaultValue) {
|
||||
return Optional.ofNullable(f)
|
||||
.filter(Objects::nonNull)
|
||||
.map(x -> x.getValue())
|
||||
.orElse(defaultValue);
|
||||
}
|
||||
|
||||
public static String removePrefix(final String s) {
|
||||
|
|
|
|||
|
|
@ -1,8 +1,14 @@
|
|||
[
|
||||
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
|
||||
{"paramName":"is", "paramLongName":"isLookupUrl", "paramDescription": "URL of the isLookUp Service", "paramRequired": true},
|
||||
{"paramName":"o", "paramLongName":"outputPath", "paramDescription": "the path used to store temporary output files", "paramRequired": true},
|
||||
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the path of the sequence file to read", "paramRequired": true},
|
||||
{"paramName":"t", "paramLongName":"otherDsTypeId", "paramDescription": "list of datasource types to populate field datasourcetypeui", "paramRequired": true},
|
||||
{"paramName":"sp", "paramLongName":"sparkSqlShufflePartitions", "paramDescription": "Configures the number of partitions to use when shuffling data for joins or aggregations", "paramRequired": true}
|
||||
{
|
||||
"paramName": "in",
|
||||
"paramLongName": "inputPath",
|
||||
"paramDescription": "the path of the sequence file to read",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "out",
|
||||
"paramLongName": "outputPath",
|
||||
"paramDescription": "the path used to store temporary output files",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
[
|
||||
{
|
||||
"paramName": "issm",
|
||||
"paramLongName": "isSparkSessionManaged",
|
||||
"paramDescription": "when true will stop SparkSession after job execution",
|
||||
"paramRequired": false
|
||||
},
|
||||
{
|
||||
"paramName": "irp",
|
||||
"paramLongName": "inputRelationsPath",
|
||||
"paramDescription": "path to input relations prepare",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "op",
|
||||
"paramLongName": "outputPath",
|
||||
"paramDescription": "root output location for prepared relations",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -0,0 +1,32 @@
|
|||
[
|
||||
{
|
||||
"paramName": "issm",
|
||||
"paramLongName": "isSparkSessionManaged",
|
||||
"paramDescription": "when true will stop SparkSession after job execution",
|
||||
"paramRequired": false
|
||||
},
|
||||
{
|
||||
"paramName": "irp",
|
||||
"paramLongName": "inputRelationsPath",
|
||||
"paramDescription": "path to input relations from the graph",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "iep",
|
||||
"paramLongName": "inputEntityPath",
|
||||
"paramDescription": "path to input entity from the graph",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "clazz",
|
||||
"paramLongName": "graphTableClassName",
|
||||
"paramDescription": "class name associated to the input entity path",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "op",
|
||||
"paramLongName": "outputPath",
|
||||
"paramDescription": "root output location for prepared relations",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -0,0 +1,26 @@
|
|||
[
|
||||
{
|
||||
"paramName": "issm",
|
||||
"paramLongName": "isSparkSessionManaged",
|
||||
"paramDescription": "when true will stop SparkSession after job execution",
|
||||
"paramRequired": false
|
||||
},
|
||||
{
|
||||
"paramName": "irp",
|
||||
"paramLongName": "inputRelatedEntitiesPath",
|
||||
"paramDescription": "path to input relations from the graph",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "iep",
|
||||
"paramLongName": "inputGraphPath",
|
||||
"paramDescription": "root graph path",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "op",
|
||||
"paramLongName": "outputPath",
|
||||
"paramDescription": "root output location for prepared relations",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
[
|
||||
{"paramName":"mt", "paramLongName":"master", "paramDescription": "should be local or yarn", "paramRequired": true},
|
||||
{"paramName":"is", "paramLongName":"isLookupUrl", "paramDescription": "URL of the isLookUp Service", "paramRequired": true},
|
||||
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the path of the sequence file to read the XML records", "paramRequired": true},
|
||||
{"paramName":"i", "paramLongName":"inputPath", "paramDescription": "the path of the sequence file to read the XML records", "paramRequired": true},
|
||||
{"paramName":"f", "paramLongName":"format", "paramDescription": "MDFormat name found in the IS profile", "paramRequired": true},
|
||||
{"paramName":"b", "paramLongName":"batchSize", "paramDescription": "size of the batch of documents sent to solr", "paramRequired": false}
|
||||
]
|
||||
|
|
|
|||
|
|
@ -0,0 +1,26 @@
|
|||
[
|
||||
{
|
||||
"paramName": "in",
|
||||
"paramLongName": "inputPath",
|
||||
"paramDescription": "the path of the sequence file to read",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "out",
|
||||
"paramLongName": "outputPath",
|
||||
"paramDescription": "the path used to store temporary output files",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "ilu",
|
||||
"paramLongName": "isLookupUrl",
|
||||
"paramDescription": "URL of the isLookUp Service",
|
||||
"paramRequired": true
|
||||
},
|
||||
{
|
||||
"paramName": "odt",
|
||||
"paramLongName": "otherDsTypeId",
|
||||
"paramDescription": "list of datasource types to populate field datasourcetypeui",
|
||||
"paramRequired": true
|
||||
}
|
||||
]
|
||||
|
|
@ -1,6 +1,11 @@
|
|||
<workflow-app name="index_infospace_graph" xmlns="uri:oozie:workflow:0.5">
|
||||
|
||||
<parameters>
|
||||
<property>
|
||||
<name>inputGraphRootPath</name>
|
||||
<description>root location of input materialized graph</description>
|
||||
</property>
|
||||
|
||||
<property>
|
||||
<name>sparkDriverMemoryForJoining</name>
|
||||
<description>memory for driver process</description>
|
||||
|
|
@ -64,7 +69,7 @@
|
|||
|
||||
<decision name="reuse_records">
|
||||
<switch>
|
||||
<case to="adjancency_lists">${wf:conf('reuseRecords') eq false}</case>
|
||||
<case to="prepare_relations">${wf:conf('reuseRecords') eq false}</case>
|
||||
<case to="to_solr_index">${wf:conf('reuseRecords') eq true}</case>
|
||||
<default to="adjancency_lists"/>
|
||||
</switch>
|
||||
|
|
@ -74,16 +79,12 @@
|
|||
<message>Action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
|
||||
</kill>
|
||||
|
||||
<action name="adjancency_lists">
|
||||
<action name="prepare_relations">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<prepare>
|
||||
<delete path="${outputPath}"/>
|
||||
<mkdir path="${outputPath}"/>
|
||||
</prepare>
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>build_adjacency_lists</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.SparkXmlRecordBuilderJob_v2</class>
|
||||
<name>PrepareRelations</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.PrepareRelationsJob</class>
|
||||
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-cores=${sparkExecutorCoresForJoining}
|
||||
|
|
@ -94,12 +95,135 @@
|
|||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
</spark-opts>
|
||||
<arg>-mt</arg> <arg>yarn</arg>
|
||||
<arg>-is</arg> <arg>${isLookupUrl}</arg>
|
||||
<arg>-t</arg> <arg>${otherDsTypeId}</arg>
|
||||
<arg>-s</arg><arg>${sourcePath}</arg>
|
||||
<arg>-o</arg><arg>${outputPath}</arg>
|
||||
<arg>-sp</arg><arg>${sparkSqlShufflePartitions}</arg>
|
||||
<arg>--inputRelationsPath</arg><arg>${inputGraphRootPath}/relation</arg>
|
||||
<arg>--outputPath</arg><arg>${workingDir}/relation</arg>
|
||||
</spark>
|
||||
<ok to="prepare_publication_table"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="join_relation_publication">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Join[relation.target = publication.id]</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.CreateRelatedEntitiesJob_phase1</class>
|
||||
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-cores=${sparkExecutorCoresForJoining}
|
||||
--executor-memory=${sparkExecutorMemoryForJoining}
|
||||
--driver-memory=${sparkDriverMemoryForJoining}
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=3840
|
||||
</spark-opts>
|
||||
<arg>--inputRelationsPath</arg><arg>${workingDir}/relations</arg>
|
||||
<arg>--inputEntityPath</arg><arg>${inputGraphRootPath}/publication</arg>
|
||||
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Publication</arg>
|
||||
<arg>--outputPath</arg><arg>${workingDir}/join_partial</arg>
|
||||
</spark>
|
||||
<ok to="join_relation_dataset"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="join_relation_dataset">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Join[relation.target = dataset.id]</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.CreateRelatedEntitiesJob_phase1</class>
|
||||
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-cores=${sparkExecutorCoresForJoining}
|
||||
--executor-memory=${sparkExecutorMemoryForJoining}
|
||||
--driver-memory=${sparkDriverMemoryForJoining}
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=3840
|
||||
</spark-opts>
|
||||
<arg>--inputRelationsPath</arg><arg>${workingDir}/relations</arg>
|
||||
<arg>--inputEntityPath</arg><arg>${inputGraphRootPath}/dataset</arg>
|
||||
<arg>--graphTableClassName</arg><arg>eu.dnetlib.dhp.schema.oaf.Dataset</arg>
|
||||
<arg>--outputPath</arg><arg>${workingDir}/join_partial</arg>
|
||||
</spark>
|
||||
<ok to="join_all_entities"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="join_all_entities">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>Join[relation.target = dataset.id]</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.CreateRelatedEntitiesJob_phase2</class>
|
||||
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-cores=${sparkExecutorCoresForJoining}
|
||||
--executor-memory=${sparkExecutorMemoryForJoining}
|
||||
--driver-memory=${sparkDriverMemoryForJoining}
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=3840
|
||||
</spark-opts>
|
||||
<arg>--inputRelatedEntitiesPath</arg><arg>${workingDir}/join_partial</arg>
|
||||
<arg>--inputEntityPath</arg><arg>${inputGraphRootPath}</arg>
|
||||
<arg>--outputPath</arg><arg>${workingDir}/join_entities</arg>
|
||||
</spark>
|
||||
<ok to="adjancency_lists"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="adjancency_lists">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>build_adjacency_lists</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.AdjacencyListBuilderJob</class>
|
||||
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-cores=${sparkExecutorCoresForJoining}
|
||||
--executor-memory=${sparkExecutorMemoryForJoining}
|
||||
--driver-memory=${sparkDriverMemoryForJoining}
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=3840
|
||||
</spark-opts>
|
||||
<arg>--inputPath</arg> <arg>${${workingDir}/join_entities</arg>
|
||||
<arg>--outputPath</arg><arg>${workingDir}/joined</arg>
|
||||
</spark>
|
||||
<ok to="convert_to_xml"/>
|
||||
<error to="Kill"/>
|
||||
</action>
|
||||
|
||||
<action name="convert_to_xml">
|
||||
<spark xmlns="uri:oozie:spark-action:0.2">
|
||||
<master>yarn</master>
|
||||
<mode>cluster</mode>
|
||||
<name>build_adjacency_lists</name>
|
||||
<class>eu.dnetlib.dhp.oa.provision.XmlConverterJob</class>
|
||||
<jar>dhp-graph-provision-${projectVersion}.jar</jar>
|
||||
<spark-opts>
|
||||
--executor-cores=${sparkExecutorCoresForJoining}
|
||||
--executor-memory=${sparkExecutorMemoryForJoining}
|
||||
--driver-memory=${sparkDriverMemoryForJoining}
|
||||
--conf spark.extraListeners=${spark2ExtraListeners}
|
||||
--conf spark.sql.queryExecutionListeners=${spark2SqlQueryExecutionListeners}
|
||||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
--conf spark.sql.shuffle.partitions=3840
|
||||
</spark-opts>
|
||||
<arg>--inputPath</arg><arg>${${workingDir}/joined</arg>
|
||||
<arg>--outputPath</arg><arg>${workingDir}/xml</arg>
|
||||
<arg>--isLookupUrl</arg><arg>${isLookupUrl}</arg>
|
||||
<arg>--otherDsTypeId</arg><arg>${otherDsTypeId}</arg>
|
||||
</spark>
|
||||
<ok to="to_solr_index"/>
|
||||
<error to="Kill"/>
|
||||
|
|
@ -122,9 +246,8 @@
|
|||
--conf spark.yarn.historyServer.address=${spark2YarnHistoryServerAddress}
|
||||
--conf spark.eventLog.dir=${nameNode}${spark2EventLogDir}
|
||||
</spark-opts>
|
||||
<arg>-mt</arg> <arg>yarn</arg>
|
||||
<arg>-is</arg> <arg>${isLookupUrl}</arg>
|
||||
<arg>--sourcePath</arg><arg>${outputPath}/xml</arg>
|
||||
<arg>--isLookupUrl</arg> <arg>${isLookupUrl}</arg>
|
||||
<arg>--inputPath</arg><arg>${workingDir}/xml</arg>
|
||||
<arg>--format</arg><arg>${format}</arg>
|
||||
<arg>--batchSize</arg><arg>${batchSize}</arg>
|
||||
</spark>
|
||||
|
|
|
|||
Loading…
Reference in New Issue