BrBETA_dnet-hadoop/dhp-workflows/dhp-propagation/src/main/java/eu/dnetlib/dhp/countrypropagation/SparkCountryPropagationJob2...

290 lines
9.5 KiB
Java

package eu.dnetlib.dhp.countrypropagation;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
import static jdk.nashorn.internal.objects.NativeDebug.map;
import java.util.*;
import java.util.stream.Collectors;
import org.apache.commons.io.IOUtils;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.MapFunction;
import org.apache.spark.broadcast.Broadcast;
import org.apache.spark.sql.*;
import org.apache.spark.sql.Dataset;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.oaf.*;
import scala.Tuple2;
public class SparkCountryPropagationJob2 {
private static final Logger log = LoggerFactory.getLogger(SparkCountryPropagationJob2.class);
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils
.toString(
SparkCountryPropagationJob2.class
.getResourceAsStream(
"/eu/dnetlib/dhp/countrypropagation/input_countrypropagation_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
Boolean isSparkSessionManaged = isSparkSessionManaged(parser);
log.info("isSparkSessionManaged: {}", isSparkSessionManaged);
String inputPath = parser.get("sourcePath");
log.info("inputPath: {}", inputPath);
final String outputPath = parser.get("outputPath");
log.info("outputPath: {}", outputPath);
final String datasourcecountrypath = parser.get("preparedInfoPath");
log.info("preparedInfoPath: {}", datasourcecountrypath);
final String resultClassName = parser.get("resultTableName");
log.info("resultTableName: {}", resultClassName);
final String resultType = resultClassName.substring(resultClassName.lastIndexOf(".") + 1).toLowerCase();
log.info("resultType: {}", resultType);
final String possibleUpdatesPath = datasourcecountrypath
.substring(0, datasourcecountrypath.lastIndexOf("/") + 1)
+ "possibleUpdates/" + resultType;
log.info("possibleUpdatesPath: {}", possibleUpdatesPath);
final Boolean saveGraph = Optional
.ofNullable(parser.get("saveGraph"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
log.info("saveGraph: {}", saveGraph);
Class<? extends Result> resultClazz = (Class<? extends Result>) Class.forName(resultClassName);
SparkConf conf = new SparkConf();
conf.set("hive.metastore.uris", parser.get("hive_metastore_uris"));
runWithSparkHiveSession(
conf,
isSparkSessionManaged,
spark -> {
removeOutputDir(spark, possibleUpdatesPath);
execPropagation(
spark,
datasourcecountrypath,
inputPath,
outputPath,
resultClazz,
saveGraph, possibleUpdatesPath);
});
}
private static <R extends Result> void execPropagation(
SparkSession spark,
String datasourcecountrypath,
String inputPath,
String outputPath,
Class<R> resultClazz,
boolean saveGraph, String possilbeUpdatesPath) {
// final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
// Load file with preprocessed association datasource - country
Dataset<DatasourceCountry> datasourcecountryassoc = readAssocDatasourceCountry(spark, datasourcecountrypath);
// broadcasting the result of the preparation step
// Broadcast<Dataset<DatasourceCountry>> broadcast_datasourcecountryassoc =
// sc.broadcast(datasourcecountryassoc);
Dataset<ResultCountrySet> potentialUpdates = getPotentialResultToUpdate(
spark, inputPath, resultClazz, datasourcecountryassoc)
.as(Encoders.bean(ResultCountrySet.class));
potentialUpdates.write().option("compression", "gzip").mode(SaveMode.Overwrite).json(possilbeUpdatesPath);
if (saveGraph) {
// updateResultTable(spark, potentialUpdates, inputPath, resultClazz, outputPath);
potentialUpdates = spark
.read()
.textFile(possilbeUpdatesPath)
.map(
(MapFunction<String, ResultCountrySet>) value -> OBJECT_MAPPER
.readValue(value, ResultCountrySet.class),
Encoders.bean(ResultCountrySet.class));
updateResultTable(spark, potentialUpdates, inputPath, resultClazz, outputPath);
}
}
private static <R extends Result> void updateResultTable(
SparkSession spark,
Dataset<ResultCountrySet> potentialUpdates,
String inputPath,
Class<R> resultClazz,
String outputPath) {
log.info("Reading Graph table from: {}", inputPath);
Dataset<R> result = readPathEntity(spark, inputPath, resultClazz);
Dataset<R> new_table = result
.joinWith(
potentialUpdates, result
.col("id")
.equalTo(potentialUpdates.col("resultId")),
"left_outer")
.map((MapFunction<Tuple2<R, ResultCountrySet>, R>) value -> {
R r = value._1();
Optional<ResultCountrySet> potentialNewCountries = Optional.ofNullable(value._2());
if (potentialNewCountries.isPresent()) {
HashSet<String> countries = r
.getCountry()
.stream()
.map(c -> c.getClassid())
.collect(Collectors.toCollection(HashSet::new));
r
.getCountry()
.addAll(
potentialNewCountries
.get()
.getCountrySet()
.stream()
.filter(c -> !countries.contains(c.getClassid()))
.map(c -> getCountry(c.getClassid(), c.getClassname()))
.collect(Collectors.toList()));
// Result res = new Result();
// res.setId(r.getId());
// List<Country> countryList = new ArrayList<>();
// for (CountrySbs country : potentialNewCountries
// .get()
// .getCountrySet()) {
// if (!countries.contains(country.getClassid())) {
// countryList
// .add(
// getCountry(
// country.getClassid(),
// country.getClassname()));
// }
// }
// res.setCountry(countryList);
// r.mergeFrom(res);
}
return r;
}, Encoders.bean(resultClazz));
// Dataset<Tuple2<String, R>> result_pair = result
// .map(
// r -> new Tuple2<>(r.getId(), r),
// Encoders.tuple(Encoders.STRING(), Encoders.bean(resultClazz)));
//
// Dataset<R> new_table = result_pair
// .joinWith(
// potentialUpdates,
// result_pair.col("_1").equalTo(potentialUpdates.col("resultId")),
// "left_outer")
// .map(
// (MapFunction<Tuple2<Tuple2<String, R>, ResultCountrySet>, R>) value -> {
// R r = value._1()._2();
// Optional<ResultCountrySet> potentialNewCountries = Optional.ofNullable(value._2());
// if (potentialNewCountries.isPresent()) {
// HashSet<String> countries = new HashSet<>();
// for (Qualifier country : r.getCountry()) {
// countries.add(country.getClassid());
// }
// Result res = new Result();
// res.setId(r.getId());
// List<Country> countryList = new ArrayList<>();
// for (CountrySbs country : potentialNewCountries
// .get()
// .getCountrySet()) {
// if (!countries.contains(country.getClassid())) {
// countryList
// .add(
// getCountry(
// country.getClassid(),
// country.getClassname()));
// }
// }
// res.setCountry(countryList);
// r.mergeFrom(res);
// }
// return r;
// },
// Encoders.bean(resultClazz));
log.info("Saving graph table to path: {}", outputPath);
log.info("number of saved recordsa: {}", new_table.count());
new_table.write().option("compression", "gzip").mode(SaveMode.Overwrite).json(outputPath);
}
private static <R extends Result> Dataset<ResultCountrySet> getPotentialResultToUpdate(
SparkSession spark,
String inputPath,
Class<R> resultClazz,
Dataset<DatasourceCountry> datasourcecountryassoc) {
Dataset<R> result = readPathEntity(spark, inputPath, resultClazz);
result.createOrReplaceTempView("result");
// log.info("number of results: {}", result.count());
createCfHbforresult(spark);
return countryPropagationAssoc(spark, datasourcecountryassoc);
}
private static Dataset<ResultCountrySet> countryPropagationAssoc(
SparkSession spark,
Dataset<DatasourceCountry> datasource_country) {
// Dataset<DatasourceCountry> datasource_country = broadcast_datasourcecountryassoc.value();
datasource_country.createOrReplaceTempView("datasource_country");
log.info("datasource_country number : {}", datasource_country.count());
String query = "SELECT id resultId, collect_set(country) countrySet "
+ "FROM ( SELECT id, country "
+ "FROM datasource_country "
+ "JOIN cfhb "
+ " ON cf = dataSourceId "
+ "UNION ALL "
+ "SELECT id , country "
+ "FROM datasource_country "
+ "JOIN cfhb "
+ " ON hb = dataSourceId ) tmp "
+ "GROUP BY id";
Dataset<ResultCountrySet> potentialUpdates = spark
.sql(query)
.as(Encoders.bean(ResultCountrySet.class))
.map((MapFunction<ResultCountrySet, ResultCountrySet>) r -> {
final ArrayList<CountrySbs> c = r
.getCountrySet()
.stream()
.limit(100)
.collect(Collectors.toCollection(ArrayList::new));
r.setCountrySet(c);
return r;
}, Encoders.bean(ResultCountrySet.class));
// log.info("potential update number : {}", potentialUpdates.count());
return potentialUpdates;
}
private static Dataset<DatasourceCountry> readAssocDatasourceCountry(
SparkSession spark, String relationPath) {
return spark
.read()
.textFile(relationPath)
.map(
(MapFunction<String, DatasourceCountry>) value -> OBJECT_MAPPER
.readValue(value, DatasourceCountry.class),
Encoders.bean(DatasourceCountry.class));
}
}