refactoring

This commit is contained in:
Miriam Baglioni 2020-04-23 11:58:26 +02:00
parent 540f70298b
commit fa2ff5c6f5
2 changed files with 228 additions and 196 deletions

View File

@ -1,47 +1,43 @@
package eu.dnetlib.dhp.countrypropagation;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.oaf.*;
import java.util.Arrays;
import java.util.List;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.io.compress.GzipCodec;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Encoders;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.SaveMode;
import java.util.Arrays;
import java.util.List;
import java.util.Optional;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
/**
* For the association of the country to the datasource
* The association is computed only for datasource of specific type or having whitelisted ids
* The country is registered in the Organization associated to the Datasource, so the
* relation provides between Datasource and Organization is exploited to get the country for the datasource
* For the association of the country to the datasource The association is computed only for
* datasource of specific type or having whitelisted ids The country is registered in the
* Organization associated to the Datasource, so the relation provides between Datasource and
* Organization is exploited to get the country for the datasource
*/
public class PrepareDatasourceCountryAssociation {
private static final Logger log = LoggerFactory.getLogger(PrepareDatasourceCountryAssociation.class);
private static final Logger log =
LoggerFactory.getLogger(PrepareDatasourceCountryAssociation.class);
private static final ObjectMapper OBJECT_MAPPER = new ObjectMapper();
public static void main(String[] args) throws Exception {
String jsonConfiguration = IOUtils.toString(PrepareDatasourceCountryAssociation.class
.getResourceAsStream("/eu/dnetlib/dhp/countrypropagation/input_prepareassoc_parameters.json"));
String jsonConfiguration =
IOUtils.toString(
PrepareDatasourceCountryAssociation.class.getResourceAsStream(
"/eu/dnetlib/dhp/countrypropagation/input_prepareassoc_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
jsonConfiguration);
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
@ -57,73 +53,83 @@ public class PrepareDatasourceCountryAssociation {
SparkConf conf = new SparkConf();
conf.set("hive.metastore.uris", parser.get("hive_metastore_uris"));
runWithSparkHiveSession(conf, isSparkSessionManaged,
runWithSparkHiveSession(
conf,
isSparkSessionManaged,
spark -> {
removeOutputDir(spark, outputPath);
prepareDatasourceCountryAssociation(spark,
prepareDatasourceCountryAssociation(
spark,
Arrays.asList(parser.get("whitelist").split(";")),
Arrays.asList(parser.get("allowedtypes").split(";")),
inputPath,
outputPath);
});
}
private static void prepareDatasourceCountryAssociation(SparkSession spark,
List<String> whitelist,
List<String> allowedtypes,
String inputPath,
String outputPath) {
private static void prepareDatasourceCountryAssociation(
SparkSession spark,
List<String> whitelist,
List<String> allowedtypes,
String inputPath,
String outputPath) {
String whitelisted = "";
for (String i : whitelist){
for (String i : whitelist) {
whitelisted += " OR id = '" + i + "'";
}
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
Dataset<Datasource> datasource =
spark.createDataset(
sc.textFile(inputPath + "/datasource")
.map(item -> OBJECT_MAPPER.readValue(item, Datasource.class))
.rdd(),
Encoders.bean(Datasource.class));
Dataset<Datasource> datasource = spark.createDataset(sc.textFile(inputPath + "/datasource")
.map(item -> OBJECT_MAPPER.readValue(item, Datasource.class)).rdd(), Encoders.bean(Datasource.class));
Dataset<Relation> relation =
spark.createDataset(
sc.textFile(inputPath + "/relation")
.map(item -> OBJECT_MAPPER.readValue(item, Relation.class))
.rdd(),
Encoders.bean(Relation.class));
Dataset<Relation> relation = spark.createDataset(sc.textFile(inputPath + "/relation")
.map(item -> OBJECT_MAPPER.readValue(item, Relation.class)).rdd(), Encoders.bean(Relation.class));
Dataset<Organization> organization = spark.createDataset(sc.textFile(inputPath + "/organization")
.map(item -> OBJECT_MAPPER.readValue(item, Organization.class)).rdd(), Encoders.bean(Organization.class));
Dataset<Organization> organization =
spark.createDataset(
sc.textFile(inputPath + "/organization")
.map(item -> OBJECT_MAPPER.readValue(item, Organization.class))
.rdd(),
Encoders.bean(Organization.class));
datasource.createOrReplaceTempView("datasource");
relation.createOrReplaceTempView("relation");
organization.createOrReplaceTempView("organization");
String query = "SELECT source dataSourceId, named_struct('classid', country.classid, 'classname', country.classname) country " +
"FROM ( SELECT id " +
" FROM datasource " +
" WHERE (datainfo.deletedbyinference = false " + whitelisted + ") " +
getConstraintList("datasourcetype.classid = '", allowedtypes) + ") d " +
"JOIN ( SELECT source, target " +
" FROM relation " +
" WHERE relclass = '" + RELATION_DATASOURCE_ORGANIZATION_REL_CLASS + "' " +
" AND datainfo.deletedbyinference = false ) rel " +
"ON d.id = rel.source " +
"JOIN (SELECT id, country " +
" FROM organization " +
" WHERE datainfo.deletedbyinference = false " +
" AND length(country.classid)>0) o " +
"ON o.id = rel.target";
String query =
"SELECT source dataSourceId, named_struct('classid', country.classid, 'classname', country.classname) country "
+ "FROM ( SELECT id "
+ " FROM datasource "
+ " WHERE (datainfo.deletedbyinference = false "
+ whitelisted
+ ") "
+ getConstraintList("datasourcetype.classid = '", allowedtypes)
+ ") d "
+ "JOIN ( SELECT source, target "
+ " FROM relation "
+ " WHERE relclass = '"
+ RELATION_DATASOURCE_ORGANIZATION_REL_CLASS
+ "' "
+ " AND datainfo.deletedbyinference = false ) rel "
+ "ON d.id = rel.source "
+ "JOIN (SELECT id, country "
+ " FROM organization "
+ " WHERE datainfo.deletedbyinference = false "
+ " AND length(country.classid)>0) o "
+ "ON o.id = rel.target";
spark.sql(query)
.as(Encoders.bean(DatasourceCountry.class))
.toJavaRDD()
.map(c -> OBJECT_MAPPER.writeValueAsString(c))
.saveAsTextFile(outputPath, GzipCodec.class);
}
}

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@ -1,28 +1,22 @@
package eu.dnetlib.dhp.countrypropagation;
import static eu.dnetlib.dhp.PropagationConstant.*;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
import com.fasterxml.jackson.databind.ObjectMapper;
import eu.dnetlib.dhp.application.ArgumentApplicationParser;
import eu.dnetlib.dhp.schema.oaf.*;
import java.util.*;
import org.apache.commons.io.IOUtils;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.io.compress.GzipCodec;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
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 scala.Tuple2;
import java.util.*;
import static eu.dnetlib.dhp.PropagationConstant.*;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import static eu.dnetlib.dhp.common.SparkSessionSupport.runWithSparkHiveSession;
import scala.Tuple2;
public class SparkCountryPropagationJob2 {
@ -30,14 +24,14 @@ public class SparkCountryPropagationJob2 {
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"));
String jsonConfiguration =
IOUtils.toString(
SparkCountryPropagationJob2.class.getResourceAsStream(
"/eu/dnetlib/dhp/countrypropagation/input_countrypropagation_parameters.json"));
final ArgumentApplicationParser parser = new ArgumentApplicationParser(
jsonConfiguration);
final ArgumentApplicationParser parser = new ArgumentApplicationParser(jsonConfiguration);
parser.parseArgument(args);
@ -56,182 +50,214 @@ public class SparkCountryPropagationJob2 {
final String resultClassName = parser.get("resultTableName");
log.info("resultTableName: {}", resultClassName);
final String resultType = resultClassName.substring(resultClassName.lastIndexOf(".") + 1).toLowerCase();
final String resultType =
resultClassName.substring(resultClassName.lastIndexOf(".") + 1).toLowerCase();
log.info("resultType: {}", resultType);
final Boolean writeUpdates = Optional
.ofNullable(parser.get("writeUpdate"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
final Boolean writeUpdates =
Optional.ofNullable(parser.get("writeUpdate"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
log.info("writeUpdate: {}", writeUpdates);
final Boolean saveGraph = Optional
.ofNullable(parser.get("saveGraph"))
.map(Boolean::valueOf)
.orElse(Boolean.TRUE);
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);
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,
runWithSparkHiveSession(
conf,
isSparkSessionManaged,
spark -> {
//createOutputDirs(outputPath, FileSystem.get(spark.sparkContext().hadoopConfiguration()));
// createOutputDirs(outputPath,
// FileSystem.get(spark.sparkContext().hadoopConfiguration()));
removeOutputDir(spark, outputPath);
execPropagation(spark, datasourcecountrypath, inputPath, outputPath, resultClazz, resultType,
writeUpdates, saveGraph);
execPropagation(
spark,
datasourcecountrypath,
inputPath,
outputPath,
resultClazz,
resultType,
writeUpdates,
saveGraph);
});
}
private static <R extends Result> void execPropagation(SparkSession spark, String datasourcecountrypath,
String inputPath, String outputPath, Class<R> resultClazz, String resultType,
boolean writeUpdates, boolean saveGraph){
private static <R extends Result> void execPropagation(
SparkSession spark,
String datasourcecountrypath,
String inputPath,
String outputPath,
Class<R> resultClazz,
String resultType,
boolean writeUpdates,
boolean saveGraph) {
final JavaSparkContext sc = new JavaSparkContext(spark.sparkContext());
//Load parque 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);
// Load parque 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,
broadcast_datasourcecountryassoc).as(Encoders.bean(ResultCountrySet.class));
Dataset<ResultCountrySet> potentialUpdates =
getPotentialResultToUpdate(
spark, inputPath, resultClazz, broadcast_datasourcecountryassoc)
.as(Encoders.bean(ResultCountrySet.class));
if(writeUpdates){
if (writeUpdates) {
writeUpdates(potentialUpdates, outputPath + "/update_" + resultType);
}
if(saveGraph){
if (saveGraph) {
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) {
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<Tuple2<String, R>> result_pair = result
.map(r -> new Tuple2<>(r.getId(), r),
Encoders.tuple(Encoders.STRING(), 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<Tuple2<String, ResultCountrySet>> potential_update_pair = potentialUpdates.map(pu -> new Tuple2<>(pu.getResultId(),
// pu),
// Encoders.tuple(Encoders.STRING(), Encoders.bean(ResultCountrySet.class)));
// Dataset<Tuple2<String, ResultCountrySet>> potential_update_pair =
// potentialUpdates.map(pu -> new Tuple2<>(pu.getResultId(),
// pu),
// Encoders.tuple(Encoders.STRING(), Encoders.bean(ResultCountrySet.class)));
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));
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
.toJSON()
.write()
.option("compression", "gzip")
.text(outputPath);
// .toJavaRDD()
// .map(r -> OBJECT_MAPPER.writeValueAsString(r))
// .saveAsTextFile(outputPath , GzipCodec.class);
log.info("Saving graph table to path: {}", outputPath);
// log.info("number of saved recordsa: {}", new_table.count());
new_table.toJSON().write().option("compression", "gzip").text(outputPath);
// .toJavaRDD()
// .map(r -> OBJECT_MAPPER.writeValueAsString(r))
// .saveAsTextFile(outputPath , GzipCodec.class);
}
}
private static <R extends Result> Dataset<Row> getPotentialResultToUpdate(SparkSession spark, String inputPath,
Class<R> resultClazz,
Broadcast<Dataset<DatasourceCountry>> broadcast_datasourcecountryassoc) {
private static <R extends Result> Dataset<Row> getPotentialResultToUpdate(
SparkSession spark,
String inputPath,
Class<R> resultClazz,
Broadcast<Dataset<DatasourceCountry>> broadcast_datasourcecountryassoc) {
Dataset<R> result = readPathEntity(spark, inputPath, resultClazz);
result.createOrReplaceTempView("result");
//log.info("number of results: {}", result.count());
// log.info("number of results: {}", result.count());
createCfHbforresult(spark);
return countryPropagationAssoc(spark, broadcast_datasourcecountryassoc);
}
// private static void createCfHbforresult(SparkSession spark) {
// String query;
// query = "SELECT id, inst.collectedfrom.key cf , inst.hostedby.key hb " +
// "FROM ( SELECT id, instance " +
// "FROM result " +
// " WHERE datainfo.deletedbyinference = false) ds " +
// "LATERAL VIEW EXPLODE(instance) i AS inst";
// Dataset<Row> cfhb = spark.sql(query);
// cfhb.createOrReplaceTempView("cfhb");
// //log.info("cfhb_number : {}", cfhb.count());
// }
// private static void createCfHbforresult(SparkSession spark) {
// String query;
// query = "SELECT id, inst.collectedfrom.key cf , inst.hostedby.key hb " +
// "FROM ( SELECT id, instance " +
// "FROM result " +
// " WHERE datainfo.deletedbyinference = false) ds " +
// "LATERAL VIEW EXPLODE(instance) i AS inst";
// Dataset<Row> cfhb = spark.sql(query);
// cfhb.createOrReplaceTempView("cfhb");
// //log.info("cfhb_number : {}", cfhb.count());
// }
private static Dataset<Row> countryPropagationAssoc(SparkSession spark,
Broadcast<Dataset<DatasourceCountry>> broadcast_datasourcecountryassoc){
private static Dataset<Row> countryPropagationAssoc(
SparkSession spark,
Broadcast<Dataset<DatasourceCountry>> broadcast_datasourcecountryassoc) {
Dataset<DatasourceCountry> datasource_country = broadcast_datasourcecountryassoc.value();
datasource_country.createOrReplaceTempView("datasource_country");
log.info("datasource_country number : {}",datasource_country.count());
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";
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<Row> potentialUpdates = spark.sql(query);
//log.info("potential update number : {}", potentialUpdates.count());
// log.info("potential update number : {}", potentialUpdates.count());
return potentialUpdates;
}
private static Dataset<DatasourceCountry> readAssocDatasourceCountry(SparkSession spark, String relationPath) {
return spark
.read()
.textFile(relationPath)
.map(value -> OBJECT_MAPPER.readValue(value, DatasourceCountry.class), Encoders.bean(DatasourceCountry.class));
private static Dataset<DatasourceCountry> readAssocDatasourceCountry(
SparkSession spark, String relationPath) {
return spark.read()
.textFile(relationPath)
.map(
value -> OBJECT_MAPPER.readValue(value, DatasourceCountry.class),
Encoders.bean(DatasourceCountry.class));
}
private static void writeUpdates(Dataset<ResultCountrySet> potentialUpdates, String outputPath){
private static void writeUpdates(
Dataset<ResultCountrySet> potentialUpdates, String outputPath) {
potentialUpdates
.toJSON()
.write()
.mode(SaveMode.Overwrite)
.option("compression", "gzip")
.text(outputPath);
// map(u -> OBJECT_MAPPER.writeValueAsString(u))
// .saveAsTextFile(outputPath, GzipCodec.class);
// map(u -> OBJECT_MAPPER.writeValueAsString(u))
// .saveAsTextFile(outputPath, GzipCodec.class);
}
}