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fixed process doiboost workflow:

- splitted OrcidToOAF into two phase preprocess and process
- updated workflow used in production
This commit is contained in:
Sandro La Bruzzo 2021-07-14 09:44:32 +02:00 committed by Claudio Atzori
parent bc4b86c27c
commit c35c117601
11 changed files with 103 additions and 54 deletions

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@ -21,7 +21,7 @@ object SparkMapDumpIntoOAF {
val logger: Logger = LoggerFactory.getLogger(SparkMapDumpIntoOAF.getClass)
val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkMapDumpIntoOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json")))
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkMapDumpIntoOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_crossref_dump_to_oaf_params.json")))
parser.parseArgument(args)
val spark: SparkSession =
SparkSession

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@ -1,61 +1,18 @@
package eu.dnetlib.doiboost.orcid
import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.oa.merge.AuthorMerger
import eu.dnetlib.dhp.schema.oaf.Publication
import eu.dnetlib.dhp.schema.orcid.OrcidDOI
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.functions._
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.apache.spark.sql._
import org.slf4j.{Logger, LoggerFactory}
object SparkConvertORCIDToOAF {
val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
def fixORCIDItem(item :ORCIDItem):ORCIDItem = {
new ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
}
def run(spark:SparkSession,sourcePath:String,workingPath:String, targetPath:String):Unit = {
import spark.implicits._
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
val inputRDD:RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s!= null).filter(s => ORCIDToOAF.authorValid(s))
spark.createDataset(inputRDD).as[OrcidAuthor].write.mode(SaveMode.Overwrite).save(s"$workingPath/author")
val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s!= null)
spark.createDataset(res).as[OrcidWork].write.mode(SaveMode.Overwrite).save(s"$workingPath/works")
val authors :Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
val works :Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
works.joinWith(authors, authors("oid").equalTo(works("oid")))
.map(i =>{
val doi = i._1.doi
var author = i._2
(doi, author)
}).groupBy(col("_1").alias("doi"))
.agg(collect_list(col("_2")).alias("authors")).as[ORCIDItem]
.map(s => fixORCIDItem(s))
.write.mode(SaveMode.Overwrite).save(s"$workingPath/orcidworksWithAuthor")
val dataset: Dataset[ORCIDItem] =spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
logger.info("Converting ORCID to OAF")
dataset.map(o => ORCIDToOAF.convertTOOAF(o)).write.mode(SaveMode.Overwrite).save(targetPath)
}
def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json")))
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_orcid_to_oaf_params.json")))
parser.parseArgument(args)
val spark: SparkSession =
SparkSession
@ -64,11 +21,16 @@ object SparkConvertORCIDToOAF {
.appName(getClass.getSimpleName)
.master(parser.get("master")).getOrCreate()
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
import spark.implicits._
val sourcePath = parser.get("sourcePath")
val workingPath = parser.get("workingPath")
val targetPath = parser.get("targetPath")
run(spark, sourcePath, workingPath, targetPath)
val dataset: Dataset[ORCIDItem] =spark.read.load(s"$workingPath/orcidworksWithAuthor").as[ORCIDItem]
logger.info("Converting ORCID to OAF")
dataset.map(o => ORCIDToOAF.convertTOOAF(o)).write.mode(SaveMode.Overwrite).save(targetPath)
}

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@ -0,0 +1,70 @@
package eu.dnetlib.doiboost.orcid
import com.fasterxml.jackson.databind.{DeserializationFeature, ObjectMapper}
import eu.dnetlib.dhp.application.ArgumentApplicationParser
import eu.dnetlib.dhp.oa.merge.AuthorMerger
import eu.dnetlib.dhp.schema.oaf.Publication
import eu.dnetlib.dhp.schema.orcid.OrcidDOI
import org.apache.commons.io.IOUtils
import org.apache.spark.SparkConf
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.functions._
import org.apache.spark.sql.{Dataset, Encoder, Encoders, SaveMode, SparkSession}
import org.slf4j.{Logger, LoggerFactory}
object SparkPreprocessORCID {
val logger: Logger = LoggerFactory.getLogger(SparkConvertORCIDToOAF.getClass)
def fixORCIDItem(item :ORCIDItem):ORCIDItem = {
ORCIDItem(item.doi, item.authors.groupBy(_.oid).map(_._2.head).toList)
}
def run(spark:SparkSession,sourcePath:String,workingPath:String):Unit = {
import spark.implicits._
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
val inputRDD:RDD[OrcidAuthor] = spark.sparkContext.textFile(s"$sourcePath/authors").map(s => ORCIDToOAF.convertORCIDAuthor(s)).filter(s => s!= null).filter(s => ORCIDToOAF.authorValid(s))
spark.createDataset(inputRDD).as[OrcidAuthor].write.mode(SaveMode.Overwrite).save(s"$workingPath/author")
val res = spark.sparkContext.textFile(s"$sourcePath/works").flatMap(s => ORCIDToOAF.extractDOIWorks(s)).filter(s => s!= null)
spark.createDataset(res).as[OrcidWork].write.mode(SaveMode.Overwrite).save(s"$workingPath/works")
val authors :Dataset[OrcidAuthor] = spark.read.load(s"$workingPath/author").as[OrcidAuthor]
val works :Dataset[OrcidWork] = spark.read.load(s"$workingPath/works").as[OrcidWork]
works.joinWith(authors, authors("oid").equalTo(works("oid")))
.map(i =>{
val doi = i._1.doi
val author = i._2
(doi, author)
}).groupBy(col("_1").alias("doi"))
.agg(collect_list(col("_2")).alias("authors")).as[ORCIDItem]
.map(s => fixORCIDItem(s))
.write.mode(SaveMode.Overwrite).save(s"$workingPath/orcidworksWithAuthor")
}
def main(args: Array[String]): Unit = {
val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkConvertORCIDToOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_orcid_to_oaf_params.json")))
parser.parseArgument(args)
val spark: SparkSession =
SparkSession
.builder()
.config(conf)
.appName(getClass.getSimpleName)
.master(parser.get("master")).getOrCreate()
val sourcePath = parser.get("sourcePath")
val workingPath = parser.get("workingPath")
run(spark, sourcePath, workingPath)
}
}

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@ -18,7 +18,7 @@ object SparkMapUnpayWallToOAF {
val logger: Logger = LoggerFactory.getLogger(SparkMapDumpIntoOAF.getClass)
val conf: SparkConf = new SparkConf()
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkMapDumpIntoOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_map_to_oaf_params.json")))
val parser = new ArgumentApplicationParser(IOUtils.toString(SparkMapDumpIntoOAF.getClass.getResourceAsStream("/eu/dnetlib/dhp/doiboost/convert_uw_to_oaf_params.json")))
parser.parseArgument(args)
val spark: SparkSession =
SparkSession

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@ -0,0 +1,6 @@
[
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path of the OAF Orcid transformed", "paramRequired": true},
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the source path ", "paramRequired": false},
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
]

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@ -0,0 +1,6 @@
[
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path of the OAF Orcid transformed", "paramRequired": true},
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the working path ", "paramRequired": false},
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
]

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@ -0,0 +1,6 @@
[
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the path of the OAF Orcid transformed", "paramRequired": true},
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the source path ", "paramRequired": false},
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
]

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@ -368,7 +368,7 @@
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Convert ORCID to Dataset</name>
<class>eu.dnetlib.doiboost.orcid.SparkConvertORCIDToOAF</class>
<class>eu.dnetlib.doiboost.orcid.SparkPreprocessORCID</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}

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@ -34,7 +34,7 @@
<master>yarn-cluster</master>
<mode>cluster</mode>
<name>Convert ORCID to Dataset</name>
<class>eu.dnetlib.doiboost.orcid.SparkConvertORCIDToOAF</class>
<class>eu.dnetlib.doiboost.orcid.SparkPreprocessORCID</class>
<jar>dhp-doiboost-${projectVersion}.jar</jar>
<spark-opts>
--executor-memory=${sparkExecutorMemory}

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@ -1,7 +1,6 @@
[
{"paramName":"s", "paramLongName":"sourcePath", "paramDescription": "the path of the Orcid Input file", "paramRequired": true},
{"paramName":"w", "paramLongName":"workingPath", "paramDescription": "the working path ", "paramRequired": false},
{"paramName":"t", "paramLongName":"targetPath", "paramDescription": "the working dir path", "paramRequired": true},
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
{"paramName":"m", "paramLongName":"master", "paramDescription": "the master name", "paramRequired": true}
]

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@ -46,7 +46,7 @@ class MappingORCIDToOAFTest {
implicit val mapEncoderPubs: Encoder[Publication] = Encoders.kryo[Publication]
import spark.implicits._
SparkConvertORCIDToOAF.run( spark,sourcePath, workingPath, targetPath)
SparkPreprocessORCID.run( spark,sourcePath, workingPath)
val mapper = new ObjectMapper()