forked from D-Net/dnet-hadoop
109 lines
3.1 KiB
Scala
109 lines
3.1 KiB
Scala
package eu.dnetlib.dhp.bioschema
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import com.fasterxml.jackson.databind.{ObjectMapper, SerializationFeature}
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import eu.dnetlib.dhp.aggregation.AbstractVocabularyTest
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//import eu.dnetlib.dhp.bioschema.{BioschemaToOAFTransformation, GenerateDataciteDatasetSpark}
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import eu.dnetlib.dhp.bioschema.BioschemaToOAFTransformation
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import eu.dnetlib.dhp.schema.oaf.Oaf
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import org.apache.commons.io.FileUtils
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import org.apache.spark.SparkConf
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import org.apache.spark.sql.functions.{col, count}
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import org.apache.spark.sql.{Dataset, Encoder, Encoders, SparkSession}
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import org.junit.jupiter.api.Assertions._
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import org.junit.jupiter.api.extension.ExtendWith
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import org.junit.jupiter.api.{AfterEach, BeforeEach, Test}
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import org.mockito.junit.jupiter.MockitoExtension
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import org.slf4j.{Logger, LoggerFactory}
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import java.nio.file.{Files, Path}
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import java.text.SimpleDateFormat
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import java.util.Locale
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import scala.io.Source
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@ExtendWith(Array(classOf[MockitoExtension]))
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class BioschemaDataciteToOAFTest extends AbstractVocabularyTest {
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private var workingDir: Path = null
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val log: Logger = LoggerFactory.getLogger(getClass)
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@BeforeEach
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def setUp(): Unit = {
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workingDir = Files.createTempDirectory(getClass.getSimpleName)
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super.setUpVocabulary()
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}
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@AfterEach
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def tearDown(): Unit = {
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FileUtils.deleteDirectory(workingDir.toFile)
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}
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@Test
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def testDateMapping: Unit = {
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val inputDate = "2021-07-14T11:52:54+0000"
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val ISO8601FORMAT = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ssZ", Locale.US)
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val dt = ISO8601FORMAT.parse(inputDate)
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println(dt.getTime)
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}
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// @Test
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// def testConvert(): Unit = {
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//
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// val path = getClass.getResource("/eu/dnetlib/dhp/actionmanager/datacite/dataset").getPath
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//
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// val conf = new SparkConf()
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// val spark: SparkSession = SparkSession
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// .builder()
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// .config(conf)
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// .appName(getClass.getSimpleName)
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// .master("local[*]")
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// .getOrCreate()
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//
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// implicit val oafEncoder: Encoder[Oaf] = Encoders.kryo[Oaf]
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// val instance = new GenerateDataciteDatasetSpark(null, null, log)
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// val targetPath = s"$workingDir/result"
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//
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// instance.generateDataciteDataset(path, exportLinks = true, vocabularies, targetPath, spark)
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//
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// import spark.implicits._
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//
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// val nativeSize = spark.read.load(path).count()
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//
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// assertEquals(100, nativeSize)
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//
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// val result: Dataset[Oaf] = spark.read.load(targetPath).as[Oaf]
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//
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// result
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// .map(s => s.getClass.getSimpleName)
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// .groupBy(col("value").alias("class"))
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// .agg(count("value").alias("Total"))
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// .show(false)
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//
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// val t = spark.read.load(targetPath).count()
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//
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// assertTrue(t > 0)
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//
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// spark.stop()
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//
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// }
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@Test
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def testMapping(): Unit = {
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val record = Source
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.fromInputStream(getClass.getResourceAsStream("/eu/dnetlib/dhp/bioschema/ped_record.json"))
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.mkString
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val mapper = new ObjectMapper().enable(SerializationFeature.INDENT_OUTPUT)
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val res: List[Oaf] = BioschemaToOAFTransformation.generateOAF(record, 0L, 0L, vocabularies, true)
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res.foreach(r => {
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println(mapper.writeValueAsString(r))
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println("----------------------------")
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})
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}
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}
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