forked from D-Net/dnet-hadoop
unit test for the preparation of the relations
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@ -1,9 +1,10 @@
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package eu.dnetlib.dhp.oa.provision;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.oa.provision.model.ProvisionModelSupport;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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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 org.apache.commons.io.FileUtils;
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import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.function.FilterFunction;
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@ -19,9 +20,10 @@ import org.junit.jupiter.api.io.TempDir;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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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 com.fasterxml.jackson.databind.ObjectMapper;
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import eu.dnetlib.dhp.oa.provision.model.ProvisionModelSupport;
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import eu.dnetlib.dhp.schema.oaf.Relation;
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public class PrepareRelationsJobTest {
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@ -74,14 +76,19 @@ public class PrepareRelationsJobTest {
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"-maxRelations", String.valueOf(maxRelations)
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});
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Dataset<Relation> out = spark.read()
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Dataset<Relation> out = spark
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.read()
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.parquet(testPath.toString())
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.as(Encoders.bean(Relation.class))
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.cache();
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Assertions.assertEquals(10, out.count());
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Dataset<Row> freq = out.toDF().cube(SUBRELTYPE).count().filter((FilterFunction<Row>) value -> !value.isNullAt(0));
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Dataset<Row> freq = out
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.toDF()
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.cube(SUBRELTYPE)
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.count()
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.filter((FilterFunction<Row>) value -> !value.isNullAt(0));
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long outcome = freq.filter(freq.col(SUBRELTYPE).equalTo(OUTCOME)).collectAsList().get(0).getAs("count");
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long supplement = freq.filter(freq.col(SUBRELTYPE).equalTo(SUPPLEMENT)).collectAsList().get(0).getAs("count");
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