forked from D-Net/dnet-hadoop
[country propagation] fixes error 'cannot resolve countrySet given input columns: []' when there is no prepared information driving the propagation process for a given result type
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@ -14,6 +14,7 @@ import org.apache.spark.SparkConf;
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import org.apache.spark.api.java.function.MapFunction;
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import org.apache.spark.sql.Dataset;
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import org.apache.spark.sql.Encoders;
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import org.apache.spark.sql.Row;
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import org.apache.spark.sql.SaveMode;
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import org.apache.spark.sql.SparkSession;
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import org.slf4j.Logger;
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@ -84,19 +85,26 @@ public class SparkCountryPropagationJob {
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Dataset<R> res = readPath(spark, sourcePath, resultClazz);
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log.info("Reading prepared info: {}", preparedInfoPath);
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Dataset<ResultCountrySet> prepared = spark
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final Dataset<Row> preparedInfoRaw = spark
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.read()
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.json(preparedInfoPath)
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.as(Encoders.bean(ResultCountrySet.class));
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res
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.joinWith(prepared, res.col("id").equalTo(prepared.col("resultId")), "left_outer")
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.map(getCountryMergeFn(), Encoders.bean(resultClazz))
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.write()
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.option("compression", "gzip")
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.mode(SaveMode.Overwrite)
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.json(outputPath);
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.json(preparedInfoPath);
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if (!preparedInfoRaw.isEmpty()) {
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final Dataset<ResultCountrySet> prepared = preparedInfoRaw.as(Encoders.bean(ResultCountrySet.class));
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res
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.joinWith(prepared, res.col("id").equalTo(prepared.col("resultId")), "left_outer")
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.map(getCountryMergeFn(), Encoders.bean(resultClazz))
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.write()
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.option("compression", "gzip")
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.mode(SaveMode.Overwrite)
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.json(outputPath);
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} else {
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res
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.write()
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.option("compression", "gzip")
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.mode(SaveMode.Overwrite)
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.json(outputPath);
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}
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}
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private static <R extends Result> MapFunction<Tuple2<R, ResultCountrySet>, R> getCountryMergeFn() {
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