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[SPARK-20553][ML][PYSPARK] Update ALS examples with recommend-all methods #17950

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[SPARK-20553][ML][PYSPARK] Update ALS examples with recommend-all methods #17950

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8 changes: 8 additions & 0 deletions examples/src/main/java/org/apache/spark/examples/ml/JavaALSExample.java
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Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,15 @@ public static void main(String[] args) {
.setPredictionCol("prediction");
Double rmse = evaluator.evaluate(predictions);
System.out.println("Root-mean-square error = " + rmse);

// Generate top 10 movie recommendations for each user
Dataset<Row> userRecs = model.recommendForAllUsers(10);
// Generate top 10 user recommendations for each movie
Dataset<Row> movieRecs = model.recommendForAllItems(10);
// $example off$
userRecs.show();
movieRecs.show();

spark.stop();
}
}
8 changes: 8 additions & 0 deletions examples/src/main/python/ml/als_example.py
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Expand Up @@ -55,5 +55,13 @@
predictionCol="prediction")
rmse = evaluator.evaluate(predictions)
print("Root-mean-square error = " + str(rmse))

# Generate top 10 movie recommendations for each user
userRecs = model.recommendForAllUsers(10)
# Generate top 10 user recommendations for each movie
movieRecs = model.recommendForAllItems(10)
# $example off$
userRecs.show()
movieRecs.show()

spark.stop()
7 changes: 7 additions & 0 deletions examples/src/main/scala/org/apache/spark/examples/ml/ALSExample.scala
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Expand Up @@ -75,7 +75,14 @@ object ALSExample {
.setPredictionCol("prediction")
val rmse = evaluator.evaluate(predictions)
println(s"Root-mean-square error = $rmse")

// Generate top 10 movie recommendations for each user
val userRecs = model.recommendForAllUsers(10)
// Generate top 10 user recommendations for each movie
val movieRecs = model.recommendForAllItems(10)
// $example off$
userRecs.show()
movieRecs.show()

spark.stop()
}
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