I'm getting the Task not serializable error in Spark. I've searched and tried to use a static function as suggested in some posts, but it still gives the same error.
Code is as below:
public class Rating implements Serializable {
private SparkSession spark;
private SparkConf sparkConf;
private JavaSparkContext jsc;
private static Function<String, Rating> mapFunc;
public Rating() {
mapFunc = new Function<String, Rating>() {
public Rating call(String str) {
return Rating.parseRating(str);
}
};
}
public void runProcedure() {
sparkConf = new SparkConf().setAppName("Filter Example").setMaster("local");
jsc = new JavaSparkContext(sparkConf);
SparkSession spark = SparkSession.builder().master("local").appName("Word Count")
.config("spark.some.config.option", "some-value").getOrCreate();
JavaRDD<Rating> ratingsRDD = spark.read().textFile("sample_movielens_ratings.txt")
.javaRDD()
.map(mapFunc);
}
public static void main(String[] args) {
Rating newRating = new Rating();
newRating.runProcedure();
}
}
The error gives:
How do I solve this error? Thanks in advance.
Clearly Rating
cannot be Serializable
, because it contains references to Spark structures (i.e. SparkSession
, SparkConf
, etc.) as attributes.
The problem here is in
JavaRDD<Rating> ratingsRD = spark.read().textFile("sample_movielens_ratings.txt")
.javaRDD()
.map(mapFunc);
If you look at the definition of mapFunc
, you're returning a Rating
object.
mapFunc = new Function<String, Rating>() {
public Rating call(String str) {
return Rating.parseRating(str);
}
};
This function is used inside a map
(a transformation in Spark terms). Because the transformations are executed directly into the worker nodes and not in the driver node, their code must be serializable. This forces Spark to try serialize the Rating
class, but it is not possible.
Try to extract the features you need from Rating
, and placing them in a different class that does not own any Spark structure. Finally, use this new class as return type of your mapFunc
function.
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