NullPointerException when using Word2VecModel with UserDefinedFunction - scala

Question

I am trying to pass a word2vec model object to my spark udf. Basically I have a test set with movie Ids and I want to pass the ids along with the model object to get an array of recommended movies for each row.
def udfGetSynonyms(model: org.apache.spark.ml.feature.Word2VecModel) =
udf((col : String) => {
model.findSynonymsArray("20", 1)
})
however this gives me a null pointer exception. When I run model.findSynonymsArray("20", 1) outside the udf I get the expected answer. For some reason it doesn't understand something about the function within the udf but can run it outside the udf.
Note: I added "20" here just to get a fixed answer to see if that would work. It does the same when I replace "20" with col.
Thanks for the help!
StackTrace:
SparkException: Job aborted due to stage failure: Task 0 in stage 23127.0 failed 4 times, most recent failure: Lost task 0.3 in stage 23127.0 (TID 4646648, 10.56.243.178, executor 149): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$udfGetSynonyms1$1: (string) => array<struct<_1:string,_2:double>>)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage2.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
at org.apache.spark.sql.execution.collect.UnsafeRowBatchUtils$.encodeUnsafeRows(UnsafeRowBatchUtils.scala:49)
at org.apache.spark.sql.execution.collect.Collector$$anonfun$2.apply(Collector.scala:126)
at org.apache.spark.sql.execution.collect.Collector$$anonfun$2.apply(Collector.scala:125)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:111)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:350)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.NullPointerException
at org.apache.spark.ml.feature.Word2VecModel.findSynonymsArray(Word2Vec.scala:273)
at linebb57ebe901e04c40a4fba9fb7416f724554.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$udfGetSynonyms1$1.apply(command-232354:7)
at linebb57ebe901e04c40a4fba9fb7416f724554.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$anonfun$udfGetSynonyms1$1.apply(command-232354:4)
... 12 more

Answer 1

The SQL and udf API is a bit limited and I am not sure if there is a way to use custom types as columns or as inputs to udfs. A bit of googling didn't turn up anything too useful.
Instead, you can use the DataSet or RDD API and just use a regular Scala function instead of a udf, something like:
val model: Word2VecModel = ...
val inputs: DataSet[String] = ...
inputs.map(movieId => model.findSynonymsArray(movieId, 10))
Alternatively, I guess you could serialize the model to and from a string, but that seems much uglier.

Answer 2

I think this issue happens because wordVectors is a transient variable
class Word2VecModel private[ml] (
#Since("1.4.0") override val uid: String,
#transient private val wordVectors: feature.Word2VecModel)
extends Model[Word2VecModel] with Word2VecBase with MLWritable {
I have solved this by broadcasting w2vModel.getVectors and re-creating the Word2VecModel model inside each partition