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https://issues.apache.org/jira/browse/SPARK-8565?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14599035#comment-14599035
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PJ Van Aeken commented on SPARK-8565:
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Ok, caching the source RDD works. But wouldn't the tf.cache() as described in
the documentation of TF-IDF already materialize the ES source?
> TF-IDF drops records
> --------------------
>
> Key: SPARK-8565
> URL: https://issues.apache.org/jira/browse/SPARK-8565
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.3.1
> Reporter: PJ Van Aeken
>
> When applying TFIDF on an RDD[Seq[String]] with 1213 records, I get an
> RDD[Vector] back with only 1204 records. This prevents me from zipping it
> with the original so I can reattach the document ids.
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