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  1. Spark
  2. SPARK-27758

Features won't generate after 1M rows

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    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Incomplete
    • Affects Version/s: 2.1.0
    • Fix Version/s: None
    • Component/s: Input/Output
    • Labels:
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      Description

      I am trying to fit a huge dataset with ALS. The model I use:

      val als = new ALS()
      .setImplicitPrefs(true)
      .setNonnegative(true)
      .setUserCol("userIndex")
      .setItemCol("itemIndex")
      .setRatingCol("count")
      .setMaxIter(20)
      .setRank(40)
      .setRegParam(0.5)
      .setNumUserBlocks(20)
      .setNumItemBlocks(20)
      .setAlpha(5)

      val alsModel = als.fit(data)

       

      Now I see data if the user or itemindex has more than 1M rows, features will not be calculated for this user/itemId. Nor an error is returned. Is this a know issue for spark 2.1.0?

      So what I do now is randomSplit my data in like 4 batches, process each batch through ALS and then average each feature element from the 4 batches. Is this a valid approach? 

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            • Assignee:
              Unassigned
              Reporter:
              rpartapsing Rakesh Partapsing
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              • Created:
                Updated:
                Resolved: