[jira] [Resolved] (SPARK-38139) ml.recommendation.ALS doctests failures

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-38139?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-38139.
----------------------------------
    Fix Version/s: 3.3.0
       Resolution: Fixed

Issue resolved by pull request 35503
[https://github.com/apache/spark/pull/35503]

> ml.recommendation.ALS doctests failures
> ---------------------------------------
>
>                 Key: SPARK-38139
>                 URL: https://issues.apache.org/jira/browse/SPARK-38139
>             Project: Spark
>          Issue Type: Bug
>          Components: ML, PySpark
>    Affects Versions: 3.3.0
>            Reporter: Maciej Szymkiewicz
>            Assignee: Maciej Szymkiewicz
>            Priority: Major
>             Fix For: 3.3.0
>
>
> In my dev setups, ml.recommendation:ALS test consistently converges to value lower than expected and fails with:
> {code:python}
> File "/path/to/spark/python/pyspark/ml/recommendation.py", line 322, in __main__.ALS
> Failed example:
>     predictions[0]
> Expected:
>     Row(user=0, item=2, newPrediction=0.69291...)
> Got:
>     Row(user=0, item=2, newPrediction=0.6929099559783936)
> {code}
> In can correct for that, but it creates some noise, so if anyone else experiences this, we could drop  a digit from the results
> {code}
> diff --git a/python/pyspark/ml/recommendation.py b/python/pyspark/ml/recommendation.py
> index f0628fb922..b8e2a6097d 100644
> --- a/python/pyspark/ml/recommendation.py
> +++ b/python/pyspark/ml/recommendation.py
> @@ -320,7 +320,7 @@ class ALS(JavaEstimator, _ALSParams, JavaMLWritable, JavaMLReadable):
>      >>> test = spark.createDataFrame([(0, 2), (1, 0), (2, 0)], ["user", "item"])
>      >>> predictions = sorted(model.transform(test).collect(), key=lambda r: r[0])
>      >>> predictions[0]
> -    Row(user=0, item=2, newPrediction=0.69291...)
> +    Row(user=0, item=2, newPrediction=0.6929...)
>      >>> predictions[1]
>      Row(user=1, item=0, newPrediction=3.47356...)
>      >>> predictions[2]
> {code}



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