[jira] [Created] (SPARK-27336) Incorrect DataSet.summary() result

["Gengliang Wang (JIRA)" <ji...@apache.org>]

Gengliang Wang created SPARK-27336:
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             Summary: Incorrect DataSet.summary() result
                 Key: SPARK-27336
                 URL: https://issues.apache.org/jira/browse/SPARK-27336
             Project: Spark
          Issue Type: Improvement
          Components: SQL
    Affects Versions: 3.0.0
            Reporter: Gengliang Wang


There is a single data point in the minimum_nights column that is 1.0E8 out of 8k records, but .summary() says it is the 75% and the max.

I compared this with approxQuantile, and approxQuantile for 75% gave the correct value of 30.0.

To reproduce:

{code:java}
scala> val df = spark.read.format("csv").load("test.csv").withColumn("minimum_nights", '_c0.cast("Int"))
df: org.apache.spark.sql.DataFrame = [_c0: string, minimum_nights: int]

scala> df.select("minimum_nights").summary().show()
+-------+------------------+
|summary|    minimum_nights|
+-------+------------------+
|  count|              7072|
|   mean| 14156.35407239819|
| stddev|1189128.5444975856|
|    min|                 1|
|    25%|                 2|
|    50%|                 4|
|    75%|         100000000|
|    max|         100000000|
+-------+------------------+


scala> df.stat.approxQuantile("minimum_nights", Array(0.75), 0.1)
res1: Array[Double] = Array(30.0)

scala> df.stat.approxQuantile("minimum_nights", Array(0.75), 0.001)
res2: Array[Double] = Array(30.0)

scala> df.stat.approxQuantile("minimum_nights", Array(0.75), 0.0001)
res3: Array[Double] = Array(1.0E8)
{code}




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