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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