[jira] [Created] (SPARK-26745) Non-parsing Dataset.count() optimization causes inconsistent results for JSON inputs with empty lines

["Branden Smith (JIRA)" <ji...@apache.org>]

Branden Smith created SPARK-26745:
-------------------------------------

             Summary: Non-parsing Dataset.count() optimization causes inconsistent results for JSON inputs with empty lines
                 Key: SPARK-26745
                 URL: https://issues.apache.org/jira/browse/SPARK-26745
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.4.0, 3.0.0
            Reporter: Branden Smith


The optimization introduced by [SPARK-24959|https://issues.apache.org/jira/browse/SPARK-24959] (improving performance of {{{color:#0000FF}count(){color}}} for DataFrames read from non-multiline JSON in {{{color:#0000FF}PERMISSIVE{color}}} mode) appears to cause {{{color:#0000FF}count(){color}}} to erroneously include empty lines in its result total if run prior to JSON parsing taking place.

For the following input:

{code:json}
{ "a" : 1 , "b" : 2 , "c" : 3 }

        { "a" : 4 , "b" : 5 , "c" : 6 }
     
{ "a" : 7 , "b" : 8 , "c" : 9 }


{code}

*+Spark 2.3:+*

{code:scala}
scala> val df = spark.read.json("sql/core/src/test/resources/test-data/with-empty-line.json")
df: org.apache.spark.sql.DataFrame = [a: bigint, b: bigint ... 1 more field]

scala> df.count
res0: Long = 3

scala> df.cache.count
res3: Long = 3
{code}

*+Spark 2.4:+*

{code:scala}
scala> val df = spark.read.json("sql/core/src/test/resources/test-data/with-empty-line.json")
df: org.apache.spark.sql.DataFrame = [a: bigint, b: bigint ... 1 more field]

scala> df.count
res0: Long = 7

scala> df.cache.count
res1: Long = 3
{code}

Since the count is apparently updated and cached when the Jackson parser runs, the optimization also causes the count to appear to be unstable upon cache/persist operations, as shown above.

CSV inputs, also optimized via [SPARK-24959|https://issues.apache.org/jira/browse/SPARK-24959], do not appear to be impacted by this effect.



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