Dilip Biswal created SPARK-42118:
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Summary: Wrong result when parsing a multiline JSON file with
differing types for same column
Key: SPARK-42118
URL: https://issues.apache.org/jira/browse/SPARK-42118
Project: Spark
Issue Type: Improvement
Components: SQL
Affects Versions: 3.2.1
Reporter: Dilip Biswal
Here is a simple reproduction of the problem. We have a JSON file whose content
looks like following and is in multiLine format.
[{"name":""},{"name":123.34}]
Here is the result of spark query when we read the above content.
scala> val df = spark.read.format("json").option("multiLine",
true).load("/tmp/json")
df: org.apache.spark.sql.DataFrame = [name: double]
scala> df.show(false)
+----+
|name|
+----+
|null|
+----+
scala> df.count
res5: Long = 2
This is quite a serious problem for us as it's causing us to master corrupt
data in lake. If there is some issue with parsing the input, we expect spark
set the "_corrupt_record" so that we can act on it. Please note that df.count
is reporting 2 rows where as df.show only reports 1 row with null value.
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