Hyukjin Kwon created SPARK-22165:
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Summary: Type conflicts between dates, timestamps and date in
partition column
Key: SPARK-22165
URL: https://issues.apache.org/jira/browse/SPARK-22165
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.2.0, 2.1.1, 2.3.0
Reporter: Hyukjin Kwon
Priority: Minor
It looks we have some bugs when resolving type conflicts in partition column. I
found few corner cases as below:
Case 1: timestamp should be inferred but date type is inferred.
{code}
val df = Seq((1, "2015-01-01"), (2, "2016-01-01 00:00:00")).toDF("i", "ts")
df.write.format("parquet").partitionBy("ts").save("/tmp/foo")
spark.read.load("/tmp/foo").printSchema()
{code}
{code}
root
|-- i: integer (nullable = true)
|-- ts: date (nullable = true)
{code}
Case 2: decimal should be inferred but integer is inferred.
{code}
val df = Seq((1, "1"), (2, "1" * 30)).toDF("i", "decimal")
df.write.format("parquet").partitionBy("decimal").save("/tmp/bar")
spark.read.load("/tmp/bar").printSchema()
{code}
{code}
root
|-- i: integer (nullable = true)
|-- decimal: integer (nullable = true)
{code}
Looks we should de-duplicate type resolution logic if possible rather than
separate numeric precedence-like comparison alone.
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