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  1. Spark
  2. SPARK-22165

Type conflicts between dates, timestamps and date in partition column

    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Minor
    • Resolution: Fixed
    • Affects Version/s: 2.1.1, 2.2.0, 2.3.0
    • Fix Version/s: 2.3.0
    • Component/s: SQL
    • Labels:

      Description

      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.

      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()
      
      root
       |-- i: integer (nullable = true)
       |-- ts: date (nullable = true)
      

      Case 2: decimal should be inferred but integer is inferred.

      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()
      
      root
       |-- i: integer (nullable = true)
       |-- decimal: integer (nullable = true)
      

      Looks we should de-duplicate type resolution logic if possible rather than separate numeric precedence-like comparison alone.

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            • Assignee:
              hyukjin.kwon Hyukjin Kwon
              Reporter:
              hyukjin.kwon Hyukjin Kwon
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              • Created:
                Updated:
                Resolved: