[jira] [Created] (SPARK-25943) Corruption when writing data into a catalog table with a different struct schema

["James Baker (JIRA)" <ji...@apache.org>]

James Baker created SPARK-25943:
-----------------------------------

             Summary: Corruption when writing data into a catalog table with a different struct schema
                 Key: SPARK-25943
                 URL: https://issues.apache.org/jira/browse/SPARK-25943
             Project: Spark
          Issue Type: Bug
          Components: Optimizer, SQL
    Affects Versions: 2.3.2, 2.4.1, 2.5.0, 3.0.0
            Reporter: James Baker


Suppose I have a catalog table with schema StructType(Seq(StructField("a", StructType(Seq(StructField("b", DataTypes.StringType), StructField("c", DataTypes.StringType))).

Suppose I now try to append a record to it:
{code:java}
{"a": {"c": "data1", "b": "data2"}}
{code}
That record will actually be appended as:
{code:java}
{"a": {"b": "data1", "c": "data2"}}
{code}
which is obviously not close to what the user wanted or expected (for me it silently corrupted my data).

It turns out that the user could provide a totally different record,
{code:java}
{"a": {"this column": "is totally different", "but": "the types match up"}}
{code}
and it'd still get written out, but as
{code:java}
{"a": {"b": "is totally different", "c": "the types match up"}}
{code}
This is because [in DDLPreprocessingUtils.castAndRenameOutput|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala#L500] [,|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala#L500],] and for DSV2 in [in Analyzer.ResolveOutputRelation|https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala#L2239] Spark puts effort in to reordering column names in line with what the output expects, but merely casts any other types. This works nicely in a case where you try to e.g. write an int into a double field, but goes wrong on complex datatypes if the types match up but the field names do not.



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