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Posted to issues@spark.apache.org by "David Rabinowitz (Jira)" <ji...@apache.org> on 2020/10/16 22:57:00 UTC
[jira] [Created] (SPARK-33172) Spark SQL CodeGenerator does not
check for UserDefined type
David Rabinowitz created SPARK-33172:
----------------------------------------
Summary: Spark SQL CodeGenerator does not check for UserDefined type
Key: SPARK-33172
URL: https://issues.apache.org/jira/browse/SPARK-33172
Project: Spark
Issue Type: New Feature
Components: SQL
Affects Versions: 3.0.1, 2.4.7
Reporter: David Rabinowitz
The CodeGenerator takes the DataType given to `getValueFromVector()` as is, and generates code based on its type. The generated code is not aware of the actual type, and therefore cannot be compiled. For example, using a DataFrame with a Spark ML Vector (VectorUDT) the generated code is:
```
InternalRow datasourcev2scan_value_2 = datasourcev2scan_isNull_2 ? null : (datasourcev2scan_mutableStateArray_2[2].getStruct(datasourcev2scan_rowIdx_0, 4));
```
Which leads to a runtime error of
```
20/10/14 13:20:51 ERROR CodeGenerator: failed to compile: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 153, Column 126: No applicable constructor/method found for actual parameters "int, int"; candidates are: "public org.apache.spark.sql.vectorized.ColumnarRow org.apache.spark.sql.vectorized.ColumnVector.getStruct(int)"
org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 153, Column 126: No applicable constructor/method found for actual parameters "int, int"; candidates are: "public org.apache.spark.sql.vectorized.ColumnarRow org.apache.spark.sql.vectorized.ColumnVector.getStruct(int)"
at org.codehaus.janino.UnitCompiler.compileError(UnitCompiler.java:12124)
```
which then throws Spark to an infinite loop of this error.
The solution is quite simple, `getValueFromVector()` should match nad handle UserDefinedType the same as `CodeGenerator.javaType()` is doing.
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