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Posted to issues@spark.apache.org by "David Rabinowitz (Jira)" <ji...@apache.org> on 2020/10/16 22:58:00 UTC
[jira] [Updated] (SPARK-33172) Spark SQL CodeGenerator does not
check for UserDefined type
[ https://issues.apache.org/jira/browse/SPARK-33172?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
David Rabinowitz updated SPARK-33172:
-------------------------------------
Description:
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.
was:
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.
> 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: 2.4.7, 3.0.1
> Reporter: David Rabinowitz
> Priority: Minor
>
> 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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