Standardization can fail with `Task not serializable` when casting to date is requested

## Describe the bug
When conversion from an integer to a date in format of `yyyyMM` (possibly `YYYYMM`), Standardization had thrown a big error message starting from:
> Job aborted. (Job aborted due to stage failure: Task not serializable: = java.io.NotSerializableException: za.co.absa.standardization.config.Default= StandardizationConfig$ Serialization stack: - object not serializable (class: za.co.absa.standardization.config.Defaul= tStandardizationConfig$, value: za.co.absa.standardization.config.DefaultSt= andardizationConfig$@3ba3e058) - element of array (index: 3) - array (class [Ljava.lang.Object;, size 5) - field (class: java.lang.invoke.SerializedLambda, name: capturedArgs, typ= e: class [Ljava.lang.Object;) - object (class java.lang.invoke.SerializedLambda, SerializedLambda[captur= ingClass=3Dclass za.co.absa.standardization.udf.UDFBuilder$, functionalInte= rfaceMethod=3Dscala/Function1.apply:(Ljava/lang/Object;)Ljava/lang/Object;,= implementation=3DinvokeStatic za/co/absa/standardization/udf/UDFBuilder$.$= anonfun$stringUdfViaNumericParser$1:(Lza/co/absa/standardization/types/pars= ers/NumericParser;ZLjava/lang/String;Lza/co/absa/standardization/config/Sta= ndardizationConfig;Lscala/Option;Ljava/lang/String;)Lza/co/absa/standardiza= tion/udf/UDFResult;, instantiatedMethodType=3D(Ljava/lang/String;)Lza/co/ab= sa/standardization/udf/UDFResult;, numCaptured=3D5]) - writeReplace data (class: java.lang.invoke.SerializedLambda) - object (class za.co.absa.standardization.udf.UDFBuilder$$$Lambda$5214/36= 0225670,

## To Reproduce
Steps to reproduce the behavior OR commands run:
1. Go to '...'
2. Use value '...'
3. Run using
4. See error

Try also to have an integer type with metadata:
```json
{"name": "MY_DATE", "type": "integer", "metadata": {"pattern": "yyyyMM", "timezone": "Africa/Johannesburg"}, "nullable": true}
```

## Expected behavior
- The standardization should have data errors if incorrect date format is passed, not failing the pipeline.
- If the above is not an option, at least, the error message should say which coulmn or condition have caused the error.

## Screenshots
If applicable, add screenshots to help explain your problem.

## Desktop (please complete the following information):
- OS: [e.g. iOS]
- Versions of libraries (Spark, Scala, ...)
- Version [e.g. 22]

## Additional context
Add any other context about the problem here.