Insert New Rows FAQS

1. What is the purpose of this command?

• The command is designed to insert new rows from the staging table into the target table. 
• It pulls data from various datasets, performs necessary transformations, and inserts it into the target table as part of an ETL (Extract, Transform, Load) process.

2. How does the insertion work?

• The command constructs a SELECT query for each dataset.
• These queries are then merged using set-based operations (like UNION or INTERSECT). 
• The merged result is inserted into the target table using the INSERT INTO command.

3. What is the role of odiRef.getColList()?

• odiRef.getColList() is used to dynamically generate the list of columns to be inserted into the target table and to align the data correctly.
• It helps to build the list of target columns based on specified conditions (like (INS and !TRG) and REW).

4. What is the purpose of the for loop in the code?

• The for loop iterates over all defined datasets.
• For each dataset, it generates a SELECT statement that gathers the necessary data, applies any required filtering, and applies any joins or grouping conditions.

5. How are datasets combined?

• The SELECT queries for each dataset are combined using set-based operations such as UNION or INTERSECT.
• This ensures that the resulting data is merged and ready for insertion into the target table.

6. What does the JRN_FLAG condition do?

• The JRN_FLAG condition ensures that rows marked for deletion (i.e., JRN_FLAG = 'D') are excluded from the insertion process if the dataset includes a journal flag.
• If no journal flag is present, the condition (1=1) is used, meaning no filtering is applied.

7. What happens if multiple datasets are involved?

• If multiple datasets are involved, the system will generate and merge separate queries for each dataset.
• Each dataset may come from different tables, and the respective SELECT queries will be joined and filtered according to the dataset’s conditions.

8. What is the role of the Commit statement?

• The Commit statement ensures that the transaction is finalized and the changes made to the target table are committed.
• Until the Commit is issued, the transaction remains open, and changes can be rolled back if necessary.

9. Can this process be rolled back?

• Yes, the entire process (including data insertion) is part of a single transaction.
• If there is an issue, the transaction can be rolled back before the final Commit is issued, preventing partial or incorrect data from being inserted.

10. What happens if there is an error during the insertion process?

• If an error occurs before the Commit statement is issued, the entire transaction can be rolled back, ensuring that no partial data is committed to the target table.
• Once the Commit is executed, the changes are permanent.

11. Can this command handle large datasets?

• Yes, this approach can handle large datasets efficiently by using set-based operations (like UNION and INTERSECT) to merge data.
• However, performance depends on the size of the datasets and the efficiency of the SQL queries used.

12. What happens if there are missing or incorrect mappings in the datasets?

• If there are missing or incorrect mappings, the insertion might fail, resulting in errors.
• It's important to ensure that column mappings are accurate and that the datasets are correctly defined and referenced.

13. What does the DISTINCT_ROWS expression do?

• The DISTINCT_ROWS ensures that only unique rows are selected for insertion into the target table, eliminating any duplicate data before the insert.

14. How does this affect the target table schema?

• The target table's schema should be compatible with the data being inserted.
• This means that the column names and data types in the source datasets should align with the target table.
• Any mismatch can lead to errors during the insertion process.

15. What happens if there are null values in the data?

• Null values can be inserted into the target table if the target columns allow nulls.
• If the target columns are defined as NOT NULL, the insertion will fail unless the data is transformed to provide non-null values.