The difference in results between TO_CHAR and TO_TIMESTAMP in Oracle when filtering by date and time often stems from the data type and internal storage of dates and timestamps. Here’s a breakdown of why they can produce different records:
1. Data Type Matters (DATE vs TIMESTAMP):
• DATE in Oracle stores date and time up to seconds, but it doesn’t include fractional seconds.
• TIMESTAMP includes fractional seconds.
• If you compare TO_CHAR with a formatted string and the underlying column is DATE, it truncates to seconds, so it matches based on the exact string representation.
• If you use TO_TIMESTAMP(), it is trying to match with precision, including fractional seconds if the column is TIMESTAMP.
2. TO_CHAR Behavior:
• When you use TO_CHAR(date_column, 'YYYY-MM-DD HH24:MI:SS'), it converts the date to a string representation in that format.
• This comparison is purely text-based after conversion, so it won’t consider fractional seconds.
• It can match exact HH24:MI:SS, but any fractional seconds are ignored.
3. TO_TIMESTAMP Behavior:
• When you filter with TO_TIMESTAMP(), you are comparing timestamp values.
• If your modified_date column is of type DATE, comparing it with TIMESTAMP can cause implicit type conversion, which might not work as expected.
• If modified_date is TIMESTAMP and has fractional seconds, filtering by TO_TIMESTAMP('05-FEB-25 09:46:56', 'DD-MON-YY HH24:MI:SS') will exclude rows with fractional seconds like 09:46:56.123.
4. Implicit Conversion Issues:
• Oracle might implicitly convert DATE to TIMESTAMP or vice versa when you mix types in comparison.
• This can lead to precision loss or unexpected results.
5. Best Practice:
• If modified_date is DATE type:
WHERE modified_date = TO_DATE('05-FEB-25 09:46:56', 'DD-MON-YY HH24:MI:SS')
• If modified_date is TIMESTAMP type:
WHERE modified_date = TO_TIMESTAMP('05-FEB-25 09:46:56', 'DD-MON-YY HH24:MI:SS')
• If you don’t care about fractional seconds:
WHERE TRUNC(modified_date) = TO_DATE('05-FEB-25', 'DD-MON-YY')
6. When You Use TO_CHAR:
• You are forcing a string comparison, which might work but is slower and can lead to confusion.
• It is not recommended for date filtering.
Would you like help reworking your query for your specific data type?