Here Are Some Common Strategies For Incremental Loading:
Timestamp Or Date-Based Incremental Loading:
Include a timestamp or date column in your data to track when records were last modified.
During each update, retrieve records with timestamps or dates greater than the maximum timestamp or date from the previous load.
SELECT *
FROM your_table
WHERE modification_timestamp > last_load_timestamp;
Change Data Capture (CDC):
Implement a mechanism to capture changes in the source data. This could involve using triggers, database logs, or tracking columns
Identify and load only the changed records during each update.
SELECT *
FROM your_table
WHERE is_modified = true;
Flag-Based Incremental Loading:
Introduce a flag column in your data to mark records that have been added or modified.
During each update, process only the records with specific flag values.
SELECT *
FROM your_table
WHERE incremental_flag = 'Y';
Log -Based Incremental Loading:
Utilize transaction logs or change logs from the source system to identify changes.
Query the logs to determine the added or modified records since the last load.
Example pseudo-code (assuming a function get Changes that retrieves changes from logs):
changes = getChanges(last_load_timestamp)
processChanges(changes)
Hash-Based Incremental Loading:
Generate a hash for each record based on its attributes.
Compare the hashes to identify records that have changed.
Example SQL query (assuming a hash column named record_hash):