By Alex Zaballa Hi all,
I was in a project where logical replication was in place.
It was going from 11g non-exa to 19c on Exadata and they ran into some issues during their last migration attempt a year ago.
At that time OGG was sending data from 11g to 19c and another third-party tool was sending from 19c back to 11g (in case of rollback needed). The problem was that this tool is based on triggers to capture and DML commands to replicate, but you can imagine how bad it is when you have a large number of transactions and 2 database nodes.
Now, they decided to use OGG for everything and it was a great decision.
The customer asked me to validate the data (source vs destination) to make sure everything was in sync.
My first thought was to use OGG Veridata, but the license cost was an impediment to this project.
Last time, they used some procedures to do row counts at source and destination and compare the data. I got this code and worked for a few minutes to improve it. There were 16 procedures and about 30 tables and it’s now one procedure and a few tables. It’s not perfect and there is room to improve, but you can get an idea here.
As mentioned by Connor in this video, it’s not a regular situation and this kind of thing should be carefully analyzed before starting to count every row in every table.
Here you can see an example of how to generate the scripts to validate:
comparison_name => ''cutover_comp_bm'');
comparison_name => ''cutover_comp_bm'',
schema_name => ''YOUR_SCHEMA'',
object_name => '''||table_name||''',
dblink_name => ''db_compare'',
remote_schema_name => ''YOUR_SCHEMA'',
remote_object_name => '''||table_name||''');
SET SERVEROUTPUT ON
v_comparison_name varchar2(100):= ''cutover_comp_bm'';
l_result := DBMS_COMPARISON.compare (
comparison_name => v_comparison_name,
scan_info => l_scan_info,
perform_row_dif => TRUE
IF NOT l_result THEN
DBMS_OUTPUT.put_line(v_comparison_name||'' Differences found. scan_id='' || l_scan_info.scan_id);
DBMS_OUTPUT.put_line(v_comparison_name||'' No differences found.'');
Some tables were really big in this database(billion of rows) and for this situation, I found the parameter scan_mode.
scan_mode => dbms_comparison.CMP_SCAN_MODE_RANDOM,
scan_percent => 0.001
column_list => 'YOUR COLUMNS SEPARATED BY COMMA'
SELECT LISTAGG(column_name, ',') WITHIN GROUP (ORDER BY column_id)
WHERE owner = 'YOUR_OWNER'
and data_type not like '%LOB%';
Fonte: Alex Zaballa