Two similar tables but different join performances - sql

Question

I am running the exact same join query using two different tables, but the first one (table A) times out whereas the second (table B) does not.
SELECT * FROM table_X
INNER JOIN table_A
ON table_A.point_origin = table_X.item_id
WHERE ROWNUM < 10;
SELECT * FROM table_X
INNER JOIN table_B
ON table_B.point_origin = table_X.item_id
WHERE ROWNUM < 10;
As far as I know, table A is a subset of table B. Neither table A nor table B have point_origin indexed.
(Edit for clarification: table A is a only a subset of table B in terms of row identifiers, not in terms of exact column data.)
For what it's worth, I'm dealing with very large tables and item_id is indexed.
Is there anything else that would affect performance here or am I definitely wrong about some information provided?
Edit: Additional information per a comment below
table_A:
---------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Pstart| Pstop |
---------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 9 | 4743 | 12 (0)| | |
|* 1 | COUNT STOPKEY | | | | | | |
| 2 | TABLE ACCESS BY INDEX ROWID| table_X | 1 | 227 | 1 (0)| | |
| 3 | NESTED LOOPS | | 11 | 5797 | 12 (0)| | |
| 4 | PARTITION RANGE ALL | | 10M| 2969M| 2 (0)| 1 | 4 |
| 5 | TABLE ACCESS FULL | table_A | 10M| 2969M| 2 (0)| 1 | 4 |
|* 6 | INDEX RANGE SCAN | table_X_IP_PK | 1 | | 1 (0)| | |
---------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(ROWNUM<10)
6 - access("table_A"."POINT_ORIGIN"="table_X"."ITEM_ID")
Note
-----
- 'PLAN_TABLE' is old version
table_B:
-----------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)|
-----------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 9 | 3879 | 11 (0)|
|* 1 | COUNT STOPKEY | | | | |
| 2 | TABLE ACCESS BY INDEX ROWID| table_X | 1 | 227 | 1 (0)|
| 3 | NESTED LOOPS | | 10 | 4310 | 11 (0)|
| 4 | TABLE ACCESS FULL | table_B | 118M| 22G| 2 (0)|
|* 5 | INDEX RANGE SCAN | table_X_IP_PK | 1 | | 1 (0)|
-----------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(ROWNUM<10)
5 - access("table_B"."POINT_ORIGIN"="table_X"."ITEM_ID")
Note
-----
- 'PLAN_TABLE' is old version

Answer 1

It appears that table_a is partitioned and that the query only needs to scan 4 partitions while table_b is not partitioned and must be read in its entirety. The optimizer estimates that 4 partitions of table_a have 10 million rows while table_b has 118 million rows. You're using a nested loop so you'd expect O(n) performance so based on the statistics, it would make sense that the second query would take ~11.8 times as long as the first query.
Are the optimizer's estimates accurate? The optimizer is only as good as the statistics you've given it and it is possible that one or both tables have stale statistics.