count() query taking more than 20 seconds
Table_a = 7022536 rows
Table_b (GTT) = 5601 rows
Query:
SELECT COUNT (a.ssn_head)
FROM table_a a, table_b b
WHERE b.hoh = a.head AND a.flag = 'Y';
take开发者_如何学Pythons 20+ seconds to bring 17214 records.
Explain plan is:
Plan hash value: 1901401324
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | C
--------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 25 | 1
| 1 | SORT AGGREGATE | | 1 | 25 |
|* 2 | HASH JOIN | | 114K| 2801K| 1
| 3 | TABLE ACCESS FULL| table_b | 49188 | 528K|
| 4 | REMOTE | table_a | 7022K| 93M| 1
--------------------------------------------------------------------------------
table_b
(GTT) has no indices on it...I think since the query is going through all of table_b it will always do a full table scan..right?
table_a
has index on head
What other way is there to make this query run faster?
IS hoh in table_b unique ? If so, then
SELECT COUNT (a.ssn_head)
FROM table_a a, table_b b
WHERE b.hoh = a.head AND a.flag = 'Y';
is logically equivalent to
SELECT COUNT (a.ssn_head)
FROM table_a a
WHERE a.flag = 'Y'
and a.head in (select hoh FROM table_b);
Given that the larger data volume is on the remote server, I'd suggest pushing the query over there with the DRIVING_SITE hint.
SELECT /*+DRIVING_SITE (r) */ COUNT (r.col_a)
FROM owner.table@other r
WHERE r.col_b in (select l.col_c FROM local l);
That should work with a synonym instead of table@dblink. But it probably won't work with a view.
Make a materialized view of table_a on the local server and operate off of that.
It might also help (mildly) to put an index on a.flag, but this will be minor compared to operating locally.
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