Well there are many answers and my experiences have shown that it always depends on the use-cases.
What you can do to make inserts faster:
1) Bulking (if you want to make it fast, do bulking!) which reduces commits and commit time
2) Enough ITL on the block (INITRANS)
3) Depending on the size of a row: Blocksize, PCTFREE
4) No Indexing
5) No integrity checks (Foreign keys, not null constraints)
6) Buffer cache (if it's to small you'll early end up with I/O)
And the list goes on....
APPEND hint is also very useful on inserts because it's using DIRECT-PATH inserts which will append the data simply on the table. But be aware the unused space by the table will then not be filled up!
Gerald made an excellent exposition and I totally agree withg him.
From my personal experience I would recommend partitioning. But my experience is in the telecom world were we could easily make 20/30 million inserts per hour and some of these tables were partitioned by (day,hour) to improve insert speed, we had indexes and we could not use /*+append*/ because of backup restrictions.
If you need real insight or your specific case, may be you could post your full scenario.
Hi, do you have a column in the table to store the radius server id (i.ex server1, server2, ...)?
If so, is it indexed? Is it partitioned?
maybe you could consider partitioning the table according to the server. For instance
if table looks like this
c1, c2, radius_server_id, ...
You could use range or list partition by radious_server and the on each server, when you issue the insert statement you could specify the corresponding server id.
If your planning to rebuilt table and add partitions, i don't think hash would do the trick on this one...
I stand by adding a range or list partition using a column server_id and forcing each server to specify its own partition while doing the insert.
insert into abc partition (s2_server) values(1,2,'s2') ;
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Related computing can be: Inner join or outer join. The outer join can be further divided into left join, right join, and full join. With esProc, such kinds ofrelated computing can be easily implemented. In the discussion below, we will introduce the join operations with some examples using the table emp and table sOrder.
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