Yep - looks like I didn't pay enough attention when skimming through the
original email - I thought that the top 2 SQLMon reports were the good ones
and bottom 2 the bad ones. Should have read the explanation!
Indeed the smart scan had kicked in in both cases listed in the 1st
section, so not much to add to Jonathan's comments ... perhaps some ideas
about what may cause this (minding that there's no info about the DB/table
layout differences, if there's any difference in query text/columns
accessed in different DBs etc):
1) there's transactional activity on the queried table in the slow
database, but not in the fast database. in the slow database the smart scan
has to fall back to regular block shipping mode for many blocks due to
consistent reads (and/or delayed block cleanouts) that also need to access
undo blocks. this can cause orders of magnitude performance difference for
scanning.
2) the rows are very wide and in the slow database they are chained, but
not in the fast database (if the fast DB has bigger block size than smaller
- this assumes no HCC is used)
3) the query in the fast DB accesses columns lower than column number 255,
in slow DB higher than col #255 (historically there have been a few bugs
with smart scans & queries that access data from columns >255)
There are other reasons, but no need to guess, looking into V$SESSTAT
metrics for this query should help to narrow down the root cause
systematically.
--
Tanel Poder
https://blog.tanelpoder.com
On Fri, Dec 15, 2017 at 5:29 PM, Jonathan Lewis <jonathan@xxxxxxxxxxxxxxxxxx
wrote:
Tanel,
The top set both show Cell Offload, so I don't think it's (purely) a smart
scan thing.
I'd like to see the session stats for the executions, since that will
probably explain what the I/O and CPU are spent on, but from the top set
one thing I note is that the cell physical reads are single block, and the
slow system does 62,900 compared to 6,000 on the fast system. To me this
suggests either a chained rows or a read-consistency/cleanout/commit time
effect on the slow system.
With repeated executions and offload disabled the slow query does 4M
buffer gets (which is remarkably similar to the number of rows is that a
coincidence, or a comment on the number of migrated rows?) and only 324MB
read in 9,000 read requests against 3GB in 6,000 requests - that suggests a
lot of table blocks cached on the tablescan - perhaps because so many of
them have been pre-read and got into the hot cache area thanks to
"continued row fetches" in the initial runs.
Regards
Jonathan Lewis
________________________________________
From: oracle-l-bounce@xxxxxxxxxxxxx <oracle-l-bounce@xxxxxxxxxxxxx> on
behalf of Tanel Poder <tanel@xxxxxxxxxxxxxx>
Sent: 14 December 2017 23:06:37
To: wbeldma@xxxxxx
Cc: ORACLE-L
Subject: Re: Comparing apples to apples on Exadata
In the fast case, the direct path read (thus also smart scan) has kicked
in. In the slow case it hasn't and regular buffered IO via buffer cache is
used.
One indicator of that is the fast query having a Cell offload column in
its stats, the slow query doesn't (therefore there was no smart scan).
The other indicator is that you have "cell...physical read" wait events
showing up in the slow scenario. Smart scan can be so fast asynchronously
feeding data for your query, so that in the fast case you see only CPU
usage and no IO wait events at all.
