Exadata: When A Smart Scan Isn’t

Exadata is a powerful system, able to provide exceptional performance. Much of this peformance is due to Smart Scans, Exadata’s mechanism for shifting the workload to the storage cells and having them filter and reduce the amount of data the database servers must process. Not every Smart Scan that starts ends up completing, though. Oracle may decide that a different path, one that doesn’t include a Smart Scan, may be more efficient. Certain conditions must be met and there is a metric that records Smart Scan starts and another that records how many of those starts actually execute Smart Scans. Let’s look at why Oracle may decide a Smart Scan isn’t the ‘smartest’ route to the data and which metrics you can use to see how many Smart Scans end up using another execution path.

Three conditions can trigger Oracle foregoing a smart scan: setting optimizer_mode to either FIRST_ROWS or FIRST_ROWS_n or executing a query using the ‘where rownum’ predicate. Oracle originally opts to do the Smart Scan then can perform a few block I/O operations to see if that pathway can satisfy the query more efficiently. When that happens a metric, cell num fast response sessions, is incremented. If the block I/O is indeed faster Oracle foregoes the Smart Scan and completes the operation with conventional block I/O. If the block I/O proves that correct results won’t be returned to the calling session in a timely fashion Oracle resumes the Smart Scan and continues processing. Simply because this counter is incremented does not mean, by itself, that Oracle didn’t execute a Smart Scan. You’ll need another metric for that.

When Oracle decides to return to Smart Scan execution another metric is incremented, cell num fast response sessions continuing to smart scan. The same conditions that triggered the previous metric also apply here. Thus when Oracle decides to forego a Smart Scan only the previous metric, cell num fast response sessions, is incremented.

It’s fairly easy to see how many Smart Scans followed through and how many didn’t with the following query:

select a.value smart_scan_started, b.value smart_scan_cont, a.value - b.value no_smart_scan
from v$sysstat a, v$sysstat b
where a.statistic#=262
and b.statistic#=263

You may find that none of the Smart Scans that were started actually went on to finish:

------------------ --------------- -------------
              1222               0          1222

Or you may find that all of them finished:

------------------ --------------- -------------
               407             407             0

You may also find that some did, and some didn’t, continue:

------------------ --------------- -------------
                53              27            26

What is important to note is that simply because Oracle started a Smart Scan then chose to not continue on with it doesn’t indicate there is any problem with your Exadata system. On the contrary it indicates that Exadata is doing exactly what it’s supposed to do, efficiently return query results to the calling session. That may be through a Smart Scan, it may be through conventional I/O. Think of it as adjusting your route to a destination to avoid heavy traffic. If Oracle can get the correct results through a few conventional I/O operations it will do so; if a Smart Scan is necessary Oracle can again ‘change gears’ and resume it to ensure correct data is sent to the calling session. It all comes down to using the right tool for the job.

Smart Scans are great when you need them; it’s also good to know that Oracle, on Exadata, can decide when to use them and when it’s best not to. It’s also good to realize that when that happens it’s not because of a problem with Exadata. It’s simply Oracle choosing the right method to get the correct data. Sometimes the shorter path is the better path.

See all articles by David Fitzjarrell

David Fitzjarrell
David Fitzjarrell
David Fitzjarrell has more than 20 years of administration experience with various releases of the Oracle DBMS. He has installed the Oracle software on many platforms, including UNIX, Windows and Linux, and monitored and tuned performance in those environments. He is knowledgeable in the traditional tools for performance tuning – the Oracle Wait Interface, Statspack, event 10046 and 10053 traces, tkprof, explain plan and autotrace – and has used these to great advantage at the U.S. Postal Service, American Airlines/SABRE, ConocoPhilips and SiriusXM Radio, among others, to increase throughput and improve the quality of the production system. He has also set up scripts to regularly monitor available space and set thresholds to notify DBAs of impending space shortages before they affect the production environment. These scripts generate data which can also used to trend database growth over time, aiding in capacity planning. He has used RMAN, Streams, RAC and Data Guard in Oracle installations to ensure full recoverability and failover capabilities as well as high availability, and has configured a 'cascading' set of DR databases using the primary DR databases as the source, managing the archivelog transfers manually and montoring, through scripts, the health of these secondary DR databases. He has also used ASM, ASMM and ASSM to improve performance and manage storage and shared memory.

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