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Don Burleson Blog 







Visualizing Oracle performance data to spot trend changes

Oracle Database Tips by Donald BurlesonJune 1,  2015

Visualizing Oracle data is a critical task and it can be done with a variety of tools:
  • Ion - A tool for quickly visualizing Oracle performance analysis.

  • Excel-DB - A Excel spreadsheet Oracle plug-in that allow for fast charting of Oracle performance data.

So, how do we add a third dimension to an Oracle query and visualize it?  Let's start with this sample Ion screenshot of a two-dimensional plot of tablespace activity over time.  Note the three variables (tablespace_name, physical_writes, and time):

Ion screenshot for tablespace physical writes over time

Creating 2d charts in Excel is easy, and the ability to visualize Oracle performance is critical for Oracle troubleshooting, in cases where the database performance has changed.

 What kind of changes can cause unexpected performance problems?  Here are some common examples:

  • SQL- changes to optimizer parameters  (optimizer_mode, optimizer_index_cost_adj, db_file_multiblock_read_count )(before 11g)) and CBO statistics can cause system-wide performance changes.  This will manifest as changes in logical I/O, and the problem can be spotted by graphing consistent gets by top SQL ordered by gets, plotted along the time dimension.

  • Disk changes - Changing disk characteristics (RAID level, stripe size, controllers) will impact performance.  The salient metrics are physical_reads and file_name, plotted over time.  We can also plot I/O time and top-5 tablespace, total I/O and top-5 sessions.

  • Buffer efficiency - You can visualize the buffer changes over time in two dimensions by plotting the ratio of logical reads (consistent_gets) to physical disk reads over time (the data buffer hit ratio).  To enhance this in three dimensions we add (top-5 SQL ordered by reads, or buffer busy waits) and plot over time.

  • Network performance - Oracle network bottleneck analysis is well understood, and you can plot SQL*Net messages to client + sql*Net message.

  • CPU performance - We can also plot CPU time and consistent gets over time to evaluate CPU efficiency.

We are allowing the end-user to choose the x, y values as well as the start and end snapshots.  We then dynamically create the SQL, run the query and pipe the results to a three dimensional charting tool. 

Network performance - This plots "SQL*Net" waits over time

set pages 999;

column mydate heading 'Yr. Mo Dy Hr'      format a13;
column event                              format a30;
column waits                              format 999,999;
column secs_waited                        format 999,999,999;
column avg_wait_secs                      format 99,999;

   to_char(snap_time,'yyyy-mm-dd HH24')           mydate,
   e.total_waits - nvl(b.total_waits,0)           waits,
   ((e.time_waited - nvl(b.time_waited,0))/100) /
   nvl((e.total_waits - nvl(b.total_waits,0)),.01)  avg_wait_secs
   stats$system_event b,
   stats$system_event e,
   stats$snapshot     sn
   e.snap_id = sn.snap_id
   b.snap_id = e.snap_id-1
   b.event = e.event
   e.event like 'SQL*Net%'
   e.total_waits - b.total_waits  > 100
   e.time_waited - b.time_waited > 100




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