Average Active Sessions

John Beresniewicz, Oracle America

What is this?

Agenda

•  DB Time

•  Average Active Sessions

•  Performance Monitoring

•  Comparing Load

•  Diving Deep with ASH

•  Relationship to Queuing Theory

Database Time (DB Time)

•  Time spent in the database by foreground sessions

•  Includes CPU time, IO wait time and active wait time

•  Excludes idle wait time

Database time is total time spent by user processes either actively working or actively waiting in a

database call.

EM Performance Page

•  DB Time per Second •  Broken down into CPU + Wait Classes

•  Averaged over 1 minute intervals

•  Sources: v$waitclassmetric_history; v$sysmetric_history

•  Question: What are the chart units and label?

Historical Note

on Naming

• We knew what we were graphing, but what was it?

• Team met multiple times to discuss

• This is from when we finally “got it”

What Are the Units?

•  Time / time = unit-less (?)

•  DB time accumulates in micro, milli, or centi-seconds

•  Time-normalized sysmetrics are per second of elapsed

•  Centi-seconds (foreground time) per second (elapsed)

•  Centi-users per second

•  User seconds per elapsed second (normalize time units)

•  Active session seconds per second

•  Active sessions

Average Active Sessions

•  NOTE: Time units must synchronize

AAS = DB time / elapsed time

(during some workload)

Average Active Sessions

•  A time-based measure of “user load” on the database

•  Where the “time” is really user time…important

•  The derivative (calculus) of DB Time over time

•  This is why Top Activity and Perf Page are literal pictures of DB Time

•  The “velocity” of DB Time accumulation in the database

Performance Monitoring

•  DB Time increases when user load increases

•  Average Active Sessions measures the rate of increase

•  DB Time increases when performance degrades

•  Average Active Sessions captures the rate of increase of DB Time over time

•  Therefore, AAS is the best single metric to monitor for overall performance

Performance monitoring

•  Average Active Sessions captures both load and performance •  Severe performance degradation will spike the metric

•  Server-generated metrics for monitoring: •  Database Time Per Sec (10g)

•  Average Active Sessions (11g)

•  Adaptive Thresholds technology •  Set thresholds to high percentile (99th) values (unusual spike)

•  Moving window baseline and seasonality adjust to expected load changes

Bad Friday?

Comparing Database Load

•  How to compare load on two different databases?

•  How to compare load on same database from two different time periods?

•  Answer: normalize DB Time by time

•  That is, use Average Active Sessions!

•  Remember, DB Time is “user time”

•  It is “fungible”

Enterprise Loadmap

Enterprise Loadmap

Enterprise Loadmap

Diving Deep with ASH

•  ASH is used to estimate DB Time accumulation over some time interval, and thus also AAS

•  With ASH we can break down total AAS within a Database across many dimensions of interest

•  Come to “ASH Deep-dive: Advanced Performance Analysis Tips” •  Wednesday 3:30 pm, Moscone South Room 104

EM Top Activity

ASH Analytics

Breakdown by SQL_ID

Historical Note: ASH Analytics Mockup

ASH Analytics Loadmap

Relationship to Queuing Theory

•  Consider the Oracle database as a black-box service center

•  User calls come in (SQL) from outside

•  Results computed inside and returned to user

•  What is the relationship of Average Active Sessions to black-box queuing models?

•  Average Active Sessions measures an important queuing theoretic concept

Little’s Law for Queuing Systems

N = X * R

N = number of active requests in system

X = serviced request throughput

R = average service time per request

Little’s Law: Database Black-box server

N = X * R

N = ????

X = User Calls per Second

R = Response (DB time) per Call

Average Active Sessions

This explains why DB time increases with both performance degradation and load increase.

Compute AAS from AWR snapshots

•  Step 1: Prepare raw data stream by joining:

•  DBA_HIST_SNAPSHOT

•  DBA_HIST_SYS_TIME_MODEL

•  Statistic “DB Time”

•  Step 2: Compute elapsed time and DB Time deltas per snapshot

•  Step 3: Compute Average Active Sessions per snapshot

•  DELTA(DB Time) / DELTA(Elapsed time)

Step 1: Prepare Raw Data Stream

WITH snapDBtime as (select SN.snap_id as snap_id ,SN.instance_number as inst_num ,ROUND(SN.startup_time,'MI') as startup_time ,ROUND(SN.begin_interval_time,'MI') as begin_time ,ROUND(SN.end_interval_time,'MI') as end_time ,TM.value / 1000000 as DBtime_secs from dba_hist_snapshot SN ,dba_hist_sys_time_model TM where SN.dbid = TM.dbid and SN.instance_number = TM.instance_number and SN.snap_id = TM.snap_id and TM.stat_name = 'DB time' ),

Step 2: Compute Time Deltas

DeltaDBtime as (select inst_num ,snap_id ,startup_time ,end_time ,DBtime_secs ,CASE WHEN begin_time = startup_time THEN DBtime_secs ELSE DBtime_secs - LAG(DBtime_secs,1) OVER (PARTITION BY inst_num, startup_time ORDER BY snap_id ASC) END as DBtime_secs_delta ,(end_time - begin_time)*24*60*60 as elapsed_secs from snapDBtime order by inst_num, snap_id ASC )

Step 3: Compute Avg Active Sessions

select inst_num ,snap_id ,ROUND(DBtime_secs,1) as DBtime_secs ,ROUND(DBtime_secs_delta / elapsed_secs,3) as AvgActive_sess from DeltaDBtime /