Hyperthreading with Oracle (update)

After my first post on hyperthreading, and all the hits I've been getting I've decided to update it..

My first post was pased on testing with a DL980.. This is an 8 socket server with   X7560  @ 2.27GHz processes.

My currently updated post is on a new 2 socket server with the E7- 2870 @ 2.40GHz chipset.

The servers I tested on were

2 Socket
10 Core (dual threaded)
11.2.0.3 Oracle
Linux RHEL  2.6.18-274.17.1.el5
132g of ram.


I tested by using Kevin Clossons SLOB test which can be found here.

I tested using multiple process settings, and you see how these  servers scaled up with the processes.

I warmed up with 15 processes.  Looking at the LIO count, we are doing 7.2 million. output

Load Profile              Per Second    Per Transaction   Per Exec   Per Call
~~~~~~~~~~~~         ---------------    --------------- ---------- ----------
      DB Time(s):               14.4               24.9       0.00       4.60
       DB CPU(s):               14.3               24.7       0.00       4.56
       Redo size:           13,974.5           24,137.1
   Logical reads:        7,259,470.5       12,538,708.3
   Block changes:               32.9               56.8
  Physical reads:               69.9              120.8
 Physical writes:               15.8               27.2
      User calls:                3.1                5.4
          Parses:                3.8                6.6
     Hard parses:                0.0                0.0
W/A MB processed:                0.4                0.7
          Logons:                0.1                0.2
        Executes:           28,206.8           48,719.3
       Rollbacks:                0.0                0.0
    Transactions:                0.6

Then 20 processes.  8.7 million still looking good.  output

Load Profile              Per Second    Per Transaction   Per Exec   Per Call
~~~~~~~~~~~~         ---------------    --------------- ---------- ----------
      DB Time(s):               18.9              127.0       0.00      10.83
       DB CPU(s):               18.9              126.8       0.00      10.82
       Redo size:           15,073.6          101,207.6
   Logical reads:        8,714,693.4       58,512,431.8
   Block changes:               39.2              263.4
  Physical reads:                2.1               13.9
 Physical writes:               13.0               87.0
      User calls:                1.8               11.7
          Parses:                3.8               25.6
     Hard parses:                0.0                0.1
W/A MB processed:                0.4                2.5
          Logons:                0.1                0.4
        Executes:           33,859.7          227,341.5
       Rollbacks:                0.0                0.0
    Transactions:                0.2

Now lets try 25.. see how we go past the number of cores .  9.4 million.. Hyperthreading is scaling nicely. output

Load Profile              Per Second    Per Transaction   Per Exec   Per Call
~~~~~~~~~~~~         ---------------    --------------- ---------- ----------
      DB Time(s):               23.1               91.7       0.00       9.26
       DB CPU(s):               23.0               91.6       0.00       9.24
       Redo size:           21,634.2           86,063.7
   Logical reads:        9,406,658.2       37,420,998.8
   Block changes:               68.2              271.4
  Physical reads:                3.7               14.8
 Physical writes:                5.7               22.5
      User calls:                2.5                9.9
          Parses:                3.3               13.3
     Hard parses:                0.1                0.3
W/A MB processed:                0.4                1.6
          Logons:                0.1                0.5
        Executes:           36,544.7          145,380.0
       Rollbacks:                0.0                0.0
    Transactions:                0.3

Next 35.. Still scaling... output

Load Profile              Per Second    Per Transaction   Per Exec   Per Call
~~~~~~~~~~~~         ---------------    --------------- ---------- ----------
      DB Time(s):               33.5              310.9       0.00      18.74
       DB CPU(s):               33.5              310.3       0.00      18.70
       Redo size:            9,379.2           86,997.8
   Logical reads:       11,039,158.6      102,395,221.3
   Block changes:               17.7              164.4
  Physical reads:                1.3               12.0
 Physical writes:                4.0               36.9
      User calls:                1.8               16.6
          Parses:                2.0               18.9
     Hard parses:                0.1                1.0
W/A MB processed:                0.2                2.2
          Logons:                0.1                0.6
        Executes:           42,882.8          397,765.4
       Rollbacks:                0.0                0.0
    Transactions:                0.1

Finally the number of threads.  This appears to be the peak. output

Load Profile              Per Second    Per Transaction   Per Exec   Per Call
~~~~~~~~~~~~         ---------------    --------------- ---------- ----------
      DB Time(s):               38.3              387.0       0.00      17.48
       DB CPU(s):               37.6              380.4       0.00      17.18
       Redo size:            9,207.1           93,060.2
   Logical reads:       11,577,951.1      117,023,088.1
   Block changes:               16.4              166.1
  Physical reads:                1.1               11.5
 Physical writes:                4.5               45.1
      User calls:                2.2               22.1
          Parses:                2.0               19.9
     Hard parses:                0.1                0.6
W/A MB processed:                0.2                2.5
          Logons:                0.1                0.9
        Executes:           44,975.6          454,587.0
       Rollbacks:                0.0                0.0
    Transactions:                0.1

Now lets go up to 45 ...   things start dropping off.  output

oad Profile              Per Second    Per Transaction   Per Exec   Per Call
~~~~~~~~~~~~         ---------------    --------------- ---------- ----------
      DB Time(s):               40.7              482.9       0.00      16.78
       DB CPU(s):               36.0              427.5       0.00      14.86
       Redo size:            8,205.8           97,318.2
   Logical reads:       11,100,719.6      131,651,002.6
   Block changes:               14.0              165.9
  Physical reads:                0.9               10.3
 Physical writes:                3.2               38.3
      User calls:                2.4               28.8
          Parses:                2.3               27.5
     Hard parses:                0.1                0.6
W/A MB processed:                0.3                3.6
          Logons:                0.1                1.4
        Executes:           43,122.5          511,418.6
       Rollbacks:                0.0                0.0
    Transactions:                0.1

So if you look at the throughput..

20 processes    8,7 Million LIO's
40 Processes   11.6 Million LIO's

Not quite linaear progression, but things don't really top off until I get to the number of threads..  This scaled much better, and it seems that hyperthreading is helpgin push more workload through.

Analyzing the last query run

I don't know how many times I find myself trying to tune a query, and going through the same tasks.

I run the sql in my session (most likely on sqlplus on the unix server), but I then try to track down the sql_id, and finally (if I am lucky) find the SQL Monitor report (tuning pack license required).

So I came up with a script that I am putting on all my severs. post_execute.sql

This script can be executed in your shell as the next step after running the query in question.. but first.

If you want to use the SQL Monitor output, you are best adding the /*+monitor */ hint to your query just to be sure it is captured.

Well this is what the script does.

1) run your query.. I used this query for my example.

select /*+monitor */ a.owner,b.table_name ,sum(bytes) from dba_segments a,
                                     dba_tables b
where a.owner=b.owner and 
      a.segment_name=b.table_name 
group by a.owner,b.table_name
order by a.owner,b.table_name;

2) It captures the dbms_xplan.display_cursor output for the last run sql.. Here is snippet of what the output looked like..

Plan information for current query




SQL_ID  208ttrm2nbt0u, child number 0
-------------------------------------
select /*+monitor */ a.owner,b.table_name ,sum(bytes) from dba_segments 
a,                                      dba_tables b where 
a.owner=b.owner and       a.segment_name=b.table_name group by 
a.owner,b.table_name order by a.owner,b.table_name
 
Plan hash value: 1601540958
 
--------------------------------------------------------------------------------------------------------------
| Id  | Operation                                   | Name           | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                            |                |       |       | 14425 (100)|          |
|   1 |  SORT GROUP BY                              |                |     6 |  2184 | 14425   (1)| 00:02:54 |
|*  2 |   HASH JOIN OUTER                           |                |     6 |  2184 | 14424   (1)| 00:02:54 |
|   3 |    NESTED LOOPS OUTER                       |                |     6 |  2160 | 14422   (1)| 00:02:54 |
|   4 |     NESTED LOOPS OUTER                      |                |     6 |  2106 | 14410   (1)| 00:02:53 |
|   5 |      NESTED LOOPS OUTER                     |                |     6 |  2070 | 14408   (1)| 00:02:53 |
|   6 |       NESTED LOOPS                          |                |     6 |  1998 | 14396   (1)| 00:02:53 |
|   7 |        NESTED LOOPS                         |                |     6 |  1974 | 14390   (1)| 00:02:53 |
|*  8 |         HASH JOIN                           |                |    67 | 19899 | 14318   (1)| 00:02:52 |
|*  9 |          HASH JOIN                          |                |  5095 |  1298K| 13638   (1)| 00:02:44 |
|  10 |           MERGE JOIN CARTESIAN              |                |   131 | 11135 |     5  (20)| 00:00:01 |
|* 11 |            HASH JOIN                        |                |     1 |    68 |     1 (100)| 00:00:01 |
|* 12 |             FIXED TABLE FULL                | X$KSPPI        |     1 |    55 |     0   (0)|          |
|  13 |             FIXED TABLE FULL                | X$KSPPCV       |   100 |  1300 |     0   (0)|          |
|  14 |            BUFFER SORT                      |                |   131 |  2227 |     5  (20)| 00:00:01 |
|  15 |             TABLE ACCESS STORAGE FULL       | USER$          |   131 |  2227 |     4   (0)| 00:00:01 |
|  16 |           VIEW                              | SYS_DBA_SEGS   |  5095 |   875K| 13633   (1)| 00:02:44 |
|  17 |            UNION-ALL                        |                |       |       |            |          |
|* 18 |             HASH JOIN RIGHT OUTER           |                |   672 |   103K| 12305   (1)| 00:02:28 |
|  19 |              TABLE ACCESS STORAGE FULL      | USER$          |   131 |  2227 |     4   (0)| 00:00:01 |
|* 20 |              HASH JOIN                      |                |   672 | 94752 | 12301   (1)| 00:02:28 |
|  21 |               NESTED LOOPS                  |                |   672 | 68544 | 11623   (1)| 00:02:20 |
|* 22 |                HASH JOIN                    |                |   672 | 63168 | 11623   (1)| 00:02:20 |
|  23 |                 TABLE ACCESS STORAGE FULL   | TS$            |   167 |  1336 |    48   (0)| 00:00:01 |
|* 24 |                 HASH JOIN                   |                |   672 | 57792 | 11574   (1)| 00:02:19 |
|  25 |                  TABLE ACCESS STORAGE FULL  | SEG$           | 16421 |   449K|   821   (1)| 00:00:10 |
|  26 |                  VIEW                       | SYS_OBJECTS    | 21369 |  1210K| 10752   (1)| 00:02:10 |
|  27 |                   UNION-ALL                 |                |       |       |            |          |
|* 28 |                    TABLE ACCESS STORAGE FULL| TAB$           |  7284 |   177K|  2681   (1)| 00:00:33 |
|  29 |                    TABLE ACCESS STORAGE FULL| TABPART$       |  1525 | 28975 |    12   (0)| 00:00:01 |
|  30 |                    TABLE ACCESS STORAGE FULL| CLU$           |    10 |   140 |  2680   (1)| 00:00:33 |
|* 31 |                    TABLE ACCESS STORAGE FULL| IND$           |  9647 |   188K|  2681   (1)| 00:00:33 |
|  32 |                    TABLE ACCESS STORAGE FULL| INDPART$       |  1322 | 25118 |    12   (0)| 00:00:01 |
|* 33 |                    TABLE ACCESS STORAGE FULL| LOB$           |  1547 | 32487 |  2680   (1)| 00:00:33 |
|  34 |                    TABLE ACCESS STORAGE FULL| TABSUBPART$    |    32 |   448 |     2   (0)| 00:00:01 |
|  35 |                    TABLE ACCESS STORAGE FULL| INDSUBPART$    |     1 |    52 |     2   (0)| 00:00:01 |
|  36 |                    TABLE ACCESS STORAGE FULL| LOBFRAG$       |     1 |    17 |     2   (0)| 00:00:01 |
|* 37 |                INDEX UNIQUE SCAN            | I_FILE2        |     1 |     8 |     0   (0)|          |
|  38 |               TABLE ACCESS STORAGE FULL     | OBJ$           | 88138 |  3356K|   677   (1)| 00:00:09 |
|  39 |             NESTED LOOPS                    |                |    34 |  3638 |   450   (1)| 00:00:06 |
|  40 |              NESTED LOOPS                   |                |    34 |  3366 |   450   (1)| 00:00:06 |
|* 41 |               HASH JOIN OUTER               |                |    34 |  3094 |   416   (1)| 00:00:05 |
|  42 |                NESTED LOOPS                 |                |    34 |  2516 |   411   (0)| 00:00:05 |
|* 43 |                 TABLE ACCESS STORAGE FULL   | UNDO$          |   204 |  8568 |     3   (0)| 00:00:01 |
|* 44 |                 TABLE ACCESS CLUSTER        | SEG$           |     1 |    32 |     2   (0)| 00:00:01 |
|* 45 |                  INDEX UNIQUE SCAN          | I_FILE#_BLOCK# |     1 |       |     1   (0)| 00:00:01 |
|  46 |                TABLE ACCESS STORAGE FULL    | USER$          |   131 |  2227 |     4   (0)| 00:00:01 |
|  47 |               TABLE ACCESS CLUSTER          | TS$            |     1 |     8 |     1   (0)| 00:00:01 |
|* 48 |                INDEX UNIQUE SCAN            | I_TS#          |     1 |       |     0   (0)|          |
|* 49 |              INDEX UNIQUE SCAN              | I_FILE2        |     1 |     8 |     0   (0)|          |
|* 50 |             HASH JOIN                       |                |  4389 |   321K|   878   (1)| 00:00:11 |
|  51 |              TABLE ACCESS STORAGE FULL      | FILE$          |   569 |  6828 |     3   (0)| 00:00:01 |
|* 52 |              HASH JOIN RIGHT OUTER          |                |  4389 |   270K|   874   (1)| 00:00:11 |
|  53 |               TABLE ACCESS STORAGE FULL     | USER$          |   131 |  2227 |     4   (0)| 00:00:01 |
|* 54 |               HASH JOIN                     |                |  4389 |   197K|   870   (1)| 00:00:11 |
|  55 |                TABLE ACCESS STORAGE FULL    | TS$            |   167 |  1336 |    48   (0)| 00:00:01 |
|* 56 |                TABLE ACCESS STORAGE FULL    | SEG$           |  4389 |   162K|   821   (1)| 00:00:10 |
|* 57 |          TABLE ACCESS STORAGE FULL          | OBJ$           | 88138 |  3098K|   679   (1)| 00:00:09 |
|* 58 |         TABLE ACCESS CLUSTER                | TAB$           |     1 |    32 |     2   (0)| 00:00:01 |
|* 59 |          INDEX UNIQUE SCAN                  | I_OBJ#         |     1 |       |     1   (0)| 00:00:01 |
|  60 |        TABLE ACCESS CLUSTER                 | TS$            |     1 |     4 |     1   (0)| 00:00:01 |
|* 61 |         INDEX UNIQUE SCAN                   | I_TS#          |     1 |       |     0   (0)|          |
|  62 |       TABLE ACCESS CLUSTER                  | SEG$           |     1 |    12 |     2   (0)| 00:00:01 |
|* 63 |        INDEX UNIQUE SCAN                    | I_FILE#_BLOCK# |     1 |       |     1   (0)| 00:00:01 |
|* 64 |      INDEX RANGE SCAN                       | I_OBJ1         |     1 |     6 |     2   (0)| 00:00:01 |
|* 65 |     INDEX RANGE SCAN                        | I_OBJ1         |     1 |     9 |     2   (0)| 00:00:01 |
|  66 |    INDEX FULL SCAN                          | I_USER2        |   131 |   524 |     1   (0)| 00:00:01 |
--------------------------------------------------------------------------------------------------------------
 
Predicate Information (identified by operation id):
---------------------------------------------------
 
   2 - access("CX"."OWNER#"="CU"."USER#")
   8 - access("SEGMENT_NAME"="O"."NAME" AND "O"."OWNER#"="U"."USER#")
   9 - access("OWNER"="U"."NAME")
  11 - access("KSPPI"."INDX"="KSPPCV"."INDX")
  12 - filter("KSPPI"."KSPPINM"='_dml_monitoring_enabled')
  18 - access("O"."OWNER#"="U"."USER#")
  20 - access("O"."OBJ#"="SO"."OBJECT_ID" AND "O"."TYPE#"="SO"."OBJECT_TYPE_ID")
  22 - access("S"."TS#"="TS"."TS#")
  24 - access("S"."FILE#"="SO"."HEADER_FILE" AND "S"."BLOCK#"="SO"."HEADER_BLOCK" AND 
              "S"."TS#"="SO"."TS_NUMBER" AND "S"."TYPE#"="SO"."SEGMENT_TYPE_ID")
  28 - filter(BITAND("T"."PROPERTY",1024)=0)
  31 - filter(("I"."TYPE#"=1 OR "I"."TYPE#"=2 OR "I"."TYPE#"=3 OR "I"."TYPE#"=4 OR "I"."TYPE#"=6 OR 
              "I"."TYPE#"=7 OR "I"."TYPE#"=8 OR "I"."TYPE#"=9))
  33 - filter((BITAND("L"."PROPERTY",64)=0 OR BITAND("L"."PROPERTY",128)=128))
  37 - access("S"."TS#"="F"."TS#" AND "S"."FILE#"="F"."RELFILE#")
  41 - access("S"."USER#"="U"."USER#")
  43 - storage("UN"."STATUS$"<>1)
       filter("UN"."STATUS$"<>1)
  44 - filter(("S"."TYPE#"=1 OR "S"."TYPE#"=10))
  45 - access("S"."TS#"="UN"."TS#" AND "S"."FILE#"="UN"."FILE#" AND "S"."BLOCK#"="UN"."BLOCK#")
  48 - access("S"."TS#"="TS"."TS#")
  49 - access("UN"."TS#"="F"."TS#" AND "UN"."FILE#"="F"."RELFILE#")
  50 - access("S"."TS#"="F"."TS#" AND "S"."FILE#"="F"."RELFILE#")
  52 - access("S"."USER#"="U"."USER#")
  54 - access("S"."TS#"="TS"."TS#")
  56 - filter(("S"."TYPE#"<>6 AND "S"."TYPE#"<>5 AND "S"."TYPE#"<>8 AND "S"."TYPE#"<>10 AND 
              "S"."TYPE#"<>1))
  57 - storage(BITAND("O"."FLAGS",128)=0)
       filter(BITAND("O"."FLAGS",128)=0)
  58 - filter(BITAND("T"."PROPERTY",1)=0)
  59 - access("O"."OBJ#"="T"."OBJ#")
  61 - access("T"."TS#"="TS"."TS#")
  63 - access("T"."TS#"="S"."TS#" AND "T"."FILE#"="S"."FILE#" AND "T"."BLOCK#"="S"."BLOCK#")
  64 - access("T"."BOBJ#"="CO"."OBJ#")
  65 - access("T"."DATAOBJ#"="CX"."OBJ#")

3) It captures some execution statistics that I like to look at .. Here is the output below.

Summary of query stats





 ************** plan_hash_value       = 1188305021
 ************** sql_id               = 208ttrm2nbt0u

avg_elapsed_time      = 2.59
total_executions      = 2
avg_rows_processed    = 5372
avg_disk_reads        = 202
avg_buffer_gets       = 189970
avg_cpu_time          = 2426631
avg_iowait            = 99965
avg_cluster_wait      = 245947
avg_direct_writes     = 0
avg_plssql_exec_time  = 162398
avg_cell_offload      = 0

And finally it creates the beautiful sql_monitor output we are all used to.

Pretty cool huh ?  It creates these 3 pieces based on the last sql executed in the session.. Now this is the best part.. At the end of the script is this code.

!echo "From: bryan.grenn@oracle.com"  > /tmp/file
!echo "To: bryan.grenn@oracle.com"   >> /tmp/file
!echo "Subject: analyze output sql_monitor"   >> /tmp/file
!echo "Mime-Version: 1.0"      >> /tmp/file
!echo 'Content-Type: multipart/mixed; boundary="DMW.Boundary.605592468"'   >> /tmp/file
!echo "--DMW.Boundary.605592468" >> /tmp/file
!echo " " >> /tmp/file
!echo " analyze report sql_monitor " >> /tmp/file
!echo " " >> /tmp/file
!echo "--DMW.Boundary.605592468" >> /tmp/file
!echo 'Content-Disposition: inline; filename="analyze_dbms_xplan.txt"' >> /tmp/file
!echo "Content-Transfer-Encoding: 7bit" >> /tmp/file
!cat /tmp/analyze_dbms_xplan.txt >> /tmp/file
!echo "--DMW.Boundary.605592468" >> /tmp/file

!echo 'Content-Disposition: inline; filename="analyze_query_stats.txt"' >> /tmp/file
!echo "Content-Transfer-Encoding: 7bit" >> /tmp/file
!cat /tmp/analyze_query_stats.txt >> /tmp/file
!echo "--DMW.Boundary.605592468" >> /tmp/file

!echo 'Content-Disposition: inline; filename="analyze_sql_monitor.htm"' >> /tmp/file
!echo "Content-Transfer-Encoding: 7bit" >> /tmp/file
!cat /tmp/analyze_html.htm >> /tmp/file
!echo "--DMW.Boundary.605592468" >> /tmp/file

!/usr/sbin/sendmail bryan.grenn@oracle.com < /tmp/file

This code will take the 3 output files, and mail them to you as attachments.  Notice my e-mail is in the script, so change it to what you need to get it going.  

I'm going to use the often, by putting it on all my servers and just running it after any stubborn sql show up. I will be instantly e-mailed the mail pieces I need to figure out what is going on with the sql.

R and visualing your execution times

Well, I think I'm a little late to the party..   I know Greg Rahn did a great post on utilizing R to visual your ash data.  I figure I would do a simple example of how to build something myself to show how easy it is to utilyze R to visualize query execution times..

Well first I stated by downloading R from cran.r-project.org.

Once I downloaded R, I went to one of my databases, and found a query that had different execution times I wanted to play with.  I created an output file from the query.. Here is the script I used..

set pagesize 10000
set feedback off
spool rtest.txt

select trunc((elapsed_time_delta/executions_delta)/1000000,4) avg_execution_time "AVG_EXECUTION_TIME",
       PLAN_HASH_VALUE "PLAN_HASH_VALUE",
       execution_date "EXECUTION_DATE"
from
(
select sum(elapsed_time_delta) elapsed_time_delta,
       sum(executions_delta) executions_delta,
              PLAN_HASH_VALUE,
              to_char(trunc(end_interval_time),'mm/dd/yy') execution_date
from dba_hist_sqlstat a,
     dba_hist_snapshot b
 where sql_id='19sqmxkc58wqm'
and a.snap_id=b.snap_id
and a.instance_number=b.instance_number
--and executions_delta>0
group by plan_hash_value,to_char(trunc(end_interval_time),'mm/dd/yy')
)
where executions_delta > 0
order by execution_date;
spool off

This script created a file I brought over to my pc and cleaned up the format. Here is part of the file..

AVG_EXECUTION_TIME PLAN_HASH_VALUE execution_date                                     
           20.4368       566875892 01/01/12                                     
           50.3253      4009342004 01/01/12                                     
           21.4655       566875892 01/02/12                                     
           19.8312      4009342004 01/02/12                                     
           69.9299      4009342004 01/03/12                                     
          135.7153      4009342004 01/04/12                                     
           39.3972      4009342004 01/05/12                                     
           65.2833      4009342004 01/06/12                                     
           39.8093      4009342004 01/07/12                                     
           35.8615      4009342004 01/08/12                                     
           18.7553       566875892 01/09/12                                     
          134.7431      4009342004 01/09/12                                     
           76.2954      4009342004 01/10/12                                     
          115.8707      4009342004 01/11/12                                     
           60.0754      4009342004 01/12/12                                     
          102.6432      4009342004 01/13/12                                     
           22.2528       566875892 01/14/12                                     
          119.8541      4009342004 01/14/12                                     
           21.8552       566875892 01/15/12                                     
           18.5785      4009342004 01/15/12                                     
           19.3179       566875892 01/16/12                                     
            80.794      4009342004 01/16/12                                     
           67.0872      4009342004 01/17/12                                     
          107.1604      4009342004 01/18/12                                     
           28.9797      4009342004 01/19/12                                     
          

I put this file into c:\r and named it query_performance .txt.

I then went into R and ran the following commands.

setwd("c:\\r")
query_data <- read.table("query_performance.txt",header=T)


max_num <- max(query_data$AVG_EXECUTION_TIME)

hist(query_data$AVG_EXECUTION_TIME,col=heat.colors(max_num),breaks=max_num,xlim=c(0,max_num),
     right=F,main="Execution Time Histogram",las=1)

You can see I just ran a few simple commands...

setwd --- set the working directory to c:\r
read.table --- read in my space delimitted table (there is a read.csv for a comma separated file)
max_num  --- is set to the maximum execution time in the file

hist   -- creates a histogram of the execution times.. Check out below what comes out. Sweet !!

This was easy, and gives me a great picture of the variance in execution times. 

I am going to work more with this file since it had 2 different plans I want to visual the differences.