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Introducing SQLdb360: merging eDB360 and SQLd360, while rising the bar to community engagement

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Today, we are very happy to release SQLdb360, a new tool that merges together eDB360 and SQLd360, under a single package.

Tools eDB360 and SQLd360 can still be used independently, but now there is only one package to download and keep updated. All the new features and updates to both tools are now in that one package.

The biggest change that comes with SQLdb360 is the kind invitation to everyone interested to contribute to its development. This is why the new blended name and its release format.

We do encourage your help and ideas to continue building a free, open-source, and hopefully a YMMV great tool!

Over the years, a few community members requested new features, but they were ultimately slowed down by our speed of reaction to their requests. Well, no more!

Few consumers of these tools implemented cool changes they needed, sometimes sending us the changes (or pull requests) until a later time. This means good ideas were available to others after some time. Not anymore!

If there is something you’d like to have as part of SQLdb360 (aka SQLd360 and eDB360), just write and test the additional code, then send us the pull request! Next, we will review, validate, and merge your code changes to the main tool.

There are several advantages to this new approach:

  1. Carlos and Mauro won’t dictate the direction of the tool anymore: we will continue helping and contributing, but we won’t “own” it anymore (the community will!)
  2. Carlos and Mauro won’t slow down the development anymore: nobody is the bottleneck now!
  3.  Carlos and Mauro wan’t run out of ideas anymore!!! The community has great ideas to share!!!

Due to the nature of this new collaborative effort, the way we now publish SQLdb360 is this:

  1. Instead of linking to the current master repository, the tool now implements “releases”. This, in order to snapshot stable versions that bundle several changes together (better than creating separate versions per merge into master).
  2. Links in our blogs are now getting updated, with references to the latest (and current) stable release of SQLdb360 (starting with v18.1).

Note: Version names sound awfully familiar to Oracle nomenclature, right? Well, we started using this numbering back in 2014!!!

Carlos & Mauro


Written by Carlos Sierra

June 11, 2018 at 7:00 am

Creating a SQL Plan Baseline from Cursor Cache or AWR

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A DBA deals with performance issues often, and having a SQL suddenly performing poorly is common. What do we do? We proceed to “pin” an execution plan, then investigate root cause (the latter is true if time to next fire permits).

DBMS_SPM provides some APIs to create a SQL Plan Baseline (SPB) from the Cursor Cache, or from a SQL Tuning Set (STS), but not from the Automatic Workload Repository (AWR). For the latter, you need a two-steps approach: create a STS from AWR, then load a SPB from the STS. Fine, except when your next fire is waiting for you, or when deciding which is the “best” plan is not trivial.

Take for example chart below, which depicts multiple execution plans with different performance for one SQL statement. The SQL statement is actually quite simple, and data is not significantly skewed. On this particular application, usually one-size-fits-all (meaning one-and-only-one plan) works well for most values passed on variable place holders. Then, which plan would you choose?

Sample chart created by SQLd360

Looking at summary of known Execution Plans’ performance below (as reported by planx.sql), we can see the same 6 Execution Plans.

1st Plan on list shows an average execution time of 2.897ms according to AWR, and 0.896ms according to Cursor Cache; and number of recorded executions for this Plan are 2,502 and 2,178 respectively. We see this Plan contains one Nested Loop, and if we look at historical performance we notice this Plan takes less than 109ms 95% of the time, less than 115ms 97% of the time, and less then 134ms 99% of the time. We also see that worst recorded AWR period, had this SQL performing in under 150ms (on average for that one period).

We also notice that last plan on list performs one execution in 120.847ms on average (as per AWR) and 181.113ms according to Cursor Cache (on average as well). Then, “pinning” 1st plan on list seems like a good choice, but not too different than all but last plan, specially when we consider both: average performance and historical performance according to percentiles reported.


       Plan ET Avg      ET Avg      CPU Avg     CPU Avg           BG Avg       BG Avg   Executions   Executions                                   ET 100th    ET 99th     ET 97th     ET 95th     CPU 100th   CPU 99th    CPU 97th    CPU 95th
 Hash Value AWR (ms)    MEM (ms)    AWR (ms)    MEM (ms)             AWR          MEM          AWR          MEM   MIN Cost   MAX Cost  NL  HJ  MJ Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)
----------- ----------- ----------- ----------- ----------- ------------ ------------ ------------ ------------ ---------- ---------- --- --- --- ----------- ----------- ----------- ----------- ----------- ----------- ----------- -----------
 4113179674       2.897       0.896       2.715       0.714           96            5        2,502        2,178          8        738   1   0   0     149.841     133.135     114.305     108.411     147.809     133.007     113.042     107.390
  578709260      29.576      32.704      28.865      31.685        1,583        1,436        6,150        1,843         67        875   1   0   0     154.560      84.264      65.409      57.311     148.648      75.209      62.957      56.305
 1990606009      74.399      79.054      73.163      77.186        1,117        1,192          172          214        905      1,108   0   1   0     208.648     208.648      95.877      95.351     205.768     205.768      94.117      93.814
 1242077371      77.961                  77.182                    1,772                     8,780                     949      1,040   0   1   0     102.966      98.206      91.163      89.272     100.147      97.239      90.165      88.412
 2214147219      79.650      82.413      78.242      80.817        1,999        2,143       42,360       24,862        906      1,242   0   1   0     122.535     101.293      98.442      95.737     119.240      99.118      95.266      93.156
 1214505235     120.847     181.113     105.485     162.783          506        1,355           48           12        114        718   1   0   0     285.950     285.950     285.950     285.950     193.954     193.954     193.954     193.954

Plans performance summary above is displayed in a matter of seconds by planx.sql, sqlperf.sql and by a new script spb_create.sql. This output helps make a quick decision about which Execution Plan is better for “pinning”, meaning: to create a SPB on it.

Sometimes such decision is not that trivial, as we can see on sample below. Which plan is better? I would go with 2nd on list. Why? performance-wise this plan is more stable. It does a Hash Join, so I am expecting to see a Plan with full scans, but if I can get consistent executions under 0.4s (according to percentiles), I would be tempted to “pin” this 2nd Plan instead of 1st one. And I would stay away from 3rd and 5th. So maybe I would create a SPB with 3 plans instead of just one, and include on this SPB 1st, 2nd and 4th on the list.


       Plan ET Avg      ET Avg      CPU Avg     CPU Avg           BG Avg       BG Avg   Executions   Executions                                   ET 100th    ET 99th     ET 97th     ET 95th     CPU 100th   CPU 99th    CPU 97th    CPU 95th
 Hash Value AWR (ms)    MEM (ms)    AWR (ms)    MEM (ms)             AWR          MEM          AWR          MEM   MIN Cost   MAX Cost  NL  HJ  MJ Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)   Pctl (ms)
----------- ----------- ----------- ----------- ----------- ------------ ------------ ------------ ------------ ---------- ---------- --- --- --- ----------- ----------- ----------- ----------- ----------- ----------- ----------- -----------
 1917891576       0.467       0.334       0.330       0.172          119           33  554,914,504   57,748,249          6      1,188   2   0   0   6,732.017      10.592       1.628       1.572   1,420.864       1.557       1.482       1.261
   99953997       1.162       2.427       0.655       0.492           83           55   58,890,160    2,225,247         12      2,311   0   1   0     395.819     235.474     108.142      34.909      56.008      22.329      12.926       3.069
 3559532534       1.175   1,741.041       0.858      91.486          359           46   21,739,877          392          4         20   1   0   0  89,523.768   4,014.301     554.740     298.545  21,635.611     216.456      54.050      30.130
 3650324870       2.028      20.788       1.409       2.257          251          199   24,038,404      143,819         11      5,417   0   1   0     726.964     254.245      75.322      20.817     113.259      21.211      13.591       8.486
 3019880278      43.465                  43.029                   20,217                    13,349                   5,693      5,693   0   1   0      43.465      43.465      43.465      43.465      43.029      43.029      43.029      43.029

About new script spb_create.sql

This new script is a life-saver for us, since our response time for an alert is usually measured in minutes, with a resolution (and sometimes a root cause analysis) expected in less than one hour from the time the incident is raised.

This script is quite simple:

  • it provides a list of known Execution Plans including current (Cursor Cache) and historical (AWR) performance as displayed in two samples above, then
  • asks on which Plan Hash Values (PHVs) you want to create a SPB on. It allows you to enter up to 3 PHVs; last
  • asks if you want these plans to be set as FIXED

After you respond to ACCEPT parameters, then a SPB for your SQL is created and displayed. It does not matter if the Plan exists on Cursor Cache and/or on AWR, it finds the Plan and creates the SPB for you. Then: finding known Execution Plans, deciding which one is a better choice (or maybe more than one), and creating a SPB, all can be done very rapidly.

If you still prefer to use SQL Profiles and not SPBs for whatever reason, script coe_xfr_sql_profile.sql is still around and updated. On these 12c days, and soon 18c and beyond, I’d much rather use SQL Plan Management and create SPBs although!

Anyways, enjoy these free scripts and become a faster hero “pinning” good plans. Then don’t forget to do diligent root cause analysis afterwards. I use SQLd360 by Mauro Pagano for deep understanding of what is going on with my SQL statements.

Soon, I will post about a cool free tool that automates the implementation of SQL Plan Management on a high-rate OLTP where stability is more important than flexibility (frequently changing Execution Plans). Stay tuned!

Written by Carlos Sierra

December 1, 2017 at 6:32 am

eDB360 new features (March 2017)

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As many of you know, eDB360 is a free tool that provides a 360-degree view of an Oracle database without any installation. A new version is available like once per month, but occasionally a large number of enhancements are implemented at once. This new release v1708 (March 25, 2017) includes several new features requested recently by some users of the tool, thus the need to blog about what is new:

  1. Reducing the scope of eDB360 is now possible without having to generate a custom configuration file. Prior to this version, if a user wanted to generate output for let’s say AWR reports only (section 7a), the tool needed a custom.sql file with line DEF edb360_sections = ‘7a’;. Then we would pass to edb360.sql as 2nd execution parameter the name of this custom configuration file (too cumbersome!). Starting on v1708, we can directly pass to edb360.sql the section that we desire (i.e. SQL> @edb360 T 7a). This 2nd parameter can either input the name of a custom configuration file (legacy functionality), but now it also accepts a column, a section, a list of columns or a list of sections; for example: 7a, 7, 7a-7b, 1-4 and 3 are all valid values.
  2. A couple of reports were added to section 3h: “SQL in logon storms” and “SQL executed row-by-row”. The former identifies those SQL statements that are seen frequently on very short-lived sessions (based on ASH), and the latter presents a list of SQL statements with large number of executions and small number of rows processed.
  3. eDB360 now extracts ASH from eAdam for top 16 SQL_ID (as per SQLd360 list) + top 12 SNAP_ID (as per AWR MAX from column 7a). What it means is that eDB360 includes now a tar file with raw ASH data for both: SQL statements of interest and for AWR periods of interest (both according to what eDB360 considers important). Using eAdam is easy, so when content of eDB360 does not include a very specific aggregation of ASH data that we need, or when we have to understand the sequence of some ASH samples for example, we can then restore this eAdam data on any Oracle database and data mine it.
  4. Some reports on section 2b show now totals at the bottom. That is to SUM some numeric values. Other reports may follow in future releases.
  5. RMAN section includes now a new report “Blocks with Corruption or Non-logged”.
  6. Added Load Profile (Per Sec, Per Txn and Count) as per DBA_HIST_SYSMETRIC_SUMMARY. This Load Profile resembles what we see on AWR at the top, but this is computed for the entire period of diagnostics (31 days by default). It shows max values, average, median and several percentiles. With this new report on section 1a, we can glance over it and discover in minutes some areas of further interest, for example: logons per second too high, just to mention one.
  7. There is a new section 4i with “Waits Count v.s. Average Latency for top 24 Wait Events”. With this set of 24 reports (one for each of the top wait events) we can observe if patterns on the number of counts relate to patterns on the latency for such wait event; for example we are able to see if an increase in the number of waits for db file sequential reads correlates to an increase of average latency for such wait event. We can also observe cases were latency for a wait event cannot be explained by load on current database, thus hinting an external influence.
  8. Fixed “ORA-01476: divisor is equal to zero” on planx at DBA_HIST_SQLSTAT.
  9. Added AWR DIFF reports for RAC and per instance. These are computed comparing MAX reports to MEDIAN reports, and they help to quickly identify large differences on load. These new AWR DIFF reports are regulated by configuration parameter edb360_conf_incl_addm_rpt (enabled by default). They exist on 11R2 and higher.
  10. Added the ASH Analytics Active report for 12c. This new ASH report is regulated by configuration parameter edb360_conf_incl_ash_analy_rpt (enabled by default). This applies to 12c and higher.
  11. The name of the database is now part of the main filename. Some users requested to include this database name as part of the main zip file since they are using eDB360 periodically on several databases. This new feature is regulated by configuration parameter edb360_conf_incl_dbname_file (disabled by default).
  12. At completion, main eDB360 zip file can now by automatically moved to a location other than the standard SQL*Plus working directory. All output files are still generated on the local SQL*Plus directory from where the script edb360.sql is executed (i.e. edb360-master directory), but at the completion of the execution the consolidated output zip file is now moved to a location specified by a new parameter. This new feature is regulated by configuration parameter edb360_move_directory (disabled by default).
  13. Added new report on “Database and Schema Triggers” under column 3h. This new report can be used to see potential LOGON or other global triggers. For triggers on specific tables, refer to SQLd360 which is automatically included on eDB360 for top SQL.
  14. All queries executed by eDB360 to generate its output were modified. New format is q'[query]’. Reason for this change is to improve readability of the code.

Always download and use the latest version of this tool. For questions or feedback email me. And I hope you get to enjoy eDB360 as much as I do!

Written by Carlos Sierra

March 25, 2017 at 6:51 pm

SQL Monitoring without MONITOR Hint

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I recently got this question:

<<<Is there a way that I can generate SQL MONITORING report for a particular SQL_ID ( This SQL is generated from application code so I can’t add “MONITOR”  hint) from command prompt ? If yes can you please help me through this ?>>>

Since this question is of general interest, I’d rather respond here:

As you know, SQL Monitoring starts automatically on a SQL that executes a PX plan, or when its Serial execution has consumed over 5 seconds on CPU or I/O.

If you want to force SQL Monitoring on a SQL statement, without modifying the SQL text itself, I suggest you create a SQL Patch for it. But before you do, please be aware that SQL Monitoring requires the Oracle Tuning Pack.

How to turn on SQL Monitoring for a SQL that executes Serial, takes less than 5 seconds, and without modifying the application that issues such SQL

Use SQL Patch with the MONITOR Hint. An easy way to do that is by using the free sqlpch.sql script provided as part of the cscripts (see right-hand side of this blog under Downloads).

To use sqlpch.sql script, pass as parameter #1 your SQL_ID and for parameter #2 pass “GATHER_PLAN_STATISTICS MONITOR” (without the double quotes).

This sqlpch.sql script will create a SQL Patch for your SQL, which will produce SQL Monitoring (and the collection of A-Rows) for every execution of your SQL.

Be aware there is some overhead involved, so after you are done with your analysis drop the SQL Patch.

Script sqlpch.sql shows the name of the SQL Patch it creates (look at its spool file), and it gives you the command to drop such SQL Patch.

For the actual analysis and diagnostics of your SQL (after you have executed it with SQL Patch in place) use free tool SQLd360.

And for more details about sqlpch.sql and other uses of this script please refer to this entry on my blog.

Written by Carlos Sierra

February 29, 2016 at 10:16 am

SQLT and SQLd360 interview and one-day class on Practical SQL Tuning announcement

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With permission of the Northern California Oracle Users Group (NoCOUG) I am reproducing a warm interview on SQLTXPLAIN and SQLd360. During this interview Mauro Pagano and myself talk about the history behind these two free tools and how the former has evolved into the latter. You can find the full transcript of the interview here: YesSQL(T). If you want to read the entire free online NoCOUG Journal, you will discover other cool articles.

Anyways, I am glad Iggy Fernandez invited us to participate first on this interview, and second to collaborate on the meeting planned for January. On that meeting Mauro and I will conduct a one full day workshop on “Practical SQL Tuning” (January 28) in Northern California. We hope to see many of you guys there, and please bring questions and case studies.


Written by Carlos Sierra

November 6, 2015 at 9:42 am