Carlos Sierra's Tools and Tips

Tools and Tips for Oracle Performance and SQL Tuning

Archive for the ‘AWR’ Category

Scripts to deal with SQL Plan Baselines, SQL Profiles and SQL Patches

with 3 comments

To mitigate SQL performance issues, I do make use of SQL Plan Baselines, SQL Profiles and SQL Patches, on a daily basis. Our environments are single-instance 12.1.0.2 CDBs, with over 2,000 PDBs. Our goal is Execution Plan Stability and consistent performance, over CBO plan flexibility. The CBO does a good job, considering the complexity imposed by current applications design. Nevertheless, some SQL require some help in order to enhance their plan stability.

I have written and shared a set of scripts that simply make the use of a bunch of APIs a lot easier, with better documented actions, and fully consistent within the organization. I have shared with the community these scripts in the past, and I keep them updated as per needs change. All these “CS” scripts are available under the download section on the right column.

Current version of the CS scripts is more like a toolset. You treat them as a whole. All of them call some other script that exists within the cs_internal subdirectory, then I usually navigate to the parent sql directory, and connect into SQL*Plus from there. All these scripts can be easily cloned and/or customized to your specific needs. They are available as “free to use” and “as is”. There is no requirement to keep their heading intact, so you can reverse-engineer them and make them your own if you want. Just keep in mind that I maintain, enhance, and extend this CS toolset every single day; so what you get today is a subset of what you will get tomorrow. If you think an enhancement you need (or a fix) is beneficial to the larger community (and to you), please let me know.

SQL Plan Baselines scripts

With the set of SQL Plan Baselines scripts, you can: 1) create a baseline based on a cursor or a plan stored into AWR; 2) enable and disable baselines; 3) drop baselines; 4) store them into a local staging table; 5) restore them from their local staging table; 6) promote as “fixed” or demote from “fixed”; 7) “zap” them if you have installed “El Zapper” (iod_spm).

Note: “El Zapper” is a PL/SQL package that extends the functionality of SQL Plan Management by automagically creating SQL Plan Baselines based on proven performance of a SQL statement over time, while considering a large number of executions, and a variety of historical plans. Please do not confuse “El Zapper” with auto-evolve of SPM. They are based on two very distinct premises. “El Zapper” also monitors the performance of active SQL Plan Baselines, and during an observation window it may disable a SQL Plan Baseline, if such plan no longer performs as “promised” (according to some thresholds). Most applications do not need “El Zapper”, since the use of SQL Plan Management should be more of an exception than a rule.

SQL Profiles scripts

With the set of SQL Profiles scripts, you can: 1) create a profile based on the outline of a cursor, or from a plan stored into AWR; 2) enable and disable profiles; 3) drop profiles; 4) store them into a local staging table; 5) restore them from their local staging table; 6) transfer them from one location to another (very similar to coe_xfr_sql_profile.sql, but on a more modular way).

Note: Regarding the transfer of a SQL Profile, the concept is simple: 1) on source location generate two plain text scripts, one that contains the SQL text, and a second that includes the Execution Plan (outline); 2) execute these two scripts on a target location, in order to create a SQL Profile there. The beauty of this method is not only that you can easily move Execution Plans between locations, but that you can actually create a SQL Profile getting the SQL Text from SQL_ID “A”, and the Execution Plan from SQL_ID “B”, allowing you to do things like: removing CBO Hints, or using a plan from a similar SQL but not quite the same (e.g. I can tweak a stand-alone cloned version of a SQL statement, and once I get the plan that I need, I associate the SQL Text from the original SQL, with the desired Execution Plan out of the stand-alone customized version of the SQL, after that I create a SQL Plan Baseline and drop the staging SQL Profile).

SQL Patches scripts

With the set of SQL Patches scripts, you can: 1) create a SQL patch based on one or more CBO Hints you provide (e.g.: GATHER_PLAN_STATISTICS MONITOR FIRST_ROWS(1) OPT_PARAM(‘_fix_control’ ‘5922070:OFF’) NO_BIND_AWARE); 2) enable and disable SQL patches; 3) drop SQL patches; 4) store them into a local staging table; 5) restore them from their local staging table.

Note: I use SQL Patches a lot, specially to embed CBO Hints that generate some desirable diagnostics details (and not so much to change plans), such as the ones provided by GATHER_PLAN_STATISTICS and MONITOR. In some cases, after I use the pathfinder tool written by Mauro Pagano, I have to disable a CBO patch (funny thing: I use a SQL Patch to disable a CBO Patch!). I also use a SQL Patch if I need to enable Adaptive Cursor Sharing (ACS) for one SQL (we disabled ACS for one major application). Bear in mind that SQL Plan Baselines, SQL Profiles and SQL Patches happily co-exist, so you can use them together, but I do prefer to use SQL Plan Baselines alone, whenever possible.

Advertisements

Written by Carlos Sierra

December 15, 2018 at 5:57 am

Creating a SQL Plan Baseline from Cursor Cache or AWR

with 21 comments

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

Note: please get all scripts using the download column on the right

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.

PLANS PERFORMANCE
~~~~~~~~~~~~~~~~~

       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.

PLANS PERFORMANCE
~~~~~~~~~~~~~~~~~

       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

Update: Scripts to deal with SQL Plan Baselines, SQL Profiles and SQL Patches

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!

Note: please get all scripts using the download column on the right

Written by Carlos Sierra

December 1, 2017 at 6:32 am

eDB360 meets eAdam 3.0 – when two heads are better than one!

with one comment

Version v1711 of eDB360 invites eAdam 3.0 to the party. What does it mean? We recently learned that eDB360 v1706 introduced the eDB360 repository, which materialized the content of 26 core DBA_HIST views into a staging repository made of heap tables. This in order to expedite the execution of eDB360 on a database with an enlarged AWR. New version v1711 expands the list from 26 views to a total of 219. And these 219 views include now DBA_HIST, DBA, GV$ and V$.

Expanding existing eDB360 repository 8.4x from 26 to 219 views is not what is key on version v1710. The real impact of the latest version of eDB360 is that now it benefits of eAdam 3.0, providing the same benefits of the 219 views of the eDB360 heap-tables repository, but using External Tables, which are easily transported from a source database to a target database. This simple fact opens many doors.

Using the eAdam 3.0 repository from eDB360, we can now extract the metadata from a production database, then restore it on a staging database where we can produce the eDB360 report for the source database. We could also use this new external repository for: finer-granularity data mining; capacity planning; sizing for potential hardware refresh; provisioning tools; to estimate candidate segments for partitioning or for offloading into Hadoop; etc.

With the new external-tables eAdam 3.0 repository, we could easily build a permanent larger heap-table permanent repository for multiple databases (multiple tenants), or for multiple time versions of the same database. Thus, now that eDB360 has met eAdam 3.0, the combination of these two enables multiple innovative future features (custom or to be packaged and shipped with eDB360).

eDB360 recap

eDB360 is a free tool that gives a 360-degree view of an Oracle database. It installs nothing on the database, and it runs on 10g to 12c Oracle databases. It is designed for Linux and UNIX, but runs well on Windows as well (you may want to install first UNIX Utilities UnxUtils and a zip program, else a few OS commands may not properly work on Windows). This repository-less version is the default way to use eDB360, and is the right method for most cases. But now, in addition to the default use, eDB360 can also make use of one of two repositories.

eDB360 takes time to execute (several hours). It is designed to time-out after 24 hours by default. First reason for long execution times is the intentional serial-processing method used, with sequential execution of query after query, while consuming little resources. Such serial execution, plus the fact that it is common to have the tool execute on large databases where the state of AWR is suboptimal, causes the execution to take long.  We often discover that source AWR repositories lack expected partitioning, and in many cases they hold years of data instead of expected 8 to 31 days. Therefore, the nature of serial-execution combined with enlarged and suboptimal AWR repositories, usually cause eDB360 to execute for many hours more than expected. With 8 to 31 days of AWR data, and when such reasonable history is well partitioned, eDB360 usually executes in less than 6 hours.

To overcome the undesired extended execution times of eDB360, and besides the obvious (partition and purge AWR), the tool provides the capability to execute in multiple threads splitting its content by column. And now, in addition to the divide-and-conquer approach of column execution, eDB360 provides 2 repositories with different objectives in mind:

  1. eDB360 repository: Use this method to create a staging repository based on heap tables inside the source database. This method helps to expedite the execution of eDB360 by at least 10x. Repository heap-tables are created and consumed inside the same database.
  2. eAdam3 repository: Use this method to generate a repository based on external tables on the source database. Such external-tables repository can be moved easily to a remote target system, allowing to efficiently generate the eDB360 report there. This method helps to reduce computations in the source database, and enables potential data mining on the external repository without any resources impact on the source database. This method also helps to build other functions on top of the 219-tables repository.

Views included on both eDB360 and eAdam3 repositories:

  1. dba_2pc_neighbors
  2. dba_2pc_pending
  3. dba_all_tables
  4. dba_audit_mgmt_config_params
  5. dba_autotask_client
  6. dba_autotask_client_history
  7. dba_cons_columns
  8. dba_constraints
  9. dba_data_files
  10. dba_db_links
  11. dba_extents
  12. dba_external_tables
  13. dba_feature_usage_statistics
  14. dba_free_space
  15. dba_high_water_mark_statistics
  16. dba_hist_active_sess_history
  17. dba_hist_database_instance
  18. dba_hist_event_histogram
  19. dba_hist_ic_client_stats
  20. dba_hist_ic_device_stats
  21. dba_hist_interconnect_pings
  22. dba_hist_memory_resize_ops
  23. dba_hist_memory_target_advice
  24. dba_hist_osstat
  25. dba_hist_parameter
  26. dba_hist_pgastat
  27. dba_hist_resource_limit
  28. dba_hist_seg_stat
  29. dba_hist_service_name
  30. dba_hist_sga
  31. dba_hist_sgastat
  32. dba_hist_snapshot
  33. dba_hist_sql_plan
  34. dba_hist_sqlstat
  35. dba_hist_sqltext
  36. dba_hist_sys_time_model
  37. dba_hist_sysmetric_history
  38. dba_hist_sysmetric_summary
  39. dba_hist_sysstat
  40. dba_hist_system_event
  41. dba_hist_tbspc_space_usage
  42. dba_hist_wr_control
  43. dba_ind_columns
  44. dba_ind_partitions
  45. dba_ind_statistics
  46. dba_ind_subpartitions
  47. dba_indexes
  48. dba_jobs
  49. dba_jobs_running
  50. dba_lob_partitions
  51. dba_lob_subpartitions
  52. dba_lobs
  53. dba_obj_audit_opts
  54. dba_objects
  55. dba_pdbs
  56. dba_priv_audit_opts
  57. dba_procedures
  58. dba_profiles
  59. dba_recyclebin
  60. dba_registry
  61. dba_registry_hierarchy
  62. dba_registry_history
  63. dba_registry_sqlpatch
  64. dba_role_privs
  65. dba_roles
  66. dba_rsrc_consumer_group_privs
  67. dba_rsrc_consumer_groups
  68. dba_rsrc_group_mappings
  69. dba_rsrc_io_calibrate
  70. dba_rsrc_mapping_priority
  71. dba_rsrc_plan_directives
  72. dba_rsrc_plans
  73. dba_scheduler_job_log
  74. dba_scheduler_jobs
  75. dba_scheduler_windows
  76. dba_scheduler_wingroup_members
  77. dba_segments
  78. dba_sequences
  79. dba_source
  80. dba_sql_patches
  81. dba_sql_plan_baselines
  82. dba_sql_plan_dir_objects
  83. dba_sql_plan_directives
  84. dba_sql_profiles
  85. dba_stat_extensions
  86. dba_stmt_audit_opts
  87. dba_synonyms
  88. dba_sys_privs
  89. dba_tab_cols
  90. dba_tab_columns
  91. dba_tab_modifications
  92. dba_tab_partitions
  93. dba_tab_privs
  94. dba_tab_statistics
  95. dba_tab_subpartitions
  96. dba_tables
  97. dba_tablespace_groups
  98. dba_tablespaces
  99. dba_temp_files
  100. dba_triggers
  101. dba_ts_quotas
  102. dba_unused_col_tabs
  103. dba_users
  104. dba_views
  105. gv$active_session_history
  106. gv$archive_dest
  107. gv$archived_log
  108. gv$asm_disk_iostat
  109. gv$database
  110. gv$dataguard_status
  111. gv$event_name
  112. gv$eventmetric
  113. gv$instance
  114. gv$instance_recovery
  115. gv$latch
  116. gv$license
  117. gv$managed_standby
  118. gv$memory_current_resize_ops
  119. gv$memory_dynamic_components
  120. gv$memory_resize_ops
  121. gv$memory_target_advice
  122. gv$open_cursor
  123. gv$osstat
  124. gv$parameter
  125. gv$pga_target_advice
  126. gv$pgastat
  127. gv$pq_slave
  128. gv$pq_sysstat
  129. gv$process
  130. gv$process_memory
  131. gv$px_buffer_advice
  132. gv$px_process
  133. gv$px_process_sysstat
  134. gv$px_session
  135. gv$px_sesstat
  136. gv$resource_limit
  137. gv$result_cache_memory
  138. gv$result_cache_statistics
  139. gv$rsrc_cons_group_history
  140. gv$rsrc_consumer_group
  141. gv$rsrc_plan
  142. gv$rsrc_plan_history
  143. gv$rsrc_session_info
  144. gv$rsrcmgrmetric
  145. gv$rsrcmgrmetric_history
  146. gv$segstat
  147. gv$services
  148. gv$session
  149. gv$session_blockers
  150. gv$session_wait
  151. gv$sga
  152. gv$sga_target_advice
  153. gv$sgainfo
  154. gv$sgastat
  155. gv$sql
  156. gv$sql_monitor
  157. gv$sql_plan
  158. gv$sql_shared_cursor
  159. gv$sql_workarea_histogram
  160. gv$sysmetric
  161. gv$sysmetric_summary
  162. gv$sysstat
  163. gv$system_parameter2
  164. gv$system_wait_class
  165. gv$temp_extent_pool
  166. gv$undostat
  167. gv$waitclassmetric
  168. gv$waitstat
  169. v$archive_dest_status
  170. v$archived_log
  171. v$ash_info
  172. v$asm_attribute
  173. v$asm_client
  174. v$asm_disk
  175. v$asm_disk_stat
  176. v$asm_diskgroup
  177. v$asm_diskgroup_stat
  178. v$asm_file
  179. v$asm_template
  180. v$backup
  181. v$backup_set_details
  182. v$block_change_tracking
  183. v$cell_config
  184. v$cell_state
  185. v$controlfile
  186. v$database
  187. v$database_block_corruption
  188. v$datafile
  189. v$flashback_database_log
  190. v$flashback_database_stat
  191. v$instance
  192. v$io_outlier
  193. v$iostat_file
  194. v$kernel_io_outlier
  195. v$lgwrio_outlier
  196. v$log
  197. v$log_history
  198. v$logfile
  199. v$mystat
  200. v$nonlogged_block
  201. v$option
  202. v$parallel_degree_limit_mth
  203. v$parameter
  204. v$pdbs
  205. v$recovery_area_usage
  206. v$recovery_file_dest
  207. v$restore_point
  208. v$rman_backup_job_details
  209. v$rman_output
  210. v$segstat
  211. v$spparameter
  212. v$standby_log
  213. v$sys_time_model
  214. v$sysaux_occupants
  215. v$system_parameter2
  216. v$tablespace
  217. v$tempfile
  218. v$thread
  219. v$version

Instructions to use eDB360 and eAdam3 repositories

Both repositories are implemented under the edb360-master/repo subdirectory. Each has a readme file, which explains how to create the repository, consume it and drop it. The eAdam3 repository also includes instructions how to clone an external-table-based eAdam repository into a heap-table-based eDB360 repository.

Executing eDB360 on the eDB360 repository is faster than executing it on the eAdam3 repository, while avoiding new bug 25802477. This new Oracle database bug inflicts compressed external-tables like the ones used by the eAdam3 repository.

If you use eDB360 or eAdam3 repositories and have questions or concerns, do not hesitate to contact the author.

 

Written by Carlos Sierra

April 10, 2017 at 2:41 pm

eDB360 new features (March 2017)

with 2 comments

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

eDB360 includes now an optional staging repository

with 6 comments

eDB360 has always worked under the premise “no installation required”, and still is the case today – it is part of its fundamental essence: give me a 360-degree view of my Oracle database with no installation whatsoever. With that in mind, this free tool helps sites that have gone to the cloud, as well as those with “on-premises” databases; and in both cases not installing anything certainly expedites diagnostics collections. With eDB360, you simply connect to SQL*Plus with an account that can select from the catalog, execute then a set of scripts behind eDB360 and bingo!, you get to understand what is going on with your database just by navigating the html output. With such functionality, we can remotely diagnose a database, and even elaborate on the full health-check of it. After all, that is how we successfully use it every day!, saving us hundreds of hours of metadata gathering and cross-reference analysis.

Starting with release v1706, eDB360 also supports an optional staging repository of the 26 AWR views listed below. Why? the answer is simple: improved performance! This can be quite significant on large databases with hundreds of active sessions, with frequent snapshots, or with a long history on AWR. We have seen cases where years of data are “stuck” on AWR, specially in older releases of the database. Of course cleaning up the outdated AWR history (and corresponding statistics) is highly recommended, but in the meantime trying to execute edb360 on such databases may lead to long execution hours and frustration, taking sometimes days for what should take only a few hours.

  1. dba_hist_active_sess_history
  2. dba_hist_database_instance
  3. dba_hist_event_histogram
  4. dba_hist_ic_client_stats
  5. dba_hist_ic_device_stats
  6. dba_hist_interconnect_pings
  7. dba_hist_memory_resize_ops
  8. dba_hist_memory_target_advice
  9. dba_hist_osstat
  10. dba_hist_parameter
  11. dba_hist_pgastat
  12. dba_hist_resource_limit
  13. dba_hist_service_name
  14. dba_hist_sga
  15. dba_hist_sgastat
  16. dba_hist_sql_plan
  17. dba_hist_sqlstat
  18. dba_hist_sqltext
  19. dba_hist_sys_time_model
  20. dba_hist_sysmetric_history
  21. dba_hist_sysmetric_summary
  22. dba_hist_sysstat
  23. dba_hist_system_event
  24. dba_hist_tbspc_space_usage
  25. dba_hist_wr_control
  26. dba_hist_snapshot

Thus, if you are contemplating executing eDB360 on a large database, and provided pre-check script edb360-master/sql/awr_ash_pre_check.sql shows that eDB360 might take over 24 hours, then while you clean up your AWR repository you can use the eDB360 staging repository as a workaround to speedup eDB360 execution. The use of this optional staging repository is very simple, just look inside the edb360-master/repo directory for instructions. And as always, shoot me an email or comment here if there were any questions.

Written by Carlos Sierra

February 19, 2017 at 8:43 pm

edb360 taking a long time

with 2 comments

In most cases edb360 takes less than 1hr to execute. But I often hear of cases where it takes a lot longer than that. In a corner case it was taking several days and it had to be killed.

So the question is WHY edb360 takes that long?

Well, edb360 executes thousands of SQL statements sequentially (intentionally). Many of these queries read data from AWR and in particular from ASH. So, lets say your ASH historical table has 2B rows, and on top of that you have not gathered statistics on AWR tables in years, thus CBO under-estimates cardinality and tends to use index access and nested loops. In such extreme cases you may end up with suboptimal execution plans that expect to return a few rows, but actually read a couple of billion rows using index access operations and nested loops. A query like this may take hours to complete!

As of version v1515, edb360 has a shortcut algorithm that ends an execution after 8 hours. So you may get an incomplete output, but it ends normally and the partial output can actually be used. This is not a solution but a workaround for those long executions.

How to troubleshoot edb360 taking long?

Steps:

1. Review files 00002_edb360_dbname_log.txt, 00003_edb360_dbname_log2.txt, 00004_edb360_dbname_log3.txt and 00005_edb360_dbname_tkprof_sort.txt. First log shows the state of the statistics for AWR Tables. If stats are old then gather them fresh with script edb360/sql/gather_stats_wr_sys.sql

2. If number of rows on WRH$_ACTIVE_SESSION_HISTORY as per 00002_edb360_dbname_log.txt is several millions, then you may not be purging data periodically. There are some known bugs and some blog posts on this regard. Review MOS 387914.1 and proceed accordingly. Execute query below to validate ASH age:

SELECT TRUNC(sample_time, 'MM'), COUNT(*)
  FROM dba_hist_active_sess_history
 GROUP BY TRUNC(sample_time, 'MM')
 ORDER BY TRUNC(sample_time, 'MM')
 /

3. If edb360 version (first line on its readme) is older than 1 month, download and use latest version: https://github.com/carlos-sierra/edb360/archive/master.zip (link is also provided on the right-hand side of this blog under downloads).

4. Consider suppressing text and or csv reports. Each for an estimated gain of about 20%. Keep in mind that when suppressing reports, you start loosing some functionality. To suppress lets say text and csv reports, place the following two commands at the end of script edb360/sql/edb360_00_config.sql

DEF edb360_conf_incl_text = ‘N’;
DEF edb360_conf_incl_csv = ‘N’;

5. If after going through steps 1-4 above, edb360 still takes longer than a few hours, feel free to email author carlos.sierra.usa@gmail.com and provide 4 files from step 1.

Written by Carlos Sierra

May 6, 2015 at 8:19 pm

Discovering if a System level Parameter has changed its value (and when it happened)

with 4 comments

Quite often I learn of a system where “nobody changed anything” and suddenly the system is experiencing some strange behavior. Then after diligent investigation it turns out someone changed a little parameter at the System level, but somehow disregarded mentioning it since he/she thought it had no connection to the unexpected behavior.  As we all know, System parameters are big knobs that we don’t change lightly, still we often see “unknown” changes like the one described.

Script below produces a list of changes to System parameter values, indicating when a parameter was changed and from which value into which value. It does not filter out cache re-sizing operations, or resource manager plan changes. Both would be easy to exclude, but I’d rather see those global changes listed as well.

Note: This script below should only be executed if your site has a license for the Oracle Diagnostics pack (or Tuning pack), since it reads from AWR.

WITH
all_parameters AS (
SELECT snap_id,
       dbid,
       instance_number,
       parameter_name,
       value,
       isdefault,
       ismodified,
       lag(value) OVER (PARTITION BY dbid, instance_number, parameter_hash ORDER BY snap_id) prior_value
  FROM dba_hist_parameter
)
SELECT TO_CHAR(s.begin_interval_time, 'YYYY-MM-DD HH24:MI') begin_time,
       TO_CHAR(s.end_interval_time, 'YYYY-MM-DD HH24:MI') end_time,
       p.snap_id,
       p.dbid,
       p.instance_number,
       p.parameter_name,
       p.value,
       p.isdefault,
       p.ismodified,
       p.prior_value
  FROM all_parameters p,
       dba_hist_snapshot s
 WHERE p.value != p.prior_value
   AND s.snap_id = p.snap_id
   AND s.dbid = p.dbid
   AND s.instance_number = p.instance_number
 ORDER BY
       s.begin_interval_time DESC,
       p.dbid,
       p.instance_number,
       p.parameter_name
/

Sample output follows, where we can see a parameter affecting Degree of Parallelism was changed. This is just to illustrate its use. Enjoy this new free script! It is now part of edb360.
Screen Shot 2015-03-25 at 19.15.26

Written by Carlos Sierra

March 25, 2015 at 7:25 pm