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Oracle database internals

IOUG Collaborate 2017

I have a few presentations scheduled in IOUG Collaborate 2017, Las Vegas.

1. Session: 621: RAC Clusterware internals
**Date/time: Mon, Apr 03, 2017 (01:30 PM – 02:30 PM) : Jasmine A

2. Session: RAC cache fusion internals. ( OakTable track )
**Date/time: Wed, Apr 05, 2017 (09:45 AM – 10:45 AM) Room: South Seas C

3. Session: 479: An in-depth review of ASM and internals
**Date/time: Wed, Apr 05, 2017 (02:45 PM – 03:45 PM) : Palm B

Presentation files ( Updated after the presentations).

Thank you for coming to my presentation(s).

RMOUG Training days 2017

I will be speaking about the following topics in Rocky Mountain Oracle User group Training days (RMOUG, Denver) February 7-9, 2017.

Come to my presentations and say Hi to me </p />

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CPU profiling using perf utility in Linux

After reading my blog entry about a performance issue due to excessive HCC decompression ( Accessing HCC compressed objects using index access path, a reader asked me about the CPU profiling method I mentioned in that blog entry. I started responding to that comment, and realized that the response was too big for a comment. So, in this blog entry, I will cover basics of the CPU profiling in Linux. Other platform provides similar utilities, for example, Solaris provides an utility dtrace.

Tool Box

Accessing HCC compressed objects using an index


I came across another strange SQL performance issue: Problem was that a SQL statement was running for about 3+ hours in an User Acceptance (UA) database, compared to 1 hour in a development database. I ruled out usual culprits such as statistics, degree of parallelism etc. Reviewing the SQL Monitor output posted below, you can see that the SQL statement has already done 6 Billion buffer gets and steps 21 through 27 were executed 3 Billion times so far.

Statistics and execution plan

library cache lock on BUILD$ object

I was testing an application performance in 12c, and one job was constantly running slower than 11g. This post is to detail the steps. I hope the steps would be useful if you encounter similar issue.


In an one hour period, over 90% of the DB time spent on waiting for library cache lock waits. Upon investigation, one statement was suffering from excessive waits for ‘library cache lock’ event. We recreated the problem and investigated it further to understand the issue.

Following is the output of wait_details_rac.sql script (that I will upload here) and there are many PX query servers are waiting for ‘library cache lock’ wait event.

OOUG RAC day presentation files and scripts

Thanks for coming to my presentations in RAC day at Dublin, Ohio. Please find the presentation files below. Hopefully, I will get video files and upload that here too.

OOUG presentation files and scripts

md5 checksum of the zip file is:


RAC day with Ohio Oracle User Group

I will be talking about RAC and performance in-depth, with lots of demos, in a RAC day training with Ohio Oracle User group on Nov 16,2015 Monday. Venue for the presentation is Dublin, Ohio.

Agenda for the day:

08:00a – 09:00: Registration / Breakfast

09:00a – 09:15: Announcements -Introduction of the speaker

09:15a – 10:30: Underpinning for Oracle RAC and Clusterware

10:30a – 10:45: Break

10:45a – 11:45: RAC cache fusion internals

11:45a – 01:00: Lunch

01:00p – 02:00: RAC Performance tuning Part 1 – Wait events and object tuning

02:00p – 02:15: Break

02:15p – 03:30: RAC performance tuning Part 2 – locks, library cache locks etc.

03:30p – 03:45: Member Announcements, Gift Drawings

Please RSVP to the co-ordinators so that you will have a seat </p />

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IOUG Collaborate 2015

I will be presenting two topics in IOUG Collaborate 2015 in Vegas. Use the show planner and add my presentations to your schedule </p />

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In-memory pre-population speed

While presenting at Oaktable World 2014 in San Fransisco, I discussed the in-memory pre-population speed and indicated that it takes about 30 minutes to 1 hour to load ~300GB of tables. Someone asked me “Why?” and that was a fair question. So, I profiled the in-memory pre-population at startup.

Profiling methods

I profiled all in-memory worker sessions using Tanel’s snapper script and also profiled the processes in OS using Linux perf tool with 99Hz sample rate. As there is no other activity in the database server, it is okay to sample everything in the server. Snapper output will indicate where the time is spent; if the time is spent executing in CPU, then the perf report output will tell us the function call stack executing at that CPU cycle. Data from these two profiling methods will help us to understand the root cause of slowness.

Inmemory: Not all inmemory_size is usable to store tables.

I have been testing the inmemory column store product extensively and the product is performing well for our workload. However, I learnt a bit more about inmemory column store and I will be blogging a few them here. BTW, I will be talking about internals of inmemory in Oaktable world presentation, if you are in the open world 2014, you can come and see my talk: