A few facts about TimesTen

  • TimesTen gets usually deployed in the Middle Tier – same location where the application runs
  • TimesTen is persistent and can run as the only database on a system
  • TimesTen persists to the disk over a background process
  • TimesTen supports High Availability
  • TimesTen can be used as cache between the application and the Oracle database
  • TimesTen can be linked into applications directly – the calls to TimesTen happens over normal subroutine calls in the code which require no context switches on the system
  • You can cache either a group of related tables or even a subset of specific rows
  • TimesTen supports read-only and update able caches
  • TimesTen supports “DynamicLoad” which loads the data from Oracle when you need it
  • You can have as much read-only subscribers as you want
  • TimesTen supports SQL and PL/SQL
  • TimesTen is certified on all main application servers and OR-Mapping tools like Hibernate

The big picture

A couple of weeks ago a customer had some troubles with the overall performance. He complained that everything is slow and (of course) nothing changed since the last few weeks. They also immediately blamed the database on their side to be the issue. The usual stuff also, I’m sure that sounds just too familiar to you.

So as they “identified” the database already as being the issue my team requested some AWR reports and as we got them I noticed a strange but all to common behavior. My team mates got the AWR reports, went to the SQL Statistics, sections “SQL ordered by Elapsed Time” and “SQL ordered by CPU Time” and identified immediately a materialized view rebuild as cause for the problem. That looked like this:

SQL ordered by Elapsed Time

  • Resources reported for PL/SQL code includes the resources used by all SQL statements called by the code.
  • % Total DB Time is the Elapsed Time of the SQL statement divided into the Total Database Time multiplied by 100
Elapsed Time (s) CPU Time (s) Executions Elap per Exec (s) % Total DB Time SQL Id SQL Module SQL Text
1,343 679 1 1342.85 33.00 f20ccnxhvbk65 DECLARE job BINARY_INTEGER := …
770 323 1 770.24 18.93 1usnr4gmcq60d /* MV_REFRESH (DEL) */ delete …
571 355 1 571.23 14.04 gz04689vd55db /* MV_REFRESH (INS) */INSERT /…
311 311 1 310.91 7.64 0vhmfumrjchnh SQL*Plus BEGIN dm_incr_symbols_post_pro…
288 9 0 7.09 bb3f2gjndvjss oracle@crptd1 (TNS V1-V3) SELECT /*+ OPAQUE_TRANSFORM */…
258 258 1 257.76 6.34 75vtwb7j4jzdm SQL*Plus INSERT INTO SYMB_EXTRACTT SELE…
149 121 1 148.80 3.66 90wtn50vy6af6 DECLARE job BINARY_INTEGER := …
114 103 1 113.75 2.80 9993mp6h7kqkp INSERT /*+ BYPASS_RECURSIVE_CH…
48 38 2 24.00 1.18 3nkcg1h5ysqss DECLARE job BINARY_INTEGER := …
48 38 2 23.98 1.18 fvb5prrr7b0c3 MERGE INTO FT_E_UPS1 UPS1 USIN…

Back to SQL Statistics
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SQL ordered by CPU Time

  • Resources reported for PL/SQL code includes the resources used by all SQL statements called by the code.
  • % Total DB Time is the Elapsed Time of the SQL statement divided into the Total Database Time multiplied by 100
CPU Time (s) Elapsed Time (s) Executions CPU per Exec (s) % Total DB Time SQL Id SQL Module SQL Text
679 1,343 1 679.06 33.00 f20ccnxhvbk65 DECLARE job BINARY_INTEGER := …
355 571 1 355.50 14.04 gz04689vd55db /* MV_REFRESH (INS) */INSERT /…
323 770 1 323.18 18.93 1usnr4gmcq60d /* MV_REFRESH (DEL) */ delete …
311 311 1 310.89 7.64 0vhmfumrjchnh SQL*Plus BEGIN dm_incr_symbols_post_pro…
258 258 1 257.74 6.34 75vtwb7j4jzdm SQL*Plus INSERT INTO SYMB_EXTRACTT SELE…
121 149 1 121.05 3.66 90wtn50vy6af6 DECLARE job BINARY_INTEGER := …
103 114 1 102.58 2.80 9993mp6h7kqkp INSERT /*+ BYPASS_RECURSIVE_CH…
38 48 2 19.20 1.18 3nkcg1h5ysqss DECLARE job BINARY_INTEGER := …
38 48 2 19.20 1.18 fvb5prrr7b0c3 MERGE INTO FT_E_UPS1 UPS1 USIN…
29 29 12 2.38 0.70 68930z34bm3db SQL*Plus select ‘file[‘ || substr(trim(…
9 288 0 7.09 bb3f2gjndvjss oracle@dftg1 (TNS V1-V3) SELECT /*+ OPAQUE_TRANSFORM */…

So here we have a PL/SQL job which does the materialized view refresh (first line) and the statements for the refresh itself as second and third line. For completeness here the first statement:

 job BINARY_INTEGER := :job;
 next_date DATE := :mydate;
 broken BOOLEAN := FALSE;
 :mydate := next_date;
 IF broken THEN
 :b := 1;
 :b := 0;

So all what they did was to go there, look the first SQL with high elapsed and cpu time and nearly reported back to them that this is the problem and they have to solve this. I call this the “lucky shot method”. Sometimes when you are lucky than the reason for the issue on the DB is a bad SQL or a bunch of bad SQLs which max out the DB on CPU power, or I/O or whatever. In such a case you just go to those sections, identify the SQLs, fix them and everything is good again – you were lucky. This works sometimes and you are a hero because it took you just 5 minutes for fixing the issue but sometimes it doesn’t and you blame it on some weird constellation of OS, network and something else so that nobody recognizes that you are just a fool and didn’t look at the big picture. Thinking of that I noticed that this is just far too common in IT. Tech admins, DBA, developers – in every section you have people like this. Looking 5 minutes into the issue and telling you then that this and that is the issue. You go ahead and fix them but still no change. So next round trip, and next, and next, and next. All could have been prevented if the person had just once a look into the big picture…

So what is the big picture, what do I mean by that?

I’m a fan of knowing what happens and why. Always analyze all the information you got, even request some more if you think that some vital information is missing and make your conclusions out of that. Stop the try and error method, the lucky shot method. The AWR report I got from the customer is an all too good example. There were 2 simple lines which made me curious:

Snap Id Snap Time Sessions Cursors/Session
Begin Snap: 17934 05-May-10 09:00:59 129 144.1
End Snap: 17935 05-May-10 10:00:12 130 143.0
Elapsed: 59.21 (mins)
DB Time: 67.81 (mins)

I’m talking about the last two. The first tells me that the snapshot which got compared are in a time range of 59.21 minutes. The DB time, so the time when the DB was actually working was 67.81 minutes. So something looks strange here. If I would be in a single core environment I wouldn’t be over my 59.21. If I would be in a dual-core environment then the database was just working 57% of the time (59.21 x 2 cores = 118.42 – DB time multiplies by the amount of cores where work was performed parallel). Next I had a look into the locks going on. If you have high locking then the DB time is also idle but the throughput is low. But it turned that this was also no issue. The next information confirmed then that the DB wasn’t the problem at all:

Operating System Statistics

Statistic Total

The average idle time statistic is much higher than the busy time. So I requested the amount of cores on that system and it turned out that there are 14 available. A busy database would have a DB time of max. 828.94 minutes. No locking going on. I followed up with them and it turned out as I thought: The database wasn’t the problem at all. In fact it was pretty much idle over the whole time. The issue was on the application side. A java application which memory got filled up so that it had to do full garbage collection all the time to continue processing.

Instead of doing the lucky shot we prevented us and them from a lot of headache by looking into the big picture.

Bitmap indexes and cardinality

In my last two posts I talked a little bit about bitmap indexes, how they work and why they lock. I also mentioned that they should be used for low cardinality but that there is no cut-and-dried answer about what low cardinality is. I’m not starting here to talk about cardinality on bitmap indexes, actually Richard Foote did a much better job on that so if you interested in that check out the following blog posts from him:

Oracle Seminar

Last Wednesday I had the chance to visit an Oracle seminar at the Marriot hotel in New York City. I was really happy since it was already a long time ago when I last visited an Oracle event (except the Oracle User Group Meeting but that’s not Oracle itself). There were four tracks to join: Database developer, .NET developer, Java developer and APEX developer. All of them sounded interesting but as you had to bring your own laptop and install a specific image for each track I had to decide for one. Well it wasn’t to hard for me and I took the Database developer track with Hands-On on SQL Developer, SQL Developer Data Modeler, TimesTen and last but not least XML database. I have to say, that I was really excited about the sessions. I use SQL Developer and the Data Modeler part already quite a long time so there wasn’t much new for me but still something to learn (there is always something to learn!) The TimesTen and the XML database part was totally new to me and I was surprised what Oracle can already do with all the other products the own. Funniest thing was that I won a book of SQL Developer 2.1 which is brand-new and still wet from the press! ūüėČ This was because I was the first who finished all SQL Developer related hands-on – I wasn’t aware that I can win a prize for this, but hey, a book is always good! ūüôā

So the best things out of this seminar were:

  • SQL Developer can debug PL/SQL (not really new)
  • SQL Developer can build, maintain and execute Unit tests for PL/SQL
  • SQL Developer can connect to TimesTen since 1.6
  • SQL Developer has a new Query Executor which makes executing stuff against different databases much more flexible
  • TimesTen is really fast if you use it right (made selfwritten tests on my laptop bringing me 8.6 times more performance)

Well at the end here it’s time for some pics:

And here the prize I won:

SQL CASE expression

How often have you been in a situation where you wanted to do an IF/ELSE in a SQL query. How often have you then written “SELECT … DECODE (expression, value, return, value, return, default return) FROM….” or even worse and selected the values and did then an IF/ELSE in PL/SQL?

The good thing in Oracle is that you can do a really IF/ELSE in the SQL query using the CASE expression. The documentation says following:

CASE expressions let you use IFTHENELSE logic in SQL statements without having to invoke procedures. The syntax is:

CASE { simple_case_expression
     | searched_case_expression
     [ else_clause ]

Ok here first a short example of the “simple_case_expression”:

2            CASE salery
3¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬† WHEN 1000 THEN ‘Low’
4¬†¬†¬†¬† ¬† ¬† ¬† ¬† ¬† ¬† WHEN 2000 THEN ‘Medium’
5¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬† WHEN 3000 THEN ‘Medium’
6¬†¬†¬† ¬† ¬† ¬† ¬† ¬† ¬†¬† ELSE ‘High’
7           END
8           FROM employee;

NAME                      CASESA
————————- ——
John                      Low
Andreas               Medium
Harry                    Medium
Mike                      High

So here you can see a simple IF/ELSIF/ELSE based on a column value. But what if you have some more complex logic like comparing two values with and AND. Well also that works in the “searched_case_expression”:

SQL> select name,
2             CASE
3¬†¬†¬†¬† ¬† ¬† ¬† ¬† ¬† ¬† WHEN salery = 1000 THEN ‘Low’
4¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬†¬† WHEN salery = 2000 OR salery = 3000 THEN ‘Medium’
5¬†¬†¬† ¬† ¬† ¬† ¬† ¬† ¬†¬† ELSE ‘High’
6             END
7             FROM employee;

NAME                      CASEWH
————————- ——
John                        Low
Andreas                 Medium
Harry                      Medium
Mike                         High

Here you can see that I’m using¬† an OR clause like in the ELSIF. That also works with bind variables of course!

So this should help you in future when you have a select and you think of DECODE or PL/SQL IF/ELSE!