ORA-22905 when calling ODCI Table functions from PL/SQL

Back in 2015 I experimented using ODCITable* functions to dynamically parse delimited text (see blog post here.)

Now blog reader Daniel Cabanillas points out, that it raises an error when used in PL/SQL. Silly me - I had only tried it out in SQL (my favorite language) and had completely missed that it failed in PL/SQL.

Lucky for me, the classic workaround of dynamic SQL works here too 😁


Look in the old blog (more...)

Securing Oracle scripts with a wallet

It’s that time of year when I try to clean up some of my bad habits from the year before. This time, it’s plain-text passwords in SQL scripts. Here’s a way to make them a little more secure. You can move all your passwords into a secure wallet file stored on your PC. This is not the most secure option available (and you should keep the wallet in a private location) but it is better (more...)

Splitting strings before they’re CLOBs!

After I tokenized two CLOBs in response to a forum question, Andy Sayer mentioned that they were probably files first. So I smacked my forehead and used external tables.

Splitting strings when they are CLOBs

Like many of you, I have enjoyed using SQL to make data processing go hundreds of times faster. My new record is: 7000 times faster :-)

Top-N again: fetch first N rows only vs rownum

Three interesting myths about rowlimiting clause vs rownum have recently been posted on our Russian forum:

  1. TopN query with rownum<=N is always faster than "fetch first N rows only" (ie. row_number()over(order by ...)<=N)
  2. “fetch first N rows only” is always faster than rownum<=N
  3. “SORT ORDER BY STOPKEY” stores just N top records during sorting, while “WINDOW SORT PUSHED RANK” sorts all input and stores all records sorted in memory.

Interestingly that after Vyacheslav posted first statement as an axiom and someone posted old tests(from 2009) and few people made own tests which showed that “fetch first N rows” is about 2-3 times faster than the query with rownum, the final decision was that “fetch first” is always faster.

First of all I want to show that statement #3 is wrong and “WINDOW SORT PUSHED RANK” with row_number works similarly as “SORT ORDER BY STOPKEY”:
It’s pretty easy to show using sort trace:
Let’s create simple small table Tests1 with 1000 rows where A is in range 1-1000 (just 1 block):

create table test1(a not null, b) as
  select level, level from dual connect by level<=1000;

alter session set max_dump_file_size=unlimited;
ALTER SESSION SET EVENTS '10032 trace name context forever, level 10';

ALTER SESSION SET tracefile_identifier = 'rownum';
select * from (select * from test1 order by a) where rownum<=10;

ALTER SESSION SET tracefile_identifier = 'rownumber';
select * from test1 order by a fetch first 10 rows only;

And we can see from the trace files that both queries did the same number of comparisons:

rownum:
----- Current SQL Statement for this session (sql_id=bbg66rcbt76zt) -----
select * from (select * from test1 order by a) where rownum<=10

---- Sort Statistics ------------------------------
Input records                             1000
Output records                            10
Total number of comparisons performed     999
  Comparisons performed by in-memory sort 999
Total amount of memory used               2048
Uses version 1 sort
---- End of Sort Statistics -----------------------

[collapse]
row_number

----- Current SQL Statement for this session (sql_id=duuy4bvaz3d0q) -----
select * from test1 order by a fetch first 10 rows only

---- Sort Statistics ------------------------------
Input records                             1000
Output records                            10
Total number of comparisons performed     999
  Comparisons performed by in-memory sort 999
Total amount of memory used               2048
Uses version 1 sort
---- End of Sort Statistics -----------------------

[collapse]

Ie. each row (except first one) was compared with the biggest value from top 10 values and since they were bigger than top 10 value, oracle doesn’t compare it with other TopN values.

And if we change the order of rows in the table both of these queries will do the same number of comparisons again:

from 999 to 0

create table test1(a not null, b) as
  select 1000-level, level from dual connect by level<=1000;

alter session set max_dump_file_size=unlimited;
ALTER SESSION SET EVENTS '10032 trace name context forever, level 10';

ALTER SESSION SET tracefile_identifier = 'rownum';
select * from (select * from test1 order by a) where rownum<=10;


ALTER SESSION SET tracefile_identifier = 'rownumber';
select * from test1 order by a fetch first 10 rows only;

[collapse]
rownum

----- Current SQL Statement for this session (sql_id=bbg66rcbt76zt) -----
select * from (select * from test1 order by a) where rownum<=10

---- Sort Statistics ------------------------------
Input records                             1000
Output records                            1000
Total number of comparisons performed     4976
  Comparisons performed by in-memory sort 4976
Total amount of memory used               2048
Uses version 1 sort
---- End of Sort Statistics -----------------------

[collapse]
row_number

----- Current SQL Statement for this session (sql_id=duuy4bvaz3d0q) -----
select * from test1 order by a fetch first 10 rows only

---- Sort Statistics ------------------------------
Input records                             1000
Output records                            1000
Total number of comparisons performed     4976
  Comparisons performed by in-memory sort 4976
Total amount of memory used               2048
Uses version 1 sort
---- End of Sort Statistics -----------------------

[collapse]

We can see that both queries required much more comparisons(4976) here, that’s because each new value is smaller than the biggest value from the topN and even smaller than lowest value, so oracle should get right position for it and it requires 5 comparisons for that (it compares with 10th value, then with 6th, 3rd, 2nd and 1st values from top10). Obviously it makes less comparisons for the first 10 rows.

Now let’s talk about statements #1 and #2:
We know that rownum forces optimizer_mode to switch to “first K rows”, because of the parameter “_optimizer_rownum_pred_based_fkr”

SQL> @param_ rownum

NAME                               VALUE  DEFLT  TYPE      DESCRIPTION
---------------------------------- ------ ------ --------- ------------------------------------------------------
_optimizer_rownum_bind_default     10     TRUE   number    Default value to use for rownum bind
_optimizer_rownum_pred_based_fkr   TRUE   TRUE   boolean   enable the use of first K rows due to rownum predicate
_px_rownum_pd                      TRUE   TRUE   boolean   turn off/on parallel rownum pushdown optimization

while fetch first/row_number doesn’t (it will be changed after the patch #22174392) and it leads to the following consequences:
1. first_rows disables serial direct reads optimization, that’s why the tests with big tables showed that “fetch first” were much faster than the query with rownum.
So if we set “_serial_direct_read”=always, we get the same performance in both tests (within the margin of error).

2. In cases when index access (index full scan/index range scan) is better, CBO differently calculates the cardinality of underlying INDEX FULL(range) SCAN:
the query with rownum is optimized for first_k_rows and the cardinality of index access is equal to K rows, but CBO doesn’t reduce cardinality for “fetch first”, so the cost of index access is much higher, compare them:

rownum
SQL> explain plan for
  2  select *
  3  from (select * from test order by a,b)
  4  where rownum<=10;

--------------------------------------------------------------------------------------------
| Id  | Operation                     | Name       | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT              |            |    10 |   390 |     4   (0)| 00:00:01 |
|*  1 |  COUNT STOPKEY                |            |       |       |            |          |
|   2 |   VIEW                        |            |    10 |   390 |     4   (0)| 00:00:01 |
|   3 |    TABLE ACCESS BY INDEX ROWID| TEST       |  1000K|    12M|     4   (0)| 00:00:01 |
|   4 |     INDEX FULL SCAN           | IX_TEST_AB |    10 |       |     3   (0)| 00:00:01 |
--------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter(ROWNUM<=10)

[collapse]
fetch first

SQL> explain plan for
  2  select *
  3  from test
  4  order by a,b
  5  fetch first 10 rows only;

-----------------------------------------------------------------------------------------
| Id  | Operation                | Name | Rows  | Bytes |TempSpc| Cost (%CPU)| Time     |
-----------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT         |      |    10 |   780 |       |  5438   (1)| 00:00:01 |
|*  1 |  VIEW                    |      |    10 |   780 |       |  5438   (1)| 00:00:01 |
|*  2 |   WINDOW SORT PUSHED RANK|      |  1000K|    12M|    22M|  5438   (1)| 00:00:01 |
|   3 |    TABLE ACCESS FULL     | TEST |  1000K|    12M|       |   690   (1)| 00:00:01 |
-----------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter("from$_subquery$_002"."rowlimit_$$_rownumber"<=10)
   2 - filter(ROW_NUMBER() OVER ( ORDER BY "TEST"."A","TEST"."B")<=10)

[collapse]
fetch first + first_rows

SQL> explain plan for
  2  select/*+ first_rows */ *
  3  from test
  4  order by a,b
  5  fetch first 10 rows only;

--------------------------------------------------------------------------------------------
| Id  | Operation                     | Name       | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT              |            |    10 |   780 | 27376   (1)| 00:00:02 |
|*  1 |  VIEW                         |            |    10 |   780 | 27376   (1)| 00:00:02 |
|*  2 |   WINDOW NOSORT STOPKEY       |            |  1000K|    12M| 27376   (1)| 00:00:02 |
|   3 |    TABLE ACCESS BY INDEX ROWID| TEST       |  1000K|    12M| 27376   (1)| 00:00:02 |
|   4 |     INDEX FULL SCAN           | IX_TEST_AB |  1000K|       |  2637   (1)| 00:00:01 |
--------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter("from$_subquery$_002"."rowlimit_$$_rownumber"<=10)
   2 - filter(ROW_NUMBER() OVER ( ORDER BY "TEST"."A","TEST"."B")<=10)

[collapse]
fetch first + index

SQL> explain plan for
  2  select/*+ index(test (a,b)) */ *
  3  from test
  4  order by a,b
  5  fetch first 10 rows only;

--------------------------------------------------------------------------------------------
| Id  | Operation                     | Name       | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT              |            |    10 |   780 | 27376   (1)| 00:00:02 |
|*  1 |  VIEW                         |            |    10 |   780 | 27376   (1)| 00:00:02 |
|*  2 |   WINDOW NOSORT STOPKEY       |            |  1000K|    12M| 27376   (1)| 00:00:02 |
|   3 |    TABLE ACCESS BY INDEX ROWID| TEST       |  1000K|    12M| 27376   (1)| 00:00:02 |
|   4 |     INDEX FULL SCAN           | IX_TEST_AB |  1000K|       |  2637   (1)| 00:00:01 |
--------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter("from$_subquery$_002"."rowlimit_$$_rownumber"<=10)
   2 - filter(ROW_NUMBER() OVER ( ORDER BY "TEST"."A","TEST"."B")<=10)

[collapse]

So in this case we can add hints “first_rows” or “index”, or install the patch #22174392.

ps. I thought to post this note later, since I hadn’t time enough to add other interesting details about the different TopN variants, including “with tie”, rank(), etc, so I’ll post another note with more details later.

Another day…another “use the right datatype” post

Here’s an interesting little oddity (aka bug) with scalar queries.

We’ll start with a simple working example


SQL> create table t1 ( c1 number );

Table created.

SQL> insert into t1 values (1);

1 row created.

SQL> create table t2 ( c1 int, c2 varchar2(10));

Table created.

SQL>
SQL> insert into t2 values(1,'t1');

1 row created.

SQL> insert into t2 values(1,'t01');

1 row created.

SQL> commit;

Commit complete.

SQL> exec dbms_stats.gather_table_stats('','T1')

PL/SQL procedure successfully  (more...)

Querying the amount of redo in Oracle Database

When a database starts to churn more redo then normal, it is handy to be able to extract the amount of redo over time, to be able to plot this in a graph.  The below allows you to extract this info 🙂

Query for redo generation

Query to obtain the amount of redo generation over time by hour and MB:

set pages 999 lines 400
select to_char(trunc(first_time, 'HH24'), 'DD/MM/YYYY HH24:MI:SS') date_by_hour, sum(round(blocks*block_size/1024/1024)) CHURN_IN_MB
from v$archived_log
 (more...)

Polymorphic Table Functions – Part 2

In my previous post I wrote about a possible use-case for Polymorphic Table Functions. I also wrote that I had some ideas to implement extra functionality to make the function more generic.
After attending DOAG Konferentz und ausstellung 2018 and UKOUG Tech18 I finally came around to publishing my new version.
Lets start off with a table to hold my data, I chose to use the NATO phonetic alphabet for this:

create table t_alphabet
(thecount  (more...)

Ranges with NULLs 07: Swiss Army Knife

I came up with this name a few years ago for a problem that I couldn't solve then: analyse a series of ranges and say whether and how they overlap. It turns out the solution is not that hard.

Lab Correction

Anyone using the August 2018 Fedora image should note that I neglected to put the right transaction_upload2.csv file in the /u01/app/oracle/upload directory. You can fix that by navigating to the Lab 12 Instructions web page and click on the zip file link to download the correct file. You will see the following dialog asking whether you want to open the file with the Ark utility, click OK to continue:

After clicking OK to open (more...)

Ranges with NULLs 06: Overlaps with Conflicting Data

In 2014 I attacked the problem of "Overlapping ranges with priorities". This time I'll deal with NULLs and propose an improved solution.

Ranges with NULLs 05: Segments

Take two overlapping ranges: "1 to 3" and "2 to 4". We can divide them into three smaller ranges: "1 to 2", "2 to 3" and "3 to 4". I'll call these smaller ranges segments. We sometimes need these segments to solve advanced range problems.

Logging Triggers

Oracle Logging Trigger Results

This article demonstrates how you can write log files from triggers on different tables to the same logging table. This approach leverages Oracle’s object types and column substitutability features. It also eliminates the requirement to create a unique logging table for each logging trigger. The trick to accomplishing this requires mastering two skills.

The first skill requires you to learn how to create user-defined types (UDTs) and subtypes. The UDT stores (more...)

Critical Triggers

Oracle Critical and Non-critical Triggers

This article demonstrates how you can write critical and non-critical row-level triggers. You may ask yourself, what are critical and non-critical triggers? That’s a great question. A critical trigger stops processing and raises an exception within the scope of an Application Programming Interface (API). An API is typically a series of end-user forms that help you solve business problems. A non-critical trigger either allows users to perform undesired behavior or (more...)

Oracle Trigger Basics

Oracle Trigger Basics

Once you master the basics of inserting, updating, and deleting data from the database, you typically learn about database triggers. Database triggers are coding elements that let you manage events beyond the limit of database constraints.

Before you can appreciate the power of database triggers, you need to understand what database constraints can and can’t do. Then, together we’ll explore how you can implement database triggers.
Database constraints let you manage events. (more...)

Types & Column Substitutability

Object Types and Column Substitutability

This article shows you how to use extend parent (or superclass) objects. You extend parent classes when you implement specialized behaviors (or methods) in subtypes. That’s because SQL statements can’t work with specialized methods when a table’s column stores subclasses in a superclass column type.

Substitutability is the process of storing subtypes in a super type column. It is a powerful feature of the Oracle database. The “type evolution” feature (more...)

Types & Subtypes

Object Types and Subtypes

This article teaches you how to use subtypes or subclasses. You can define an object type with or without dependencies. Object types can have two types of dependencies. The simplest case occurs when you define an object attribute with an object type instead of a data type. The more complex case occurs when you define an object subtype because it inherits the behavior of the base object type. The base object (more...)

Type Getters & Setters

Object Types with Getters and Setters

This article is for you when you know the basics about how you work Oracle’s object types. It teaches you how to write effective getters, setters, comparators, and static methods. Please read my Object Types & Bodies Basic article if you’re not sure how to work with object types.

Getters access an object instance and return values from an instance variable. Along with getters, you have setters. Setters let (more...)

Building a Conference Session Recommendation engine using Neo4J Graph Database

This article describes a use case for which a traditional SQL-powered relational database approach can provide a solution – but for which that traditional approach is not the optimal solution. SQL is jack of all trades – you can make it do almost anything you need. And therefore it is easy to become your hammer and every challenge a nail. This article is if anything meant to open my and maybe your eyes to the (more...)

Polymorphic Table Functions

I have been working on a presentation on Polymorphic Table Functions. During this time I was looking for a real use case for Polymorphic Table Functions. I came up with an example which is not very useful in real life, but very useful to explain the technique.
At my current job I came across a piece of code that I had to copy and adjust to fit the needs for that specific case. The idea (more...)