online

If you have performed some sort of data cleanup or similar on a table, then the deleted space will be reused by future insertions. But if

• that cleanup was the last task you were performing on that table, ie, you were not expecting a lot of new data to ever come in again, or
• you are performing a lot of full scan queries on that table and you want to make sure they are as efficient as possible

then there may be benefits to performing a shrink on that table to reclaim that space. One of the cool things about the segment advisor is that it will detect if there are some benefits to be gained by shrinking a segment. Here’s an example of that. I create a large table and then delete every 2nd row.

Just a quick post here by request of an attendee of the September Office Hours. I had a demo converting the data type of a primary key without losing data and with minimal impact to the availability of the database using DBMS_REDEFINITION.  You can see that video here

but here is the script used to run that demo. 

As you can tell, I have no idea on a name for what I am about to describe. So let me start from the beginning, and set the scene for an idea I have to utilize a cool new 18c feature.

Often in a transactional-style system the busiest table (let us call it SALES for the sake of this discussion) is also

• the biggest table, after all, it has all of our sales in it,
• the most demanded for table, in that, almost every query in our application wants to access it in some way shape or form.

This is in effect the database version of the Pareto Principle. Everyone wants a slice of that SALES “pie”, and the piece of that pie that is in most demand is typically the most recent data. Your application may have pages that will be showing:

Want to test some DDL, a query, check an execution plan? You need only a browser. And you can copy-paste, or simply link, your test-case in a forum, a tweet, an e-mail, a tweet. Here is a small list (expecting to grow from your comments) of free online services which can run with an Oracle Database: SQL Fiddle, Rextester, db<>fiddle and Oracle Live SQL

SQL Fiddle

SQL Fiddle let you build a schema and run DDL on the following databases:

• Oracle 11gR2
• Microsoft SQL Server 2014
• MySQL 5.6
• Postgres 9.6 and 9.3
• SQLLite (WebSQL and SQL.js)

As an Oracle user, the Oracle 11gR2 is not very useful as it is a version from 2010. But there’s a simple reason for that: that’s the latest free version – the Oracle XE Edition. And a free online service can run only free software. Now that Oracle plans to release an XE version every year, this should be better soon.

It doesn’t take a rocket scientist to know that even if you have incredibly stringent controls on user authentication, user authorisation etc, that wont save you if your data on disk is not encrypted.  All you need is an errant tape, a missing disk, a misplaced flash stick…and kersplat, someone has a copy of your datafiles from your Oracle database.

Data at rest should be encrypted, but that often meant taking applications offline to do so.

I’ve put my Speed Racer hat on and here’s a video on a new 12c Release 2 feature covered in 60 seconds !

The ability to move datafiles as an online operation is bloody awesome! It’s another one of those cool little things that you will wonder how you ever lived without. I can’t wait to move to 12c just for this feature. I could clean up so much crap so easily. Here’s a little write-up on it.

• Online Move Datafile in Oracle Database 12c Release 1 (12.1)

I’ve also amended this article to mention this new feature and link to the article.

• Renaming or Moving Oracle Files

Cheers

Tim…

The other day I was posed with an interesting problem regarding the refresh of the materialized views. First, a little background. MVs are nothing new in Oracle; they have been around since Oracle 7 (called snapshots then). Essentially they are similar to tables (as they actually store data) but populated by running a query on some source tables. This query is the defining query of the MV. So, the user can select from the MV instead of executing the defining query – reducing the execution time significantly.

However, the MV and the query would both give the same result if the source tables have not changed. If the data has changed, the MV will not have known about it and will give a stale result. Therefore, you need to refresh the MV from time to time. Usually the MVs are refreshed by the following method:

begin
dbms_mview.refresh(‘’);
end;

So, what’s the problem? The problem is, during complete refreshes, the MV remains unavailable to the users. This duration of refresh depends on the size of the MV, the execution time of the underlying query and so on; and the unavailability is a nuisance for most applications. In some cases the applications are designed to timeout after some wait; and they do so quite consistently in this case – making it more than just a nuisance.

So, I was asked to devise a solution to make the MVs available during the complete refreshes. I accomplished that with a not-so-common use of partitions. Here is how I did it.

Prebuilt Table

First, as an architectural standard, I advocate the use of prebuilt tables in MVs. Here is how an MV is usually created:

create materialized view mv_bookings_01
refresh complete on demand
enable query rewrite
as
select hotel_id, sum(book_txn) tot_txn
from bookings
group by hotel_id
/

This creates the segment mv_bookings_01 during this process. Instead of this approach, I recommend first creating and populating a regular table and then converting that to an MV. In this revised approach, you would first create the table:

create table mv_bookings_01
as
select HOTEL_ID, sum(book_txn) tot_txn
from bookings
group by HOTEL_ID
/

Then, you would create the MV using the prebuilt table option:

create materialized view mv_bookings_01
on prebuilt table
refresh complete on demand
enable query rewrite
as
select HOTEL_ID, sum(book_txn) tot_txn
from bookings
group by HOTEL_ID
/

This does not do anything to the functionality of the MV itself. The MV feels, looks and smells like it was before; but with two significant advantages:

(1) You can easily alter the columns
(2) You can manipulate the table

I blogged about it at http://arup.blogspot.com/2009/01/ultra-fast-mv-alteration-using-prebuilt.html. Anyway, back to the issue at hand. Using the prebuilt trick, I can create a partitioned MV as well. In this specific case, I will add a column to partition on. Remember, this column does not actually participate in the application; it simply creates an anchor point for the partition.

create table mv_bookings_01
(
ref_type number,
hotel_id number(3),
tot_txn number
)
partition by list (ref_type)
(
partition p0 values (0),
partition p1 values (1)
)
/

After the table is created, I can insert data into it:

insert /*+ append */ into mv_bookings_01
select 0, hotel_id, sum(book_txn) tot_txn
from bookings
group by 0, hotel_id
/

Of course I could have selected the data from the source tables directly while creating the prebuilt table; but I just wanted to show a different approach of data loading. The column REF_TYPE is not part of the application; but I have added it to divide the table along a value by list partitioning. The column can hold only two values – 0 and 1, and hence the table has only two partitions.

Once the table is created, I can use the prebuilt table option to create the MV as shown above. However, the presence of the new column makes it a little different. My MV creation script now looks like this:

create materialized view mv_bookings_01
on prebuilt table
enable query rewrite
as
select 0 as ref_type, HOTEL_ID, sum(book_txn) tot_txn
from bookings
group by 0, HOTEL_ID
/

Note that I have used “0 as ref_type” in the select clause, i.e. the ref_type will always be 0. This is not going to a problem as you can see later. When the MV is first created, the value of ref_type is 0; hence the partition p0 is the one is that is populated; not the partition p1. We can confirm that:

SQL> select count(1) from mv_bookings_01 partition (p0);

COUNT(1)
----------
2

SQL> select count(1) from mv_bookings_01 partition (p1);

COUNT(1)
----------
0

Now that the partitions are in place, let’s see how we refresh this MV. We will no longer use the dbms_mview approach. Rather, we will use this:

(1) Create a temporary table
(2) Create all the indexes
(3) Exchange the partition that is not used with this temporary table

Step 1: Temporary table

First we create a temporary table that is identical to the prebuilt table of the MV in structure; but just not partitioned. We will use the value of ref_type column as 0 or 1 based on the value already in the table, in fact exactly opposite of what is in the table. Since we have 0 in the table, we will use 1 in the temporary table. This temporary table will contain the data that we need refreshed as.

create table tmp1
as
select 1 as ref_type, hotel_id, sum(book_txn) tot_txn
from bookings
group by 1, hotel_id
/

We also need to create another temporary table with no data.

create table tmp0
(
ref_type number,
hotel_id number(3),
tot_txn number
)
/

Step 2: Create Indexes

In this case we don’t have any indexes on the MV; but if we had, we would have created them here on the TMP0 and TMP1 tables.

Step 3: Exchange Partitions

When the temporary table is ready, we can exchange the inactive partition with this.

alter table mv_bookings_01
exchange partition p1
with table tmp1
including indexes
without validation
update global indexes
/
alter table mv_bookings_01
exchange partition p0
with table tmp0
including indexes
without validation
update global indexes
/

This SQL performs a switch: the segment that was called partition P1 in the table mv_bookings_01 is now called TMP1 and former segment TMP1 is now called partition P1 in the table mv_bookings_01. This occurs at the data dictionary level; no actual data is ever transferred from one segment to the other. As a result this is very quick. A lock is required on the table only for that instance is such an insignificant amount of time that it may not be even noticeable. Similarly the segment used to be called P0 partition is now known as TMP0 table and TMP0 is called P0.

There are several key things to note here. Note the clause “without validation”, which tells Oracle not to bother checking inside the TMP0 table that it will confirm to the partition specification. This is critical for the performance. Since we built the table with “1” as a hardcoded value, we know that the REF_TYPE column will definitely contain 1, satisfying the partition requirement for P1. A further checking is not required.

The “including indexes” clause switched the local index partitions as well. If there is a global index on the MV’s prebuilt table, that would have been invalidated and needed rebuilding afterwards. But, we avoided that invalidation by using a “update global indexes” clause in the alter statement.

Once the switchover is complete, we can check the MV to see if the data has been visible.

SQL> select count(1) from mv_bookings_01 partition (p0)
2 /

COUNT(1)
----------
0

SQL> select count(1) from mv_bookings_01 partition (p1)
2 /

COUNT(1)
----------
2

This completes the refreshing of the MV and the data is visible to end users. Let’s see the timeline

(1) Building of temporary table
(2) Building of indexes on the temporary table
(3) Exchange partitions

Steps 1 and 2 take most of the time; but that is done offline, without affecting the MV itself. So, long time there does not affect the availability of the MV itself. The step 3 is where the availability is impacted; but that is miniscule.

The table TMP0 now has the rows from partition P0 of the MV. To confirm that:

SQL> select count(1) from tmp0;

COUNT(1)
----------
2

You can drop the table by “drop table tmp0 purge”. You should also drop TMP1 since that table will contain the previous contents of the partition P1, which is useless now.

The next time this MV needs refreshing, you have to repeat the process; but with a very important distinction – the partition P0 needs exchange now. I used a script that checks the value of REF_TYPE in the MV now and use the other value passed to an SQL script with a positional parameter that accepts 0 or 1. Using this approach you can refresh a MV very quickly.

Oracle 11g Variation

In Oracle 11g, there is a new feature – Virtual Column. You can define a column as virtual in the table, which is not actually stored in the table; but calculated during runtime. What’s more, this virtual column can also be used as a partition key. You can define the REF_TYPE as a virtual column in that case.

Takeaways

(1) Just because there is an Materialized View, it does not have to be refreshed by the usual approach, i.e. dbms_mview.refresh. There are other options as well.
(2) Partitioning is not just for performance or purge reasons; it can be used in clever ways such as MV refreshes.
(3) In this specific case, we didn’t have a column that could have been used as a partitioning key; so we had to resort to adding a column. In many cases, the table may already have a column for that purpose, making the process even simpler.