Oracle 19C New Feature Availability

trump-exasperatedSince Oracle Open World 2018, Oracle have been trumpetting a few cool new features in the Oracle 19C database, the headline two for administrators being “Automatic Indexing” and “Real-Time Statistics“.

With the release of Oracle 19.2 on Exadata (on-premises – not yet on Cloud!) this week, we also got the documentation released which allow us to answer a very important question: on which platforms will we be able to use these 2 (and other) new awesome features. We may not like the answers – Oracle has decreed that we cannot have them on-premises for SE2, Enterprise Edition or on an ODA.

This is confined purely to Exadata on-prem and the cloud offerings. That’s it. There are no technical reasons why this should be the case – it’s just code – so the restrictions can only be marketing-based (like Hybrid Columnar Compression).

I’m disappointed, but it does mean that the over 80% of Oracle database clients still not living in the cloud should continue to need that aspect of my services!

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Pre-creating Interval Partitions

One of the major problems with interval-based partitioning is the statistics. Partitions appear dynamically as-needed based upon data being inserted or udpated, and any partition magically appearing isn’t going to have any statistics.

This is generally a stability issue as you will, at best, be using dynamic statistics for your optimizations. So how do we deal with it? My preferred method is to pre-create the partitions and copy statistics from a good partition into the pre-created partition. But how do we get the partitions to appear? Here’s 2 options:

  1. Insert data into the row with the partition key for the partition we wish to create, and rollback. This can be tricky, especially with tables containing many NOT NULL columns, and is subject to failure based upon table evolution.
  2. Lock the relevant partition in shared mode using the commandLOCK TABLE .x. PARTITION FOR <partition-key> IN SHARE MODE;

    This will place a shared lock on the non-existant partition, which Oracle will create so it can lock it. A much less messy solution, and not one I had thought of until shown the light by Dan Jankowski.

So does option 2 work? Here’s a quick example:

10:51:55 NEIL @ ORCL01 > CREATE TABLE interval_table (id NUMBER, created_date DATE)
10:51:55   2             PARTITION BY RANGE (created_date) INTERVAL (NUMTOYMINTERVAL(1,'MONTH'))
10:51:55   3           ( PARTITION part_01 values LESS THAN (TO_DATE('01-JAN-2015','DD-MON-YYYY')))
10:51:55   4  /
Table created.

10:51:55 NEIL @ ORCL01 > select table_name, partition_name,high_value from user_tab_partitions order by 1,2;
TABLE_NAME                     PARTITION_NAME                 HIGH_VALUE
------------------------------ ------------------------------ --------------------------------------------------------------------------------
INTERVAL_TABLE                 PART_01                        TO_DATE(' 2015-01-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA


use a shared lock to generate a new partition

10:51:55 NEIL @ ORCL01 > lock table interval_table partition for (to_date('01-JAN-2016','DD-MON-YYYY')) in share mode;
Table(s) Locked.

10:51:55 NEIL @ ORCL01 > select table_name, partition_name,high_value from user_tab_partitions order by 1,2;
TABLE_NAME                     PARTITION_NAME                 HIGH_VALUE
------------------------------ ------------------------------ --------------------------------------------------------------------------------
INTERVAL_TABLE                 PART_01                        TO_DATE(' 2015-01-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA
INTERVAL_TABLE                 SYS_P647                       TO_DATE(' 2016-02-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA

10:51:55 NEIL @ ORCL01 > lock table interval_table partition for (to_date('01-FEB-2016','DD-MON-YYYY')) in share mode;
Table(s) Locked.
10:51:55 NEIL @ ORCL01 > lock table interval_table partition for (to_date('01-MAR-2016','DD-MON-YYYY')) in share mode;
Table(s) Locked.
10:51:55 NEIL @ ORCL01 > lock table interval_table partition for (to_date('01-APR-2016','DD-MON-YYYY')) in share mode;
Table(s) Locked.
10:51:55 NEIL @ ORCL01 > select table_name, partition_name,high_value from user_tab_partitions order by 1,2;
TABLE_NAME                     PARTITION_NAME                 HIGH_VALUE
------------------------------ ------------------------------ --------------------------------------------------------------------------------
INTERVAL_TABLE                 PART_01                        TO_DATE(' 2015-01-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA
INTERVAL_TABLE                 SYS_P647                       TO_DATE(' 2016-02-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA
INTERVAL_TABLE                 SYS_P648                       TO_DATE(' 2016-03-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA
INTERVAL_TABLE                 SYS_P649                       TO_DATE(' 2016-04-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA
INTERVAL_TABLE                 SYS_P650                       TO_DATE(' 2016-05-01 00:00:00', 'SYYYY-MM-DD HH24:MI:SS', 'NLS_CALENDAR=GREGORIA

10:51:55 NEIL @ ORCL01 > -- and release the locks... the rollback doesn't rollback the creation of the new partitions.
10:51:55 NEIL @ ORCL01 > rollback;
Rollback complete.

So now what? To get the stats right I follow the following rule set:

Firstly, lock the table stats when you create the table and have a dedicated, focused stats job. This stop the general stats job from getting in the way of this this important partitioned table.

  • Create a new partition
  • Copy stats using DBMS_STATS.COPY_TABLE_STATS from your fullest partition (with FORCE=TRUE to override the locked stats option). Always try to pretend you have more data than you really have if faking it – it’s safer as an optimized plan with larger expected data sets processing a smaller data set tends to work much better than the stats assuming a small data set and being surprised by lots of data. Consider using SCALE_FACTOR if you have a growing dataset. Don’t reply upon Optimizer magic, such as Adaptive Execution Plans to dig out of a hole.
  • Once a partition becomes “old” (like a no-longer used date-range partition), gather actual stats to get all your stats for that partition accurate. That may even become your new baseline stats copy partition. You will possibly never need to gather stats again for that partition.
  • Be careful if you are copying stats when you have an object-level change. For example, if you put a new index on, you need to re-copy stats post change to any pre-created partitions. Empty pre-created partitions will have accurate (i.e. empty) stats and that’s really not what you want.
  • Repeat as often as you pre-create a new partition
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