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12cR1

Temp Table Transformation Cardinality Estimates - 2

Continuing from the previous part - which was about the Temp Table Transformation and join cardinality estimates - using the same simple table setup here is a slight variation of the previously used query to demonstrate the potential impact on single table cardinality estimates:


explain plan for
with
cte as (
select /* inline */ id from t1 t
where 1 = 1
)
select /*+
no_merge(a) no_merge(b)
*/ * from cte a, cte b
where a.id = b.id
and a.id > 990 and b.id > 990
;

-- 11.2.0.x Plan with TEMP transformation
--------------------------------------------------------------------------------

Temp Table Transformation Cardinality Estimates - 1

Having published recently two notes about the Temp Table Transformation highlighting the heuristics based decision and other weaknesses, for example regarding the projection of columns, it's time to publish some more notes about it.The transformation can also have significant impact on cardinality estimates, both join and single table cardinality.Looking at the difference in the join cardinality estimates of following simple example:


create table t1
as
select
rownum as id
, mod(rownum, 10) + 1 as id2
, rpad('x', 100) as filler
from
dual
connect by
level <= 1000
;

Heuristic Temp Table Transformation - 2

Some time ago I've demonstrated the non-cost based decision for applying the temp table transformation when using CTEs (Common Table/Subquery Expressions). In this note I want to highlight another aspect of this behaviour.Consider the following data creating a table with delibrately wide columns:


create table a
as
select
rownum as id
, rownum as id2
, rpad('x', 4000) as large_vc1
, rpad('x', 4000) as large_vc2
, rpad('x', 4000) as large_vc3
from
dual
connect by
level <= 1000
;

exec dbms_stats.gather_table_stats(null, 'a')

Enabling Edition Based Redefinition On A Schema With Object-Relational Tables

This is just a heads-up for those thinking about using Edition Based Redefinition (EBR) and enabling it on an existing schema with objects. Although EBR isn't exactly a new feature its current adoption level is probably not that high (which probably changes in future as Oracle E-Business Suite uses EBR now as part of their default upgrade procedure as far as I understood).I was recently contacted by someone who enabled EBR on an existing schema using ALTER USER ... ENABLE EDITIONS and had to use the "FORCE" option since there were (according to the official ALTER USER documentation) "objects that are not editionable and that depend on editionable type objects in the schema. ...

Combined ACCESS And FILTER Predicates - Excessive Throw-Away

Catchy title... Let's assume the following data setup:


create table t1
as
select
rownum as id
, 1 as id2
, rpad('x', 100) as filler
from
dual
connect by
level <= 1e4
;

create table t2
as
select
rownum as id
, 1 as id2
, rpad('x', 100) as filler
from
dual
connect by
level <= 1e4
;

create table t3
as
select
rownum as id
, 1 as id2
, rpad('x', 100) as filler
from
dual
connect by
level <= 1e4
;

exec dbms_stats.gather_table_stats(null, 't1')

exec dbms_stats.gather_table_stats(null, 't2')

exec dbms_stats.gather_table_stats(null, 't3')

12c Parallel Execution New Features: Concurrent UNION ALL - Part 3

In the final part of this instalment I want to focus on the possible optimisation of remote access that I outlined in the initial part, which is based on the idea of running multiple concurrent remote branches of a UNION ALL to overcome the query coordinator bottleneck of straightforward remote queries that need to transfer larger amounts of data.For that purpose I now simply change my sample query to access the serial table T2 via the DB link defined in the setup of the initial part, like that:


set echo on timing on time on

select /*+ PQ_CONCURRENT_UNION(@"SET$1") */ count(*) from (
select id, regexp_replace(t2.filler, '^\s+([[:alnum:]]+)\s+$', lpad('\1', 10), 1, 1, 'c') as result from t2@loop

12c Parallel Execution New Features: Concurrent UNION ALL - Part 2

In the first part of this series I've focused on the parallel degree chosen by the optimizer when dealing with the new concurrent UNION ALL feature.I've shown that for the variant with serial branches only in the UNION ALL in principle the number of branches dictates the parallel degree determined, even in cases of more complex plans that mix such a serial branch only UNION ALL operator with some other parallel stuff for example via a join.In this part I'll focus on the runtime behaviour of the feature, but before doing so let me show you what happens if you start mixing serial and parallel branches in the UNION ALL, like that (using the identical table setup as in the previous part):


select count(*) from (

12c Parallel Execution New Features: Concurrent UNION ALL - Part 1

12c introduces the concurrent UNION ALL operator that allows multiple branches below the UNION ALL to become active concurrently - which is a significant change. Before the introduction of this feature Oracle never executed multiple branches of an execution plan concurrently (in terms of Parallel Execution) - the parallelism so far was about executing the same operations of a particular branch of the execution plan by multiple processes / sessions.

12c Parallel Execution New Features: Hybrid Hash Distribution - Part 2

In the second part of this post (go to part 1) I want to focus on the hybrid distribution for skewed join expressions.

2. Hybrid Distribution For Skewed Join Expressions

The HYBRID HASH distribution allows to some degree addressing data distribution skew in case of HASH distributions, which I've described in detail already in the past.

12c Parallel Execution New Features: Hybrid Hash Distribution - Part 1

In this blog post I want to cover some aspects of the the new HYBRID HASH adaptive distribution method that I haven't covered yet in my other posts.As far as I know it serves two purposes for parallel HASH and MERGE JOINs, adaptive broadcast distribution and hybrid distribution for skewed join expressions. In the first part of this post I want to focus on former one (goto part 2).

1. Adaptive Broadcast Distribution For Small Left Row Sources

It allows the PX SEND / RECEIVE operation for the left (smaller estimated row source) of the hash join to decide dynamically at runtime, actually at each execution, if it should use either a BROADCAST or HASH distribution, and correspondingly for the other row source to use then either a ROUND-ROBIN or a HASH distribution, too.