Logical I/O Evolution - Part 3: 11g

Preface (with apologies to Kevin Closson)

This blog post is too long

Introduction

In the previous part of this series I've already demonstrated that the logical I/O optimization of the Table Prefetching feature depends on the order of the row sources - and 11g takes this approach a big step further.

It is very interesting that 11g does not require any particular feature like Table Prefetching or Nested Loop Join Batching (another new feature introduced in 11g) to take advantage of the Logical I/O optimization - it seems to be available even with the most basic form of a Nested Loop join.

Note that this optimization has already been mentioned several times, but there was always some confusion so far whether this optimization was related to another new feature that has been introduced with 11g - the so called "fastpath" consistent gets.

Buffer Pinning Optimization

So, let's repeat the already known test case from the previous parts in 11g. Another nice feature of 11g is that we have now full control over the Nested Loop plan shapes / features used by Oracle - we can choose from "classic" Nested Loop Join, Table Prefetching and Nested Loop Join Batching.

This is controlled via the [NO_]NLJ_BATCHING and [NO_]NLJ_PREFETCH hints which you will also find in the "outline" hint list generated for Plan Stability from 11g on.

Interestingly if I wanted to have the "classic" Nested Loop shape then I couldn't achieve that by combining the NO_NLJ_BATCHING and NO_NLJ_PREFETCH hint - one seemed to disable the other one - so I had to resort to the "_nlj_batching_enabled" parameter to disable Nested Loop Join Batching.

So this is what the query hints need to look like if we want to have the classic Nested Loop Join shape in 11g:

select
max(b_filler), max(a_filler)
from (
select /*+ leading(a) use_nl(a b) opt_param('_nlj_batching_enabled', 0) no_nlj_prefetch(b) */
a.id as a_id, a.filler as a_filler, b.id as b_id, b.filler as b_filler
from
t2 a
, t1 b
where
a.id = b.id
);

If you want to test with different plan shapes you can simply modify the hint section as required, for example you can get the Table Prefetching shape by changing above hint from NO_NLJ_PREFETCH to NLJ_PREFETCH etc.

Let's start with the data set where T1 and T2 are not in the same order, and stick to the classic plan shape:

11.2.0.1 Classic Nested Loop - Random order

Inner row source Unique Index - T1 different order than T2

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.67 | 310K|
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.67 | 310K|
| 2 | NESTED LOOPS | | 1 | 100K| 202K (1)| 100K|00:00:03.47 | 310K|
| 3 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.21 | 10010 |
| 4 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:02.54 | 300K|
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.76 | 200K|
---------------------------------------------------------------------------------------------------------------

Inner row source Non-Unique Index - T1 different order than T2

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:04.40 | 311K|
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:04.40 | 311K|
| 2 | NESTED LOOPS | | 1 | 100K| 202K (1)| 100K|00:00:04.20 | 311K|
| 3 | TABLE ACCESS FULL | T1 | 1 | 100K| 2720 (1)| 100K|00:00:00.20 | 10010 |
| 4 | TABLE ACCESS BY INDEX ROWID| T2 | 100K| 1 | 2 (0)| 100K|00:00:03.28 | 301K|
|* 5 | INDEX RANGE SCAN | T2_IDX | 100K| 1 | 1 (0)| 100K|00:00:01.08 | 201K|
---------------------------------------------------------------------------------------------------------------

So far no difference to previous results, the non-unique index variant is still slower than the unique one, and we do not see any special buffer pinning optimization apart from the one we've already seen in the baseline test.

The relevant session statistics:

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..table scan blocks gotten 10,000 10,000 0
STAT..table scan rows gotten 100,000 100,000 0
STAT..table fetch by rowid 100,000 100,002 2
STAT..consistent gets 310,012 311,108 1,096
STAT..consistent gets from cache 310,012 311,108 1,096
STAT..session logical reads 310,012 311,108 1,096
STAT..buffer is not pinned count 200,002 100,012 -99,990
STAT..buffer is pinned count 99,999 199,993 99,994
STAT..index fetch by key 100,000 2 -99,998
STAT..rows fetched via callback 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000
STAT..consistent gets - examination 300,001 100,007 -199,994
STAT..consistent gets from cache (fastpath) 10,011 211,101 201,090
STAT..no work - consistent read gets 10,001 211,091 201,090
LATCH.cache buffers chains 320,024 522,216 202,192

Nothing spectacular here either, but there are at least some interesting points to mention:

- We can see that Oracle took advantage of the so called "fastpath" consistent gets for the "normal" consistent gets - they still took two latch acquisitions per get though. The "fastpath" seems to be about a code optimization when buffers get pinned that probably requires less CPU cycles. I don't know if the code change addresses any further contention/concurrency issues apart from being "faster" (faster is always better, isn't it :-)

- The "buffer is pinned count" statistics are not consistent with what we've seen from 10g:

* The "unique index" variant already misses 90,000 pins, but does not produce more consistent gets, so in total we do not arrive at the anticipated 500,000 buffer visits any more - either something seems to be missing from the instrumentation or Oracle does something fundamentally different
* The "non-unique index" variant however records 10,000 excess pinned buffers, so we end up with 510,000 buffer visits recorded in total

Let's repeat the same with the T1 and T2 data ordered in the same way - but not ordered by ID (so simply uncomment the second call to DBMS_RANDOM.SEED(0)):

11.2.0.1 Classic Nested Loop - Same random order

Inner row source Unique Index - T1 same random order as T2

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.55 | 310K|
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.55 | 310K|
| 2 | NESTED LOOPS | | 1 | 100K| 202K (1)| 100K|00:00:03.35 | 310K|
| 3 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.22 | 10010 |
| 4 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:02.41 | 300K|
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.77 | 200K|
---------------------------------------------------------------------------------------------------------------

Inner row source Non-Unique Index - T1 same random order as T2

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:04.23 | 221K|
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:04.23 | 221K|
| 2 | NESTED LOOPS | | 1 | 100K| 202K (1)| 100K|00:00:04.02 | 221K|
| 3 | TABLE ACCESS FULL | T1 | 1 | 100K| 2720 (1)| 100K|00:00:00.21 | 10010 |
| 4 | TABLE ACCESS BY INDEX ROWID| T2 | 100K| 1 | 2 (0)| 100K|00:00:03.10 | 211K|
|* 5 | INDEX RANGE SCAN | T2_IDX | 100K| 1 | 1 (0)| 100K|00:00:01.09 | 201K|
---------------------------------------------------------------------------------------------------------------

So, that's interesting: We can already see here the same optimization for the non-unique index kicking in as we saw in 10g with Table Prefetching, although the classic plan shape gets used.

The statistics correspond to the result - but there is a slight difference to the 10.2 Table Prefetching case: The "buffer is pinned count" is at least "self-consistent" for the "non-unique index" variant, so there is no "excess" pinning recorded as with the Table Prefetching.

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..table scan blocks gotten 10,000 10,000 0
STAT..table scan rows gotten 100,000 100,000 0
STAT..table fetch by rowid 100,000 100,002 2
LATCH.cache buffers chains 320,030 342,242 22,212
STAT..consistent gets 310,012 221,124 -88,888
STAT..consistent gets from cache 310,012 221,124 -88,888
STAT..session logical reads 310,012 221,124 -88,888
STAT..Cached Commit SCN referenced 110,000 20,007 -89,993
STAT..index fetch by key 100,000 2 -99,998
STAT..rows fetched via callback 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000
STAT..consistent gets from cache (fastpath) 10,011 121,117 111,106
STAT..no work - consistent read gets 10,001 121,107 111,106
STAT..buffer is not pinned count 200,002 10,028 -189,974
STAT..buffer is pinned count 99,999 289,977 189,978
STAT..consistent gets - examination 300,001 100,007 -199,994

Redundant Filter Optimization

As I've just demonstrated the inner table lookup for the "unique index" variant does not use the buffer pinning optimization. It's an interesting little detail that in 11.1.0.7 and 11.2.0.1 putting a filter on the inner table lookup changes the result for the "unique index" variant, so running a query like this using a redundant filter that doesn't change the overall result:

select
max(b_filler), max(a_filler)
from (
select /*+ leading(a) use_nl(a b) opt_param('_nlj_batching_enabled', 0) no_nlj_prefetch(b) */
a.id as a_id, a.filler as a_filler, b.id as b_id, b.filler as b_filler
from
t2 a
, t1 b
where
a.id = b.id
and substr(b.filler, 1, 1) = 'x'
);

will result in such an output:

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.25 | 220K|
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.25 | 220K|
| 2 | NESTED LOOPS | | 1 | 1000 | 202K (1)| 100K|00:00:03.05 | 220K|
| 3 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.21 | 10010 |
|* 4 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:02.12 | 210K|
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.77 | 200K|
---------------------------------------------------------------------------------------------------------------

Session Statistics:

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..buffer is pinned count 289,998 289,977 -21
STAT..buffer is not pinned count 10,003 10,028 25
LATCH.JS queue state obj latch 0 36 36
LATCH.row cache objects 67 110 43
STAT..CPU used when call started 59 119 60
STAT..DB time 59 119 60
STAT..CPU used by this session 56 119 63
LATCH.enqueues 2 78 76
LATCH.enqueue hash chains 3 80 77
LATCH.simulator hash latch 9,111 9,304 193
STAT..consistent gets 220,012 221,124 1,112
STAT..consistent gets from cache 220,012 221,124 1,112
STAT..session logical reads 220,012 221,124 1,112
STAT..consistent gets - examination 200,001 100,007 -99,994
STAT..index fetch by key 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000
STAT..consistent gets from cache (fastpath) 20,011 121,117 101,106
STAT..no work - consistent read gets 20,001 121,107 101,106
LATCH.cache buffers chains 240,024 342,248 102,224

The interesting part here is that the "unique index" variant now uses the same buffer pinning optimization as the "non-unique index" one - but resorts to "normal" consistent gets (using the "fastpath" version in this case) for the random table access.

I don't know if this is feature or a side-effect of a bug because it ceases to work in 11.2.0.2 - there the "unique index" variant can not be convinced to make use of the "buffer pinning" optimization, it always performs the "shortcut" logical I/O on in the inner table lookup even with a filter specified.

We'll see later on that this has some interesting consequences with concurrent executions.

Ordered Data Sets

OK, now finally the big one: Let's repeat the test case with data sorted by ID, so by using the ORDER BY ID instead of ORDER BY DBMS_RANDOM.VALUE when populating the tables:

11.2.0.1 Classic Nested Loop - data ordered by ID

Inner row source Unique Index - T1 and T2 ordered by ID

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.42 | 122K|
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.42 | 122K|
| 2 | NESTED LOOPS | | 1 | 100K| 202K (1)| 100K|00:00:03.21 | 122K|
| 3 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.21 | 10010 |
| 4 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:02.27 | 112K|
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.55 | 12314 |
---------------------------------------------------------------------------------------------------------------

Inner row source Non-Unique Index - T1 and T2 ordered by ID

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.64 | 33143 |
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.64 | 33143 |
| 2 | NESTED LOOPS | | 1 | 100K| 202K (1)| 100K|00:00:03.45 | 33143 |
| 3 | TABLE ACCESS FULL | T1 | 1 | 100K| 2720 (1)| 100K|00:00:00.20 | 10010 |
| 4 | TABLE ACCESS BY INDEX ROWID| T2 | 100K| 1 | 2 (0)| 100K|00:00:02.55 | 23133 |
|* 5 | INDEX RANGE SCAN | T2_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.67 | 13126 |
---------------------------------------------------------------------------------------------------------------

The result is staggering: The "non-unique" index variant apparently manages to visit 500,000 buffers with just 33K logical I/Os. It is also almost as fast as the "unique index" variant that obviously does not keep the buffers pinned for the inner table random lookup - let's check the session statistics:

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..table scan blocks gotten 10,000 10,000 0
STAT..table scan rows gotten 100,000 100,000 0
STAT..table fetch by rowid 100,000 100,002 2
STAT..consistent gets from cache (fastpath) 11,059 26,587 15,528
STAT..no work - consistent read gets 11,049 26,577 15,528
LATCH.cache buffers chains 133,384 60,829 -72,555
STAT..consistent gets 122,324 33,149 -89,175
STAT..consistent gets from cache 122,324 33,149 -89,175
STAT..session logical reads 122,324 33,149 -89,175
STAT..index fetch by key 100,000 2 -99,998
STAT..rows fetched via callback 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000
STAT..consistent gets - examination 111,265 5,470 -105,795
STAT..buffer is not pinned count 200,014 10,028 -189,986
STAT..buffer is pinned count 5,107 195,440 190,333

We can tell now different things from these statistics:

- The "non-unique index" variant requires just 60,000 latch acquisitions - which corresponds to the reduced number of logical I/Os

- The session statistics only "explain" 195,000 buffer visits via already pinned and 33,000 buffer visits recorded as logical I/Os, so we are missing approx. 270,000 buffer visits from the statistics. Compared to the results of the "unordered" test case we actually see a "reduction" of buffers visited that are already pinned (199,993 vs. 195,440), so that seems to be questionable

- The "unique index" variant still does the "short-cut" logical I/O on the inner table random lookup and hence requires actually more logical I/O and latch acquisitions in this case than the "non-unique index" variant

As we've seen above if in 11.1.0.7 and 11.2.0.1 a filter is put on the inner table random lookup Oracle 11g switches to "normal" consistent gets for the "unique index" variant, and in fact when repeating this experiment with the ordered data set, we see these results:

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:02.97 | 32315 |
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:02.97 | 32315 |
| 2 | NESTED LOOPS | | 1 | 1000 | 202K (1)| 100K|00:00:02.76 | 32315 |
| 3 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.22 | 10010 |
|* 4 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:01.81 | 22305 |
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.56 | 12302 |
---------------------------------------------------------------------------------------------------------------

So by switching to the "normal" consistent gets the buffer pinning optimization gets used for the inner table lookup also for the "unique index" variant (only reproducible in 11.1.0.7 and 11.2.0.1). The session statistics:

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..table scan blocks gotten 10,000 10,000 0
STAT..table scan rows gotten 100,000 100,000 0
STAT..table fetch by rowid 100,000 100,002 2
STAT..buffer is not pinned count 10,018 10,028 10
STAT..buffer is pinned count 195,103 195,440 337
STAT..consistent gets 32,315 33,149 834
STAT..consistent gets from cache 32,315 33,149 834
STAT..session logical reads 32,315 33,149 834
STAT..consistent gets from cache (fastpath) 21,050 26,587 5,537
STAT..no work - consistent read gets 21,040 26,577 5,537
STAT..consistent gets - examination 11,265 5,470 -5,795
LATCH.cache buffers chains 53,366 60,835 7,469
STAT..index fetch by key 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000

So we see now the "unique index" variant with similar results and the also a similar "gap" in the buffer visits explained by the statistics.

A slightly funny point is that by adding a "useless" filter we seem to arrive actually at a faster execution time due to the optimization kicking in - something that looks quite counter-intuitive and only seems to work in particular versions.

"Fastpath" consistent gets

To see if this optimization depends on the new "fastpath" consistent gets, let's turn this new feature off by setting "_fastpin_enable" to 0 and restarting the instance:

alter system set "_fastpin_enable" = 0 scope = spfile;

I'm showing here the results for the "inner table filter" variation - but those for the original case without the additional filter are also corresponding to those with "fast pinning" enabled:

11.2.0.1 Classic Nested Loop - data ordered by ID, fast pins disabled, inner table filter

Inner row source Unique Index - T1 and T2 ordered by ID

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:02.90 | 32315 |
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:02.90 | 32315 |
| 2 | NESTED LOOPS | | 1 | 1000 | 202K (1)| 100K|00:00:02.70 | 32315 |
| 3 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.21 | 10010 |
|* 4 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:01.79 | 22305 |
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.53 | 12302 |
---------------------------------------------------------------------------------------------------------------

Inner row source Non-Unique Index - T1 and T2 ordered by ID

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.86 | 33143 |
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.86 | 33143 |
| 2 | NESTED LOOPS | | 1 | 1000 | 202K (1)| 100K|00:00:03.67 | 33143 |
| 3 | TABLE ACCESS FULL | T1 | 1 | 100K| 2720 (1)| 100K|00:00:00.21 | 10010 |
|* 4 | TABLE ACCESS BY INDEX ROWID| T2 | 100K| 1 | 2 (0)| 100K|00:00:02.74 | 23133 |
|* 5 | INDEX RANGE SCAN | T2_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.71 | 13126 |
---------------------------------------------------------------------------------------------------------------

So the same optimization kicked in, and we can tell from the session statistics that the "fastpath" consistent gets indeed have not been used:

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..table scan blocks gotten 10,000 10,000 0
STAT..table scan rows gotten 100,000 100,000 0
STAT..table fetch by rowid 100,000 100,002 2
STAT..buffer is not pinned count 10,018 10,028 10
STAT..buffer is pinned count 195,103 195,440 337
STAT..consistent gets 32,315 33,149 834
STAT..consistent gets from cache 32,315 33,149 834
STAT..session logical reads 32,315 33,149 834
STAT..no work - consistent read gets 21,040 26,577 5,537
STAT..consistent gets - examination 11,265 5,470 -5,795
LATCH.cache buffers chains 53,372 60,829 7,457
STAT..index fetch by key 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000

The only significant difference is the absence of the "consistent gets from cache (fastpath)" statistics.

Nested Loop Join Batching

Finally let's check if the new "Nested Loop Batching" optimization does have any additional effects on the test case here by enabling the Nested Loop Join Batching. Changing the hints like this does the job:

.
.
.
select /*+ leading(a) use_nl(a b) opt_param('_nlj_batching_enabled', 1) no_nlj_prefetch(b) */
.
.
.

11.2.0.1 Nested Loop Batching - data ordered by ID, inner table filter

Inner row source Unique Index - T1 and T2 ordered by ID

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:02.89 | 32306 |
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:02.89 | 32306 |
| 2 | NESTED LOOPS | | 1 | | | 100K|00:00:02.70 | 32306 |
| 3 | NESTED LOOPS | | 1 | 1000 | 202K (1)| 100K|00:00:01.43 | 22306 |
| 4 | TABLE ACCESS FULL | T2 | 1 | 100K| 2720 (1)| 100K|00:00:00.20 | 10010 |
|* 5 | INDEX UNIQUE SCAN | T1_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.53 | 12296 |
|* 6 | TABLE ACCESS BY INDEX ROWID| T1 | 100K| 1 | 2 (0)| 100K|00:00:00.57 | 10000 |
---------------------------------------------------------------------------------------------------------------

Inner row source Non-Unique Index - T1 and T2 ordered by ID

---------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | Cost (%CPU)| A-Rows | A-Time | Buffers |
---------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 202K(100)| 1 |00:00:03.05 | 33128 |
| 1 | SORT AGGREGATE | | 1 | 1 | | 1 |00:00:03.05 | 33128 |
| 2 | NESTED LOOPS | | 1 | | | 100K|00:00:02.85 | 33128 |
| 3 | NESTED LOOPS | | 1 | 1000 | 202K (1)| 100K|00:00:01.57 | 23128 |
| 4 | TABLE ACCESS FULL | T1 | 1 | 100K| 2720 (1)| 100K|00:00:00.20 | 10010 |
|* 5 | INDEX RANGE SCAN | T2_IDX | 100K| 1 | 1 (0)| 100K|00:00:00.67 | 13118 |
|* 6 | TABLE ACCESS BY INDEX ROWID| T2 | 100K| 1 | 2 (0)| 100K|00:00:00.57 | 10000 |
---------------------------------------------------------------------------------------------------------------

Apart from some minor differences in the number of logical I/Os it doesn't change the outcome. The same applies to the session statistics:

Statistics Name Unique Non-Unique Difference
----------------------------------------------------- -------- ----------- -----------
STAT..table scan blocks gotten 10,000 10,000 0
STAT..table scan rows gotten 100,000 100,000 0
STAT..table fetch by rowid 100,000 100,002 2
STAT..buffer is not pinned count 10,006 10,010 4
STAT..buffer is pinned count 195,115 195,458 343
STAT..consistent gets 32,306 33,134 828
STAT..consistent gets from cache 32,306 33,134 828
STAT..session logical reads 32,306 33,134 828
STAT..consistent gets from cache (fastpath) 21,041 26,572 5,531
STAT..no work - consistent read gets 21,031 26,562 5,531
STAT..consistent gets - examination 11,265 5,470 -5,795
LATCH.cache buffers chains 53,348 60,816 7,468
STAT..index fetch by key 100,000 2 -99,998
STAT..index scans kdiixs1 0 100,000 100,000

What is interesting to see however is that it seems to perform faster, in particular the "non-unique index" variant is now really pretty close to the "unique index" variant - so although the Nested Loop Join Batching doesn't show any significant changes in the statistics and latch acquisition, it seems to save CPU cycles and performs better even without any physical I/O involved.

As a side note, if you want to check the effects of the "Nested Loop Join Batching" on physical I/O you need to be aware of an odd behaviour I've experienced during my tests: If any kind of row source statistics sampling was enabled by either using STATISTICS_LEVEL = ALL, the GATHER_PLAN_STATISTICS hint or even enabling (extended) SQL trace, the optimized, batched form of physical I/O could not be reproduced. You could tell this from the session statistics that start with "Batched IO%" - these all stayed at 0. Only when disabling all these things the effects were visible and the corresponding statistics where non-zero. I don't know why this is the case, but it is an important detail when testing this feature. I'll probably publish a separate post on the physical I/O optimizations of the Vector/Batched I/O at some time in the future.

Scalability

When running the "data ordered by ID" version concurrently it can be seen that the "non-unique index" variant scales now almost equally well as the "unique index" variant - so these two variants are now quite close not only in single-user mode, but they both scale very well, too.

There is another interesting effect that can only be observed when running the test case with the unordered data set concurrently: In recent code releases (10.2.0.5, 11.2.0.1 and 11.2.0.2) the "shortcut" consistent gets on the inner table lookup that are used with the "unique index" variant gets "downgraded" to "normal" consistent gets if there is concurrent access to the block. This can be observed in the session statistics and latch acquisitions:

Statistics Name Value
----------------------------------------------------- -----------
STAT..shared hash latch upgrades - no wait 99,995
STAT..RowCR attempts 100,000
STAT..RowCR hits 100,000
STAT..consistent gets from cache (fastpath) 10,011
STAT..no work - consistent read gets 10,000
STAT..consistent gets - examination 200,013
STAT..consistent gets 310,024
STAT..consistent gets from cache 310,024
LATCH.cache buffers chains 1,680,173

Note in particular how the "consistent gets - examination" statistics have been decreased from 300,000 to 200,000. So with four concurrent executions this "unique index" variant suddenly requires approx. 420,000 latch acquisitions per execution in contrast to the usual 320,000. Since 11.2.0.2 does not support the "filter" trick to make use of the buffer pinning optimization for the inner table lookup with the ordered data set and the "unique index" variant, it suffers twice: Not only it requires single latch acquisitions for the inner table lookup but due to the "downgrade" it performs two latch acquisitions per iteration requiring a whopping 200,000 excess latch acquisitions per concurrent execution with the ordered by ID data set.

It's also interesting to note that the "RowCR" optimization is recorded in the session statistics. I couldn't find much information about this - it seems to be in the code since 10.2 (partial support already in 9.2 RAC), but until 10.2.0.5 it is only enabled in RAC mode and not in single-instance mode (see MOS note "Bug 4951888 - Row CR is not enabled for non RAC systems"). I could reproduce this only in 10.2.0.5, 11.2.0.1 and 11.2.0.2. According to the description it has been specifically introduced for using row-level consistent gets instead of rolling back complete block versions for read-consistency in RAC environments where generating the previous version of a block might require undo blocks from remote instances. Why this optimization shows up in the above single-instance, read-only scenario where no rollback to the block version is required is not clear to me. It is however measurable that the "fallback" seems to slow down execution.

Whether this is a side-effect or a deliberate design choice that performs better in RAC environments or certain consistent read scenarios I can't tell yet, however when switching off this optimization via "alter system set "_row_cr" = false" this "downgrade" with concurrent execution doesn't happen any longer, and 11.2.0.2 performs better in my test cases, although it doesn't bring back the "filter" trick, so 11.2.0.2 is the only release where the "non-unique index" variant scales better with the ordered data set than the "unique index" variant.

A final word on scalability in general: I think it is important to point out that the test harness provided so far only checks for concurrent read access. Since it is interesting to see if the "buffer pinning" optimization observed does have any negative side effects on mixed read/write access to the buffers I've published an updated script set that includes new versions of the concurrent execution master and slave scripts. These allow to run a SELECT FOR UPDATE on both tables involved as first session, and all other sessions in read-only mode in order to test the effects of a mixed read/write concurrency scenario.

The result of this quite simple test shows that the buffer pinning optimization not only scales very well for read-only concurrency but also scales very good for the tested mixed read-write scenario. The provided test case might be a specific and simplistic case (there are some specialities with SELECT FOR UPDATE) and there might be other concurrency scenarios where the buffer pinning might not scale that well (for example potentially "free buffer waits" due to many blocks being pinned) but at least with this test case the result is quite impressive.

As a side note, the mixed read-write test is very interesting on its own in several ways, for example:

- It adds additional pressure on the buffer cache due to clone copies created. A query similar to the one provided by Jonathan Lewis here can be quite revealing. You'll find out that you need a much larger cache to still have a fully cached test case (with 8KB block size at least 512MB for keeping two 80MB segments! fully cached)

- It requires additional buffer cache for the undo blocks

- It will generate a much higher contention on the "cache buffers chains" latches due to the additional buffer cache activity (creating clone copies, rollbacks for consistent reads, current mode gets etc.)

- It requires applying undo to the blocks to arrive at a read-consistent version

- The buffers will have to be accessed in exclusive mode for write access

The updated script set also contains an Excel sheet with results from my test runs on different hardware and Oracle versions as well as a sample query to analyse the buffer cache.

Summary

Oracle 11g extends the logical I/O optimizations that could already been seen in Oracle 10g when using the Table Prefetching Nested Loop shape - and it is available without any further optimizations like Table Prefetching or Nested Loop Join Batching. It is also not depending on the new "fastpath" consistent gets introduced with 11g.

The efficiency of the optimization largely depends on the order of the data, so predicting it is not that easy - a bit similar to predicting the efficiency of the Subquery / Filter caching feature that also depends on data patterns.

However this knowledge might offer additional options how to take advantage of this optimization. Of course introducing additional sort operations might easily outweigh the benefits achieved, but there might be cases where a sort is not that costly and allows to improve scalability/concurrency in extreme cases.

Closing remarks

This blog post got way too long