Posts in category 9iR2

Does the Query Optimizer Cost PX Distribution Methods?

Jan26
2010 13 Comments Written by Christian Antognini

The short answer to this question is “yes”, it does. Unfortunately, the distribution costs are not externalized through the execution plans and, as a result, this limitation (yes, it is really a limitation in the current implementation, not a bug) confuses everyone that carefully look at the information provided in an execution plan of a SQL statement executed in parallel. Hence, let’s remove some confusion…

To illustrate what the problem is, let’s have a look to a simple query that joins two tables:

SELECT * FROM master m JOIN detail d ON (m.id = d.id)

Now, let’s have a look at two parallel executions. If the two tables are equipartitioned, the following execution plan (which takes advantage of partition-wise join) is probably the most effective for such a query. Note that thanks to the partition-wise join not only there is a single set of parallel slaves (Q1,00), but, in addition, the parallel slaves do not communicate with each other (they only communicate with the query coordinator). As a result, the communication costs are equal to zero (this is because the query optimizer does not compute the costs of the communication towards the query coordinator).

----------------------------------------------------------------------------------------------
| Id  | Operation               | Name     | Bytes | Cost (%CPU)|    TQ  |IN-OUT| PQ Distrib |
----------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT        |          |    16G| 162524  (1)|        |      |            |
|   1 |  PX COORDINATOR         |          |       |            |        |      |            |
|   2 |   PX SEND QC (RANDOM)   | :TQ10000 |    16G| 162524  (1)|  Q1,00 | P->S | QC (RAND)  |
|   3 |    PX PARTITION HASH ALL|          |    16G| 162524  (1)|  Q1,00 | PCWC |            |
|   4 |     HASH JOIN           |          |    16G| 162524  (1)|  Q1,00 | PCWP |            |
|   5 |      TABLE ACCESS FULL  | MASTER   |   125M|   1422  (1)|  Q1,00 | PCWP |            |
|   6 |      TABLE ACCESS FULL  | DETAIL   |    15G| 161052  (1)|  Q1,00 | PCWP |            |
----------------------------------------------------------------------------------------------

If the two tables are not equipartitioned, the following execution plan might be chosen by the query optimizer. Since it does not take advantage of a partition-wise join, several set of parallel slaves are used. The first one (Q1,00) scans the MASTER table, the second one (Q1,01) scans the DETAIL table, and both of them send the data to the third one (Q1,02) that performs the join of the two tables and sends the data to the query coordinator. Since all data (about 15GB; yes, the estimations are good) is sent through the PX channels, the cost should not be zero. However, as you can see, the cost is exactly the same as the one of the previous execution plan.

----------------------------------------------------------------------------------------------
| Id  | Operation               | Name     | Bytes | Cost (%CPU)|    TQ  |IN-OUT| PQ Distrib |
----------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT        |          |    16G| 162524  (1)|        |      |            |
|   1 |  PX COORDINATOR         |          |       |            |        |      |            |
|   2 |   PX SEND QC (RANDOM)   | :TQ10002 |    16G| 162524  (1)|  Q1,02 | P->S | QC (RAND)  |
|   3 |    HASH JOIN BUFFERED   |          |    16G| 162524  (1)|  Q1,02 | PCWP |            |
|   4 |     PX RECEIVE          |          |   125M|   1422  (1)|  Q1,02 | PCWP |            |
|   5 |      PX SEND HASH       | :TQ10000 |   125M|   1422  (1)|  Q1,00 | P->P | HASH       |
|   6 |       PX BLOCK ITERATOR |          |   125M|   1422  (1)|  Q1,00 | PCWC |            |
|   7 |        TABLE ACCESS FULL| MASTER   |   125M|   1422  (1)|  Q1,00 | PCWP |            |
|   8 |     PX RECEIVE          |          |    15G| 161052  (1)|  Q1,02 | PCWP |            |
|   9 |      PX SEND HASH       | :TQ10001 |    15G| 161052  (1)|  Q1,01 | P->P | HASH       |
|  10 |       PX BLOCK ITERATOR |          |    15G| 161052  (1)|  Q1,01 | PCWC |            |
|  11 |        TABLE ACCESS FULL| DETAIL   |    15G| 161052  (1)|  Q1,01 | PCWP |            |
----------------------------------------------------------------------------------------------

For completeness, let’s compare the cost of several distribution methods (“none-none” is the one of the first execution plan above, “hash-hash” of the second one). As you can see the cost is always the same!

SQL> EXPLAIN PLAN SET STATEMENT_ID 'none-none' FOR SELECT /*+ pq_distribute(d none none) */ * FROM master m JOIN detail d ON (m.id = d.id);
SQL> EXPLAIN PLAN SET STATEMENT_ID 'hash-hash' FOR SELECT /*+ pq_distribute(d hash hash) */ * FROM master m JOIN detail d ON (m.id = d.id);
SQL> EXPLAIN PLAN SET STATEMENT_ID 'broadcast-none' FOR SELECT /*+ pq_distribute(d broadcast none) */ * FROM master m JOIN detail d ON (m.id = d.id);
SQL> EXPLAIN PLAN SET STATEMENT_ID 'none-broadcast' FOR SELECT /*+ pq_distribute(d none broadcast) */ * FROM master m JOIN detail d ON (m.id = d.id);
SQL> EXPLAIN PLAN SET STATEMENT_ID 'partition-none' FOR SELECT /*+ pq_distribute(d partition none) */ * FROM master m JOIN detail d ON (m.id = d.id);
SQL> EXPLAIN PLAN SET STATEMENT_ID 'none-partition' FOR SELECT /*+ pq_distribute(d none partition) */ * FROM master m JOIN detail d ON (m.id = d.id);
SQL> SELECT statement_id, cost FROM plan_table WHERE id = 0;

STATEMENT_ID                         COST
------------------------------ ----------
none-none                          162524
hash-hash                          162524
broadcast-none                     162524
none-broadcast                     162524
partition-none                     162524
none-partition                     162524

As I wrote before, the problem is not that the costs are not computed. The problem is that they are not externalized. In fact, by giving a look to a trace file generated through the event 10053 the costs are available. Here’s the relevant part (the lines starting with “---- cost” contain the most important information). As you can see there are two costs associated with every distribution method: one with the distribution costs (w/ dist) and one without them (w/o dist).

Enumerating distribution method for join between M[MASTER] and D[DETAIL]
-- Using join method #Hash Join:
---- cost NONE = 0.00
  Outer table:  MASTER  Alias: M
    resc: 5120.11  card 4118000.00  bytes: 32  deg: 4  resp: 1422.25
  Inner table:  DETAIL  Alias: D
    resc: 579787.63  card: 31954000.00  bytes: 526  deg: 4  resp: 161052.12
    using dmeth: 513  #groups: 1
    Cost per ptn: 49.68  #ptns: 4
    hash_area: 16384 (max=16384) buildfrag: 5530  probefrag: 524636  ppasses: 1
      buildfrag: 5530  probefrag: 524636  passes: 1
  Hash join: Resc: 585106.45  Resp: 162524.05  [multiMatchCost=0.00]
---- cost(Hash Join) = 162524.05 (w/o dist), 162524.05 (w/ dist)
---- cost VALUE = 278.52
---- cost with slave mapping  =   Outer table:  MASTER  Alias: M
    resc: 5120.11  card 4118000.00  bytes: 32  deg: 4  resp: 1422.25
  Inner table:  DETAIL  Alias: D
    resc: 579787.63  card: 31954000.00  bytes: 526  deg: 4  resp: 161052.12
    using dmeth: 2  #groups: 1
    Cost per ptn: 49.68  #ptns: 4
    hash_area: 16384 (max=16384) buildfrag: 5530  probefrag: 524636  ppasses: 1
      buildfrag: 5530  probefrag: 524636  passes: 1
  Hash join: Resc: 585106.45  Resp: 162524.05  [multiMatchCost=0.00]
---- cost(Hash Join) = 162524.05 (w/o dist), 162802.57 (w/ dist)
---- cost PARTITION-RIGHT = 271.40
  Outer table:  MASTER  Alias: M
    resc: 5120.11  card 4118000.00  bytes: 32  deg: 4  resp: 1422.25
  Inner table:  DETAIL  Alias: D
    resc: 579787.63  card: 31954000.00  bytes: 526  deg: 4  resp: 161052.12
    using dmeth: 576  #groups: 1
    Cost per ptn: 49.68  #ptns: 4
    hash_area: 16384 (max=16384) buildfrag: 5530  probefrag: 524636  ppasses: 1
      buildfrag: 5530  probefrag: 524636  passes: 1
  Hash join: Resc: 585106.45  Resp: 162524.05  [multiMatchCost=0.00]
---- cost(Hash Join) = 162524.05 (w/o dist), 162795.46 (w/ dist)
---- cost PARTITION-LEFT = 7.12
  Outer table:  MASTER  Alias: M
    resc: 5120.11  card 4118000.00  bytes: 32  deg: 4  resp: 1422.25
  Inner table:  DETAIL  Alias: D
    resc: 579787.63  card: 31954000.00  bytes: 526  deg: 4  resp: 161052.12
    using dmeth: 544  #groups: 1
    Cost per ptn: 49.68  #ptns: 4
    hash_area: 16384 (max=16384) buildfrag: 5530  probefrag: 524636  ppasses: 1
      buildfrag: 5530  probefrag: 524636  passes: 1
  Hash join: Resc: 585106.45  Resp: 162524.05  [multiMatchCost=0.00]
---- cost(Hash Join) = 162524.05 (w/o dist), 162531.17 (w/ dist)
---- cost BROADCAST-RIGHT = 920.78
---- cost with slave mapping  =   Outer table:  MASTER  Alias: M
    resc: 5120.11  card 4118000.00  bytes: 32  deg: 4  resp: 1422.25
  Inner table:  DETAIL  Alias: D
    resc: 579787.63  card: 31954000.00  bytes: 526  deg: 4  resp: 161052.12
    using dmeth: 8  #groups: 4
    Cost per ptn: 49.68  #ptns: 4
    hash_area: 16384 (max=16384) buildfrag: 5530  probefrag: 524636  ppasses: 1
      buildfrag: 5530  probefrag: 524636  passes: 1
  Hash join: Resc: 585106.45  Resp: 162524.05  [multiMatchCost=0.00]
---- cost(Hash Join) = 162524.05 (w/o dist), 162755.25 (w/ dist)
---- cost BROADCAST-LEFT = 7.22
---- cost with slave mapping  =   Outer table:  MASTER  Alias: M
    resc: 5120.11  card 4118000.00  bytes: 32  deg: 4  resp: 1422.25
  Inner table:  DETAIL  Alias: D
    resc: 579787.63  card: 31954000.00  bytes: 526  deg: 4  resp: 161052.12
    using dmeth: 16  #groups: 4
    Cost per ptn: 49.68  #ptns: 4
    hash_area: 16384 (max=16384) buildfrag: 5530  probefrag: 524636  ppasses: 1
      buildfrag: 5530  probefrag: 524636  passes: 1
  Hash join: Resc: 585106.45  Resp: 162524.05  [multiMatchCost=0.00]
---- cost(Hash Join) = 162524.05 (w/o dist), 162526.86 (w/ dist)

Since the cost are (correctly) computed, the query optimizer is able to choose the optimal plan. However, it would be nice to have the actual costs in the execution plans.

Posted in 10gR1, 10gR2, 11gR1, 11gR2, Parallel Processing, Query Optimizer

Does CREATE INDEX Gather Global Statistics?

Dec17
2009 4 Comments Written by Christian Antognini

You can add the COMPUTE STATISTICS clause to the CREATE INDEX statement. It instructs the SQL statement to gather and store index statistics in the data dictionary, while creating the index. This is useful because the overhead associated with the gathering of statistics while executing this SQL statement is negligible. In Oracle9i, the gathering of statistics is performed only when this clause is specified. As of Oracle Database 10g, whenever statistics are not locked, their gathering is done by default, which means the COMPUTE STATISTICS clause is deprecated and available for backward compatibility only.

Unfortunately, CREATE INDEX does not gather global statistics. As a result, whenever you are creating partitioned indexes, the global statistics might be inaccurate. Let me show you an example:

Create partitioned table, insert data (notice that the number of distinct values is equal to the number of rows) and create a local index

SQL> CREATE TABLE t (n1 number, n2 number)
  2  PARTITION BY RANGE (n1) (
  3    PARTITION p1 VALUES LESS THAN (11),
  4    PARTITION p2 VALUES LESS THAN (21)
  5  );

Table created.

SQL> INSERT INTO t
  2  SELECT rownum, rownum
  3  FROM dual
  4  CONNECT BY level <= 20;

20 rows created.

SQL> CREATE INDEX i ON t (n2) LOCAL;

Index created.

The CREATE INDEX statement gathered the statistics for the index; let’s check them…

SQL> SELECT partition_name, global_stats, distinct_keys
  2  FROM user_ind_statistics
  3  WHERE index_name = 'I';

PARTITION_NAME GLOBAL_STATS DISTINCT_KEYS
-------------- ------------ -------------
               NO                      10
P1             NO                      10
P2             NO                      10

As you can see 1) the number of distinct keys at the global level is wrong; it should be 20! 2) the GLOBAL_STATS column at the index level is set to NO. As a result, when you create a partitioned index, you should manually gather the global index statistics straight after. In other words, you should do the following:

Manually gather global level index statistics

SQL> execute dbms_stats.gather_index_stats(ownname=>user, indname=>'i', granularity=>'global')

PL/SQL procedure successfully completed.

Check whether the index statistics are accurate

SQL> SELECT partition_name, global_stats, distinct_keys
  2  FROM user_ind_statistics
  3  WHERE index_name = 'I';

PARTITION_NAME GLOBAL_STATS DISTINCT_KEYS
-------------- ------------ -------------
               YES                     20
P1             NO                      10
P2             NO                      10

There are situations, however, where it is not necessary to manually gather the global index statistics. For example, when the index is prefixed. But, as a general rule, I would not rely on the automatically gathered statistics for partitioned indexes.

Posted in 10gR1, 10gR2, 11gR1, 11gR2, Indexes, Object Statistics, Partitioning

Hints for Direct-path Insert Statements

Oct23
2009 12 Comments Written by Christian Antognini

Up to Oracle Database 10g Release 2, direct-path inserts are supported only by INSERT INTO … SELECT … statements (including multitable inserts), MERGE statements (for the part inserting data), and applications using the OCI direct-path interface (for example, the SQL*Loader utility). At the statement level two methods are available to specify that a direct-path insert has to be used:

Specify the APPEND hint in the SQL statement
Execute the SQL statement (actually, at least the INSERT part) in parallel

Let’s have a look to an example. Notice that:

The APPEND hint is used to execute a direct-path insert.
The APPEND hint does not work with a “regular” INSERT statement that uses the VALUES clause.
To check whether the direct-path insert is performed, the modified table is queried without committing (or rolling back) the transaction. As a result, after a direct-path insert the database engine raises an ORA-12838.

SQL> SELECT * FROM v$version WHERE rownum = 1;

BANNER
----------------------------------------------------------------
Oracle Database 10g Enterprise Edition Release 10.2.0.4.0 - 64bi

SQL> CREATE TABLE t (n NUMBER);

SQL> INSERT /*+ append */ INTO t SELECT 1 FROM dual;

SQL> SELECT * FROM t;
SELECT * FROM t
              *
ERROR at line 1:
ORA-12838: cannot read/modify an object after modifying it in parallel

SQL> COMMIT;

SQL> INSERT /*+ append */ INTO t VALUES (2);

SQL> SELECT * FROM t;

         N
----------
         1
         2

Strangely enough, at least for me, in Oracle Database 11g Release 1 the behavior of the APPEND hint has changed. In fact, it is accepted also for a “regular” INSERT statement that uses the VALUES clause. Let’s run the same test as before to illustrate the new behavior.

SQL> SELECT * FROM v$version WHERE rownum = 1;

BANNER
--------------------------------------------------------------------------------
Oracle Database 11g Enterprise Edition Release 11.1.0.6.0 - 64bit Production

SQL> CREATE TABLE t (n NUMBER);

SQL> INSERT /*+ append */ INTO t SELECT 1 FROM dual;

SQL> SELECT * FROM t;
SELECT * FROM t
              *
ERROR at line 1:
ORA-12838: cannot read/modify an object after modifying it in parallel

SQL> COMMIT;

SQL> INSERT /*+ append */ INTO t VALUES (1);

SQL> SELECT * FROM t;
SELECT * FROM t
              *
ERROR at line 1:
ORA-12838: cannot read/modify an object after modifying it in parallel

Even more strange, in Oracle Database 11g Release 2 the behavior of the APPEND hint was reverted to the pre-11g one! But, since the feature is really useful in some situations, a new hint called APPEND_VALUES is available. The following example illustrates the new behavior.

SQL> SELECT * FROM v$version WHERE rownum = 1;

BANNER
--------------------------------------------------------------------------------
Oracle Database 11g Enterprise Edition Release 11.2.0.1.0 - 64bit Production

SQL> CREATE TABLE t (n NUMBER);

SQL> INSERT /*+ append */ INTO t SELECT 1 FROM dual;

SQL> SELECT * FROM t;
SELECT * FROM t
              *
ERROR at line 1:
ORA-12838: cannot read/modify an object after modifying it in parallel

SQL> COMMIT;

SQL> INSERT /*+ append */ INTO t VALUES (2);

SQL> SELECT * FROM t;

         N
----------
         1
         2

SQL> COMMIT;

SQL> INSERT /*+ append_values */ INTO t VALUES (3);

SQL> SELECT * FROM t;
SELECT * FROM t
*
ERROR at line 1:
ORA-12838: cannot read/modify an object after modifying it in parallel

Posted in 10gR1, 10gR2, 11gR1, 11gR2, Direct Path