12.1.0.2 New Features PDB CONTAINERS Clause

When 12.1.0.2 came out, one of the features I wanted to play was the Cross-container functionality, and I finally had time to play with it.

First here is the description of the feature.

The CONTAINERS clause is a new way of looking at multitenant container databases (CDBs). With this clause, data can be aggregated from a single identical table or view across many pluggable databases (PDBs) from the root container. The CONTAINERS clause accepts a table or view name as an input parameter that is expected to exist in all PDBs in that container. Data from a single PDB or a set of PDBs can be included with the use of CON_ID in the WHERE clause. 

I decided to play with this and see what it really means.... And mostly to see the explain plan to see what happens under the covers.

Step 1 --   The first thing you need to do is create a "common user".  A common user is a new term that comes with Pluggable databases.  A common user is a user which is created in the CDB (the Root container), and is then available as a user in all the PDB's that are part of the CDB.  There are some rules around this.

• In Oracle Database 12c Release 1 (12.1.0.1), the name of a common user must begin with C## or c## and the name of a local user must not begin with C## or c##.
• Starting with Oracle Database 12c Release 1 (12.1.0.2):
• The name of a common user must begin with characters that are a case-insensitive match to the prefix specified by the COMMON_USER_PREFIX initialization parameter. By default, the prefix is C##.
• The name of a local user must not begin with characters that are a case-insensitive match to the prefix specified by the COMMON_USER_PREFIX initialization parameter. Regardless of the value of COMMON_USER_PREFIX, the name of a local user can never begin with C## or c##.

 So here goes for step 1 ..

$ sqlplus "/ as sysdba"

SQL*Plus: Release 12.1.0.2.0 Production on Thu Aug 7 22:23:26 2014

Copyright (c) 1982, 2014, Oracle.  All rights reserved.


Connected to:
Oracle Database 12c Enterprise Edition Release 12.1.0.2.0 - 64bit Production
With the Partitioning, OLAP, Advanced Analytics and Real Application Testing options

SQL create user c##bgrenn identified by bgrenn;
grant dba to c##bgrenn;

User created.

SQL 
Grant succeeded.

One thing to mention at this point is that I granted DBA role to my new common user c##bgrenn.  You also need to set individual privileges at each PDB level

Step 2 --   Now that I have a common user (c##bgrenn), I now need to go into my pdb's and create the objects that I want to have shared across PDB's. 

For simplicity, I chose DBA_TABLES, and DBA_OBJECTS.

The 3  PDBS I want to create this in are "orclpdb", "orclpdba" and "orcldbb"

SQL> COLUMN NAME FORMAT A15
COLUMN RESTRICTED FORMAT A10
COLUMN OPEN_TIME FORMAT A30
 
SELECT NAME, OPEN_MODE, con_id  FROM V$PDBS
SQL /

NAME   OPEN_MODE      CON_ID
--------------- ---------- ----------
PDB$SEED  READ ONLY     2
ORCLPDB  READ WRITE     3
ORCLPDBA  READ WRITE     4
ORCLPDBB READ WRITE     5

I then went into all 3 PDB's and created a local copy of DBA_OBJECTS and DBA_TABLES.

connect sys/oracle@localhost:1521/orclpdb as sysdba

grant dba to c##bgrenn;

create table c##bgrenn.local_objects as select * from dba_objects;

create table c##bgrenn.local_tables as select * from dba_tables; 

Connected.
SQL

Grant succeeded.

SQL 

Table created.

SQL 

 Table created.

SQL

Step 3 - Now that the same objects are created with data in all 3 PDB's, I can now do a combined query from the root PDB.  The next step is create a table in the CDB (root PDB) that is empty.

create table c##bgrenn.local_objects as select * from dba_objects where 1=0;

create table c##bgrenn.local_tables as select * from dba_tables where 1=0;

Table created.

Table created.

Then finally query and see the rows in the local_objects tables across all the PDB's

select count(*) from containers(c##bgrenn.local_objects) where con_id in (3) ;
  COUNT(*)
----------
     90925
select count(*) from containers(c##bgrenn.local_objects) where con_id in (4) ;
  COUNT(*)
----------
     90923
select count(*) from containers(c##bgrenn.local_objects) where con_id in (5) ;
  COUNT(*)
----------
     90925
select count(*) from containers(c##bgrenn.local_objects)  ;
 
  COUNT(*)
----------
    272773

Step 4 - Now to  look at the explain plan for one of the tables across containers

SET LINESIZE 130
SET PAGESIZE 0
SELECT * FROM table(DBMS_XPLAN.DISPLAY);
SQL> SQL> Plan hash value: 1439328272

----------------------------------------------------------------------------------------------------------------------
| Id  | Operation                   | Name       | Rows  | Bytes | Cost (%CPU)| Pstart| Pstop |    TQ  |IN-OUT| PQ Distrib |
----------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT            |            |     1 |   381 |     0   (0)|       |       |        |      |         |
|   1 |  PX COORDINATOR     |       |            |       |       |            |       |       |        |      |
|   2 |   PX SEND QC (RANDOM)       | :TQ10000   |     1 |   381 |            |       |       |  Q1,00 | P->S | QC (RAND)  |
|   3 |    PX PARTITION LIST ALL    |            |     1 |   381 |            |     1 |   254 |  Q1,00 | PCWC |         |
|   4 |     FIXED TABLE FULL        | X$CDBVW$   |     1 |   381 |            |       |       |  Q1,00 | PCWP |         |
----------------------------------------------------------------------------------------------------------------------

Finally, this is the explain plan for a join query to get all the tables

explain plan for
select *
  from containers(c##bgrenn.local_objects) a,
       containers(c##bgrenn.local_tables) b
where
  a.object_name = b.table_name and
  a.object_type = 'TABLE';

SET LINESIZE 150
SET PAGESIZE 0
SELECT * FROM table(DBMS_XPLAN.DISPLAY);

  2    3    4    5    6    7  
Explained.

SQL> SQL> SQL> SQL> Plan hash value: 198107036

-------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                    | Name      | Rows  | Bytes | Cost (%CPU)| Time     | Pstart| Pstop |    TQ    |IN-OUT| PQ Distrib |
-------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |           |     1 |  1226 |     0     (0)| 00:00:01|       |       |        |      |        |
|   1 |  PX COORDINATOR              |           |       |       |            |           |       |       |        |      |        |
|   2 |   PX SEND QC (RANDOM)        | :TQ10002  |     1 |  1226 |     0     (0)| 00:00:01|       |       |  Q1,02 | P-S  | QC (RAND)  |
|*  3 |    HASH JOIN BUFFERED        |           |     1 |  1226 |     0     (0)| 00:00:01|       |       |  Q1,02 | PCWP |        |
|   4 |     PX RECEIVE               |           |     1 |   381 |            |           |       |       |  Q1,02 | PCWP |        |
|   5 |      PX SEND HYBRID HASH     | :TQ10000  |     1 |   381 |            |           |       |       |  Q1,00 | P-P  | HYBRID HASH|
|   6 |       STATISTICS COLLECTOR   |           |       |       |            |           |       |       |  Q1,00 | PCWC |        |
|   7 |        PX PARTITION LIST ALL |           |     1 |   381 |            |           |     1 |   254 |  Q1,00 | PCWC |        |
|*  8 |     FIXED TABLE FULL         | X$CDBVW$  |     1 |   381 |            |           |       |       |  Q1,00 | PCWP |        |
|   9 |     PX RECEIVE               |           |     1 |   845 |            |           |       |       |  Q1,02 | PCWP |        |
|  10 |      PX SEND HYBRID HASH     | :TQ10001  |     1 |   845 |            |           |       |       |  Q1,01 | P-P  | HYBRID HASH|
|  11 |       PX PARTITION LIST ALL  |           |     1 |   845 |            |           |     1 |   254 |  Q1,01 | PCWC |        |
|  12 |        FIXED TABLE FULL      | X$CDBVW$  |     1 |   845 |            |           |       |       |  Q1,01 | PCWP |        |
-------------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   3 - access("A"."OBJECT_NAME"="B"."TABLE_NAME")
   8 - filter("A"."OBJECT_TYPE"='TABLE')

25 rows selected.

This looks like a very useful feature to get a high level view of all PDB's.  The things to note are.

1) You need to use a common user and this user needs to be the schema owner in all PDB's
2) By looking at the plan, I'm sure there is some high level view that does this using partitions.

Performance tuning using Oracle Internal Packages

I had an interesting problem last week with a customer who was performance testing on a new system compared to their current system.

The script was pretty simple. It was a PL/SQL package that inserted into a table 10M rows, and committed every 1,000 rows.  To make the data more "normal" the customer used DBMS_RANDOM .

The basic insert looked like this.

INSERT INTO TEST_TABLE1
     (ID,DTVAL,
      DTSTAMP,
      COL1,
      NUM)
VALUES
    (:B1 ,
      SYSDATE,
      SYSTIMESTAMP,
      DBMS_RANDOM.STRING('A', 100),
      DBMS_RANDOM.RANDOM);

To me it seemed like a simple test.  Unfortunately the performance results were not as expected.    To step back for a minute the current system was running on 11.1.0.7 and the new system they were benchmarking against was 11.2.0.4.

I even had them check the output of the  Table to ensure no changes in the output.. Everything looked the same.

You wouldn't think that would matter, but the differences in DBMS_RANDOM between versions seemed to be issue.  You see DBMS_RANDOM periodically has logic changes, and the performance of DBMS_RANDOM cannot be compared between versions in a performance benchmark.

I had the customer re-run the tests with constants instead of calling DBMS_RANDOM and the results were much better.

To reproduce what they saw  I finally tested against 11.2.0.2 and  12.1.0.1 (on the same machine).  I could not get a copy of 11.1.0.7 and 11.2.0.4 to test.  These 2 versions were enough to see the difference that affected the Customers Benchmark.

Below I've included the TKPROF formatted output from the trace file on 11.2.0.2

SQL ID: fg7gf0m6a2ca4 Plan Hash: 0

INSERT INTO TEST_TABLE1 (ID,DTVAL,DTSTAMP,COL1,NUM)
VALUES
(:B1 , SYSDATE, SYSTIMESTAMP, DBMS_RANDOM.STRING('A', 100),
  DBMS_RANDOM.RANDOM)


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.00          0          0          0           0
Execute 100000     25.81      39.51          0       2464     119161      100000
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total   100001     25.81      39.51          0       2464     119161      100000

Notice the CPU time.. 25.81 seconds of CPU time on 11.2.0.2

Below is the TKPROF formatted output from the trace file on 12..1.0.1

INSERT INTO TEST_TABLE1 (ID,DTVAL,DTSTAMP,COL1,NUM)
VALUES
(:B1 , SYSDATE, SYSTIMESTAMP, DBMS_RANDOM.STRING('A', 100),
  DBMS_RANDOM.RANDOM)


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.00          0          0          0           0
Execute 100000     74.01      90.31          1       3722     111116      100000
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total   100001     74.01      90.31          1       3722     111116      100000

This time notice that it 74.01 seconds of CPU.. Same statement executed the same number of times..

The difference between the 2 versions is almost 3X longer in 12.1.0.1

No I re-ran it with constants

11.2.0.2 Test

INSERT INTO TEST_TABLE1 (ID,DTVAL,DTSTAMP,COL1,NUM)
VALUES
(:B1 , SYSDATE, SYSTIMESTAMP, 'a', 1)


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.00          0          0          0           0
Execute 100000      4.62       6.02          0        536     108087      100000
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total   100001      4.62       6.02          0        536     108087      100000

12.1.0.1 test

INSERT INTO TEST_TABLE1 (ID,DTVAL,DTSTAMP,COL1,NUM)
VALUES
(:B1 , SYSDATE, SYSTIMESTAMP, 'a', 1)


call     count       cpu    elapsed       disk      query    current        rows
------- ------  -------- ---------- ---------- ---------- ----------  ----------
Parse        1      0.00       0.00          0          0          0           0
Execute 100000      4.78       7.09          1        586     105731      100000
Fetch        0      0.00       0.00          0          0          0           0
------- ------  -------- ---------- ---------- ---------- ----------  ----------
total   100001      4.78       7.09          1        586     105731      100000

Wow.. Now that I use constants, the CPU time was almost identical.

There are absolutely some major performance differences with DBMS_RANDOM between versions.

Moral of the story is don't use internal packages for benchmarking (unless they are critical to your application).



Finally, this is the package code I used for testing..

OWNER        SET TIME ON
SET TIMING ON
SET ECHO ON
SET SERVEROUTPUT ON
SET TERMOUT ON
SET VERIFY ON
SET FEEDBACK ON

WHENEVER SQLERROR CONTINUE

select to_char(sysdate,'mm/dd/yyyy hh:mi:ss AM') from dual;


prompt create the test_table1

drop table test_table1;

create table test_table1
(
id NUMBER,
dtval DATE,
dtstamp TIMESTAMP,
col1 varchar2(100),
num NUMBER
);   

prompt Insert 1M with commit every 1000 records

alter session set tracefile_identifier = 'test_sess_1';
exec dbms_monitor.session_trace_enable( waits => true );


DECLARE
 x  PLS_INTEGER;
 rn NUMBER(20); 
BEGIN

  SELECT hsecs
  INTO rn
  FROM v$timer;
  
  dbms_random.initialize(rn);
  FOR i IN 1..100000
  LOOP
    x := dbms_random.random;
    rn := x; 
    
    insert into test_table1 (id,dtval,dtstamp,col1,num)
    values(x, sysdate, systimestamp, DBMS_RANDOM.string('A', 100), dbms_random.random);
    
    If ( MOD(i,100) = 0) then
        commit;
    end if;
    
  END LOOP;
  dbms_random.terminate;
END;
/

EXEC DBMS_MONITOR.session_trace_disable;

prompt Count of all records

select count(*) from test_table1;
select count(distinct col1) from test_table1 ;
select count(distinct num) from test_table1 ;