Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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CHAPTER 14 ■ PARALLEL EXECUTION 641 3 ( user, 'T1', numrows=>10000000,numblks=>100000 ); 4 end; 5 / PL/SQL procedure successfully completed. ops$tkyte-ORA10G> create table t2 2 as 3 select t1.*, 0 session_id 4 from t1 5 where 1=0; Table created. We used DBMS_STATS to “trick” the optimizer into thinking that there are 10,000,000 rows in that input table and that it consumes 100,000 database blocks. We want to simulate a big table here. The second table, T2, is simply a copy of the first table’s structure with the addition of a SESSION_ID column. That column will be useful to actually “see” the parallelism that takes place. Next, we need to set up object types for our pipelined function to return. The object type is simply a structural definition of the “output” of the procedure we are converting. In this case, it looks just like T2: ops$tkyte-ORA10G> CREATE OR REPLACE TYPE t2_type 2 AS OBJECT ( 3 id number, 4 text varchar2(30), 5 session_id number 6 ) 7 / Type created. ops$tkyte-ORA10G> create or replace type t2_tab_type 2 as table of t2_type 3 / Type created. And now for the pipelined function, which is simply the original PROCESS_DATA procedure rewritten. The procedure is now a function that produces rows. It accepts as an input the data to process in a ref cursor. The function returns a T2_TAB_TYPE, the type we just created. It is a pipelined function that is PARALLEL_ENABLED. The partition clause we are using says to Oracle, “Partition, or slice up, the data by any means that work best. We don’t need to make any assumptions about the order of the data.” You may also use hash or range partitioning on a specific column in the ref cursor. That would involve using a strongly typed ref cursor, so the compiler knows what columns are available. Hash partitioning would just send equal rows to each parallel execution server to process based on a hash of the column supplied. Range partitioning would send nonoverlapping ranges of data to each parallel execution server, based on the partitioning key. For example, if you range partitioned on ID, each parallel execution server might get ranges 1. . .1000, 1001. . .20000, 20001. . .30000, and so on (ID values in that range).
642 CHAPTER 14 ■ PARALLEL EXECUTION Here, we just want the data split up. How the data is split up is not relevant to our processing, so our definition looks like this: ops$tkyte-ORA10G> create or replace 2 function parallel_pipelined( l_cursor in sys_refcursor ) 3 return t2_tab_type 4 pipelined 5 parallel_enable ( partition l_cursor by any ) We’d like to be able to see what rows were processed by which parallel execution servers, so we’ll declare a local variable L_SESSION_ID and initialize it from V$MYSTAT: 6 7 is 8 l_session_id number; 9 l_rec t1%rowtype; 10 begin 11 select sid into l_session_id 12 from v$mystat 13 where rownum =1; Now we are ready to process the data. We simply fetch out a row (or rows, as we could certainly use BULK COLLECT here to array process the ref cursor), perform our complex process on it, and pipe it out. When the ref cursor is exhausted of data, we close the cursor and return: 14 loop 15 fetch l_cursor into l_rec; 16 exit when l_cursor%notfound; 17 -- complex process here 18 pipe row(t2_type(l_rec.id,l_rec.text,l_session_id)); 19 end loop; 20 close l_cursor; 21 return; 22 end; 23 / Function created. And that’s it. We’re ready to process the data in parallel, letting Oracle figure out based on the resources available what the most appropriate degree of parallelism is: ops$tkyte-ORA10G> alter session enable parallel dml; Session altered. ops$tkyte-ORA10G> insert /*+ append */ 2 into t2(id,text,session_id) 3 select * 4 from table(parallel_pipelined 5 (CURSOR(select /*+ parallel(t1) */ * 6 from t1 ) 7 ))
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Expert Oracle Database Architecture
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Contents Foreword . . . . . . . . .
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■CONTENTS v Block Buffer Cache .
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■CONTENTS vii ■CHAPTER 9 Redo a
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■CONTENTS ix ■CHAPTER 12 Dataty
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Foreword “THINK.” In 1914, Thom
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■FOREWORD xiii Tom is an aficiona
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About the Technical Reviewers ■JO
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Introduction The inspiration for th
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■INTRODUCTION xix • Exposure to
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■INTRODUCTION xxi Chapter 3: File
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■INTRODUCTION xxiii Next up are t
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Setting Up Your Environment In this
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■SETTING UP YOUR ENVIRONMENT xlii
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CHAPTER 1 ■ ■ ■ Developing Su
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CHAPTER 1 ■ DEVELOPING SUCCESSFUL
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CHAPTER 4 ■ MEMORY STRUCTURES 117
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CHAPTER 5 ■ ORACLE PROCESSES 157
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CHAPTER 8 ■ ■ ■ Transactions
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338 CHAPTER 10 ■ DATABASE TABLES
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CHAPTER 11 ■ ■ ■ Indexes Inde
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Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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