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

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CHAPTER 14 ■ PARALLEL EXECUTION 627 • There are certain declarative referential-integrity constraints that are not supported during the PDML, since each slice of the table is modified as a separate transaction in the separate session. Self-referential integrity is not supported, for example. Consider the deadlocks and other locking issues that would occur if it were supported. • You cannot access the table you’ve modified with PDML until you commit or roll back. • Advanced replication is not supported with PDML (because the implementation of advanced replication is trigger based). • Deferred constraints (i.e., constraints that are in the deferred mode) are not supported. • PDML may only be performed on tables that have bitmap indexes or LOB columns if the table is partitioned, and then the degree of parallelism would be capped at the number of partitions. You cannot parallelize an operation within partitions in this case, as each partition would get a single parallel execution server to operate on it. • Distributed transactions are not supported when performing PDML. • Clustered tables are not supported with PDML. If you violate any of those restrictions, one of two things will happen: either the statement will be performed serially (no parallelism will be involved) or an error will be raised. For example, if you already performed the PDML against table T and then attempted to query table T before ending your transaction, then you will receive an error. Parallel DDL I believe that parallel DDL is the real “sweet spot” of Oracle’s parallel technology. As we’ve discussed, parallel execution is generally not appropriate for OLTP systems. In fact, for many data warehouses, parallel query is becoming less and less of an option. It used to be that a data warehouse was built for a very small, focused user community—sometimes consisting of just one or two analysts. However, over the last decade I’ve watched them grow from small user communities to user communities of hundreds or thousands. Consider a data warehouse front-ended by a web-based application: it could be accessible to literally thousands or more users instantly. But a DBA performing the large batch operations, perhaps during a maintenance window, is a different story. The DBA is still a single individual and he might have a huge machine with tons of computing resources available. The DBA has only “one thing to do”: load this data, reorganize that table, rebuild that index. Without parallel execution, the DBA would be hardpressed to really use the full capabilities of the hardware. With parallel execution, he can. The following SQL DDL commands permit “parallelization”: • CREATE INDEX: Multiple parallel execution servers can scan the table, sort the data, and write the sorted segments out to the index structure. • CREATE TABLE AS SELECT: The query that executes the SELECT may be executed using parallel query, and the table load itself may be done in parallel. • ALTER INDEX REBUILD: The index structure may be rebuilt in parallel.
628 CHAPTER 14 ■ PARALLEL EXECUTION • ALTER TABLE MOVE: A table may be moved in parallel. • ALTER TABLE SPLIT|COALESCE PARTITION: The individual table partitions may be split or coalesced in parallel. • ALTER INDEX SPLIT PARTITION: An index partition may be split in parallel. The first four of these commands work for individual table/index partitions as well—that is, you may MOVE an individual partition of a table in parallel. To me, parallel DDL is where the parallel execution in Oracle is of greatest measurable benefit. Sure, it can be used with parallel query to speed up certain long-running operations, but from a maintenance standpoint, and from an administration standpoint, parallel DDL is where the parallel operations affect us, DBAs and developers, the most. If you think of parallel query as being designed for the end user for the most part, then parallel DDL is designed for the DBA/developer. Parallel DDL and Data Loading Using External Tables One of my favorite new features in Oracle 9i is external tables, which are especially useful in the area of data loading. We’ll cover data loading and external tables in some detail in the next chapter but, as a quick introduction, we’ll take a brief look at these topics here to study the effects of parallel DDL on extent sizing and extent trimming. External tables allow us to easily perform parallel direct path loads without thinking too hard about it. Oracle 7.1 gave us the ability to perform parallel direct path loads, whereby multiple sessions could write directly to the Oracle data files, bypassing the buffer cache entirely, bypassing undo for the table data, and perhaps even bypassing redo generation. This was accomplished via SQL*Loader. The DBA would have to script multiple SQL*Loader sessions, split the input data files to be loaded manually, determine the degree of parallelism, and coordinate all of the SQL*Loader processes. In short, it could be done, but it was hard. With parallel DDL plus external tables, we have a parallel direct path load that is implemented via a simple CREATE TABLE AS SELECT or INSERT /*+ APPEND */. No more scripting, no more splitting of files, and no more coordinating the N number of scripts that would be running. In short, this combination provides pure ease of use, without a loss of performance. Let’s take a look at a simple example of this in action. We’ll see shortly how to create an external table. We’ll look at data loading with external tables in much more detail in the next chapter. For now, we’ll use a “real” table to load another table from, much like many people do with staging tables in their data warehouse. The technique in short is as follows: 1. Use some extract, transform, load (ETL) tool to create input files. 2. Load these input files into staging tables. 3. Load a new table using queries against these staging tables. We’ll use the same BIG_TABLE from earlier, which is parallel-enabled and contains 10 million records. We’re going to join this table to a second table, USER_INFO, which contains OWNERrelated information from the ALL_USERS dictionary view. The goal is to denormalize this information into a flat structure.
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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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