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

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CHAPTER 10 ■ DATABASE TABLES 369 In this situation, regardless of the size of the data stored in it, Z will be stored “out of line” in the overflow segment. Which is better, then: PCTTHRESHOLD, INCLUDING, or some combination of both? It depends on your needs. If you have an application that always, or almost always, uses the first four columns of a table and rarely accesses the last five columns, using INCLUDING would be appropriate. You would include up to the fourth column and let the other five be stored out of line. At runtime, if you need them, the columns will be retrieved in much the same way as a migrated or chained row would be. Oracle will read the “head” of the row, find the pointer to the rest of the row, and then read that. If, on the other hand, you cannot say that you almost always access these columns and hardly ever access those columns, you should give some consideration to PCTTHRESHOLD. Setting PCTTHRESHOLD is easy once you determine the number of rows you would like to store per index block on average. Suppose you wanted 20 rows per index block. Well, that means each row should be one-twentieth (5 percent). Your PCTTHRESHOLD would be 5, and each chunk of the row that stays on the index leaf block should consume no more than 5 percent of the block. The last thing to consider with IOTs is indexing. You can have an index on an IOT itself— sort of like having an index on an index. These are called secondary indexes. Normally, an index contains the physical address of the row it points to, the rowid. An IOT secondary index cannot do this; it must use some other way to address the row. This is because a row in an IOT can move around a lot, and it does not “migrate” in the way a row in a heap organized table would. A row in an IOT is expected to be at some position in the index structure, based on its primary key value; it will only be moving because the size and shape of the index itself is changing. (We’ll cover more about how index structures are maintained in the next chapter.) To accommodate this, Oracle introduced a logical rowid. These logical rowids are based on the IOT’s primary key. They may also contain a “guess” as to the current location of the row, although this guess is almost always wrong because after a short while, data in an IOT tends to move. The guess is the physical address of the row in the IOT when it was first placed into the secondary index structure. If the row in the IOT has to move to another block, the guess in the secondary index becomes “stale.” Therefore, an index on an IOT is slightly less efficient than an index on a regular table. On a regular table, an index access typically requires the I/O to scan the index structure and then a single read to read the table data. With an IOT, typically two scans are performed: one on the secondary structure and the other on the IOT itself. That aside, indexes on IOTs provide fast and efficient access to the data in the IOT using columns other than the primary key. Index Organized Tables Wrap-Up Getting the right mix of data on the index block versus data in the overflow segment is the most critical part of the IOT setup. Benchmark various scenarios with different overflow conditions, and see how they will affect your INSERTs, UPDATEs, DELETEs, and SELECTs. If you have a structure that is built once and read frequently, stuff as much of the data onto the index block as you can. If you frequently modify the structure, you will have to achieve some balance between having all of the data on the index block (great for retrieval) versus reorganizing data in the index frequently (bad for modifications). The freelist consideration you had for heap tables applies to IOTs as well. PCTFREE and PCTUSED play two roles in an IOT. PCTFREE is not nearly as important for an IOT as for a heap table, and PCTUSED doesn’t come into play normally.
370 CHAPTER 10 ■ DATABASE TABLES When considering an OVERFLOW segment, however, PCTFREE and PCTUSED have the same interpretation as they do for a heap table; set them for an overflow segment using the same logic as you would for a heap table. Index Clustered Tables I generally find people’s understanding of what a cluster is in Oracle to be inaccurate. Many people tend to confuse a cluster with a SQL Server or Sybase “clustered index.” They are not the same. A cluster is a way to store a group of tables that share some common column(s) in the same database blocks and to store related data together on the same block. A clustered index in SQL Server forces the rows to be stored in sorted order according to the index key, similar to an IOT as just described. With a cluster, a single block of data may contain data from many tables. Conceptually, you are storing the data “prejoined.” It can also be used with single tables, where you are storing data together grouped by some column. For example, all of the employees in department 10 will be stored on the same block (or as few blocks as possible, if they all don’t fit). It is not storing the data sorted—that is the role of the IOT. It is storing the data clustered by some key, but in a heap. So, department 100 might be right next to department 1, and very far away (physically on disk) from departments 101 and 99. Graphically, you might think of it as shown in Figure 10-8. On the left side of the image, we are using conventional tables. EMP will be stored in its segment. DEPT will be stored on its own. They may be in different files and different tablespaces, and they are definitely in separate extents. On the right side of the image, we see what would happen if we clustered these two tables together. The square boxes represent database blocks. We now have the value 10 factored out and stored once. Then, all of the data from all of the tables in the cluster for department 10 is stored in that block. If all of the data for department 10 does not fit on the block, then additional blocks will be chained to the original block to contain the overflow, in the same fashion as the overflow blocks for an IOT. Figure 10-8. Index clustered data So, let’s look at how we might go about creating a clustered object. Creating a cluster of tables in the object is straightforward. The definition of the storage of the object (PCTFREE, PCTUSED, INITIAL, and so on) is associated with the CLUSTER, not the tables. This makes sense aving
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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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CHAPTER 1 ■ ■ ■ Developing Su
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CHAPTER 1 ■ DEVELOPING SUCCESSFUL
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CHAPTER 3 ■ ■ ■ Files In this
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CHAPTER 3 ■ FILES 71 all operatio
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CHAPTER 3 ■ FILES 89 A Brief Revi
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CHAPTER 3 ■ FILES 91 Redundant Ar
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CHAPTER 3 ■ FILES 93 (data from m
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CHAPTER 3 ■ FILES 95 dictionary t
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CHAPTER 4 ■ ■ ■ Memory Struct
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CHAPTER 4 ■ MEMORY STRUCTURES 117
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CHAPTER 5 ■ ORACLE PROCESSES 157
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284 CHAPTER 9 ■ REDO AND UNDO cri
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CHAPTER 11 ■ ■ ■ Indexes Inde
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CHAPTER 11 ■ INDEXES 423 value of
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CHAPTER 11 ■ INDEXES 431 The data
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CHAPTER 11 ■ INDEXES 445 Indicate
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CHAPTER 11 ■ INDEXES 447 an index
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CHAPTER 11 ■ INDEXES 449 Table 11
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CHAPTER 13 ■ ■ ■ Partitioning
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706 ■INDEX autonomous transaction
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Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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