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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. 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.
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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.
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CHAPTER 10 DATABASE TABLES
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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 since there will be many tables in the cluster, and they will be on the same block. Having different PCTFREEs would not make sense. Therefore, a CREATE CLUSTER statement looks a lot like a CREATE TABLE statement with a small number of columns (just the cluster key columns): ops$tkyte@ORA11GR2> create cluster emp_dept_cluster 2 ( deptno number(2) ) 3 size 1024 4 / Cluster created. Here, we have created an index cluster (the other type being a hash cluster, which we ll look at in the next section Index Clustered Tables Wrap-up ). The clustering column for this cluster will be the DEPTNO column. The columns in the tables do not have to be called DEPTNO but they must be NUMBER(2) to match this definition. We have, on the cluster definition, a SIZE 1024 option. This is used to tell Oracle that we expect about 1,024 bytes of data to be associated with each cluster key value. Oracle will use that to compute the maximum number of cluster keys that could fit per block. Given that we have an 8KB block size, Oracle will fit up to seven cluster keys (but maybe less if the data is larger than expected) per database block. For example, the data for departments 10, 20, 30, 40, 50, 60, and 70 would tend to go onto one block, and as soon as we insert department 80, a new block will be used. This does not mean that the data is stored in a sorted manner; it just means that if we inserted the departments in that order, they would naturally tend to be put together. If we inserted the departments in the order 10, 80, 20, 30, 40, 50, 60, and then 70, the final department (70) would tend to be on the newly added block. As we ll see below, both the size of the data and the order in which the data is inserted will affect the number of keys we can store per block. The SIZE parameter therefore controls the maximum number of cluster keys per block. It is the single largest influence on the space utilization of our cluster. Set the size too high, and we ll get very few keys per block and we ll use more space than we need. Set the size too low, and we ll get excessive chaining of data, which offsets the purpose of the cluster to store all of the data together on a single block. It is the most important parameter for a cluster.
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