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

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CHAPTER 10 ■ DATABASE TABLES 389 Creating a sorted hash cluster is much the same as the other clusters. To set up a sorted hash cluster capable of storing the above data, we could use the following: ops$tkyte@ORA10G> CREATE CLUSTER shc 2 ( 3 cust_id NUMBER, 4 order_dt timestamp SORT 5 ) 6 HASHKEYS 10000 7 HASH IS cust_id 8 SIZE 8192 9 / Cluster created. We’ve introduced a new keyword here: SORT. When we created the cluster, we identified the HASH IS CUST_ID and we added an ORDER_DT of type timestamp with the keyword SORT. This means the data will be located by CUST_ID (where CUST_ID=:X) and physically retrieved and sorted by ORDER_DT. Technically, it really means we’ll store some data that will be retrieved via a NUMBER column and sorted by the TIMESTAMP. The column names here are not relevant, as they were not in the B*Tree or HASH clusters, but convention would have us name them after what they represent. The CREATE TABLE for our CUST_ORDERS would look like this: ops$tkyte@ORA10G> CREATE TABLE cust_orders 2 ( cust_id number, 3 order_dt timestamp SORT, 4 order_number number, 5 username varchar2(30), 6 ship_addr number, 7 bill_addr number, 8 invoice_num number 9 ) 10 CLUSTER shc ( cust_id, order_dt ) 11 / Table created. We’ve mapped the CUST_ID column of this table to the hash key for the sorted hash cluster and the ORDER_DT column to the SORT column. We can observe using AUTOTRACE in SQL*Plus that the normal sort operations we expect are missing when accessing the sorted hash cluster: ops$tkyte@ORA10G> set autotrace traceonly explain ops$tkyte@ORA10G> variable x number ops$tkyte@ORA10G> select cust_id, order_dt, order_number 2 from cust_orders 3 where cust_id = :x 4 order by order_dt;
390 CHAPTER 10 ■ DATABASE TABLES Execution Plan ---------------------------------------------------------- 0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=0 Card=4 Bytes=76) 1 0 TABLE ACCESS (HASH) OF 'CUST_ORDERS' (CLUSTER (HASH)) ops$tkyte@ORA10G> select job, hiredate, empno 2 from scott.emp 3 where job = 'CLERK' 4 order by hiredate; Execution Plan ---------------------------------------------------------- 0 SELECT STATEMENT Optimizer=ALL_ROWS (Cost=3 Card=3 Bytes=60) 1 0 SORT (ORDER BY) (Cost=3 Card=3 Bytes=60) 2 1 TABLE ACCESS (BY INDEX ROWID) OF 'EMP' (TABLE) (Cost=2 Card=3 ... 3 2 INDEX (RANGE SCAN) OF 'JOB_IDX' (INDEX) (Cost=1 Card=3) ops$tkyte@ORA10G> set autotrace off I added the query against the normal SCOTT.EMP table (after indexing the JOB column for this demonstration) to compare what we normally expect to see: the SCOTT.EMP query plan versus what the sorted hash cluster can do for us when we want to access the data in a FIFO mode (like a queue). As you can see, the sorted hash cluster has one step: it takes the CUST_ID=:X, hashes the input, finds the first row, and just starts reading the rows, as they are in order already. The regular table is much different: it finds all the JOB='CLERK' rows (which could be anywhere in that heap table), sorts them, and then returns the first one. So, the sorted hash cluster has all the retrieval aspects of the hash cluster, in that it can get to the data without having to traverse an index, and many of the features of the IOT, in that the data will be sorted within that key by some field of your choice. This data structure works well when the input data arrives “in order” by the sort field, by key. That is, over time the data arrives in increasing sort order for any given key value. Stock information fits this requirement as an example. Every night you get a new file full of stock symbols, the date (the date would be the sort key and the stock symbol would be the hash key), and related information. You receive and load this data in sort key order. The stock data for stock symbol ORCL for yesterday does not arrive after today—you would load yesterday’s value, and then today’s value, and later tomorrow’s value. If the information arrives randomly (not in sort order), this data structure quickly breaks down during the insert process, as much data has to be moved to put the rows physically in order on disk. A sorted hash cluster is not recommended in that case (an IOT, on the other hand, could well be useful for that data). When considering using this structure, you should employ the same considerations from the hash cluster section, in addition to the constraint that the data should arrive sorted for each key value over time. Nested Tables Nested tables are part of the object-relational extensions to Oracle. A nested table, one of the two collection types in Oracle, is very similar to a child table in a traditional parent/child table
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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 xxiii Next up are t
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CHAPTER 13 ■ ■ ■ Partitioning
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