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

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CHAPTER 13 ■ PARTITIONING 605 Sure enough, we see a similar effect for the INDEX RANGE SCAN. Our indexes are used and can provide high-speed OLTP access to the underlying data. If they were partitioned, they would have to be prefixed and enforce index partition elimination; hence, they are scalable as well, meaning we can partition them and observe the same behavior. In a moment, we’ll look at what would happen if we used LOCAL indexes only. Lastly, let’s look at the area of availability. The Oracle documentation claims that globally partitioned indexes make for “less available” data than locally partitioned indexes. I don’t fully agree with this blanket characterization. I believe that in an OLTP system they are as highly available as a locally partitioned index. Consider the following: ops$tkyte@ORA10G> alter tablespace p1 offline; Tablespace altered. ops$tkyte@ORA10G> alter tablespace p2 offline; Tablespace altered. ops$tkyte@ORA10G> alter tablespace p3 offline; Tablespace altered. ops$tkyte@ORA10G> select empno, job, loc from emp where empno = 7782; EMPNO JOB LOC ---------- --------- ------------- 7782 MANAGER NEW YORK Here, even though most of the underlying data is unavailable in the table, we can still gain access to any bit of data available via that index. As long as the EMPNO we want is in a tablespace that is available, and our GLOBAL index is available, our GLOBAL index works for us. On the other hand, if we had been using the “highly available” local index in the preceding case, we might have been prevented from accessing the data! This is a side effect of the fact that we partitioned on LOC but needed to query by EMPNO. We would have had to probe each local index partition and would have failed on the index partitions that were not available. Other types of queries, however, will not (and cannot) function at this point in time: ops$tkyte@ORA10G> select empno, job, loc from emp where job = 'CLERK'; select empno, job, loc from emp where job = 'CLERK' * ERROR at line 1: ORA-00376: file 13 cannot be read at this time ORA-01110: data file 13: '/home/ora10g/oradata/.../o1_mf_p2_1dzn8jwp_.dbf' The CLERK data is in all of the partitions, and the fact that three of the tablespaces are offline does affect us. This is unavoidable unless we had partitioned on JOB, but then we would have had the same issues with queries that needed data by LOC. Anytime you need to access the data from many different “keys,” you will have this issue. Oracle will give you the data whenever it can.
606 CHAPTER 13 ■ PARTITIONING Note, however, that if the query can be answered from the index, avoiding the TABLE ACCESS BY ROWID, the fact that the data is unavailable is not as meaningful: ops$tkyte@ORA10G> select count(*) from emp where job = 'CLERK'; COUNT(*) ---------- 4 Since Oracle didn’t need the table in this case, the fact that most of the partitions were offline doesn’t affect this query. As this type of optimization (i.e., answer the query using just the index) is common in an OLTP system, there will be many applications that are not affected by the data that is offline. All we need to do now is make the offline data available as fast as possible (restore it and recover it). Partitioning and Performance, Revisited Many times I hear people say, “I’m very disappointed in partitioning. We partitioned our largest table and it went much slower. So much for partitioning being a performance increasing feature.” Partitioning can do one of the following three things to overall query performance: • Make your queries go faster • Not impact the performance of your queries at all • Make your queries go much slower and use many times the resources as the nonpartitioned implementation In a data warehouse, with an understanding of the questions being asked of the data, the first bullet point is very much achievable. Partitioning can positively impact queries that frequently full scan large database tables by eliminating large sections of data from consideration. Suppose you have a table with 1 billion rows in it. There is a timestamp attribute. Your query is going to retrieve one years’ worth of data from this table (and it has ten years of data). Your query uses a full table scan to retrieve this data. Had it been partitioned by this timestamp entry—say, a partition per month—then you could have full scanned one-tenth the data (assuming a uniform distribution of data over the years). Partition elimination would have removed the other 90 percent of the data from consideration. Your query would likely run faster. Now, take a similar table in an OLTP system. You would never retrieve 10 percent of a 1 billion row table in that type of application. Therefore, the massive increase in speed seen by the data warehouse just would not be achievable in a transactional system. You are not doing the same sort of work, and the same possible improvements just are not realistic. Therefore, in general, in your OLTP system the first bullet point is not achievable, and you won’t be applying partitioning predominantly for increased performance. Increased availability— absolutely. Administrative ease of use—very much so. But in an OLTP system, I say you have to work hard to make sure you achieve the second point: that you do not impact the performance of your queries at all, negatively or positively. Many times, your goal is to apply partitioning without affecting query response time.
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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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Setting Up Your Environment In this
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CHAPTER 11 ■ ■ ■ Indexes Inde
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