New Term: The Oracle Relational Database Management System, or RDBMS, is designed to allow simultaneous access to large amounts of stored information. The RDBMS consists of the database (the information) and the instance (the embodiment of the system). The database contains the physical files that reside on the system and the logical pieces such as the database schema. These database files take various forms, as described in the following section. The instance is the method used to access the data and consists of processes and system memory.
NOTE: Object extensions have been added to the RDBMS with Oracle8. The object extension to tables is covered in detail on Day 12, "Working with Tables, Views, and Synonyms." Oracle refers to Oracle8 as an O-RDBMS (Object-Relational Database Management System). In this book, I refer to Oracle as an RDBMS for clarity.
The Oracle database has a logical layer and a physical layer. The physical layer consists of the files that reside on the disk; the components of the logical layer map the data to these physical components.
The physical layer of the database consists of three types of files:
The logical layer of the database consists of the following elements:
New Term: The database is divided into one or more logical pieces known as tablespaces. A tablespace is used to logically group data together. For example, you can create one tablespace for accounting and a separate tablespace for purchasing. Segmenting groups into different tablespaces simplifies the administration of these groups (see Figure 2.1). Tablespaces consist of one or more datafiles. By using more than one datafile per tablespace, you can spread data over many different disks to distribute the I/O load and improve performance.
The relationship between the database, tablespaces, and datafiles.
As part of the process of creating the database, Oracle automatically creates the SYSTEM tablespace for you. Although a small database can fit within the SYSTEM tablespace, it's recommended that you create a separate tablespace for user data. The SYSTEM tablespace is where the data dictionary is kept. The data dictionary contains information about tables, indexes, clusters, and so on.
Datafiles can be operating system files or, in the case of some operating systems, RAW devices. Datafiles and data access methods are described in detail on Day 12.
New Term: The database schema is a collection of logical-structure objects, known as schema objects, that define how you see the database's data. These schema objects consist of structures such as tables, clusters, indexes, views, stored procedures, database triggers, and sequences.
NOTE: A new feature in Oracle8 is the index-only table. In an index-only table, the data and index are stored together. This is discussed in detail on Day 13, "Using Indexes and Sequences."
Within Oracle, the space used to store data is controlled by the use of logical structures. These structures consist of the following:
Segments, extents, and data blocks.
An Oracle database can use four types of segments:
Extents are the building blocks of segments; in turn, they consist of data blocks. An extent is used to minimize the amount of wasted (empty) storage. As more and more data is entered into tablespaces in your database, the extents used to store that data can grow or shrink as necessary. In this manner, many tablespaces can share the same storage space without preallocating the divisions between those tablespaces.
At tablespace-creation time, you can specify the minimum number of extents to allocate as well as the number of extents to add at a time when that allocation has been used. This arrangement gives you efficient control over the space used in your database.
Data blocks are the smallest pieces of an Oracle database; they are physically stored on disk. Although the data block in most systems is 2KB (2,048 bytes), you can change this size for efficiency depending on your application or operating system.
NOTE: Oracle blocks do not need to be, and may not be the same as, operating system data blocks. In fact, in most cases they are not.
The Oracle instance consists of the Oracle processes and shared memory necessary to access information in the database. The instance is made up of the user processes, the Oracle background processes, and the shared memory used by these processes (see Figure 2.3).
New Term: Oracle uses shared memory for several purposes, including caching of data and indexes as well as storing shared program code. This shared memory is broken into various pieces, or memory structures. The basic memory structures associated with Oracle are the System Global Area (SGA) and the Program Global Area (PGA).
The Oracle instance.
The SGA is a shared memory region that Oracle uses to store data and control information for one Oracle instance. The SGA is allocated when the Oracle instance starts and deallocated when the Oracle instance shuts down. Each Oracle instance that starts has its own SGA. The information in the SGA consists of the following elements, each of which has a fixed size and is created at instance startup:
The database buffer cache--This stores the most recently used data blocks. These blocks can contain modified data that has not yet been written to disk (sometimes known as dirty blocks), blocks that have not been modified, or blocks that have been written to disk since modification (sometimes known as clean blocks). Because the buffer cache keeps blocks based on a most recently used algorithm, the most active buffers stay in memory to reduce I/O and improve performance.
The Library Cache
The library cache is used to store shared SQL. Here the parse tree and the execution plan for every unique SQL statement are cached. If multiple applications issue the same SQL statement, the shared SQL area can be accessed by each to reduce the amount of memory needed and to reduce the processing time used for parsing and execution planning.
The Data-Dictionary Cache
The data dictionary contains a set of tables and views that Oracle uses as a reference to the database. Oracle stores information here about the logical and physical structure of the database. The data dictionary contains information such as the following:
The data dictionary is frequently accessed by Oracle for the parsing of SQL statements. This access is essential to the operation of Oracle; performance bottlenecks in the data dictionary affect all Oracle users. Because of this, you should make sure that the data-dictionary cache is large enough to cache this data. If you do not have enough memory for the data-dictionary cache, you see a severe performance degredation. If you ensure that you have allocated sufficient memory to the shared pool where the data-dictionary cache resides, you should see no performance problems.
The PGA is a memory area that contains data and control information for the Oracle server processes. The size and content of the PGA depends on the Oracle server options you have installed. This area consists of the following components:
New Term: In many operating systems, traditional processes have been replaced by threads or lightweight processes. The term process is used in this book to describe a thread of execution, or a mechanism that can execute a set of code; process refers to the mechanism of execution and can refer to a traditional process or a thread.
The Oracle RDBMS uses two types of processes: user processes and Oracle processes (also known as background processes). In some operating systems (such as Windows NT), these processes are actually threads; for the sake of consistency, I will refer to them as processes.
User, or client, processes are the user's connections to the RDBMS system. The user process manipulates the user's input and communicates with the Oracle server process through the Oracle program interface. The user process is also used to display the information requested by the user and, if necessary, can process this information into a more useful form.
Oracle processes perform functions for users. Oracle processes can be split into two groups: server processes (which perform functions for the invoking process) and background processes (which perform functions on behalf of the entire RDBMS).
Server Processes (Shadow Processes)
Server processes, also known as shadow processes, communicate with the user and interact with Oracle to carry out the user's requests. For example, if the user process requests a piece of data not already in the SGA, the shadow process is responsible for reading the data blocks from the datafiles into the SGA. There can be a one-to-one correlation between user processes and shadow processes (as in a dedicated server configuration); although one shadow process can connect to multiple user processes (as in a multithreaded server configuration), doing so reduces the utilization of system resources.
Background processes are used to perform various tasks within the RDBMS system. These tasks vary from communicating with other Oracle instances and performing system maintenance and cleanup to writing dirty blocks to disk. Following are brief descriptions of the nine Oracle background processes:
New Term: To give you a better idea how Oracle operates, this section analyzes a sample transaction. Throughout this book, the term transaction is used to describe a logical group of work that can consist of one or many SQL statements and must end with a commit or a rollback. Because this example is of a client/server application, SQL*Net is necessary. The following steps are executed to complete the transaction:
2. The server picks up the connection request and creates a server process on behalf of the user.
3. The user executes a SQL statement or statements. In this example, the user changes the value of a row in a table.
4. The server process checks the shared pool to see whether there is a shared SQL area that has this identical SQL statement. If it finds an identical shared SQL area, the server process checks whether the user has access privileges to the data. If so, the server process uses the shared SQL area to process the request. If a shared SQL area is not found, a new shared SQL area is allocated, and the statement is parsed and executed.
5. The server process finds the data in the SGA (if it is present there) or reads the data from the datafile into the SGA.
6. The server process modifies the data in the SGA. Remember that the server processes can read only from the datafiles. At some later time, the DBWR process writes the modified blocks to permanent storage.
7. The user executes either the COMMIT or ROLLBACK statement. A COMMIT will finalize the transaction, a ROLLBACK will undo the changes. If the transaction is being committed, the LGWR process immediately records the transaction in the redo log file.
8. If the transaction is successful, a completion code is returned across the network to the client process. If a failure has occurred, an error message is returned.
NOTE: A transaction is not considered committed until the write to the redo log file is complete. This arrangement ensures that in the event of a system failure, a committed transaction can be recovered. If a transaction has been committed, it is set in stone.
While transactions occur, the Oracle background processes do their jobs, keeping the system running smoothly. While this process occurs, hundreds of other users might be performing similar tasks. Oracle's job is to keep the system in a consistent state, to manage contention and locking, and to perform at the necessary rate.
This overview is intended to give you an understanding of the complexity and amount of interaction involved in the Oracle RDBMS. As you look in detail at the tuning of the server processes and applications later in this book, you can use this overview as a reference to the basics of how the Oracle RDBMS operates. Because of the differences in operating systems, minor variances in different environments will be discussed individually.
If the RDBMS is to operate, you must provide for certain functions, including data integrity, recovery from failure, error handling, and so on. This is accomplished via events such as checkpointing, logging, and archiving. The following sections list and describe some of these functions.
You know that Oracle uses either the CKPT background process or the LGWR process to signal a checkpoint; but what is a checkpoint and why is it necessary?
Because all modifications to data blocks are done on the block buffers, some changes to data in memory are not necessarily reflected in the blocks on disk. Because caching is done using a least recently used algorithm, a buffer that is constantly modified is always marked as recently used and is therefore unlikely to be written by the DBWR. A checkpoint is used to ensure that these buffers are written to disk by forcing all dirty buffers to be written out on a regular basis. This does not mean that all work stops during a checkpoint; the checkpoint process has two methods of operation: the normal checkpoint and the fast checkpoint.
In the normal checkpoint, the DBWR merely writes a few more buffers every time it is active. This type of checkpoint takes much longer but affects the system less than the fast checkpoint. In the fast checkpoint, the DBWR writes a large number of buffers at the request of the checkpoint each time it is active. This type of checkpoint completes much quicker and is more efficient in terms of I/Os generated, but it has a greater effect on system performance at the time of the checkpoint.
You can use the time between checkpoints to improve instance recovery. Frequent checkpoints reduce the time required to recover in the event of a system failure. A checkpoint automatically occurs at a log switch.
The redo log records all changes made to the Oracle database. The purpose of the redo log is to ensure that in the event of the loss of a datafile as a result of some sort of system failure, the database can be recovered. By restoring the datafiles back to a known good state from backups, the redo log files (including the archive log files) can replay all the transactions to the restored datafile, thus recovering the database to the point of failure.
When a redo log file is filled in normal operation, a log switch occurs and the LGWR process starts writing to a different redo log file. When this switch occurs, the ARCH process copies the filled redo log file to an archive log file. When this archive process has finished copying the entire redo log file to the archive log file, the redo log file is marked as available. It's critical that this archive log file be safely stored because it might be needed for recovery.
NOTE: Remember that a transaction has not been committed until the redo log file has been written. Slow I/Os to the redo log files can slow down the entire system.
Because one of the roles of the DBA is to anticipate, find, and fix performance problems, you must know what types of things affect performance. To understand why these things affect performance, you must first review the basics of how a computer system works.
Your computer system consists of thousands of individual components that work in harmony to process data. Each of these components has its own job to perform, and each has its own performance characteristics.
The brainpower of the system is the Central Processing Unit (CPU), which processes all the calculations and instructions that run on the computer. The job of the rest of the system is to keep the CPU busy with instructions to process. A well-tuned system runs at maximum performance if the CPU or CPUs are busy 100% of the time.
So how does the system keep the CPUs busy? In general, the system consists of different layers, or tiers, of progressively slower components. Because faster components are typically the most expensive, you must perform a balancing act between speed and cost efficiency.
New Term: The CPU and the CPU's cache are the fastest components of the system. The cache is high-speed memory used to store recently used data and instructions so that it can provide quick access if this data is used again in a short time. Most CPU hardware designs have a cache built into the CPU chip. This internal cache is known as a Level 1 (or L1) cache. Typically, an L1 cache is quite small--8-16KB.
When a certain piece of data is wanted, the hardware looks first in the L1 cache. If the data is there, it's processed immediately. If the data is not available in the L1 cache, the hardware looks in the L2 cache, which is external to the CPU chip but located close to it. The L2 cache is connected to the CPU chip(s) on the same side of the memory bus as the CPU. To get to main memory, you must use the memory bus, which affects the speed of the memory access.
Although the L2 cache is twice as slow as the L1 cache, it's usually much larger. Its larger size means you have a better chance of getting a cache hit. Typical L2 caches range in size from 128KB to 4MB.
Slower yet is the speed of the system memory--it's probably five times slower than the L2 cache. The size of system memory can range from 4MB for a small desktop PC to 2-4GB for large server machines. Some supercomputers have even more system memory than that.
As you can see from the timeline shown in Figure 2.4, there is an enormous difference between retrieving data from the L1 cache and retrieving data from the disk. This is why you spend so much time trying to take advantage of the SGA in memory. This is also why hardware vendors spend so much time designing CPU caches and fast memory buses.
Component speed comparison.
Most instruction processing occurs in the CPU. Although certain intelligent devices, such as disk controllers, can process some instructions, the instructions these devices can handle are limited to the control of data moving to and from the devices. The CPU works from the system clock and executes instructions based on clock signals. The clock rate and type of CPU determine how quickly these instructions are executed.
The CPU usually falls into one of two groups of processors: Complex Instruction Set Computer (CISC) or Reduced Instruction Set Computer (RISC).
CISC processors (like the ones Intel builds) are by far the most popular processors. They are more traditional and offer a large instruction set to the program developer. Some of these instructions can be quite complicated; most instructions require several clock cycles to complete.
CISC processors are complex and difficult to build. Because these chips contain millions of internal components, the components are extremely close together. The physical closeness causes problems because there is no room for error. Each year, technology allows more complex and faster chips to be built, but eventually, physics will limit what can be done.
CISC processors carry out a wide range of tasks and can sometimes perform two or more instructions at a time in parallel. CISC processors perform most tasks, such as RDBMS processing, very well.
RISC processors are based on the principle that if you can reduce the number of instructions processed by the CPU, the CPU can be simpler to build and can run faster. By putting fewer internal components inside the chip, the speed of the chip can be accelerated. One of the most popular RISC chips on the market is the DEC Alpha.
The system compiler determines what instructions are executed on the CPU chips. When the number of instructions was reduced, compilers were written to exploit this and to compensate for the missing instructions.
By reducing the instruction set, RISC manufacturers have been able to increase the clock speed to many times that of CISC chips. Although the faster clock speed is beneficial in some cases, it offers little improvement in others. One effect of a faster CPU is that the surrounding components such as L2 cache and memory must also run faster at an increase in cost.
One goal of some RISC manufacturers is to design the chip so that the majority of instructions complete within one clock cycle. Some RISC chips can already do this. But because some operations that require a single instruction for a CISC chip might require many instructions for a RISC chip, a speed-to-speed comparison cannot be made.
Both CISC and RISC processors have their advantages and disadvantages; it's up to you to determine whether a RISC processor or a CISC processor will work best for you. When comparing the two types of processors, be sure to look at performance data and not just clock speed. Although the RISC chips have a much faster clock speed, they do less work per instruction. The performance of the system cannot be determined by clock speed alone.
Multiprocessor systems can provide significant performance with very good value. With such a system, you can start with one or two processors and add more as needed. Multiprocessors fall into several categories; two of the main types of multiprocessor systems are the Symmetric Multiprocessor (SMP) system and the Massively Parallel Processing (MPP) system.
SMP systems usually consist of a standard computer architecture with two or more CPUs that share the system memory, I/O bus, and disks. The CPUs are called symmetric because each processor is identical to any other processor in terms of function. Because the processors share system memory, each processor looks at the same data and the same operating system. In fact, the SMP architecture is sometimes called tightly coupled because the CPUs can even share the operating system.
In the typical SMP system, only one copy of the operating system runs. Each processor works independently by taking the next available job. Because the Oracle architecture is based on many processes working independently, you can see great improvement by adding processors.
The SMP system has these advantages:
A typical SMP system supports between four and eight CPUs. Because the SMP system shares the system bus and memory, only a certain amount of activity can occur before the bandwidth of the bus is saturated. To add more processors, you must go to an MPP architecture.
MPP systems are based on many independent units. Each processor in an MPP system typically has its own resources (such as its own local memory and I/O system). Each processor in an MPP system runs an independent copy of the operating system and its own independent copy of Oracle. An MPP system is sometimes called loosely coupled.
Think of an MPP system as a large cluster of independent units that communicate through a high-speed interconnect. As with SMP systems, you will eventually hit the bandwidth limitations of the interconnect as you add processors. However, the number of processors with which you hit this limit is typically much larger than with SMP systems.
If you can divide the application among the nodes in the cluster, MPP systems can achieve quite high scalability. Although MPP systems can achieve much higher performance than SMP systems, they are less economical: MPP systems are typically much higher in cost than SMP systems.
Regardless of whether you use a single-processor system, an SMP system, or an MPP system, the basic architecture of the CPUs is similar. In fact, you can find the same Intel processors in both SMP and MPP systems.
As you learned earlier today, the system cache is important to the system. The cache allows quick access to recently used instructions or data. A cache is always used to store and retrieve data more quickly than the next level of storage (the L1 cache is faster than the L2 cache, the L2 cache is faster than main memory, and so on).
By caching frequently used instructions and data, you increase the likelihood of a cache hit. This can save precious clock cycles that would otherwise have been spent retrieving data from memory or disk.
The system memory is basically a set of memory chips, either protected or not protected, that stores data and instructions used by the system. System memory can be protected by parity or by a more sophisticated advanced ECC correction method. Data parity will detect an incorrect value in memory and flag it to the system. An advanced ECC correction method will not only detect an incorrect value in memory, but in many cases can correct it. The system memory can range in size from 4MB on a small PC to 4GB on a large SMP server.
Typically, the more memory available to Oracle, the better your performance. Allocation of a large SGA allows Oracle to cache more data, thus speeding access to that data.
New Term: System memory is accessed by the CPUs through a high-speed bus that allows large amounts of data and instructions to be quickly moved from the CPU to L2 cache. Data and instructions are typically read from memory in large chunks and put into the cache. Because the CPU expects that memory will be read sequentially, in most cases it will read ahead the data or instruction that it thinks will be needed next. Sometimes this works, so the data that is needed next is already in cache; sometimes the CPU has guessed incorrectly and other data needs to be retrieved. This process of prereading the data is known as prefetching.
Depending on the specific implementation of an SMP system, the memory bus might be shared by all system processors; alternatively, each processor might have a private bus to memory.
New Term: In a virtual memory system, the OS and hardware allow programs and users to use more memory than is actually available in the system hardware. This memory, known as virtual memory, can be mapped to physical memory. Code or data that is being run by the CPU must reside in physical memory. If a program or data that is larger than physical memory is being accessed, the parts of code and data that are not immediately needed by the program can reside in virtual memory, not physical memory. As that bit of code or data is needed, it can be copied into physical memory, and parts no longer needed can be copied to disk. The process of mapping virtual memory onto physical memory by copying the memory to and from disk is called paging or swapping (depending on the OS architecture).
Both paging and swapping serve the same purpose, but each operates slightly differently from the other. In a swapping system, an entire process is swapped out (moved from memory to disk) or swapped in (moved from disk to memory). In a paging system, the movement of data to and from the secondary storage occurs on a memory page basis; when more memory is needed, one or more pages is paged out (moved from memory to disk) to make room. A memory page is the smallest unit of memory that is used in the operating system. A typical memory page size is 4KB. If data is requested from virtual memory and is not in physical memory, that data is paged in (moved from disk to memory) as needed. The rest of this section uses the term paging to describe both paging and swapping.
Suppose you have a computer system with 16MB of physical memory. If you have a program that needs to access 20MB of data, it obviously won't fit in physical memory. In a virtual memory system, the data is read until little memory remains (the OS reserves some for itself), then the OS copies some of the data pages to disk with the paging mechanism. This is usually done using a least recently used algorithm in which the oldest data is moved out. When some memory has been freed, the program can read more data into memory. As far as the program is concerned, all the data is still in memory; in fact, it is--in virtual memory. As the program begins to reread some of the data and manipulate it, different pieces might be paged in (from disk to physical memory) and paged out (from physical memory to disk).
As you can imagine, paging in or out can be time consuming and uses a lot of system resources. This is why I warn you several times in this book to avoid using so much memory that you cause paging or swapping. Access to disk is approximately 50 times slower than access to memory.
New Term: Simply put, bus is a connection path used by the system to move data from one place to another. Buses get complicated when you look at them from a performance perspective: Capacity, or bandwidth, becomes an issue. Over the years, the term bandwidth, which was originally used to describe the electronic characteristics of a circuit, has been adopted by computer designers. In this case, bandwidth refers to the amount of data that can be transmitted across a bus in a certain time.
Several bus designs have been introduced in the last few years, all with the same goal: increased capacity. As processors, network hardware, disk controllers, and disks become increasingly fast, buses must develop to support the load generated by these devices. Thankfully, as computers have increased in performance, computer designers have improved bus designs to accommodate these changes. The system bus should not be a bottleneck in your system.
The Oracle DBMS allocates different resources for various different functions, including the allocation of system memory. The memory might be allocated for database caching or for the data dictionary or library cache. The careful balance of this precious resource is very important in tuning the Oracle RDBMS.
As much data as possible must be cached to avoid the additional cost of going to disk. If you allocate a large Oracle data cache, a higher cache-hit rate can be achieved. A high cache-hit rate indicates that a large percentage of requested data is found in the Oracle cache rather than retrieved from disk.
Application design can affect performance more than any other factor. In most cases, performance can be severely degraded by an application that does not have well-tuned SQL statements or does not use indexes. A good application design can also significantly improve performance. The application is typically the first place to look when you experience system performance problems.
If a database is built with indexes on a certain set of columns but those columns are not specified in the WHERE clause of the SQL statement, the index probably won't be used. It's not enough to create the correct index on tables; you must ensure that the indexes are used.
TIP: It's wise to create a specification identifying the tables and indexes in your database. That way, the application developers and the team that creates the database have a crystal-clear document that identifies which columns are indexed. This can help avoid confusion and allow the application code to fully exploit the indexes.
Another way to improve Oracle performance is to enable Oracle performance features. Among the most important of these features (and my personal favorite) is the Oracle Parallel Query option. Other Oracle performance features include partitioned tables and the Oracle index-only table, both new in Oracle8.
The Oracle Parallel Query option allows parallelism of many different operations, which greatly enhances performance. The Oracle Parallel Query option consists of several different components, including
The Oracle parallel query allows a single query to be divided into components and run in parallel. Because a query spends much of its time waiting for I/O operations to complete, parallelizing queries can greatly improve performance. In a well-tuned system where I/O is not a problem, parallel queries can run many times faster than normal queries. Statements that can be parallelized include
NOTE: You might be wondering why parallelizing operations would help performance; after all, the work must still be done. In a typical Oracle operation (for example, a SELECT statement), the following steps occur:
2. Oracle submits an I/O request to disk (assuming that the data is not already in the SGA) and then waits for that I/O to complete.
3. This operation is repeated until all data is retrieved.
In the case of a parallel query, these steps would be adjusted like so:
2. Different Oracle processes or threads receive their instructions on what data is needed.
3. Oracle thread 1 submits an I/O request to disk (if that data is not already in the SGA) and waits for that I/O to complete.
4. Oracle thread 2 submits an I/O request to disk (if that data is not already in the SGA) and waits for that I/O to complete.
5. Oracle thread 3 submits an I/O request to disk (if that data is not already in the SGA) and waits for that I/O to complete.
As shown here, that the time-consuming job of retrieving data from disk is duplicated, thus improving performance. This parallelism allows the CPU(s) to be utilized while other threads are waiting for I/Os.
Retrieving data from disk is a slow process compared to the activity of the CPU, and your goal is to keep the CPUs busy. Because a significant part of any Oracle operation involves CPU processing and I/Os, it is possible and desirable to keep the CPUs busy while many I/Os are being processed simultaneously. This is the main goal of the Parallel Query option.
Index creation involves reading from data tables and then writing to the index tables. Because the parallel query allows reading of tables to be accelerated, the index-creation process is sped up. Index creations can be quite time consuming, so this can be a real advantage.
Recovery from a system failure can be quite time consuming. During recovery, users must usually wait for the system to come back online, so any improvement in performance is an advantage. Parallel recovery can speed the recovery process by parallelizing the read from the redo log files, and the roll forward and rollback process.
Although the Oracle Parallel Query option does not generally allow table creations to occur, it is often the case when a table is created as a subset of other tables. Data is often reduced from several large tables into a smaller subset, and this parallelism can be beneficial. In such instances, the following statement allows for parallelism:
CREATE TABLE table_name AS SELECT...
New to Oracle8, the index table allows indexes and tables to be stored together; this saves space and improves performance by reducing disk I/O. If you reduce the number of required disk I/Os, data can be accessed much faster.
New Term: In most systems, few resources can be allocated in the operating system. Most OS parameters are changed only to allocate sufficient resources to Oracle; additional resources usually do not improve performance. A lack of resources, however, can decrease performance. OS resources often refers to system memory or, in the case of UNIX, shared memory. Other OS resources and tunables include network buffers and disk I/O tunables.
TIP: Windows NT is fairly self tunable, but there are a few things, relating primarily to configuration, to look out for:
Several hardware factors can affect your system's performance. These factors include
Earlier today you saw an overview of how the system hardware operates. Clearly, any operation that must access slower components, such as a disk or network, will slow down processing. Therefore, it is important that you have sufficient memory in your system.
New Term: Most hardware architectures are limited to 4GB of physical memory, but some architectures on the market support much more. These architectures are said to support a VLM, or Very Large Memory, architecture. Soon it will be possible to support hundreds of gigabytes of physical memory in a system, allowing for very fast RDBMS operations.
System memory is allocated to Oracle and used for database caching, user memory, and the shared pool, which is used for both the data dictionary and the library cache. You must have enough memory for the shared pool because an insufficient shared pool can hurt performance. When the shared pool is satisfied, the more database buffers you can allocate to the DBMS the better. Be careful, though, to avoid starving the PGA memory needed by your processes, and avoid paging at all costs. You can never have too much memory in your system. Anything that can be cached will reduce system I/O, improving performance.
Number of CPUs
Oracle typically scales well with additional CPUs. By adding CPUs you can see significant performance improvement with little additional cost. Some factors that determine how much improvement you will see by adding more processors are the CPU cache and memory- bus bandwidth.
A large CPU cache allows more data and executable code to be stored on the local processor than in memory. This reduces the number of times the CPU must access main memory. Whenever the CPU accesses memory, a slowdown occurs while the CPU waits for that data or code to be retrieved. It is especially bad when the memory bus is busy; the CPU waits even longer until the bus becomes free.
The memory-bus bandwidth determines how quickly data can be transferred between CPU to memory. If the memory bus is busy when data or code is needed, a CPU stalls waiting for the bus to free. This can severely degrade performance in a multiprocessor computer. A fast memory bus can reduce this problem. A large CPU cache can also reduce this problem by allowing more data and code to be cached.
I/O is typically one of the biggest factors limiting system performance. Because most DBMS operations involve retrieving data from disk, I/O can be a limiting factor if you do not have adequate capacity for your system load. Fortunately, you can usually solve this problem by carefully configuring your system for proper I/O distribution and by having sufficient I/O capacity. Simply having adequate disk space is insufficient; you must also have enough disk drives to support the number of disk I/Os that the system requires.
Oracle8 has introduced many new features, and I would like to focus on a few key features for the Oracle8 DBA:
Partitioned objects allow Oracle objects, such as tables and indexes, to be broken into smaller, more manageable pieces. Partitioning these objects allows many operations that could normally be performed on only a table or an index to be divided into operations on a partition. By dividing these operations, you can often increase the parallelism of those operations, thus improving performance and minimizing system downtime.
Partitions are enabled via the PARTITION BY RANGE parameter of the CREATE TABLE statement. In this manner, ranges of data are assigned to each individual partition like so:
CREATE TABLE emp ( name CHAR(30), address CHAR(40), region INTEGER ) PARTITION BY RANGE ( region) ( PARTITION VALUES LESS THAN (10) TABLESPACE tbl0, PARTITION VALUES LESS THAN (20) TABLESPACE tbl1, PARTITION VALUES LESS THAN (30) TABLESPACE tbl2 );
This creates a table with partitioning, as shown in Figure 2.5.
Partitioning is recommended for large tables because it makes them much more manageable. Oracle does not currently support partitioning of clusters. By partitioning a table, you can break that large table into several much smaller pieces. A partitioned table can take advantage of some of the following features:
Parallel INSERT, DELETE, and UPDATE operations can occur on a partition basis. Using partitions allows these operations to be conducted either globally or locally within a partition.
Partitioning allows operations such as exports and imports to be performed on a partition basis. This can reduce the time required by some maintenance operations, such as reorganization of data or reclustering. This also allows you to change the physical layout of your database on a partition basis. If you limit the scope of export and import operations, they can benefit from a large degree of parallelism.
Range partitioning is a method whereby the partitioning of data is done based on the value of the data itself. This allows for tremendous flexibility in distributing data based on ranges of data values. Range partitioning allows you to partition high-volume data separately from low-volume data or to separate current from old data.
New Term: A local index indexes data that resides in only one partition. A global index indexes data that resides on more than one partition. This allows for great flexibility in terms of adding new indexes, reducing index sizes, and allowing for partition independence.
An example of where local indexing might be beneficial is a table where sales records are stored. Using table and index partitioning, you can store data and indexes separately based on calendar months; doing this allows reduced index size and faster index lookups for entries of a particular month. If you partition these entries you can add new months and delete outdated entries without reindexing the entire table. You could keep 12 months of partitions and indexes online in this manner.
With a partitioned table, SQL*Loader can either load an entire table in parallel by partition or simply load a single partition. Either method provides great flexibility.
If you use the conventional path load, the loader automatically distributes the data to the correct partition and updates the local and global indexes. You can also use the loader to load a partitioned table or a partition of a table. Again, indexes are built automatically. It is also possible to direct-load a partition in parallel provided that no global indexes exist, but you must rebuild the local indexes yourself.
The arrival of Oracle8 has heralded tremendous improvement in the area of parallelization. In addition to the new parallel features listed previously, some existing parallel operations have been extended.
Parallel recovery has been improved by allowing rollbacks of parallel DML operations that have failed to be performed in parallel. This parallel transaction recovery is supported on transaction and process failures but not during instance recovery.
New parallel hints have been added for parallel insert operations. The APPEND hint tells the optimizer to append the insert data beyond the high water mark of the segment.
The index-only table is new in Oracle8. With traditional indexes and tables, data and indexes are stored separately. With an index-only table, the data to which the index refers is stored in the leaf block or lowest level block of the index, so the data and indexes are stored together. Depending on your application, this can be an advantage.
Applications that access data primarily via a key value can see an advantage from the use of index-only tables. Because the data is stored within the index, the data is immediately available when the index has reached its lowest level. This can speed data retrieval.
Applications that do not access data primarily via a key value will see no improvement; indeed, performance will likely be degraded in these applications. Any application that involves table scans or requires multiple indexes will not benefit from the index table. The index table is covered in much more detail on Day 13.
Oracle has made tremendous improvements in the areas of backup and recovery. Most of these new features revolve around the Recovery Manager. Another recovery feature in Oracle8 is the image copy backup, which can improve recovery time in the event of a failure.
New Term: Recovery Manager is an online utility designed to assist the DBA with all backup and recovery operations. Not only does it perform the backup and recovery, it maintains a database called the recovery catalog that stores information about these operations.
An image copy backup essentially allows you to copy a datafile to another place on disk or to another disk on your system. In the event of a failure, no recovery is necessary from the image copy; you must simply switch to that backup copy. You must, however, perform a recovery to make that copy current. In the event of a failure, this might be the fastest way to recover.
NOTE: Days 16-18 cover backup and recovery techniques in greater detail.
As part of the overview of the Oracle system, I would like to briefly cover the optional available Oracle products. Although many of these products are covered elsewhere in this book, you should at least aware of their existence. The Oracle product line is divided into three areas:
The Oracle server is the DBMS itself, and includes many options and features such as the Parallel Query option, network protocols, and advanced system administration options. Some of the key options available to the Oracle server include
NOTE: Throughout this book, Enterprise Manager is referenced as the primary method for administering the system. Nonetheless, command-line management is also covered.
One of Oracle's strongest points has been its development tools. Not only are these tools robust and full featured, they are flexible as well. When client/server systems became popular in the early 1990s, the Oracle tools quickly adapted. When HTML and Java applications became popular in the mid-1990s, the Oracle development tools quickly adapted yet again. The adaptability of these tools guarantees that applications developed with them can be quickly adjusted for new uses and technologies. Oracle provides the following tools:
Oracle's application software falls into two main categories: traditional applications and newer OLAP (Online Analytical Processing) applications.
Traditional Oracle Applications
Oracle's suite of traditional applications is used to perform basic and essential business tasks. These applications are used by many of the world's largest companies. The suite provides support for the following areas:
The OLAP applications provide a graphical interface for DSS and data-warehousing applications. These tools lend a multidimensional model to the database, providing analysis, forecasting, and statistical operations.
Oracle offers many other products that are not mentioned here. These products handle various tasks such as networking, office automation, workgrouping, and so on. Although these products and services are too numerous to cover here, rest assured that Oracle's full line can handle most (if not all) of your database and communication needs.
Today's lesson presents an overview of the Oracle architecture, including the physical structure (consisting of datafiles, redo log files, and control files) and the Oracle instance (consisting of processes and memory). Next you saw how a computer system works and how it depends on components such as cache memory to improve performance. Finally, you reviewed some of Oracle's products to get an idea of the different areas in which the Oracle server is used. This lesson set the foundation for many of the later lessons in this book. By having an understanding of the inner workings of Oracle, you will be better able to administer the Oracle DBMS.
You'll spend tomorrow installing the Oracle8 server. The key to the installation process is understanding what components you are installing and why you are installing them.
A The main hardware components that affect performance are the speed of the CPU(s), the amount of memory, and the I/O subsystem.
Q What happens if a failure corrupts the redo log files?
A If redo log files are lost, you cannot recover the database. All changes made since the last backup will be lost. This is why redo log files should be on protected or fault-tolerant disk drives.
Q What happens if a failure corrupts the datafiles?
A When a datafile is lost, the corrupted file can be restored from a backup. After the datafile is restored, the redo log files and archive log files can reapply any changes made before the time of the failure. No data is lost.
Q Why does parallelizing a query make things faster?
A Most of the realtime or clock-time processing a query operation is spent waiting for I/Os to complete. Parallelizing a query enables you to keep the CPUs busy while you are waiting.
This workshop provides quiz questions to help you solidify your understanding of the material covered. Answers to quiz questions can be found in Appendix A, "Answers."
2. What makes up the Oracle instance?
3. Which is faster--memory or disk?
4. Name two new features of Oracle8.
© Copyright, Macmillan Computer Publishing. All rights reserved.