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DB2® Universal Database™ (UDB) is the first multimedia, Web-ready relational database management system that is strong enough to meet the demands of large corporations and flexible enough to serve small- and medium-sized businesses. DB2 product family software together with Internet technology makes information easily accessible, available, and secure across diverse platforms. There are more than 60 million DB2 users from over 300,000 companies worldwide relying on IBM data management solutions.
DB2 UDB powers the most demanding e-business applications, such as electronic commerce, enterprise resource planning, customer relationship management, supply-chain management, Web self-service, and business intelligence. It is the scalable, industrial-strength database ideal as the data management foundation for your evolution into e-business.
Online transaction processing (OLTP) is a class of application that facilitates and manages transaction-oriented applications, typically for data-entry and retrieval transactions in a number of industries, including banking, airlines, mail order, supermarkets, and manufacturers. Typically, an OLTP workload consists of many concurrently running short transactions. Today's online transaction processing increasingly requires support for transactions that span a network and may include more than one company. For this reason, new OLTP software uses client/server processing and brokering software that allows transactions to run on different computer platforms in a network.
Performance is one of the most important factors in any type of database system. This article focuses on a number of DB2 performance tuning tips based on lessons learned from running OLTP-type performance benchmarks (TPC-C, TPC-W, Trade2, etc.). Although performance of a database application can influenced by many factors, we focus on configuration rather than on such things as capacity planning, database design, or application design.
This article is organized as follows:
Updating catalog statistics, which emphasizes the importance of collecting and maintaining up-to-date database statistics, the lack of which is often the source of many of the performance problems.
Monitoring and tuning database configuration parameters, which describes a list of database manager parameters and database parameters in the order of importance. Normally it's not necessary to go through the whole list to achieve your performance goal. You can just try several of them at the top of the list to see if there's any performance improvement.
With these tips, you can get your OLTP application up and running with reasonably good performance.
- Have enough memory.
- For a 32-bit system, use at least 512 MB of RAM per CPU, up to 4 GB per machine, to support the buffer pools, DB2 agents, and other shared memory objects required for a large number of concurrent users. (See Buffer pool size (BUFFPAGE) for more information on buffer pools.) More memory may be needed to support applications that run locally or as stored procedures. On AIX®, additional memory can be used by the JFS file cache to supplement the buffer pool.
- For a 64-bit system, the buffer pool can be practically any size. However, for most e-commerce OLTP applications that use a large database, the buffer pool doesn't really need to be more than 8 GB. Bigger is still better, but at some point you'll experience diminishing returns as the buffer pool hit ratio moves to the 98+% range. The number of concurrent users (with its impact on the number of DB2 agents) determines how much more memory is required.
- The amount of memory required by each user connection into the database (that is, a DB2 agent) depends on the nature of the SQL statements performed by the application -- such as the number of concurrent cursors opened and the amount of sorting and temp space required. For OLTP applications, there should be less sorting and temp space required and only a handful of concurrent cursors opened at a time.
Rule of thumb: Use a minimum of 1 MB for UNIX and 500 KB for Windows for each DB2 agent. If fenced stored procedures are used, then each user connection has two DB2 agents, in addition to the memory required to run the stored procedure application.
- Have sufficient I/O handling capability.
- There must be enough disk arms to ensure sufficient I/O parallelism to support a high volume of concurrent transactions. There should be at least 5 to 10 disks per CPU for a moderate workload, and 20 disks for a high-I/O OLTP workload. The operating system (including paging space), DB2 logs, and DB2 table spaces should each have their own dedicated disks. There should be multiple disks for the DB2 logs, for tables, and for indexes.
- The proper way to estimate the I/O handling capability that is needed for good performance is actually to prototype the transactions and find out how many I/Os are required per transaction, and how many transactions per second are required. Then find out the I/O rate for the disk controller and the disk subsystem to help determine how many controllers and disks are required.
- Have sufficient network bandwidth.
There must be enough network bandwidth to support the workload. Make sure that the network or any intermediate hubs are not a bottleneck. This is especially significant when supporting access from remote location. For example, a T1 line supports 1.544 Mbit/sec, which is only 0.193 MB/sec, whereas a typical 10 Mbit/sec thernet LAN can support 6x the throughput at 1.25 MB/sec. Use commands such as netstat on UNIX to monitor the traffic volumes on your connections.
- Use the DB2 Performance Configuration Wizard from the DB2
Control Center to set up the initial DB2 Database Manager and
Database Configuration parameters.
This tool will ask you a series of questions about the nature of the workload to determine a starting set of configuration parameter values. You can modify these parameters to suit your production workload.
- Index your table columns appropriately.
- Ensure that columns that are joined in queries have indexes.
- It can improve performance if columns involved in ORDER BY and GROUP BY are indexed.
- Frequently accessed data can also be included within an index as INCLUDED columns.
- Use the Index Advisor (also known as Index Wizard from the DB2 Control Center) to help determine a good set of indexes to use, based on the tables and SQL statements that you use.
- Ensure that applications hold locks for as short a time as possible.
- When a user operation involves multiple interactions, each interaction should have its own transaction to commit and should free up all locks before returning activity to the user. Keep the duration of a transaction as short as possible by starting its first SQL statement (which starts a transaction) as late as possible, and its updates (inserts, updates, and deletes, which use exclusive locks) as close to the commit stage as possible.
- Use of the DB2 registry parameter DB2_RR_TO_RS can improve concurrency by not locking the next key of the row that was inserted or updated. This can be used if the isolation level RR (Repeatable Read) is not used by any programs that operate on the same set of tables. Use DB2 Snapshot to monitor the number of deadlocks and lock waits.
- Use stored procedures or compound SQL to minimize the network
- Minimizing the number of network trips for your SQL statements will save on network latency and context switches, which can result in the application holding onto locks for a shorter period of time Generally, a stored procedure should be used when an OLTP transaction has more than 4 or 5 statements.
- On the other hand, if there is some complicated CPU-intensive processing involved in the application logic, leaving this in a stored procedure running on the database server can use up excessive CPU cycles on the database server at the expense of database operations. In this case, either do not use stored procedure, or execute part of the logic in the client side and execute the rest in a stored procedure.
- Use SQL efficiently.
- In general, don't use multiple SQL statements where one will do. When you provide more detailed search conditions by having more predicates in a query, the optimizer has a chance to make better choices. You should also be selective in your query so that the database does not return more rows and columns than you need. For example, use SQL to filter the rows you want; don't return all the rows and then require the application to do the filtering.
- Analyze the access plan.
- Use Visual Explain or db2exfmt to analyze each SQL statement. Make sure appropriate indexes are used to minimize the rows that have to be fetched internally when selecting and joining tables.
Updating catalog statistics
The RUNSTATS utility updates statistics in the system catalog tables to help with the query optimization process. Without these statistics, the database manager could make a decision that would adversely affect the performance of an SQL statement. The RUNSTATS utility allows you to collect statistics on the data contained in the tables, indexes, or both tables and indexes. Use the RUNSTATS utility to collect statistics based on both the table and the index data to provide accurate information to the access plan selection process in the following situations:
- When a table has been loaded with data, and the appropriate indexes have been created.
- When a table has been reorganized with the REORG utility.
- When there have been extensive updates, deletions, and insertions that affect a table and its indexes. ("Extensive" in this case may mean that 10 to 20 percent of the table and index data has been affected.)
- Before binding application programs whose performance is critical.
- When you want to compare new statistics with previous statistics. Running statistics on a periodic basis enables you to discover performance problems at an early stage.
- When the prefetch quantity is changed.
- When you have used the REDISTRIBUTE NODEGROUP utility.
When optimizing SQL queries, the decisions made by the SQL compiler are heavily influenced by the optimizer's model of the database contents. This data model is used by the optimizer to estimate the costs of alternative access paths that can be used to resolve a particular query. A key element in the data model is the set of statistics gathered about the data contained in the database and stored in the system catalog tables. This includes statistics for tables, nicknames, indexes, columns, and user-defined functions (UDFs). A change in the data statistics can result in a change in the choice of access plan selected as the most efficient method of accessing the desired data.
Examples of the statistics available which help define the data model to the optimizer include:
- The number of pages in a table and the number of pages that are not empty.
- The degree to which rows have been moved from their original page to other (overflow) pages.
- The number of rows in a table.
- Statistics about individual columns such as he number of distinct values in a column.
- The degree of clustering of an index; that is, the extent to which the physical sequence of rows in a table follows an index.
- Statistics about the index such as the number of index levels and the number of leaf pages in each index.
- The number of occurrences of frequently used column values.
- The distribution of column values across the range of values present in the column.
- Cost estimates for user-defined functions (UDFs).
RUNSTATS can help you determine how performance is related to changes in your database. The statistics show the data distribution within a table. When used routinely, RUNSTATS provides data about tables and indexes over a period of time, thereby allowing performance trends to be identified for your data model as it evolves over time. Rebind applications that use static SQL after using RUNSTATS so that the query optimizer can choose the best access plan given the new statistics. However, for applications using dynamic SQL (e.g. most vendor applications) rebinding is not necessary since the statement will be optimized based on the statistics at run time. When statistical information about tables is not accurate, it may cause performance problems. In a worst-case scenario, a particular SQL statement may cause DB2 to use a table scan instead of an index scan.
How to update the statistics
Statistics for objects are updated in the system catalog tables only when explicitly requested. There are several ways to update some or all of the statistics:
- Using the RUNSTATS (run statistics) utility.
- Using LOAD, with statistics collection options specified.
- Coding SQL UPDATE statements that operate against a set of predefined catalog views.
- Using the "reorgchk update statistics" command.
When you do not exactly know all the table names, or there are too many, the easiest way to do RUNSTATS is to use the "db2 reorgchk update statistics" command. The exact script looks like this:
db2 -v connect to DB_NAME db2 -v "select tbname, nleaf, nlevels, stats_time from sysibm.sysindexes" db2 -v reorgchk update statistics on table all db2 -v "select tbname, nleaf, nlevels, stats_time from sysibm.sysindexes" db2 -v terminate
The example we chose above does not require table names. This one command performs RUNSTATS on all tables.
Remember: Don't run the RUNSTATS utility until after you have populated the database.
If you know the name of the table and to avoid having large numbers of tables that may take a long time to complete, it's preferable to do RUNSTATS on each table one at a time. The command looks like the following:
db2 -v runstats on table TAB_NAME and indexes all
This will collect statistics by table and all indexes (basic level).
Checking to see if RUNSTATS has been run
One quick way to see whether RUNSTATS has been performed on your database is to query some system catalog tables. For example, as shown in the script above, you can run this command:
db2 -v "select tbname, nleaf, nlevels, stats_time from sysibm.sysindexes"
If RUNSTATS has not yet been run, you will see "-1" for the nleaf and nlevels columns, and a "-" for the stats_time column. These columns contain real numbers if RUNSTATS has been run, and the stats_time column will contain the timestamp when RUNSTATS ran. If you think the time shown in stats_time is too old, it's time to do runstats again.
Monitoring and tuning database configuration parameters
The following tips on database configuration tuning will get you started in an OLTP environment with reasonably good performance and at the same time enable you to avoid obvious pitfalls. Among the configuration parameters, database manager configuration parameters require a restart of the database manager, and most database configuration parameters require the application to reconnnect to the database in order to have the changes take effect. The configuration parameters described here include:
- Buffer pool size
- Log buffer size
- Application heap size
- Sort heap size and sort heap threshold
- Number of agents
- Maximum number of active applications
- Number of asynchronous page cleaners
- Number of I/O servers
- Number of commits to group
Buffer Pool Size
A buffer pool is an area of storage in memory into which database pages (containing table rows or index entries) are temporarily read and changed. The purpose of the buffer pool is to improve database system performance. Data can be accessed much faster from memory than from a disk. Therefore, the fewer times the database manager needs to read from or write to a disk, the better the performance. The configuration of one or more buffer pools is the single most important tuning area, since it is here that most of the data manipulation takes place for applications connected to the database (excluding large objects and long field data).
By default, applications use the buffer pool called IBMDEFAULTBP, which is created when the database is created. The DB2 database configuration parameter BUFFPAGE controls the size of a buffer pool when the value of NPAGES is -1 for that buffer pool in the SYSCAT.BUFFERPOOLS catalog table. Otherwise the BUFFPAGE parameter is ignored, and the buffer pool is created with the number of pages specified by the NPAGES parameter.
For applications that only use one buffer pool, change NPAGES to -1 so that BUFFPAGE controls the size of the buffer pool. This makes it easier to update and report the buffer pool size along with other DB2 database configuration parameters.
After making sure that you can use the BUFFPAGE parameter in the database configuration to control the buffer pool size, set it to a proper value. Setting it to a reasonably large value is a safe thing based on the size of your database and the nature of your application. Usually, the default value of this parameter is very small and may not be satisfactory. Consider the following:
- As a starting point, and if you have enough memory on you your machine, set BUFFPAGE to 40,000 pages (160 MB), or 10% of the total memory on your machine.
- For for a large OLTP database, set aside as much as memory as possible for the buffer pool while keeping the system stable.As a starting point, try 1.6 GB and then experiment with more.
How to change the parameter
Run the following script to:
- Verify the catalog value
- Enable the use of the database configuration parameter BUFFPAGE
- Update the value of BUFFPAGE for all databases.
db2 -v connect to DB_NAME db2 -v select * from syscat.bufferpools db2 -v alter bufferpool IBMDEFAULTBP size -1 db2 -v connect reset db2 -v update db cfg for dbname using BUFFPAGE bigger_value db2 -v terminate
To determine whether the BUFFPAGE parameter is in use for buffer pool size of database, run:
db2 -v connect to DB_NAME db2 -v SELECT * from SYSCAT.BUFFERPOOLS db2 -v connect reset db2 -v terminate
Examine the results. If each buffer pool has an NPAGES value of -1, then the buffer pool size is being controlled through the BUFFPAGE parameter in the database configuration.
To determine whether the database buffer pool size is big enough, collect snapshots for the database and/or buffer pool while running the application. A script similar to the following will give you the needed information:
db2 -v update monitor switches using bufferpool on db2 -v get monitor switches db2 -v reset monitor all -- run your application -- db2 -v get snapshot for all databases > snap.out db2 -v get snapshot for dbm >> snap.out db2 -v get snapshot for all bufferpools >> snap.out db2 -v reset monitor all db2 -v terminate
Make sure that you issue the "db2 -v get snapshot" before you lose your database connection. When the last application disconnects from the database, the database terminates and all snapshot statistics will be lost. To ensure there is always a connection that keeps the database up, use one of the following methods:
- Maintain one separate connection in the window where you are collecting snapshots.
- Use the DB2 ACTIVATE DATABASE command.
In the snapshot output, either from the database snapshot or buffer pool snapshot, look for the following "logical reads" and "physical reads" so that you can calculate the buffer pool hit ratio, which can help you tune your buffer pools:
-- Related lines from a sample of bufferpool snapshots -- Buffer pool data logical reads = 702033 Buffer pool data physical reads = 0 Buffer pool data writes = 414 Buffer pool index logical reads = 168255 Buffer pool index physical reads = 0
The buffer pool hit ratio indicates the percentage of time that the database manager did not need to load a page from disk in order to service a page request; that is, the page was already in the buffer pool. The greater the buffer pool hit ratio, the lower the frequency of disk I/O. Calculate the buffer pool hit ratio as follows:
(1 - ( (buffer pool data physical reads + buffer pool index physical reads) / (buffer pool data logical reads + pool index logical reads) ) ) * 100%
This calculation takes into account all of the pages (index and data) that are cached by the buffer pool. Ideally this ratio should be over 95%, and as close to 100% as possible. To increase the buffer pool hit ration, try the following:
- Increase the buffer pool size.
- Consider allocating multiple buffer pools, possibly one for each frequently-accessed large table with its own table space, and one for a group of small tables, and then experiment with different sizes of buffer pools to see which combination provides the best performance.
Avoid overallocating memory to buffer pools if the memory allocated cannot help performance. The buffer pool sizes should be determined based on snapshot information taken from the test environment.
Log buffer size (LOGBUFSZ)
LOGBUFSZ is a database configuration parameter. It is the parameter for the log buffer. It allows you to specify the amount of database shared memory to use as a buffer for log records before writing these records to disk. The log records are written to disk when one of the following events occurs:
- A transaction commits.
- The log buffer is full.
- As a result of some other internal database manager event.
Buffering the log records results in more efficient log file I/O, because the log records are written to disk less frequently and more log records are written each time. Increase the size of this buffer area if there is considerable read activity on a dedicated log disk, or if there is high disk utilization. When increasing the value of this parameter, consider the DBHEAP parameter, too, because the log buffer area uses space controlled by the DBHEAP parameter.
How to change the parameter
We discovered that the default value for this parameter, 8 (4KB pages), usually is not big enough for an OLTP database. The optimal value for LOGBUFSZ is 128, or 256 4KB pages. For example, you can use the command below to change it:
db2 -v update database cfg for DB_NAME using LOGBUFSZ 256 db2 -v terminate
Use the database snapshot to determine whether the LOGBUFSZ parameter is optimal or not by looking at the lines shown in the following example:
Log pages read = 0 Log pages written = 12644
In general, the ratio between "log pages read" and "log pages written" should be as small as possible. An ideal value would be zero log pages read while seeing a good number of log pages written. When there are too many log pages read, it means a bigger LOGBUFSZ is needed.
Application heap size (APPHEAPSZ)
APPHEAPSZ is a database configuration parameter that definesthe number of private memory pages available to be used by the database manager on behalf of a specific agent or subagent. The heap is allocated when an agent or subagent is initialized for an application. The amount allocated is the minimum amount needed to process the request given to the agent or subagent. As the agent or subagent requires more heap space to process larger SQL statements, the database manager will allocate memory as needed, up to the maximum specified by this parameter.
How to change the parameter
Here is the command to change the default value (128 4KB pages for DB2 EE or 64 4KB pages for DB2 EEE) to the optimal value:
db2 -v update db cfg for DB_NAME using applheapsz 256 db2 -v terminate
When your applications receive an error indicating that there is not enough storage in the application heap, increase the value of APPHEAPSZ.
Sort heap size (SORTHEAP) and sort heap threshold (SHEAPTHRES)
SORTHEAP is a database configuration parameter that defines the maximum number of private memory pages to be used for private sorts, or the maximum number of shared memory pages to be used for shared sorts. If the sort is a private sort, then this parameter affects agent private memory. If the sort is a shared sort, then this parameter affects the database shared memory. Each sort has a separate sort heap that is allocated as needed, by the database manager. This sort heap is the area where data is sorted. If directed by the optimizer, a smaller sort heap than the one specified by this parameter is allocated using information provided by the optimizer.
SHEAPTHRES is a database manager configuration parameter. Private and shared sorts use memory from two different memory sources. The size of the shared sort memory area is statically predetermined at the time of the first connection to a database based on the value of SHEAPTHRES. The size of the private sort memory area is unrestricted. The SHEAPTHRES parameter is applied differently for private and shared sorts:
- For private sorts, SHEAPTHRES is an instance-wide soft limit on the total amount of memory that can be consumed by private sorts at any given time. When the total private-sort memory consumption for an instance reaches this limit, the memory allocated for additional incoming private-sort requests is considerably reduced.
- For shared sorts, SHEAPTHRES is a database-wide hard limit on the total amount of memory consumed by shared sorts at any given time. When this limit is reached, no further shared-sort memory requests are allowed until the total shared-sort memory consumption falls below the limit specified by SHEAPTHRES.
Examples of operations that use the sort heap include hash joins and operations where the table is in memory. Explicit definition of the threshold prevents the database manager from using excessive amounts of memory for large numbers of sorts.
- Use the database system monitor to track sort activity.
- Use appropriate indexes to minimize the use of the sort heap.
- When frequent large sorts are required, increase the value of SORTHEAP.
- If you increase SORTHEAP, determine whether the SHEAPTHRES parameter in the database manager configuration file also needs to be adjusted.
- The sort heap size is used by the optimizer in determining access paths. Consider rebinding applications (using the REBIND PACKAGE command) after changing this parameter.
- Ideally, you should set the sort heap threshold (SHEAPTHRES) parameter to a reasonable multiple of the largest SORTHEAP parameter you have in your database manager instance. This parameter should be at least two times the largest SORTHEAP defined for any database within the instance.
How to change the parameters
To change the values of SORTHEAP and SHEAPTHRES, run the following commands:
-- SORTHEAP should be changed for individual database -- db2 -v update db cfg for DB_NAME using SORTHEAP a_value -- SHEAPTHRES is a database manager parameter -- db2 -v update dbm cfg using SHEAPTHRES b_value db2 -v terminate
OLTP applications should not be performing large sorts. They are too costly in terms of CPU and I/O resource. Usually, the default value for SORTHEAP size (256 4KB pages) is adequate. In fact, for high concurrency OLTP, you may want to decrease this value from the default. When further investigation is needed, you can issue the following command:
db2 -v update monitor switches using sort on
Then, let your application run for a while, and type:
db2 -v get snapshot for database on DBNAME
Look at the output in the following example:
Total sort heap allocated = 0 Total sorts = 1 Total sort time (ms) = 0 Sort overflows = 0 Active sorts = 0 Commit statements attempted = 1 Rollback statements attempted = 0 Dynamic statements attempted = 4 Static statements attempted = 1 Binds/precompiles attempted = 0
From this, you can calculate the number of sorts per transaction and the percentage of sorts that overflowed the memory that was available to them.
SortsPerTransaction = (Total Sorts) / (Commit statements attempted + Rollback statements attempted) PercentSortOverflow = (Sort overflows * 100 ) / (Total sorts)
Rule of thumb: If SortsPerTransaction is greater than 5, it might indicate there are too many sorts per transaction. If PercentSortOverflow is greater than 3 percent, there may be serious and unexpected large sorts occurring. When this happens, increasing SORTHEAP just hides the performance problem--it does not fix it. The true solution to this problem is to improve the access plan for problematic SQL statements by adding the correct indexes.
Number of agents (MAXAGENTS, NUM_POOLAGENTS and NUM_INITAGENTS)
These are database manager configuration parameters.
- The MAXAGENTS parameter indicates the maximum number of database manager agents that are available at any given time to accept application requests. The value of MAXAGENTS should be at least the sum of the values for MAXAPPLS (maximum concurrent applications) in each database to be accessed concurrently. If the number of databases is greater than the NUMDB parameter, then the safest course is to use the product of NUMDB with the largest value for MAXAPPLS. Each additional agent requires some resource overhead that is allocated at the time the database manager is started.
- The NUM_POOLAGENTS parameter is a guideline for how large you
want the agent pool to grow. If more agents are created than is
indicated by the value of this parameter, they will be terminated
when they finish executing their current request, rather than be
returned to the pool. If the value for this parameter is 0, agents
will be created as needed, and may be terminated when they finish
executing their current request.
To avoid the costs associated with the frequent creation and termination of agents in an OLTP environment in which many applications are concurrently connected, increase the value of NUM_POOLAGENTS to be closer to the value of MAXAGENTS.
- The NUM_INITAGENTS parameter determines the initial number of idle agents that are created in the agent pool at DB2START time. Specifying a sizable number of initial agents, while not necessary, can accelerate the warming-up period.
In most cases, set MAXAGENTS and NUM_POOLAGENTS to a value that slightly exceeds the maximum expected number of concurrent application connections.
Leaving NUM_INITAGENTS as the default should be fine.
How to change the parameter
In order to change these parameters, run the following commands:
db2 -v update dbm cfg using MAXAGENTS a_value db2 -v update dbm cfg using NUM_POOLAGENTS b_value db2 -v update dbm cfg using NUM_INITAGENTS c_value db2 -v terminate
Anytime during a run, you can use the following command to get the snapshot data for database manager:
db2 -v get snapshot for database manager
and look for the following lines of output:
High water mark for agents registered = 4 High water mark for agents waiting for a token = 0 Agents registered = 4 Agents waiting for a token = 0 Idle agents = 0 Agents assigned from pool = 5 Agents created from empty pool = 4 Agents stolen from another application = 0 High water mark for coordinating agents = 4 Max agents overflow = 0
If you find that either "Agents waiting for a token" or "Agents stolen from another application" is not equal to 0, you may need to increase MAXAGENTS to allow more agents to be available to the database manager.
Locks (LOCKLIST, MAXLOCKS and LOCKTIMEOUT)
These lock-related controls are database configuration parameters:
- LOCKLIST indicates the amount of storage that is allocated to
the lock list. There is one lock list per database, and it contains
the locks held by all applications concurrently connected to the
database. Locking is the mechanism that the database manager uses
to control concurrent access to data in the database by multiple
applications. Both rows and tables can be locked. Each lock
requires 32 or 64 bytes of the lock list, depending on whether or
not other locks are held on the object:
- 64 bytes are required to hold a lock on an object that has no other locks held on it.
- 32 bytes are required to record a lock on an object that has an existing lock held on it.
- MAXLOCKS defines a percentage of the lock list held by an application that must be filled before the database manager performs lock escalation. When the percentage of the lock list used by one application reaches MAXLOCKS, the database manager escalates the locks, which means it replaces row locks with table locks, thereby reducing the number of locks in the list. When the number of locks held by any one application reaches this percentage of the total lock list size, lock escalation occurs for the locks held by that application. Lock escalation also occurs if the lock list runs out of space. The database manager determines which locks to escalate by looking through the lock list for the application and finding the table with the most row locks. If after replacing these with a single table lock, the MAXLOCKS value is no longer exceeded, lock escalation stops. If not, lock escalation continues until the percentage of the lock list held is below the value of MAXLOCKS. The MAXLOCKS parameter multiplied by the MAXAPPLS parameter cannot be less than 100.
Although the escalation process itself does not take much time, locking entire tables (versus individual rows) decreases concurrency, and overall database performance may decrease for subsequent accesses against the affected tables.
Suggestions for controlling the size of the lock list include:
- Commit frequently to release locks.
- When performing many updates, lock the entire table for the duration of the transaction before updating (using the SQL LOCK TABLE statement). This uses only one lock and keeps others from interfering with the updates, but it does reduce concurrency of the data to other users.
- Use the LOCKSIZE parameter of the ALTER TABLE statement to control how locking is done for a specific table on a permanent basis.
- Examine the isolation level used for the application. Using the Repeatable Read isolation level may result in an automatic table lock in some cases. Use the Cursor Stability isolation level when possible to decrease the number of share locks held. If application integrity requirements are not compromised, use Uncommitted Read instead of Cursor Stability to further decrease the amount of locking.
Use the following steps to determinethe number of pages required for your lock list:
- Calculate a lower bound for the size of your lock list: (512 * 32 * MAXAPPLS) / 4096, where 512 is an estimate of the average number of locks per application and 32 is the number of bytes required for each lock against an object that has an existing lock.
- Calculate an upper bound for the size of your lock list: (512 * 64 * MAXAPPLS) / 4096, where 64 is the number of bytes required for the first lock against an object.
- Estimate the amount of concurrency you will have against your
data and, based on your expectations, choose an initial value for
lock list that falls between the upper and lower bounds that you
Use the database system monitor to tune the MAXLOCKS valuer.
When setting MAXLOCKS, consider the size of the lock list (LOCKLIST):
MAXLOCKS = 100 * (512 locks per application * 32 bytes per lock * 2) / (LOCKLIST * 4096 bytes)
This sample formula allows any application to hold twice the average number of locks. You can increase MAXLOCKS if only a few applications run concurrently, because there will not be a lot of contention for the lock list space under these conditions.
LOCKTIMEOUT specifies the number of seconds that an application will wait to obtain a lock. This helps avoid global deadlocks for applications.
If you set this parameter to 0, the application will not wait for locks. In this situation, if no lock is available at the time of the request, the application immediately receives a -911.
If you set this parameter to -1, lock timeout detection is turned off. In this situation, the application will wait for a lock (if one is not available at the time of the request) until either the lock is granted or until a deadlock occurs.
Set LOCKTIMEOUT to quickly detect waits that are occurring because of an abnormal situation, such as a transaction that is stalled (possibly as a result of a user leaving their workstation.) Set it high enough so that valid lock requests do not time-out because of peak workloads, during which time there is an increased wait for locks.
In an online transaction processing (OLTP) environment, start with a value of 30 seconds. In a query-only environment you could start with a higher value. In either case, use benchmarking techniques to tune this parameter.
How to change the parameters
To change the lock parameters, run the following commands:
db2 -v update db cfg for DB_NAME using LOCKLIST a_number db2 -v update db cfg for DB_NAME using MAXLOCKS b_number db2 -v update db cfg for DB_NAME using LOCKTIMEOUT c_number db2 -v terminate
Once the lock list is full, performance can degrade because lock escalation generates more table locks and fewer row locks, thus reducing concurrency on shared objects in the database. Additionally, there may be more deadlocks between applications (because they are all waiting on a limited number of table locks), which will result in transactions being rolled back. Your application will receive an SQLCODE of -912 when the maximum number of lock requests has been reached for the database. If lock escalations are causing performance concerns you may need to increase the value of LOCKLIST parameter or the MAXLOCKS parameter. You may use the database system monitor to determine if lock escalations are occurring, to track the number of times an application (connection) experienced a lock timeout, or that a database detected a timeout situation for all applications that were connected.
- First, run the following command to turn on the DB2 monitor for
db2 -v update monitor switches using lock on db2 -v terminate
- Then collect your snapshots for the database:
db2 -v get snapshot for database on DB_NAME
- In the snapshot output, examine the following items:
Locks held currently = 0 Lock waits = 0 Time database waited on locks (ms) = 0 Lock list memory in use (Bytes) = 504 Deadlocks detected = 0 Lock escalations = 0 Exclusive lock escalations = 0 Agents currently waiting on locks = 0 Lock Timeouts = 0 Internal rollbacks due to deadlock = 0
If the "Lock list memory in use (Bytes)" exceeds 50 percent of the defined LOCKLIST size, then increase the number of 4KB pages in the LOCKLIST database configuration parameter. The lock escalations, lock timeouts and deadlocks will indicate some potential problems in your system or application. The locking problems normally indicate some fairly significant concurrency problems in the application that should be dealt with before the lock list parameter is increased.
Maximum number of active applications (MAXAPPLS)
MAXAPPLS is a database configuration parameter. It specifies the maximum number of concurrent applications (both local and remote) that can be connected to a database. Because each application that attaches to a database requires some private memory to be allocated, allowing a larger number of concurrent applications will use more memory. The value of this parameter must be equal to or greater than the sum of the connected applications, plus the number of these same applications that may be concurrently in the process of completing a two-phase commit or rollback.
To run an OLTP application, make sure that MAXAPPLS is set to the right value (large enough but not unnecessarily large) to accommodate the maximum concurrent users/connections. For those applications that use connection pooling, we suggest setting MAXAPPLS to the connection pool size plus one or two (just in case you need to invoke command line connection to do something at the same time).
How to change the parameter
To change the value of MAXAPPLS, run the following command:
db2 -v update db cfg for DB_NAME using MAXAPPLS a_number db2 -v terminate
When an application attempts to connect to a database, but the value of MAXAPPLS has already been reached, the following error is returned to the application indicating that the maximum number of applications have been connected to the database.
SQL1040N The maximum number of applications is already connected to the database. SQLSTATE=57030
Number of asynchronous page cleaners (NUM_IOCLEANERS)
NUM_IOCLEANERS is a database configuration parameter that lets you specify the number of asynchronous page cleaners for a database. These page cleaners write changed pages from the buffer pool to disk before the space in the buffer pool is required by a database agent. This allows the agents to read new pages without having to wait for changed pages to be written out. As a result, your application's transactions should run faster.
If you set the parameter to zero (0), no page cleaners are started and as a result, the database agents will perform all of the page writes from the buffer pool to disk. This parameter can have a significant performance impact on a database stored across many physical storage devices, because in this case there is a greater likelihood that one of the devices will be idle. If no page cleaners are configured, your applications may encounter periodic "log full" conditions.
If the applications for a database consist primarily of transactions that update data, an increase in the number of cleaners will speed up performance. Increasing the page cleaners will also reduce recovery time from soft failures, such as power outages, because the contents of the database on disk will be more up-to-date at any given time.
Here are some factors to consider when setting the value for this parameter:
- If transactions are run against the database, set this parameter to be between one and the number of physical storage devices used for the database. One recommendation is to set it at least to the number of CPUs on your system.
- Environments with high update transaction rates may require more page cleaners to be configured.
- Environments with large buffer pools may also require more page cleaners to be configured.
How to change the parameter
The following command can be used to set this parameter to a new value:
db2 -v update db cfg for DB_NAME using NUM_IOCLEANERS a_number db2 -v terminate
Use the database system monitor to help you tune this configuration parameter using information from the snapshot data (or event monitor) about write activity from a buffer pool.
When using snapshot and collecting snapshot data for the buffer pool, monitor the following counters: :
Buffer pool data writes = 0 Asynchronous pool data page writes = 0 Buffer pool index writes = 0 Asynchronous pool index page writes = 0 LSN Gap cleaner triggers = 0 Dirty page steal cleaner triggers = 0 Dirty page threshold cleaner triggers = 0
How do you decide whether NUM_IOCLEANERS should be reduced or increased?
Decrease NUM_IOCLEANERS if both of the following conditions are true:
- "Buffer pool data writes" is approximately equal to "Asynchronous pool data page writes."
- "Buffer pool index writes" is approximately equal to "Asynchronous pool index page writes."
Increase NUM_IOCLEANERS if either of the following conditions is true:
- "Buffer pool data writes" is much greater than "Asynchronous pool data page writes."
- "Buffer pool index writes" is much greater than "Asynchronous pool index page writes."
Dirty page steal cleaner triggers tells the number of times a page cleaner was invoked because a synchronous write was needed during the victim buffer replacement for the database. For a better response time, this number should be as low as possible. With the counters shown above, you can use the following formula to calculate what percentage of all cleaner invocations are represented by this element:
Dirty page steal cleaner triggers / (Dirty page steal cleaner triggers + Dirty page threshold cleaner triggers + LSN Gap cleaner triggers)
If this ratio is high, it may indicate that you have too few page cleaners defined. Too few page cleaners increases recovery time after failures
Number of I/O servers (NUM_IOSERVERS)
I/O servers are used on behalf of the database agents to perform prefetch I/O and asynchronous I/O by utilities such as backup and restore. This parameter, a database configuration parameter, specifies the number of I/O servers for a database. No more than this number of I/Os for prefetching and utilities can be in progress for a database at any time. An I/O server waits while an I/O operation that it initiated is in progress. Non-prefetch I/Os are scheduled directly from the database agents and as a result are not constrained by NUM_IOSERVERS.
In an OLTP environment, use the default.
How to change the parameter
Use the following command to set NUM_IOSERVERS to a new value:
db2 -v update db cfg for DB_NAME using NUM_IOSERVERS a_number db2 -v terminate
Number of commits to group (MINCOMMIT)
MINCOMMIT is database configuration parameter that lets you delay the writing of log records to disk until a minimum number of commits have been performed. This delay can help reduce the database manager overhead associated with writing log records. This can mean improved performance when you have multiple applications running against a database and many commits are requested by the applications within a very short time frame. This grouping of commits will only occur when the value of this parameter is greater than one and when the number of applications connected to the database is greater than, or equal to, the value of this parameter. When commit grouping is being performed, application commit requests are held until either one second has elapsed or the number of commit requests equals the value of this parameter.
The default value for MINCOMMIT is 1. Increase this parameter from its default value if multiple read/write applications typically request concurrent database commits. This will result in more efficient logging file I/O because it will occur less frequently and write more log records each time it does occur. If you believe the default value is not adequate, then it is recommended that you start with 3, and move it up and down to see the performance impact on your workload. You could also sample the number of transactions per second and adjust this parameter to accommodate the peak number of transactions per second (or some large percentage of it). Accommodating peak activity minimizes the overhead of writing log records during heavy load periods.
If you increase MINCOMMIT, you may also need to increase the LOGBUFSZ parameter to avoid having a full log buffer force a write during these heavy load periods. In this case, the LOGBUFSZ should be equal to:
MINCOMMIT * (log space used, on average, by a transaction)
Here is how to use the database system monitor to help you tune this parameter in the following ways:
- Calculating the peak number of transactions per second:
By taking monitor samples throughout a typical day, you can determine your heavy load periods. One way to accomplish this is as follows:
1. At the beginning of your measurements, issue the following command:
db2 -v reset monitor for database db_name
(This will not reset the counters for high water marks.)
2. At the end of your measurements, issue the following command:
db2 -v get snapshot for database on db_name
3. Use the following output to calculate the peak number of transactions:
Last reset timestamp = 06-12-2001 14:51:43.786876 Snapshot timestamp = 06-12-2001 14:56:27.787088 Commit statements attempted = 1011 Rollback statements attempted = 10 Log space used by the database (Bytes) = 3990
Let totalTransactions be the sum of "commit statements attempted" and "rollback statements attempted."
Let totalElapsedTime (in seconds) be the difference between "Last reset timestamp" and "Snapshot timestamp". Calculate the number of transactions per second as
NumOfTransPerSecond = totalTransactions / totalElapsedTime
- Calculating the log space used per transaction:
In a similar manner, by using sampling techniques over a period of time and a number of transactions, you can calculate an average of the log space used with the following monitor element: log_space_used (unit of work log space used).
1. Reset the monitor for the database of interest at the beginning of the measurements using the command:
db2 -v reset monitor for database db_name.
2. Take the snapshots at the end of the measurements using the command:
db2 -v get snapshot for database on db2_name.
3. Output like that shown above is produced.
4. Calculate the log space used per transaction can be calculated using the following formula:
LogSpaceUsedPerTrans = log_space_used / totalTransactions
How to change the parameter
Use the following command to change the MINCOMMIT value:
db2 -v update db cfg for DB_NAME using MINCOMMIT a_number db2 -v terminate
This paper describes a number of DB2 performance fundamentals, tuning tips and techniques, and major DB2 configuration parameters that can affect OLTP performance. By following some of the simple steps described here, you can set up, monitor, and tune your DB2 database system.We hope that the guidance offered in this paper will help you achieve the goal of optimizing performance for your DB2 applications.