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The Performance Balancing Act:

Capitalizing on Informix Configurations to Establish Higher Performance

Kerry Calvert 

It is a given that everyone wants higher levels of performance from their database system. The obstacles to satisfying this desire can seem daunting, given the multitude of issues that govern system throughput. The first step to take towards achieving performance nirvana, (or at least a warm and fuzzy feeling) is to relinquish the idea that there are "primary solutions" to the problem. The task in front of you is an iterative one, that requires you to make some engineering judgments, monitor the results, and then adjusting the judgments to reflect observed behavior. The better job of observation and correlation that you can do as you make structural or configuration changes to the database, the better you will be able to zero in on a configuration that is optimal for your usage of the database.

 Someone ought to write a tool to deal with this, you are probably muttering. Someone probably is, but do not buy one that promises that all you have to do is install the product and your weekends will be free for eternity. In the meantime, I hope to provide some insight into some of the key configuration parameters that impact the performance of the Informix server with this article. 

The Main Stage

 The following diagram illustrates a conceptual view of the Informix server architecture. It is not necessarily reflective of the real architecture. Its primary purpose is to illustrate conceptually how the server transports data, so the you have a better feel for what the configuration parameters are trying to control:

The objective in performance tuning is to minimize blocking between the major processing groups. In the ideal query, the required memory buffers would be available, the requested data is in the memory cache, and the connection services are not blocked servicing other users. The net effect in this ideal scenario is that the total transaction is a memory copy between the cache and the user. Since entropy rules, and things are never ideal, we have to handle the case where the disk drives are being beat to death. This is accomplished by configuring adequate memory, I/O bandwidth, data organization, and/or operating system resources to meet the task, and hopefully keep the user community from beating the DBA to death.

 The first processing group, which performs the client connection services management, is CPU and network intensive. As application programs open the database, this layer must allocate memory and possibly network connections to support the request. If your system supports large number of users with short connection life spans, insuring that there are adequate CPU resources allocated to handle this load is important to reducing connection delays. 

The second processing group, which processes the queries, is responsible for the parsing, data conversion, and filtering demanded by the query load. This group is memory and CPU intensive. Other than some general configuration parameters, which control how much CPU and memory resource a query can consume, there are no definitive tuning parameters that allow you to scale resources specifically to query processing. 

The disk I/O processing group performs cache management and data reading/writing. This area of processing is highly tunable of course, and is very important to the balancing equation. Since log activity has very high overhead, Informix provides tuning and configuration capabilities separate of data I/O. 

When performance is lagging, there is an imbalance between the processing groups. Isolating the cause is half the battle, although sometimes it can seem like both halves ! 

The Usual Suspects

 Assuming that you have already applied your genius to the logical design of the database, such that you have the 8th wonder of the world as it pertains to efficient schema implementation, the other things that affect throughput performance of your database are as follows:

  • Configuration
  • Memory
  • Disk Layout
  • Data Disorganization
  • CPU Utilization

At indicated earlier, the goal in performance tuning is to create an environment that minimizes disk I/O in conjunction with minimizing wasted efforts of the CPU, given that swapping, process scheduling, and busy waits are not productive use of the machine. If we can tune the system so that we have very high levels of read and write cache percentages, without saturating CPU resources, then we will have a responsive system. Unfortunately, this is easier said than done, which is why you are paid the big bucks to solve this type of problem: 

Configuration Parameters 

A good starting point is to evaluate the configuration parameters to insure that they make effective use of the memory in the system , connection service types, and available CPU resources. An inadequate number of memory buffers, or using the wrong connection configuration can defeat the best schema and data partitioning plan in short order. 

The critical parameters for Informix Online are located in $INFORMIXDIR/etc/$ONCONFIG. These parameters can be modified with an editor (you have to shut down the server and restart it to make the parameters take affect), or you can use the onmonitor program to make modifications. The parameters that are of particular concern to performance are documented in the Informix Online Dynamic Server Performance Guide. We will discuss the most important of these here:  NUMCPUVPS This parameter is used to define the number of CPU virtual processors that Informix Online will bring up initially. A virtual processor is different than a real CPU. In Informix implementation terms, a virtual processor is essentially a UNIX process. A virtual processor will have a class, such as CPU or AIO, and threads that perform certain types of work (compute intense, I/O, etc.) are scheduled for execution (through Informix code, not the OS) in the appropriately classed process, or "virtual processor". Since I/O is performed asynchronously, a process will not block in the OS kernel waiting for an I/O. Informix will suspend thread that needs to wait on I/O, and reactivate a different thread in the process to perform work. Thread scheduling is "lighter weight" than process scheduling, so this technique results in less OS busy work than a simple multi-process architecture.

The purpose of NUMCPUVPS is to set a limit on the number of processes started, and the amount of CPU horsepower that the database server will consume. The balancing act in deciding on an appropriate value for this parameter is the classic use of a 5 pound bag to hold 20 pounds of : stuff. If you have high cache rates in conjunction with CPU idle time, but response is lagging, you have too many threads being squeezed through too few virtual processors. Increasing NUMCPUVPS solves this problem.

If you have multiple processors, it is beneficial to set NUMCPUVPS to a value greater than one ( for a system with < 4 CPUS, set NUMCPUVPS to the number of CPUS, for a system with > 4 CPUS, set NUMCPUVPS to the number of CPUS -1 (or something less if you do not want Informix to consume all of the resources in the machine).

  • Performance Tip: Find the point where the performance is acceptable without negatively impacting other applications on the system with the minimal setting for NUMCPUVPS

NUMAIOVPS This parameter is similar to NUMCPUVPS, but is used only when the OS kernel does not support asynchronous I/O. AIO VPS process I/O requests by Informix, which are presented in a queue. The objective is to keep the queue as short as possible. The queue can be monitored with the onstat -g ioq command.

  • Performance Tip: Find the point where the queue is minimized with the minimal number of AIO VPS enabled.
  • NETTYPE The NETTYPE parameter controls how connections to the database are supported. A given connection can support up to 1024 sessions, although a limit of 300 is recommended. When your client program is running on the same machine as the database server, it is best to set the NETTYPE parameter for the local connection to a shared memory type connection. This is because it is much faster to transfer data between the server and the client program through shared memory than it is transfer data through a socket. The specification of a NETTYPE parameter is as follows:

    NETTYPE connection_type, poll_threads, connections, vp class

    The connection type can be onipcshm for shared memory, onsoctcp for a socket, or ontlitcp for a TLI socket. Other than any OS level performance advantages, there are no distinct advantages of using TLI over TCP.

    The poll_threads parameter specifies how many threads are started in the server to support connection requests. If we limit the number of connections per thread to 300, and we have to support 1000 users concurrently, we would want to set poll_threads to 4, to insure there were adequate service levels in the server.

    The connections parameter limits how many simultaneous connections can be handled per poll thread. The upper limit is 1024, but Informix recommends 300 on uni-processor systems, and 350 on multi-processor systems.

    The vp class value should be set to NET on a multi-processor system, and CPU on a uni-processor system. By setting the vp class to NET, all connection service processing is performed in a process that is dedicated to network services, so that this processing will not interfere with the disk I/O or other query processing.

    Multiple NETTYPE parameters can be specified in the $ONCONFIG file, so that multiple connection types can be supported simultaneously.

  • Performance Tip: Set the number of poll threads so that there is an adequate number of threads to support the number of users that are simultaneously trying to access the database. Do not over-specify the number, as it will waste memory and CPU bandwidth.
  • BUFFERS The BUFFERS parameter controls how many memory buffers are available in the server to cache data pages with. If insufficient memory buffers are available, data has to be flushed out of used buffers to disk to provide service to new requests. This same data will have to be read back in later when the data is needed. It is generally recommended that BUFFERS be set such that 25% of the available memory in the system is allocated to the server (BUFFERS * PAGESIZE). The problem with setting BUFFERS to high is that system memory is wasted, and this could cause paging.

  • Performance Tip: An indication that the BUFFERS setting is too small is when the read-cache value is low. The read cache value can be observed with the onstat -p command. It represents the percentage of database pages already in memory when the buffer is requested by a query. When this is the case, increase BUFFERS until the cache rate is maximized without causing paging activity in the os (see vmstat or sar operating system commands for instruction on how to monitor paging activity).
  • PHYSBUFF The parameter sets the size for 2 buffers that are used for caching pages which have changed, prior to being flushed to disk. The less often it is filled, the less often a write will occur. The size should be specified as a multiple of the system page size.

  • Performance Tip: The first instinct is to size this as large as shared memory will allow. However, you should consider the impact of losing the information in these memory buffers if a system crashes. If you make this buffer very large, you could lose 100's of transactions!
  • LOGBUFF The LOGBUFF parameter allocates shared memory for each of three buffers which hold logical log records until they are flushed to the logical log file on disk. You can reduce the number of times that disk I/O is started to flush logs by increasing this parameter to a maximum size equal to LOGSIZE.

  • Performance Tip: The memory allocated for the buffer is taken from shared memory, so you should evaluate whether allocating 3*LOGBUFF bytes from shared memory might cause swapping on the system.
  • LOGSIZE The major factor that governs how large a logical log file should be is need to insure that adequate log space is available for long transactions. Smaller logs cause checkpoints to occur more frequently which may be a disadvantage to performance. However, before making the counter move to increase the size of logs, you should consider the affect on reliability caused by less frequent back-up of logs to tape. When you use continuous logging, the logs are copied to tape when they fill up. You will be at risk of not having tape backup for the length of time that it takes to fill up a log.

  • Performance Tip: To gain the performance advantage of using large logs without being to long spans between backup to tape, use a cron job to perform the onmode -l command at some reasonable time span.
  • DBSPACETEMP This parameter specifies one or more dbspaces that the server will use for temporary tables and sort files. By specifying multiple dbspaces, the server will use parallel insert capability to fragment the temporary tables across the dbspaces.

  • Performance Tip: If you do not specify this parameter, the server will perform sorting and temp table storage in the root dbspace. This should be avoided if possible. If you are mirroring the root dbspace, you pay a double penalty in performance
  • RA_PAGES The number of pages of data that the server will read when performing sequential scans is set by this parameter. Reading more pages per I/O operation has a beneficial impact on performance during serial scans. However, the pages compete for buffers such that page cleaning may be necessary to find free buffers. If all of the pages being read in are not needed, then the page cleaning is a waste.

    This is great theory, but how do you manage it practically ? How should you set reasonable values to get the value of read ahead without causing unnecessary page cleaning ? Informix recommends the following calculation:

    RA_PAGES = (BUFFERS * fract) / (2 * queries) + 2

    RA_THRESHOLD = (BUFFERS * fract) / (2 * queries) - 2

    fract is the fraction of BUFFERS to be used for read ahead. If you want to use 50% of available buffers for read ahead, you would set fract to .5

    queries is the number of concurrent queries that will support this read-ahead logic.

    The server is triggered to read RA_PAGES on a serial scan, when the number of unprocessed pages in memory falls to the value set by RA_THRESHOLD.

    If your application performs a high number of queries that use filtering conditions with wild cards or ranges, you will be performing numerous serial scans. If you have updates occurring simultaneously, you will see the write cache rates drop if you have a higher value for RA_PAGES.

    If your application is doing a lot of serial scanning but limited, a higher value of RA_PAGES will increase the I/O performance of the reads.

  • Performance Tip: If the read speeds are close to the disks upper end capacity, then you are not experiencing the problem these parameters are trying to solve.
  • LRUS This defines the number of buffer queues that feed the page cleaners. Dirty pages that need to be flushed to disk are placed on this queue. The onstat -R command will show the percentage of dirty pages on the queues. If the number of pages on the queue exceeds LRU_MAX_DIRTY, there are either too few LRU queues, or there are too few page cleaners. See the comments in the CLEANERS section to evaluate whether you have adequate cleaners.

  • Performance Tip: All pages are flushed to disk during a checkpoint. By setting LRU_MAX_DIRTY, the page cleaners will flush dirty buffers between checkpoints, so the checkpoint will have less work to do. When all cleaning is left to the checkpoint, the system often appears to have halted, which is annoying to users.
  • CLEANERS This controls the number of threads dedicated to page cleaning. If you have fewer than 20 disks, allocate one cleaner per disk. Between 20 and 100 disks, use 1 cleaner for every 2 disks. This can be done because the demand per disk drops to a level that a single thread can adequately service two disks. For greater than 100 disks, use 1 cleaner for every 4 disks.


    The parameters discussed in this article set the stage for you to optimize the performance levels you can get out of the Informix database server. In the next installment of this article, I will discuss how to use to Informix and OS utilities to monitor the activity in the server, and use the results to make better decisions about the values that should be set in these parameters.


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