This section describes some recommended performance tuning configurations to optimize WSO2 DSS. It assumes that you have set up WSO2 DSS on a server running Unix/Linux, which is recommended for a production deployment.
- Performance tuning requires you to modify important system files, which affect all programs running on the server. We recommend you to familiarize yourself with these files using Unix/Linux documentation before editing them.
- The parameter values we discuss below are just examples. They might not be the optimal values for the specific hardware configurations in your environment. We recommend that you carry out load tests on your environment to tune the DSS accordingly.
To optimize network and OS performance, configure the following settings in
/etc/sysctl.conffile of Linux. These settings specify a larger port range, a more effective TCP connection timeout value, and a number of other important parameters at the OS-level.
When we have the localhost port range configuration lower bound to 1024, there is a possibility that some processes may pick the ports which are already used by WSO2 servers. Therefore, it's good to increase the lower bound as sufficient for production, e.g., 10,000.
To alter the number of allowed open files for system users, configure the following settings in
/etc/security/limits.conffile of Linux.
Optimal values for these parameters depend on the environment.
If one or more worker nodes in a clustered deployment require access to the management console, you need to increase the entity expansion limit in the
<DSS_HOME>/bin/wso2server.bat file (for windows) or the
<DSS_HOME>/bin/wso2server.sh file (for Linux/Solaris) as show below. The default entity expansion limit is 64000.
JDBC pool configuration
Within the WSO2 platform, we use Tomcat JDBC pooling as the default pooling framework due to its production ready stability and high performance. The goal of tuning the pool properties is to maintain a pool that is large enough to handle peak load without unnecessarily utilising resources. These pooling configurations can be tuned for your production server in general in the
<DSS_HOME>/repository/conf/datasources/master-datasources.xml file. You can separately tune the configurations for the RDBMS datasources at the time of creating the datasource using the management console. Read about configuring an RDBMS datasource and creating a data service with RDBMS datasource for details.
The following parameters should be considered when tuning the connection pool:
- The application's concurrency requirement.
- The average time taken to run a database query.
- The maximum number of connections the database server can support.
The table below indicates some recommendations on how to configure the JDBC pool. For more details about recommended JDBC configurations, see Tomcat JDBC Connection Pool.
The maximum number of active connections that can be allocated from the connection pool at the same time. The default value is
The maximum latency (approximately) = (P / M) * T ,
Therefore, by increasing the maxActive value (up to the expected highest number of concurrency), the time that requests wait in the queue for a connection to be released will decrease. But before increasing the Max. Active value, consult the database administrator, as it will create up to maxActive connections from a single node during peak times, and it may not be possible for the DBMS to handle the accumulated count of these active connections.
Note that this value should not exceed the maximum number of requests allowed for your database.
|maxWait||The maximum time that requests are expected to wait in the queue for a connection to be released. This property comes into effect when the maximum number of active connections allowed in the connection pool (see maxActive property) is used up.|
Adjust this to a value slightly higher than the maximum latency for a request, so that a buffer time is added to the maximum latency. That is,
If the maximum latency (approximately) = (P / M) * T ,
then, the maxWait = (P / M) * T + buffer time.
|minIdle||The minimum number of connections that can remain idle in the pool, without extra ones being created. The connection pool can shrink below this number if validation queries fail. Default value is 0.||This value should be similar or near to the average number of requests that will be received by the server at the same time. With this setting, you can avoid having to open and close new connections every time a request is received by the server.|
|maxIdle||The maximum number of connections that can remain idle in the pool.||The value should be less than the maxActive value. For high performance, tune maxIdle to match the number of average, concurrent requests to the pool. If this value is set to a large value, the pool will contain unnecessary idle connections.|
The indication of whether connection objects will be validated before they are borrowed from the pool. If the object validation fails, the connection is dropped from the pool, and there will be an attempt to borrow another connection.
When the connection to the database is broken, the connection pool does not know that the connection has been lost. As a result, the connection pool will continue to distribute connections to the application until the application actually tries to use the connection. To resolve this problem, set "Test On Borrow" to "true" and make sure that the "ValidationQuery" property is set. To increase the efficiency of connection validation and to improve performance,
This parameter controls how frequently a given validation query is executed (time in milliseconds). The default value is
Deciding the value for the "validationInterval" depends on the target application's behavior. Therefore, selecting a value for this property is a trade-off and ultimately depends on what is acceptable for the application.
If a larger value is set, the frequency of executing the Validation Query is low, which results in better performance. Note that this value can be as high as the time it takes for your DBMS to declare a connection as stale. For example, MySQL will keep a connection open for as long as 8 hours, which requires the validation interval to be within that range. However, note that the validation query execution is usually fast. Therefore, even if this value is only large by a few seconds, there will not be a big penalty on performance. Also, specially when the database requests have a high throughput, the negative impact on performance is negligible. For example, a single extra validation query run every 30 seconds is usually negligible.
If a smaller value is set, a stale connection will be identified quickly when it is presented. This maybe important if you need connections repaired instantly, e.g. during a database server restart.
|validationQuery||The SQL query used to validate connections from this pool before returning them to the caller. If specified, this query does not have to return any data, it just can't throw an SQLException. The default value is null. Example values are SELECT 1(mysql), select 1 from dual(oracle), SELECT 1(MS Sql Server).||Specify an SQL query, which will validate the availability of a connection in the pool. This query is necessary when |
When it comes to web applications, users are free to experiment and package their own pooling framework such BoneCP.
Setting the thread execution limit for multi-tenant mode
In multi-tenant mode, the Carbon runtime limits the thread execution time. That is, if a thread is stuck or taking a long time to process, Carbon will detect such threads, interrupts and stops them. Note that Carbon prints the current stack trace before interrupting the thread. This mechanism is implemented as an Apache Tomcat valve. Therefore, it should be configured in the
<DSS_HOME>/repository/conf/tomcat/catalina-server.xml file as shown below.
classNameis the Java class name used for the implementation. This must be set to
thresholdgives the minimum duration in seconds after which a thread is considered stuck. Default value is 600 seconds.
When you need high update/insert throughput, use Batch Processing Sample.to achieve maximum performance. Batch requests send multiple records in a single request. For more information on batch processing, see