Measures reported by OraRacTranWorkloadTest
Knowing the count of transactions executing on the Oracle cluster per second can indicate the transaction load on the server. However, the true impact of this load can be assessed and understood only if administrators are enabled to determine the number and type of database operations each transaction triggers. This is where the OraRacTranWorkloadTest test helps!
This test reports how many key database operations – eg., data modifications, block changes, reads/writes, parses, rollbacks, etc. – are performed on the server per transaction. This way, the test reveals the real workload of the server. In addition, the test also enables administrators to compare current CPU usage with the real workload, so that they can figure out whether/not the server needs to be resized to handle its load.
Outputs of the test : One set of results for every SID monitored
The measures made by this test are as follows:
| Measurement |
Description |
Measurement Unit |
Interpretation |
| Redo_size |
Indicates the rate at which modifications were written to the redo logs since the last measurement period. |
MB/Sec |
If the value of this measure keeps growing, it could indicate that data is changing rapidly in the databases. A steady drop in this value could indicate that changes are not written to the redo logs as quickly as they occur. |
| logical_reads |
Indicates the rate at which logical reads were performed by the cluster |
Reads/Sec |
These measures are good indicators of the level of activity on the database server and how well the server handles these activity levels. In the event of a slowdown, you can compare the value of these measures to know where the slowdown may have originated – when making changes to data? When reading? When writing? |
| Block_chgs_count |
Indicates the rate at which database blocks were changed. |
Blocks/Sec |
| Phy_reads |
Indicates the rate at which the cluster performed physical reads. |
Reads/Sec |
| Phy_writes |
Indicates the rate at which the cluster performed physical writes. |
Writes/Sec |
| User_calls |
Indicates the rate at which the cluster made user calls. |
Calls/Sec |
|
| Parses_count |
Indicates the rate at which the cluster parsed SQL statements. |
Parses/Sec |
Parsing is one stage in the processing of a SQL statement. When an application issues a SQL statement, the application makes a parse call to Oracle Database. During the parse call, Oracle Database:
Checks the statement for syntactic and semantic validity.
Determines whether the process issuing the statement has privileges to run it.
Allocates a private SQL area for the statement.
If the value of this measure keeps increasing consistently, it could indicate that many SQL statements are being executed on the server, thus generating more parses every second. If the value of this measure drops consistently, it could indicate a bottleneck in parsing.
|
| Hard_parses_count |
Indicates the rate at which the cluster hard parsed SQL statements. |
Parses/Sec |
As opposed to a soft parse, a hard parse loads the SQL source code into RAM for parsing. If the value of this measure is decreasing steadily, it could mean that hard parsing is taking too long. It could also mean that very few hard parses are actually performed. |
| WA_mem_processed |
Indicates the rate at which work area memory is used by the cluster. |
Secs |
Oracle Database reads and writes information in the PGA on behalf of the server process. An example of such information is the run-time area of a cursor. Each time a cursor is executed, a new run-time area is created for that cursor in the PGA memory region of the server process executing that cursor. For complex queries (such as decision support queries), a big portion of the run-time area is dedicated to work areas allocated by memory intensive operators, including:
Sort-based operators, such as ORDER BY, GROUP BY, ROLLUP, and window functions
Hash-join
Bitmap merge
Bitmap create
Write buffers used by bulk load operations
For example, a sort operator uses a work area (sometimes called the sort area) to perform the in-memory sort of a set of rows. Similarly, a hash-join operator uses a work area (also called the hash area) to build a hash table from its left input. If the amount of data to be processed by these two operators does not fit into a work area, then the input data is divided into smaller pieces. This allows some data pieces to be processed in memory while the rest are spilled to temporary disk storage to be processed later.
A consistent increase in the value of this measure is indicative of excessive usage of the work area. This could indicate that the workload is characterized by complex queries that use memory intensive operators such as sort, hash-join, etc. You may want to fine-tune the work area size in order to enable it to handle the memory-intensive load better.
|
| Logons |
Indicates the rate at which users login to the cluster. |
Logons/Sec |
A steady rise in this value is indicative of a steady increase in user activity on the server. |
| Executes |
Indicates the rate at which executions are performed by the cluster. |
Executions/Sec |
|
| Trans_rollbacks |
Indicates the rate at which the cluster performs rollbacks. |
Rollbacks/Sec |
Ideally, the value of this measure should be low. This is because, rollbacks are expensive operations and should be avoided at all costs. A consistent increase in the value of this measure is hence a cause for concern. |
|