Performance Testing Series
This post is part of a series of blog posts about my performance tests in Azure SQL Database. For the first post in this series (and links to all of the other posts) please see here. For a summary of all the results please see here.
For a general overview of the test architecture, test components and test types, please see here.
Inserts, Direct and Indirect Selects, Updates and Deletes Test Overview
This test combines the activities of the earlier Inserts and Deletes, Direct Selects, Indirect Selects and Updates tests. Please refer to those posts for a more detailed description of these activities.
The type of request generated by each worker thread at any point in time is randomly selected, based on the following probabilities:
- Inserts – 20%
- Selects – 30% – which breaks down as 75% Direct Selects and 25% Indirect Selects
- Updates – 30%
- Deletes – 20%
As in those earlier tests, the worker threads in the UT tests are not limited to a specified request rate while the worker threads in the LT tests are constrained to generate requests at a limited rate specified in the test definition.
The UT tests run against only a small set of test data. This means the entire data set generally exists in the SQL Server Buffer pool (the test table is pre-populated immediately before the test begins). This test therefore primarily investigates write rates combined with read rates from the buffer pool. In contrast to these tests, the later Scale Tests include all of the actions here but acting on data that is not always resident in the buffer pool.
UT Test Results
Results from the 30 UT tests are shown in the two charts below. In these charts, the “T” values are the number of worker threads generating requests against the database, e.g. “Business 4T” = a test against Business edition, running with 4 threads continuously generating requests.
The two charts are similar because the average row size was around 400 bytes throughout. The data volume figures here are based on the data content (i.e. summing the sizes of the data values, according to the number of bytes each data value requires in the SQL Server Data Type scheme but ignoring internal SQL Server overheads).
Several different tests of the current Web/Business edition were carried out. The Web 1T test was carried out on a A1 sized cloud instance, the Business 1T test on an A2 sized instance. This explains the slightly higher throughput on the Business 1T test. As the number of threads was increased in the Business edition tests, the throughput increases though is variable.
In contrast to the Business Edition tests, performance of the new service tiers is very consistent. From these results S2 generally equals or outperforms Business Edition.
The charts below show the performance profiles over the lifetime of the tests in the charts above. Since 30 lines is rather a lot to fit onto one chart, data for the different editions / tiers has been split across several charts.
It is also worth noting that due to the way the Azure SQL Database logging into sys.resource_stats works, data is only available at five minute intervals and the last data point in each test (which would have been plotted as minute 27 in these charts) is not useful and so is omitted.
Basic to P1 Tiers
Performance of the new tiers is again consistent. The throughput appears a little more ragged because a slight random increase in the number of Indirect Select requests can have a dramatic effect on row counts and data volumes. These requests also tend to slightly reduce the pressure on the log write quota, though it is still a relatively dominating control on overall throughput.
Std2 to P2 Tiers
The SQL Server performance data (from sys.resource_stats) has a few data points missing on these charts. It appears as though a bug or infrastructure fault within Azure was preventing some usage data being processed correctly into the view.
Nonetheless, these profiles show the much more variable nature of the Business Edition. Those tests where multiple threads are executing show considerably more variable performance, sometimes varying wildly.
LT Test Results
Three series of LT tests were carried out, against the Web, Basic and S1 editions / tiers.
As the request rate is increased, the CPU utilisation and log write utilisation increase. At around 100 rows per second, we have hit the log write limit and the database is not able to keep up with the request rate. All of the data for these tests was present in the buffer pool. Disk Read quota had no impact.
Performance is very consistent throughout.
This is a rather mixed looking chart. The tests that were performed at 120 and 160 requests per second are showing behaviour inconsistent with the other tests. The cause(s) is/are not immediately clear from this chart (i.e. none of SQL CPU, log write or disk read limits were close to being hit). The cause is also not clear from the other diagnostic data collected during the tests. The cloud service request generator CPU utilisation was only around 10% insufficient CPU power in the request generator VM is unlikely to be the cause.
This chart shows good consistency from Web Edition, with linear performance up to 120 requests per second, also consistent with (and actually slightly better than) the earlier UT test.
It is interesting to note that this chart also proves the well known fact that there is no clearly enforced log write limit per database in the Web Edition. I.e. we apparently hit the reported log write limit at 40 requests per second, but we can actually continue increasing our request rate to nearly three times this “maximum” – i.e. to 130 requests per second – before we actually see a significant number of requests failing to be processed.
Inserts, Direct and Indirect Selects, Updates and Deletes Test Conclusions
The combined tests have shown that, for a workload of purely stored procedure based row-by-row inserts, direct and indirect selects, updates and deletes (of average row size 400 bytes), where the data is already in the buffer pool, performance of the new S2 / P1 tiers generally equals the current Business Edition. P2 significantly outperforms Business for this workload.
Appendix – UT Test Configuration
|Cloud Svc Inst. Size||A1||A2||A2||A2||A3||A1||A1||A2||A2||A2|
|Req. Gen. Thread Count||1||1||2||4||8||1||1||2||4||8|
|Initial Test Data (MB)||0.1||0.2||0.2||0.2||0.8||0.1||0.1||0.4||0.8||1.2|
Appendix – UT Test Results
|Configuration||Avg Rows Per Second||Avg MB Per Minute|
|Std S1 1T||1468||1389||1526||31.0||29.2||32.1|
|Std S2 2T||3067||2880||2673||64.6||60.7||56.4|
|Prem P1 4T||4513||4400||4362||95.0||92.6||91.9|
|Prem P2 8T||8415||8648||8551||177.4||182.2||179.8|
|Configuration||SQL Avg Log Write %||SQL Avg Disk Read %||SQL Avg CPU %|
|Std S1 1T||78.5||77.8||86.5||0.1||0.0||0.0||37.1||35.9||35.4|
|Std S2 2T||85.8||81.0||76.7||1.3||0.4||0.2||34.9||32.2||39.6|
|Prem P1 4T||99.5||99.1||99.3||0.0||0.0||0.0||18.8||20.1||16.7|
|Prem P2 8T||88.1||96.3||96.4||0.0||0.0||0.0||19.6||22.2||22.0|
|Configuration||Cloud Svc Avg CPU||Error Count|
|Std S1 1T||9.0||9.3||9.5||0||0||0|
|Std S2 2T||10.6||9.4||8.7||0||0||0|
|Prem P1 4T||13.4||13.5||13.9||0||0||0|
|Prem P2 8T||26.5||27.0||27.3||0||0||0|
Appendix – LT Test Configuration
|Cloud Svc Inst. Size||A0||A0||A0|
|Req. Gen. Thread Count||1||1||1|
|Initial Test Data (MB)||0.25||0.25||0.5|
Appendix – LT Test Results
|Threads||Req. Per Sec||Avg Rows Per Second||Avg MB Per Minute|
|Web||Basic||Std 1||Web||Basic||Std 1|
|Threads||Req. Per Sec||SQL Avg Log Write %||SQL Avg Disk Read %||SQL Avg CPU %|
|Web||Basic||Std 1||Web||Basic||Std 1||Web||Basic||Std 1|
The Requests per Second maximum applies in total, not per thread.