I just launched an Azure SQL Database, and the DTU and CPU usage is behaving strangely. The database is only receiving about 30 requests per minute, and the CPU/DTU will be extremely low for hours, and then jump up to 100% and stay there (with no increase in the number of requests that triggers this). When I click to view the top queries, none of them are above 1% cpu usage. I started out on a 5 DTU plan, and yesterday upgraded to 20 DTUs and the same behavior is occurring. Any idea what else might cause the DTU/CPU to get maxed out? See images below:
https://i.imgur.com/LdbYTPw.png
https://i.imgur.com/jlus3FM.png
Thanks in advance for any advice!
Joe
EDIT: I'm getting closer, I found these repeated entries in the error log. (about 8 - 10 per SECOND)
"The incoming request has too many parameters. The server supports a maximum of 2100 parameters. Reduce the number of parameters and resend the request."
The thing is, the App Service that queries the database is only doing simple selects, updates, and inserts... none of which uses any complex WHERE IN statement. Furthermore, every query is wrapped in a try/catch block, and I'm never seeing an exception like this.
Where could these large queries be originating from?
You are only seeing the CPU component of the DTU graph, what about the "Data IO" and the "Log IO" components? Look at the top 5 queries on the 3 sections, and let me know if you find a query that start with "SELECT Statman ...". If you see that, then the Auto Update Statistics process is creating those DTU spikes.
I would suggest to install the sp_whoisactive script so that you can see what's going on more easily:
http://whoisactive.com/
Related
I’m struggling to understand how the pricing mechanism for RU/s works. Specifically my confusion comes in when the word “first” is used.
I’ve done my research here:https://devblogs.microsoft.com/cosmosdb/build-apps-for-free-with-azure-cosmos-db-free-tier/?WT.mc_id=aaronpowell-blog-aapowell
In the second paragraph it’s mentioned:
“With Azure Cosmos DB Free Tier enabled, you’ll get the first 400 RU/s throughput and 5 GB storage in your account for free each month, for the lifetime of the account.”
So hypothetically speaking if I have an app that does one query and that 1 query evaluates to 1RU. Can I safely assume that
400 users can execute the query once per second for free?
500 users can execute the query once per second and I will only be charged for 100RU
If the RU is consistently less than 401 per second, there will be no charge
Please do make mention if there’s any other costing I should be aware of. Ie. Any cosmosDb dependencies, or app service costing
You're not really thinking about RU/sec correctly.
If you have, say, 400 RU/sec, then that is your allocated # of RU within a one-second window. It has nothing to do with # of users (as I doubt you're giving end-users direct access to your Cosmos DB instance).
in the case of operations only costing 1 RU, then yes, you should be able to execute 400 operations within a 1-second window, without issue (although there is only one type of operation costing 1 RU, and that's a point-read).
in the case you run some type of operation that puts you over the 400RU quota for that 1-second period, that operation completes, but now you're "in debt" so to speak: you will be throttled until the end of the 1-second period, and likely a bit of time into the next period (or, depending on how deep in RU-debt you went, maybe a few seconds).
when you exceed your RU/sec allocation, you do not get charged. In your example, you asked what happens if you try to consume 500 RU in a 1-second window, and asserted you'd be charged for 100 RU. Nope. You'll just be throttled after exhausting the 400 RU allocation.
The only way you'll end up being charged for more RU/sec, is if you increase your RU/sec allocation.
There is some more reading out there you can do:
azure cosmos db free tier
pricing examples
I have a cosmosGB gremlin API set up with 400 RU/s. If I have to run a query that needs 800 RUs, does it mean that this query takes 2 sec to execute? If i increase the throughput to 1600 RU/s, does this query execute in half a second? I am not seeing any significant changes in query performance by playing around with the RUs.
As I explained in a different, but somewhat related answer here, Request Units are allocated on a per-second basis. In the event a given query will cost more than the number of Request Units available in that one-second window:
The query will be executed
You will now be in "debt" by the overage in Request Units
You will be throttled until your "debt" is paid off
Let's say you had 400 RU/sec, and you executed a query that cost 800 RU. It would complete, but then you'd be in debt for around 2 seconds (400 RU per second, times two seconds). At this point, you wouldn't be throttled anymore.
The speed in which a query executes does not depend on the number of RU allocated. Whether you had 1,000 RU/second OR 100,000 RU/second, a query would run in the same amount of time (aside from any throttle time preventing the query from running initially). So, aside from throttling, your 800 RU query would run consistently, regardless of RU count.
A single query is charged a given amount of request units, so it's not quite accurate to say "query needs 800 RU/s". A 1KB doc read is 1 RU, and writing is more expensive starting around 10 RU each. Generally you should avoid any requests that would individually be more than say 50, and that is probably high. In my experience, I try to keep the individual charge for each operation as low as possible, usually under 20-30 for large list queries.
The upshot is that 400/s is more than enough to at least complete 1 query. It's when you have multiple attempts that combine for overage in the timespan that Cosmos tells you to wait some time before being allowed to succeed again. This is dynamic and based on a more or less black box formula. It's not necessarily a simple division of allowance by charge, and no individual request would be faster or slower based on the limit.
You can see if you're getting throttled by inspecting the response, or monitor by checking the Azure dashboard metrics.
I have an RDS instance running MySQL 5.5.46 which has a table with a primary key of int that it is currently at 1.9 billion records and approaching the 2.1 billion limit and ~425GB in size. I'm attempting to use pt-osc to alter the column to a bigint.
I was able to successfully test the change on a test server (m3.2xlarge) and, while it took about 7 days to complete, it did finish successfully. This test server was under no additional load. (Side note: 7 days seemed like a LONG time).
For the production environment, there is no replication/slave present (but there is Multi-AZ) and, to help with resource contention and speed things up, I'm using an r3.8xlarge instance type.
After two attempts, the production migration would get to about 50% and a 1 day left and then the RDS would seemingly stop accepting connections forcing the pt-osc both times to roll back or fail outright, because the RDS needed to be rebooted.
I don't see anything obvious in the RDS console or logs to help indicate why this happened, and I feel like the instance type should be able to handle a lot of connections/load.
Looking at the CloudWatch metrics during my now third attempt, the database server itself doesn't seem to be under much load: 5% CPU, 59 DB Connections, 45GB Freeable Memory, Write IOPS ~2200-2500.
Wondering if anyone has ran into this situation and, if so, what helped with the connection issue?
If anyone has suggestions on how to speed up the process in general I'd love to hear. I was considering trying a larger chunk-size and off hours, but wasn't sure how that would end up affecting the application.
The facts:
1 Azure SQL S0 instance
a few tables one of them containing ~ 8.6 Million Rows and 1 PK
Running a Count-query on this table takes nearly 30 minutes (!) to complete.
Upscaling the instance from S0 to S1 reduces the query time to 13 minutes:
Looking into Azure Portal (new version) the resource-usage-monitor shows the following:
Questions:
Does anyone else consider even 13 minutes as rediculos for a simple COUNT()?
Does the second screenshot meen that during the 100%-period my instance isn't responding to other requests?
Why are my metrics limited to 100% in both S0 and S1? (see look under "Which Service Tier is Right for My Database?" stating " These values can be above 100% (a big improvement over the values in the preview that were limited to a maximum of 100).") I'd expect the S0 to bee like on 150% or so if the quoted statement is true.
I'm interested in experiences regarding usage of databases with more than 1.000 records or so from other people. I don't see how a S*-scaled Azure SQL for 22 - 55 € per month could help me in upscaling-strategies at the moment.
Azure SQL Database editions provide increasing levels of DTUs from Basic -> Standard -> Premium levels (CPU,IO,Memory and other resources - see https://msdn.microsoft.com/en-us/library/azure/dn741336.aspx). Once your query reaches its limits of DTU (100%) in any of these resource dimensions, it will continue to receive these resources at that level (but not more) and that may increase the latency in completing the request. It looks like in your scenario above, the query is hitting its DTU limit (10 DTUs for S0 and 20 for S1). You can see the individual resource usage percentages (CPU, Data IO or Log IO) by adding these metrics to the same graph, or by querying the DMV sys.dm_db_resource_stats.
Here is a blog that provides more information on appropriately sizing your database performance levels. http://azure.microsoft.com/blog/2014/09/11/azure-sql-database-introduces-new-near-real-time-performance-metrics/
To your specific questions
1) As you have 8.6 million rows, database needs to scan the index entries to get the count back. So, it may be hitting the IO limit for the edition here.
2) If you have multiple concurrent queries running against your DB, they will be scheduled appropriately to not starve one request or the other. But latencies may increase further for all queries since you will be hitting the available resource limits.
3) For older Web/Business editions, you may be able to see the metric values going beyond 100% (they are normalized to the limits of an S2 level), as they don't have any specific limits and run in a resource-shared environment with other customer loads. For the new editions, metrics will never exceed 100%, because system guarantees you resources upto 100% of that edition's limits, but no more. This provides predictable, guaranteed amount of resources for your DB unlike Web/Business editions, where you may get very little or lot more resources at different times depending on other competing customer DB workloads running on the same machine.
Hope this helps.
-- Srini
I am using Jmeter (started using it a few days ago) as a tool to simulate a load of 30 threads using a csv data file that contains login credentials for 3 system users.
The objective I set out to achieve was to measure 30 users (threads) logging in and navigating to a page via the menu over a time span of 30 seconds.
I have set my thread group as:
Number of threads: 30
Ramp-up Perod: 30
Loop Count: 10
I ran the test successfully. Now I'd like to understand what the results mean and what is classed as good/bad measurements, and what can be suggested to improve the results. Below is a table of the results collated in the Summary report of Jmeter.
I have conducted research only to find blogs/sites telling me the same info as what is defined on the jmeter.apache.org site. One blog (Nicolas Vahlas) that I came across gave me some very useful information,but still hasn't help me understand what to do next with my results.
Can anyone help me understand these results and what I could do next following the execution of this test plan? Or point me in the right direction of an informative blog/site that will help me understand what to do next.
Many thanks.
According to me, Deviation is high.
You know your application better than all of us.
you should focus on, avg response time you got and max response frequency and value are acceptable to you and your users? This applies to throughput also.
It shows average response time is below 0.5 seconds and maximum response time is also below 1 second which are generally acceptable but that should be defined by you (Is it acceptable by your users). If answer is yes, try with more load to check scaling.
In you requirement it is mentioned that you need have 30 concurrent users performing different actions. The response time of your requests is less and you have ramp-up of 30 seconds. Can you please check total active threads during the test. I believe the time for which there will be 30 concurrent users in system is pretty short so the average response time that you are seeing seems to be misleading. I would suggest you run a test for some more time so that there will be 30 concurrent users in the system and that would be correct reading as per your requirements.
You can use Aggregate report instead of summary report. In performance testing
Throughput - Requests/Second
Response Time - 90th Percentile and
Target application resource utilization (CPU, Processor Queue Length and Memory)
can be used for analysis. Normally SLA for websites is 3 seconds but this requirement changes from application to application.
Your test results are good, considering if the users are actually logging into system/portal.
Samples: This means the no. of requests sent on a particular module.
Average: Average Response Time, for 300 samples.
Min: Min Response Time, among 300 samples (fastest among 300 samples).
Max: Max Response Time, among 300 samples (slowest among 300 samples).
Standard Deviation: A measure of the variation (for 300 samples).
Error: failure %age
Throughput: No. of request processed per second.
Hope this will help.