I am processing (partitional) one of my tables in Analysis Services but it is failing. This partition is around 6M rows. I tried to process other partition which has 5M rows and it succeeded.
Error message is something like:
The following system error occurred: Insufficient quota to complete the requested service.
The Tabular Model has exceeded the memory limits, when loading the data in memory. You may need to alter the paging settings for the instance.
Zero (0) is the default. No paging is allowed. If memory is
insufficient, processing fails with an out-of-memory error. All
Tabular data is locked in memory
1 enables paging to disk using the operating system page file
(pagefile.sys). Lock only hash dictionaries in memory, and allow
Tabular data to exceed total physical memory
2 enables paging to disk using memory-mapped files. Lock only hash dictionaries in memory, and allow Tabular data to exceed total physical memory. This setting has now been discontinued.
The values are taken from this blog which will give you a good overview
Related
How can I limit maximum size on disk when using Ignite Persistence? For example, my data set in a database is 5TB. I want to cache maximum of 50GB of data in memory with no more than 500GB on disk. Any reasonable eviction policy like LRU for on-disk data will work for me. Parameter maxSize controls in-memory size and I will set it to 50GB. What should I do to limit my disk storage to 500GB then? Looking for something like maxPersistentSize and not finding it there.
Thank you
There is no direct parameter to limit the complete disk usage occupied by the data itself. As you mentioned in the question, you can control in-memory regon allocation, but when a data region is full, data pages are going to be flushed and loaded on demand to/from the disk, this process is called page replacement.
On the other hand, page eviction works only for non-persistent cluster preventing it from running OOM. Personally, I can't see how and why that eviction might be implemented for the data stored on disk. I'm almost sure that other "normal" DBs like Postgres or MySQL do not have this option either.
I suppose you might check the following options:
You can limit WAL and WAL archive max sizes. Though these items are rather utility ones, they still might occupy a lot of space [1]
Check if it's possible to use expiry policies on your data items, in this case, data will be cleared from disk as well [2]
Use monitoring metrics and configure alerting to be aware if you are close to the disk limits.
Am doing some POC with real-time scenarios for SaaS product to handle high volume of message, this will reach peak within few seconds(send/process) and listener side processing message then storing that computed data into Azure SQL Database(Separate Elastic Pool, 100 eDTU with Standard subscription), to mimic this am sending & processing message in parallel with few nodes and threads, in this case am facing some slowness in first few seconds of database operation when DTU reached maximum level the query execution is normal
Is this expected behavior?
What will happen if executes query during scaling of DTU?
How to avoid this?
When you scale up or down the service tier of an Azure SQL Database open transactions are rolled back, server logins may be disconnected, query plans may vary because the number of threads available for query changes, and the data cache and query cache will be cleared.
Since the data cache is empty, the first time you run a query it has to do a lot of physical IO, memory allocation raises and it's slow. You may take a look at queries performing slow and they may be showing the PAGEIOLATCH_SH and MEMORY_ALLOCATION_EXT waits and that corresponds to pages being pulled from disk to the buffer. The second time you run the query the data is stored on the data cache and it runs faster.
If the database faces high DTU usage for a good period of time throttling may see connection timeouts and poor performance on queries.
We have a SQL External Read replica set up and it isn't pulling in any updates from the external source, however, the size of the replica has increased each day (the size of the source database).
Looking at some metrics, there have been no Log Entries and no Read/Write operations, but there are CPU ticks and memory usage has been constant.
How can I determine what's happening? It's pulling in the entire size of the database every day, but not performing any actions. There are no SQL errors in the log.
In the Operations tab, there have been no operations listed except for the initial creation and seeding
From this other question:
With binary logs active, storage of your cloud sql will expand continuously. For anyone in the same situation, you can edit the instance and uncheck binary logs, after that the current binary logs will purge.
I would suggest checking if you have binary logging enabled, and check its size as stated in the documentation.
You can see the size of binary logs by using the SHOW BINARY LOGS MySQL command.
The impact of enabling binary logging are as follows:
Performance overhead
Cloud SQL uses row-based replication with MySQL flags sync_binlog=1 and innodb_support_xa=true. Therefore, an additional disk fsync is required for each write operation, which reduces performance.
Storage overhead
Storage of the binary logs is charged at the same rate as regular data. The binary logs are automatically truncated to the age of the oldest automated backup. Cloud SQL currently retains the most recent seven automated backups, and all on-demand backups. The size of the binary logs, and therefore the amount charged, depends on the workload. For example, a write-heavy workload consumes more binary log space than a read-heavy workload.
Another thing that could increase storage is to have Point-in-time recovery (PITR) enabled, as it uses binary logs. If the size of your binary logs are causing an issue for your instance, the documentation recommends:
You can increase the instance storage size, but the binary log size increase in disk usage might be temporary.
We recommend enabling automatic storage increase to avoid unexpected storage issues.
To delete the logs and recover storage, you can disable point-in-time recovery. Note, however, that decreasing the storage used does not shrink the size of the storage provisioned for the instance.
Logs are purged once daily, not continuously. Setting log retention to two days means that at least two days of logs, and at most three days of logs, are retained. We recommend setting the number of backups to one more than the days of log retention to guarantee a minimum of specified days of log retention.
I understand the native persistence mode of Apache Ignite allows to store as much as possible data in memory - and the potential remaining data on disk.
Is it possible to manually choose which table I want to store in memory and which I want to store EXCLUSIVELY on disk? If I want to save costs, should I just give Ignite a lot of disk space and just a small amount of memory? What if I know some tables should return results as fast as possible while other tables have lower priorities in terms of speed (even if they are accessed more often)? Is there any feature to prioritize data storage into memory at table level or any other level?
You can define two different data regions - one with small amount of memory and enabled persistence and second without persistence, but with bigger max memory size: https://apacheignite.readme.io/docs/memory-configuration
You can't have a cache (which contains rows for a table) to be stored exclusively on disk.
When you add a row to table it gets stored in Durable Memory, which is always located in RAM. Later it may be flushed to disk via Checkpointing process, which will use checkpoint page buffer, which is also in RAM. So you can have a separate region with low memory usage (see another answer) but you can't have data exclusively on disk.
When you access data it will always be pulled from disk to Durable Memory, too.
It starts w/the proverbial:
[Notes - F1 [107]] Error: An error occurred with the following error message: "System.OutOfMemoryException: Insufficient memory to continue the execution of the program. (SSIS Integration Toolkit for Microsoft Dynamics 365, v10.2.0.6982 - DtsDebugHost, v13.0.1601.5)".
But even in it's own diagnostics, it shows that plenty of memory is available (yes, that's 32GB I have on my system):
Error: The system reports 47 percent memory load. There are 34270687232 bytes of physical memory with 18094620672 bytes free. There are 4294836224 bytes of virtual memory with 981348352 bytes free. The paging file has 34270687232 bytes with 12832284672 bytes free.
The info messages report memory pressure:
Information: The buffer manager failed a memory allocation call for 506870912 bytes, but was unable to swap out any buffers to relieve memory pressure. 2 buffers were considered and 2 were locked. Either not enough memory is available to the pipeline because not enough are installed, other processes were using it, or too many buffers are locked.
I currently have the max rows set at 500 w/the buffer size at 506,870,912 in this example. I've tried the maximum buffer size, but that fails instantly, and the minimum buffer size still throws errors. I've fiddled w/various sizes, but it never gets anywhere close to processing the whole data set. The error I get when I set the DefaultBufferSize lower is:
[Notes - F1 [107]] Error: An error occurred with the following error message: "KingswaySoft.IntegrationToolkit.DynamicsCrm.CrmServiceException: CRM service call returned an error: Failed to allocate a managed memory buffer of 536870912 bytes. The amount of available memory may be low. (SSIS Integration Toolkit for Microsoft Dynamics 365, v10.2.0.6982 - DtsDebugHost,
I've looked for resources on how to tune this, but cannot find anything relevant to having a 64bit Window 10 machine (as opposed to a server) that has 32GB of RAM to play with.
For a bit more context, I'm migrating notes from one CRM D365 environment to another using Kingsway. The notes w/attachments are the ones causing the issue.
Properties:
Execution
Source
Destination
I have had this problem before and it was not the physical memory (i.e., RAM), but the physical disk space where the database is stored. Check to see what the available hard drive space is on the drive that stores both the database and transaction log files - chances are that it is full and therefore unable to allocate any additional disk space.
In this context, the error message citing 'memory' is a bit misleading.
UPDATE
I think this is actually caused by having too much data in the pipeline buffer. You will need to either need to look at expanding the buffer's memory allocation (i.e., DefaultBufferSize) or you will need to take a look at what data is flowing through the pipeline. Typical causes can be a lot of columns with large NVARCHAR() character counts. Copying the rows with MultiCast will only compound the problem. With respect to the 3rd party component you are using, your guess is as good as mine because I have not used them.
For anyone coming along later:
The error says "CRM service call returned an error: Failed to allocate a managed memory buffer of 536870912 bytes". I understood it to be the CRM Server that had the memory issue.
Regardless, we saw this error when migrating email attachments via the ActivityMimeAttachment entity. The problem appeared to be related to running the insert to the target CRM with too large a batch size and/or multi-threaded.
We set the batch size to 1 and turned off the multi-threading and the issue went away. (We also set the batch size to 1 on the request from the source - we saw "service unavailable" errors from an on-premise CRM when the batch size was too high and the attachments were too large.)