I want to process more requests per second in Ensemble 2015 (soap service).My problem is in a business process that makes a great transformation.I thought that I can put its group size to 4 (the current value is 1), or put 4 business processes and apply, for example, the round-robin algorithm. Which alternative is better?
Currently, we have an application running in one namespace ("Database B") that has globals and routines mapped to another database ("Database A"). After enforcing clean up on Database A, we found that 90% of the disk is free. We would like to compact Database A and release the unused space. However, we are running OpenVMS, which seems to be the issue.
For databases consisting of only globals, we are able to use ^GBLOCKCOPY; however, we need to ensure that the routines and mappings are also copied.
I recently encountered a issue with Caché and I can't figure out where the problem is coming from.
I noticed that the license limit (200) was reached whenever I was opening my Studio (so it seems). When this occurs, I restart Caché (with the Cube in the Taskbar), and the number of license used is back to 1%, but grows back after. The time taken before the number of license grows back again looks pretty random.
After what is seemed was weeks, I finally got SSL/TLS enabled on both Apache Web Server and IRIS using the Web Gateway. However while we can now use HTTPS to connect to our Development instance of IRIS, I am running into several errors when I have others try to access the Management Portal via HTTPS.
If I were trying to access an index of a global variable, what time complexity would this operation have? My understanding of languages like Java/C++ is that arrays are stored as blocks of memory so that x would have a lookup time complexity of O(1) because it just goes to (address of the array + 15) and retrieves the value stored there.
How does this work in Cache where the index of a variable isn't necessarily an integer value? If I were to have a variable like the following:
Suppose we need to store millions of values temporarily, that means, we don't care about them if we lose them but our application use them to get realtime information. Should I use Cachetemp or whatever other DB without journaling enabled? If answer is Cachetemp, shouldn't be a problem if we decide to scale using App Server + ECP? I'm not sure what would happen with the app logic in such architecture as I guess I couldn't map and share cachetemp...
Currently, namespace Alpha is configured to use database AlphaDB as its global database. How would we go about having namespace Alpha configured to use database AlphaDB for its global database except where global ^Customers(CustomerId) has a CustomerId greater than 10M, which we would like to have it redirected to database BetaDB.
In other words, ^|"AlphaDB"|Customers contains all customers between 1 and 10,000,000; and ^|"BetaDB"|Customers contains all customers greater than 10,000,000. Any help would be appreciated.
Running cache 5.0.21 64 bit on Windows server 2016 in virtual environment. Trying to understand why every single process disk read speed (simple sql data walks) caps around ~20MB/s, however 2 paralell such tasks on different data areas can reach 19MB/s each, four - 17MB/s each, that is 70MB/s total, etc. Also simple copy file to nul on that system reach ~400MB/s.
What can keep single query on idle system from reaching for example 200MB/s? Virtualization? Windows? Cache? Processors are below 1-3%
I work in a small development company that uses Caché as a database. In some support cases I have doubts about whether the client's infrastructure environment is not affecting Caché's response time. Reading a bit about comparing installations in different environments, both in production as testing and homologation environments , I understood that the TPC-E is a benchmarking method accepted in the market.
We have 1lakh records in table and while using sql select statement , it is taking more than 9mins to 12 mins to get the records. could you please how to optimize this performance issue if we have more records. how to optimize it.
A long time ago I enabled Activity Monitoring to be able to save myself headaches in the future when looking at the performance of various message routes through our productions. It's served it's purpose of answering questions on how many messages we process a week etc but I had not had the chance to really dig down into the stats for specific message types or destinations to pin point issues.
In the context of IKO (Iris Kubernetes Operator) the question of Service not redirecting dynamically to the correct Pod is still pending. In production this can be dangerous since an overload (or any other simpler problem) can cause you to change the main Pod and leave the application inoperable until we intervene.
Intersystems support warned that this is still an issue of IKO, but there are some possibilities that I am studying.
To explore an idea I had, I would like the help of this Forum to answer the following question:
We are seeing more and more customers being lured with latest infrastructure technologies, particularly Composable Infrastructure. Coming with all sorts of data center consolidations and costs savings.
Question is: are there any concerns for HealthShare/TrakCare being run on these platforms or things to look out for? Anyone out there, already on these platforms?
To be more specific this is HPe Synergy with 480 Compute blades booting as bare metal.
Please excuse my ignorance. I am trying to identify what areas would be best to review in the System Dashboard (for Cache 2010.2) for performance issues with the database. It seems to be running slower than usual, but I am trying to find out the best way to go about identifying what the issue is.
The following are captures from the System Dashboard.