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...
Any idea/suggestion?
I have a ZEN page with nine tablepanes. Each tablepane queries a table in the same SQLServer db. I have a single SQLGateWay(odbc) to this SQLServer db. I need to get better performance when I query all nine table at the same time. Would my performance improve if I had nine SQLGateWays(nine odbc configurations/connections), one for each query? I would appreciate any and all suggestions for getting the very best performance when using SQLGateWays. Thank you.
Hi,
Has anyone got any experience of using the Microsoft diskspd utility to test the storage infrastructure in Healthshare/Ensemble environment.
I am interested in getting some figures to highlight any issues with different approaches to provisioning the disks on our new environment.
I am at a loss as to what parameters I should use to give a reasonable synthetic load that will give me any indication of potential issues. Any pointers would be greatly appreciated!
Kind Regards,
Jason
Hi,
I'm trying to find the faster way to get the data from a class, and I find it very slow compared to traditional globals. So, I hope some of you can bring some light to me :-)
I have thousands of registers in a class, and to access it quickly I'm going with $o at the index. From there, I get the values using $listget(). Something like that:
Has anyone done any kind of integration with Dynatrace, which is a JVM transaction monitoring tool? Our organization uses this extensively with our Java and .Net applications and we wanted to know if it is even possible.
Currently, we are receiving an alert that states, "Write Daemon still on pass 31". It's been that way for a few hours.
I was wondering if it is possible to identify what the WD has left to work on so that we can see how we can reduce this and possibly identify if there are issues with the way something is written.
Thanks in advance for any insight.
Currently, we are running 2014.1 on two different servers (OpenVMS, RHEL). The plan is to transition from OpenVMS to RHEL, but our Write Daemon is in a Troubled state on both servers.
On the OpenVMS server, we have a WIJ file that's 26G and can grow to 40G (size of database cache). Since it hasn't grown to 40G, we don't believe the size of the WIJ file to be the issue.
What else should we be looking at regarding the performance of the Write Daemon?
Hi Guys,
Can you please advise on the below queries.
Query 1:
Example 1:
S a="345",b="arun",c="kumar",d="hi",e="yello",f="orange"
Example 2:
S a="345" S b="arun" S c="kumar" S d="hi" S e="yello" S f="orange"
Can you please advise me, which one is performance wise is better.
Query 2:
Example 1:
S:a=1 R="Arun"
Example 2:
I a=2 R="Arun"
Please advise me, which one is giving better performance in this.
Intersytems documentation says not to hold entire SDA as object in In-memory.
Here is a snippet that I learned yesterday
You can define an index on a collection property but when I tried to use it, I failed. I was using
Select ….. where …. :xx %INLIST collproperty
But this will not use an index, but the equivalent syntax
SELECT .. WHERE ... FOR SOME %ELEMENT(collproperty) (%VALUE=:xx)
will use the index
Check out
As I was going though and trying to figure out why our CACHE.dat has increased in size over the past 18 days, I found that EnsLib_HL7.Message is still retaining messages dating back to 2014 even though we have our purge set to 10 days. Has anyone else experienced this?
Thanks
Scott Roth
The Ohio State University Wexner Medical Center
Hello,
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?
Hello Community,
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.
Here is a couple of screenshots :
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.
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.
I am designing the software architecture for an Ensemble/Healthshare production to be deployed on Amazon AWS EC2 servers (2 mirrored m4.large - 4 vCPUs / 16 GiB RAM running RedHat Linux 3.10.0-327.el7.x86_64 and Healthshare for RHEL 64-bit 2016.2.1). It's a rather CPU-intensive production involving massive XSLT 2.0 transformations (massive both in terms of size and volume). I was wondering if anyone has experience configuring Ensemble productions on EC2 servers. My question or concern has to do with the following statement in the Ensemble documentation:
Caché Version String: Cache for UNIX (Red Hat Enterprise Linux for x86-64) 2016.2.1
We have a mirrored Ensemble system (110, backup and 210, primary). At one time (14:00) there is a disruption in the production. The messages are not being processed.
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.
As always, thanks a lot for your help.
Hi, colleagues!
Consider you need to put some (less than 1GB) data to an indexed array and do some data manipulations and calculations with it.
Should I prefer global or local for it?
Is there any general rule when local is faster than global and vice-versa?
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 have been asked to assist in the planning of the a new server for our database, which we will be changing operating systems from OpenVMS to Linux (RedHat distribution). However, its difficult to find material regarding what would be recommended, which is likely due to the database being proprietary.
In looking at the information provided below and hoping to decrease processing time, would anyone be able to recommend type of configuration we should have for the new Linux server? Please feel free to ask any clarifying questions.
Any recommendations, to this VMware disk type debate, with Cache installations in particular?
Thick Provision Lazy Zeroed
Thick Provision Eager Zeroed
Thin Provision
While I can see the benefits that $ZSTORAGE could have if used properly, I have not seen it used in the environments I have worked in. I was wondering if there are any developers that promote its usage.
If used properly, I would imagine it could be highly effective in maximizing free memory since some processes will never go over X amount, while others may very well need much more.
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[15] 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:
x("Adam") = "Red"
x("George") = "Blue"
x("Bryan") = "Green"
etc...
Can someone direct me to where in the documentation we can find how consumption may be calculated for global storage?
| Caché Version | 2010.1 |
| Operating System | HP OpenVMS 8.4 |
EDIT: After receiving some responses, it seems I was unclear in my initial inquiry. I am looking to determine our rate of consumption of storage; however, I am having some difficulty in doing that.
I’ve a server that is running Windows Server 2003 R2 Enterprise Edition SP2 x86.
I just noted that you cannot allocate shared memory beyond 1.6GB.
Is this a known problem between Cache and this OS architecture, and has anyone configured it beyond this?
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.
We don't often use SQL within our org, which is mostly due to the performance issue we experience due to the quantity of data we are reviewing.
Aside from the standard performance measures for non-Caché databases, are there any recommended approaches when querying large tables?
The table would have roughly 50M records, but there are not a finite amount of sub-nodes.
