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.
I'm working on a project with my client. They have a visit table which has about 7,000,000 records. The table is used in a random search page witch holds 20+ conditions to be combined. The table is defined as below:
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.
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, 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?
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 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:
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.
If I test the Native api for Node.js from the documentation, I noticed (if I'm correct) all methods and calls are synchronous. By default due to the nature of Node.js, there is only one thread of execution and normally all JavaScript methods and all calls should be asynchronous and use either a callback function (the "old way") or promises or the async/await contruct to return their result, e.g.:
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:
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.
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?
Recently, I've been working on a Business Process that processes a large JSON FHIR message containing up to 50k requests in an array within the JSON.
Currently, the code imports the JSON as a dynamic object from the original message stream, obtains an iterator from it, and processes each request one at a time in a loop.
In terms of general through-put design and long term support, I'm considering what would be a "best approach" for needing to create multiple batch files in a few different layouts from the same data-sets.
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.
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.
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.
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?
All time
