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.
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.
We are experimenting with IIS, as the PWS will be gone in newer versions.
The code which is executed, takes 15ms to run. If we execute it through PWS (REST), there is some overhead and the total execution time is 40ms, which is acceptable. However, if we go through IIS, it takes 150ms or sometimes even more.
Both PWS and IIS are running on the same server as IRIS in this case. No optimisations have been done on IIS.
Any suggestions on where to look/what to optimize on IIS?
I have created this script that does lot of writes to a single global. DB write performance is much slower than expected (compared to another similar systems).
I would like to get a list of all globals that have been read or written during a given context. In Portal, there are counters in dashboard that give the number of read/write to globals in general.
What I am looking for :
- some handler (eg: like $ZTRAP) that will be called everytime something is read/written to a global.
- to activate a "global log mode" in Portal that will dump some information to a file (like ^ISCSOAP for SOAP requests).
Is there a difference in outcome between the two screengrabs below?
In both cases, when certain conditions are met, a transformation is called and the output sent on to two targets. In the first case we surmise the transformation is called twice, and the output of the first run sent to the first target, the output of the second run to the second target. In the second case we surmise the transformation is called once, and the output duplicated and sent to the two targets.
Online document says: TUNE TABLE updates the SQL table definition (and therefore requires privileges to alter the table definition). Commonly, TUNE TABLE also updates the corresponding persistent class definition. This allows the gathered statistics to be used by the query optimizer without requiring a class compilation.
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.
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 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...
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 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:
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 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.
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.
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 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.
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