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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.
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InterSystems IRIS offers various ways how to profile your code, in most cases it produces enough information to find the places where the most time is spent or where the most global sets. But sometimes it's difficult to understand the execution flow and how it ended at that point.
To solve this, I've decided to implement a way to build a report in a way, so, it's possible to dive by stack down
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%
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.
You may have heard about our mg-dbx-napi interface for IRIS which provides insanely fast access from Node.js. If you've been following recent developments in the server-side JavaScript world, you'll be excited to know that mg-dbx-napi also works with Bun.js, the latter proving to be significantly faster than Node.js for many/most purposes.
Of course, if you're a Node.js user, you'll probably wonder how mg-dbx-napi compares with the Native API for Node.js that is included with IRIS.
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Windows Subsystem for Linux (WSL) is a feature of Windows that allows you to run a Linux environment on your Windows machine, without the need for a separate virtual machine or dual booting.
WSL is designed to provide a seamless and productive experience for developers who want to use both Windows and Linux at the same time**.
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.
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It's been a long time since I didn't write an update post on IoP.
So what's new since IoP command line interface was released?
Two new big features were added to IoP:
- Rebranding: the grongier.pex module was renamed to iop to reflect the new name of the project.
- Async support: IoP now supports async functions and coroutines.
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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?
we're planning some work on our SQL Query Plan functionality for a future release of InterSystems IRIS and are interested to hear how you're using them today, or what'd keep you from using them. Rather than try and fit everything in a rigid survey, I thought a simple thread on our beloved DC might also reveal some use patterns that we support or could do a better job on.
Since the introduction of Embedded Python there has always been doubt about its performance compared to ObjectScript and on more than one occasion I have discussed this with
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!
I would like to know if an encrypted caché database can run significantly slower than a normal "unencrypted" database, in a way that is noticeable to the end user (e.g. slower response time for most pages, especially the ones that rely on read/writing to globals).
I searched in Intersystems knowledge base and couldn't find anything related. I'm looking for possible before/after benchmarks.
One of my colleagues had developed an interface in Health Connect (HealthShare 2019.1) to add large amounts of data to an external SQL Server database. The data comes from many text files with delimited rows and data for one table per file. There is a business process to read a file line by line and send an Insert Request to an operation.
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