This post will show you an approach to size shared memory requirements for database applications running on InterSystems data platforms including global and routine buffers, gmheap, and locksize as well as some performance tips you should consider when configuring servers and when virtualizing Caché applications. As ever when I talk about Caché I mean all the data platform (Ensemble, HealthShare, iKnow and Caché).

A list of other posts in this series is here

In this post I show strategies for backing up Caché using External Backup with examples of integrating with snapshot based solutions. The majority of solutions I see today are deployed on Linux on VMware so a lot of the post shows how solutions integrate VMware snapshot technology as examples.

The topic of for/while loop performance in Caché ObjectScript came up in discussion recently, and I'd like to share some thoughts/best practices with the rest of the community. While this is a basic topic in itself, it's easy to overlook the performance implications of otherwise-reasonable approaches.

Enterprises need to grow and manage their global computing infrastructures rapidly and efficiently while simultaneously optimizing and managing capital costs and expenses. Amazon Web Services (AWS) and Elastic Compute Cloud (EC2) computing and storage services meet the needs of the most demanding Caché based application by providing
 a highly robust global computing infrastructure.

Hi all,

I have an incoming JSON message with a string field exceeding in length the 'caché long-string limit' of 3641144 characters.

Using {}.%FromJSON(instream) I am able to create %DynamicObject properly. However, I am unable to access the long property, as in every assignment, I get the <MAXSTRING> error.

Is there any way for me to obtain contents of the 'too long' string field as a stream?

Thanks

Jiri

My issue is that I don't know why Ensemble processes incoming data in the wrong encoding.

Update: Issue was solved, I think, see my answer below.

Can I connect to Cache using SSMS (SQL Server Management Studio) and view schemas and build queries as I do for SQL Server?

If yes, step-by-step instructions for setting up the connection would be greatly appreciated.

I googled the topic but didn't find any results that were on target.

Thanks,

Christian Bahnsen

Hi guys,

Couple days ago, a customer approached me with the wish to enhance their existing legacy application, that uses SOAP (Web)Services so it shares the same authorization with their new application API based on REST. As their new application uses OAuth2, the challenge was clear; how to pass access token with SOAP request to the server.

After spending some time on Google, it turned out, that one of possible ways of doing so was adding an extra header element to the SOAP envelope and then making sure the WebService implementation does what is needed to validate the access token.

Hi, I was hoping that someone could point me to the error in my ways.  I am trying to follow the examples to setup Ensemble 2017.1 in a docker container on an Ubuntu 16.04 virtual machine.

I have a directory that contains

Dockerfile
cache.key
ensemble-lnxubuntux64.tar.gz

When I execute:

docker build -t ensemble-simple .

I am getting the following error:

So, one day you're working away at WidgetsDirect, the leading supplier of widget and widget accessories, when your boss asks you to develop the new customer facing portal to allow the client base to access the next generation of Widgets..... and he wants you to use Angular 1.x to read into the department's Caché server.   

There's only one problem:  You've never used Angular, and don't know how to make it talk to Caché.

This guide is going to walk through the process of setting up a full Angular stack which communicates with a Caché backend using JSON over REST.  

I am often asked by customers, vendors or internal teams to explain CPU capacity planning for large production databases running on VMware vSphere.

In summary there are a few simple best practices to follow for sizing CPU for large production databases:

• Plan for one vCPU per physical CPU core.
• Consider NUMA and ideally size VMs to keep CPU and memory local to a NUMA node.
• Right-size virtual machines. Add vCPUs only when needed.

Generally this leads to a couple of common questions:

Here is my original query:

SELECT EventType, InitiatedAt, COUNT(*) as cnt
FROM HS_IHE_ATNA_Repository.Aggregation
WHERE EventType = 'LOGIN'
AND LocalDateTime > '2016-02-16 11:00:00'
GROUP BY EventType, InitiatedAt

This gives me data like this:

I wanted to write it as a comment to article of @Evgeny Shvarov . But it happens to be so long, so, decided to post it separately.

I would like to add a bit of clarification about how docker uses disk space and how to clean it.  I use macOS, so, everything below, is mostly for macOS, but docker commands suit any platform.