Hi All,

I have two tables LB_TestSet and LB_Transfer

LB_Transfer has a list if TestSet row IDs, so i am doing the following join

SELECT 
LBTS_RowID,
,LBTS_CollectedDate
FROM SQLUser.LB_TestSet 
JOIN SQLUser.LB_Transfer ON ($LISTBUILD(LBTS_RowID) %INLIST LBTR_TestSetList)
WHERE LBTS_CollectedDate BETWEEN '2019-01-01' AND  '2019-05-10'

 

Without the date filter the query returns data, but if i add the date filter no data is returned

I also tried using %INTERNAL, %EXTERNAL TO_DATE('2009-01-01','YYYY-MM-DD')

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Hi Community!

This is the update on what are the new applications submitted on OpenExchange in March 2019

New Applications

isc-tar  published by @Dmitry Maslennikov 

Compact files as TAR or Extract files from TAR files

Light weight EXCEL download v.1.0 published by @Robert.Cemper 

This is the working example of a light weight export to EXCEL based on data in SAMPLES namespace. Good old CSP is well equipped to produce HTML tables accepted from EXCEL as input. With modern Browsers you don't even need and tags. So the required code around your SQL result set is really slim. And you are free to add any formatting you need either by HTML or in SQL.

PythonGateway v.0.7 published by @Eduard Lebedyuk 

Python Gateway for InterSystems Data Platforms.

Adopted Bitmaps v.1.0 published by @Robert.Cemper 

This is a running example of the Bitmap Adoption

WebSockets Tutorial v.1.0 published by @Lily Taub 

A short tutorial on WebSockets in InterSystems IRIS 2018.1+ and Caché 2016.2+

Sync Data with DSTIME v.1.0.0 published by @Robert.Cemper

Other Sync-Tools just work from Caché/IRIS to Caché/IRIS. Synchronizing your data to some external DB you requires some other solution. DSTIME can do it.

HL7 and SMS Interoperability Demo v.1.3 published by @Amir Samary 

This demo shows how easy it is to integrate an Electronic Medical Record system that is sending HL7 messages with AWS.

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Hi,

  I have a permanent job opportunity which would ideally suit someone from Europe who want's to experience the UK (initially London), the requirements are fluent in Cache Objects, SQL, XML, Integration,  English Language and be self motivated with a desire to experience London.

  I am NOT a recruitment agency and will offer personal help in relocation and culture differencies to handle moving countries. 

  I do not offer a relocation package but will offer advice, guidance and help in relocation.

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Breaking news!

InterSystems just announced the availability of the InterSystems IRIS for Health™ Data Platform across the Amazon Web ServicesGoogle Cloud, and Microsoft Azure marketplaces.

With access to InterSystems unified data platform on all three major cloud providers, developers and customers have flexibility to rapidly build and scale the digital applications driving the future of care on the platform of their choice. 

To learn more please follow this link

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The Amazon Web Services (AWS) Cloud provides a broad set of infrastructure services, such as compute resources, storage options, and networking that are delivered as a utility: on-demand, available in seconds, with pay-as-you-go pricing. New services can be provisioned quickly, without upfront capital expense. This allows enterprises, start-ups, small and medium-sized businesses, and customers in the public sector to access the building blocks they need to respond quickly to changing business requirements.

 

Updated: 2-Apr, 2021 

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Hi Community!

I'm pleased to announce that we've just launched the new product in the family of InterSystems Data Platforms:

InterSystems IRIS for Health

IRIS for Health — is the world’s first and only data platform engineered specifically for healthcare. It empowers you to rapidly create and scale the industry’s next breakthrough applications.

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In the last post we scheduled 24-hour collections of performance metrics using pButtons. In this post we are going to be looking at a few of the key metrics that are being collected and how they relate to the underlying system hardware. We will also start to explore the relationship between Caché (or any of the InterSystems Data Platforms) metrics and system metrics. And how you can use these metrics to understand the daily beat rate of your systems and diagnose performance problems.

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2 10 3,148

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:

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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

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** Revised Feb-12, 2018

While this article is about InterSystems IRIS, it also applies to Caché, Ensemble, and HealthShare distributions.

Introduction

Memory is managed in pages.  The default page size is 4KB on Linux systems.  Red Hat Enterprise Linux 6, SUSE Linux Enterprise Server 11, and Oracle Linux 6 introduced a method to provide an increased page size in 2MB or 1GB sizes depending on system configuration know as HugePages.

At first HugePages required to be assigned at boot time, and if not managed or calculated appropriately could result in wasted resources.  As a result various Linux distributions introduced Transparent HugePages with the 2.6.38 kernel as enabled by default.  This was meant as a means to automate creating, managing, and using HugePages.  Prior kernel versions may have this feature as well however may not be marked as [always] and potentially set to [madvise].  

Transparent Huge Pages (THP) is a Linux memory management system that reduces the overhead of Translation Lookaside Buffer (TLB) lookups on machines with large amounts of memory by using larger memory pages.  However in current Linux releases THP can only map individual process heap and stack space.

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One of the great availability and scaling features of Caché is Enterprise Cache Protocol (ECP). With consideration during application development distributed processing using ECP allows a scale out architecture for Caché applications. Application processing can scale to very high rates from a single application server to the processing power of up to 255 application servers with no application changes.

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2 6 2,031

This post provides guidelines for configuration, system sizing and capacity planning when deploying Caché 2015 and later on a VMware ESXi 5.5 and later environment.

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Myself and the other Technology Architects often have to explain to customers and vendors Caché IO requirements and the way that Caché applications will use storage systems. The following tables are useful when explaining typical Caché IO profile and requirements for a transactional database application with customers and vendors.  The original tables were created by Mark Bolinsky.

In future posts I will be discussing more about storage IO so am also posting these tables now as a reference for those articles. 

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Index

This is a list of all the posts in the data platforms capacity planning and performance series in order. Also a general list of my other posts. I will update as new posts in the series are added.


You will notice that I wrote some of the posts before IRIS was released and refer to Caché. I will revisit the posts over time, but in the meantime; Generally, the advice for configuration is the same for Caché and IRIS. Some command names may have changed; the most obvious example is that anywhere you see ^pButtons command, you can replace it with ^SystemPerformance.

Capacity Planning and Performance Series

Generally posts build on previous, but you can also just dive in to subjects that look interesting.


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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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