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If several application servers are connected using ECP, and one of them create many locks, so many that lock table became full :

Should we expect only that application server to be impacted ? (usually, when lock table is full the system became instable). Or, are other application servers going to be impacted the same way ? (because that lock table is synchronized and maintained in sync across all servers)

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I am a first time Python Contest participant and am interested in potentially implementing the community idea found in https://ideas.intersystems.com/ideas/DPI-I-542 if it is something relevant to Python.

Would anyone be able to shed a bit of light on what the desired outcome of that idea being implemented is? There were a lot of upvotes on that idea but there wasn't very much information in it. Thanks!

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Hi Developers!

With InterSystems IRIS Cloud SQL recently becoming Generally Available, some of you may have had a chance to try it out. Or maybe you used it for your contest entry or during the EAP period. We're curious to learn what YOU think of it. So, have you already tried the new service InterSystems IRIS Cloud SQL?

We have launched a new Ideas Portal category dedicated to this database-as-a-service (DBaaS) where we're looking for your ideas on how we can improve InterSystems IRIS Cloud SQL.

Or share your experience with the service in the comments to this post.

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Hello everyone!

I have set up an EnsLib.REST.GenericService with an EnsLib.HTTP.InboundAdapter which forwards the http requests received by a web app to my Business Process.

I would like to parse HTTP multipart/form messages I am receving and be able to iterate over the various fields within the request body, accessing its content type and the content itself.

As far as I understand I should use the %Net.MIMEReader class which should return a list of %Net.MIMEPart, one for each field within the request. However if I do :

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Dear Developer Community,

It seems the Grinch got a little mischievous and swiped our recap before it could make its grand debut! 🎄💚 But don’t worry — our developer elves are hard at work tracking it down, and the full recap will be online shortly.

Hang tight, and we promise to have it back in time to spread all the holiday cheer (and the details you’re waiting for). Thanks for your patience, and keep an eye out for the return of our festive recap!

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I have a primary dispatch class that implements %CSP.REST.AccessCheck() for some high level access checks before the route table forwards the request to the implementation classes which also implement %CSP.REST.AccessCheck() for some lower level access checks. The idea is that we know where we are in the implementation class and what the user is trying to do, so it makes more sense to check some lower level items there rather than trying to parse out the request at the dispatch class.

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Hello,
Please, we would need your help 🙂:

In a development environment, we have added quite a few presentation contexts to the DICOM configurations (the associations). We would need to find a way to export them from this environment to make it easier for us to import them in PRO (and avoid doing it by hand one by one).

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After performing Concurrent External Backup and restarting the instance, if I want to perform an incremental backup of Concurrent External Backup again.

Should I redo the following steps?

  1.  Do CLRINC^DBACK("QUIET")
  2.  Set x=$$BACKUP^DBACK("","E","Dirty external backup - incrementals must be applied.","","","")
  3. Set x=$$BACKUP^DBACK("","I","Nightly","test.bck","N","bck.log","QUIET","N","Y")
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Introduction

Businesses often use in-memory databases or key-value stores (caching layers) when applications require extremely high performance. However, in-memory databases incur a high total cost of ownership and have hard scalability limits, incurring reliability problems and restart delays when memory limits are exceeded. In-memory key-value stores share these limitations and introduce architectural complexity and network latency as well.

This article explains why InterSystems IRIS™ data platform is a superior alternative to in-memory databases and key-value stores for highperformance SQL and NoSQL applications.

Taking Performance and Efficiency to the Next Level

InterSystems IRIS is the only persistent database that can match or beat the performance of in-memory databases and caching layers for concurrent data ingestion and analytics processing. It can process incoming transactions, persist the data to disk, and index it for analytics in under one microsecond on commercially available hardware without introducing network latency.

The superior ingest performance of InterSystems IRIS results in part from its multi-dimensional data engine, which allows efficient and compact storage in a rich data structure. Using an efficient, multi-dimensional data model with sparse storage techniques instead of two-dimensional tables, random data access and updates are accomplished with very high performance, fewer resources and less disk capacity. It also provides in-memory, in-process APIs in addition to traditional TCP/IP access APIs to optimize ingest performance.

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InterSystems IRIS Data Platform is a comprehensive, multi-model, multi-workload data platform that is ideal for accommodating the challenging requirements of applications for the Internet of Things. It is a complete platform for developing, executing, and maintaining IoT applications in a single, consistent, unified environment. It features a distributed architecture to support massive data-ingest rates and data volumes, while providing the flexibility and durability of an enterprise-grade transactional multi-model database to ingest, process, and persist data from a wide range of devices in different formats. It features a complete set of integration, event-processing, and integrated analytics capabilities, including full SQL support and text processing, business process orchestration, and a standards-based development environment.

Connect to, ingest, and persist a wide range of disparate device data types and formats

The data types associated with IoT applications are often heterogeneous, as they may originate from various devices with diverse functions and manufactured by different vendors. The underlying data platform must be able to ingest and process a wide range of raw data types in their original formats. Many applications also require the data platform to persist all of the disparate source data to detect deviations from normal ranges, accommodate downstream ad hoc analytics, maintain regulatory compliance, and fulfill other purposes.

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On Encounter container we want to map some data from Z segments is that possible? Presently the mapping from HL7to SDA3 is taking place from HL7 defines segments . is there a way to push the data from Z segment.

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