Hi,
In Atelier I can click File --> New --> Class File, and File --> New --> Custom File etc to launch various wizards and templates to help me quickly create DeepSee KPI classes, %Installer manifests, Web Services and the like. Of course, all these are available through Studio as well. Is there anything similar in VSCode? If so where? I've looked at several videos and the documentation, but I haven't seen anything.
Thanks!
David
The last time that I created a playground for experimenting with machine learning using Apache Spark and an InterSystems data platform, see Machine Learning with Spark and Caché, I installed and configured everything directly on my laptop: Caché, Python, Apache Spark, Java, some Hadoop libraries, to name a few. It required some effort, but eventually it worked. Paradise. But, I worried. Would I ever be able to reproduce all those steps? Maybe. Would it be possible for a random Windows or Java update to wreck the whole thing in an instant? Almost certainly.
Now that the InterSystems IRIS Data Platform Community Edition is available on Docker Hub (https://hub.docker.com/_/intersystems-iris-data-platform), it seems like a great time to try InterSystems IRIS in a container. For some time already, the community edition has been available in the cloud, for example on AWS (https://community.intersystems.com/post/free-iris-community-edition-aws), but maybe it would be nice to try it locally as well. Fellow Windows users are no doubt used to eye rolling, being told “YMMV”, etc., whenever they mention using Docker for Windows.
Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.
What would be the easiest or best way to filter the options presented by a filter control?
For example, suppose that I create a query using HoleFoods that uses a named filter to filter the product categories according to some criteria. When I display the query on the dashboard, I would like to provide a filter control that will allow users to further constrain the product categories. However, a simple filter control will display all the product categories available in the cube many of which are irrelevant to the current query.
Thanks for your help!
According to the documentation (2016.1) we can use either a system defined web application (/api/deepsee) or create a custom web application for handling requests. What are some reasons to use one rather than the other?