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#JDBC

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Java Database Connectivity (JDBC) is an application programming interface (API) for the programming language Java, which defines how a client may access a database.

Currently could be downloaded from here.

DataGrip is a multi-engine database environment targeting the specific needs of professional SQL developers, DataGrip makes working with databases an enjoyable and productive experience.

To work with InterSystems IRIS from DataGrip you'll need to add InterSystems JDBC driver first (once per DataGrip) and after that add all your InterSystems IRIS connections.

Part 1: Add InterSystems IRIS JDBC Driver

1. Go To File → DataSources

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Many times it is necessary copy or send files to your docker container instance.

In my case was with IRIS JDBC driver.

Docker has this recipe for this (credits to https://docs.docker.com/engine/reference/commandline/cp/):

docker cp [OPTIONS] CONTAINER:SRC_PATH DEST_PATH|-
docker cp [OPTIONS] SRC_PATH|- CONTAINER:DEST_PATH

But to copy you need your container name. Write this command for this:

docker ps

In my, my-iris is the container name.

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The Caché System Management Portal includes a robust web-based SQL query tool, but for some applications it’s more convenient to use a dedicated SQL client installed on a user’s PC.

SQuirreL SQL is a well known open source SQL client built in Java, which uses JDBC to connect to a DBMS. As such, we can configure SQuirreL to connect to Caché using the Caché JDBC driver.

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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.

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I've asked a lot of questions leading up to this, so I wanted to share some of my progress.

The blue line represents the number of messages processed. The background color represents the average response time. You can see ticks for each hour (and bigger ticks for each day). Hovering over any point in the graph will show you the numbers for that period in time.

This is super useful for "at a glance" performance monitoring as well as establishing patterns in our utilization.

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