Ssis-732-en-javhd-today-0804202302-26-30 Min | Fully Tested |
Finally, a wrote the CSV to /tmp/parsed_telemetry.csv . Dr. Liu ran the package. In the Execution Results window, the package executed in 12.3 seconds —far faster than Maya expected for a process involving a Docker container, a Kafka source, and a Java library.
2023-04-02 08:04:13.112 INFO [main] com.mycompany.parsers.TelemetryParser - Received payload of size 4.2 MB 2023-04-02 08:04:13.115 WARN [main] com.mycompany.parsers.TelemetryParser - Allocating buffer of 8 MB 2023-04-02 08:04:13.120 ERROR [main] com.mycompany.parsers.TelemetryParser - OutOfMemoryError: Java heap space Maya realized the issue: the were much larger than anticipated because the fleet’s new sensors were sending high‑resolution LIDAR point clouds embedded in the telemetry. The Java parser tried to load the entire payload into memory, causing the heap overflow. SSIS-732-EN-JAVHD-TODAY-0804202302-26-30 Min
Lila, a petite woman with a confident posture, typed: “Apologies for the late entry. I’m fascinated by this hybrid approach. At Orion we’ve been exploring edge‑to‑cloud pipelines that run Java analytics on the device and push results directly to Azure. Could SSIS‑732 handle a scenario where the Java component runs on an Azure IoT Edge module instead of a Docker container on the server?” A hush fell over the virtual room. Dr. Liu smiled, clearly pleased. Dr. Liu: “Great question, Lila. The beauty of the JAVAVD Bridge is that it abstracts the execution environment. Whether the Java code runs in a Docker container on‑premises, on an Azure IoT Edge device, or even in a Kubernetes pod , the SSIS package merely sends an HTTP request. The only thing that changes is the endpoint URL and authentication.” He shared a quick diagram: an IoT Edge device running a Java microservice , exposing an HTTPS endpoint secured with Azure AD . The Web Service Task in SSIS could use OAuth2 to obtain a token and call the edge service. This architecture would dramatically reduce latency, because raw sensor data would be processed at the edge before being aggregated in the cloud. Finally, a wrote the CSV to /tmp/parsed_telemetry
