Showing posts with the label industrial iot

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8 Ways to Optimize AWS Glue Jobs in a Nutshell

  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif

Industrial IoT what GE says to improve Productivity

GE is once a top company in Heavy Engineering. This is to say items related to Thermal Power plants, Turbines, and maintenance. GE had always believed that since it knew the materials and the physics of its jet engines and medical scanners, no one could best it in understanding those machines. GE Industrial Internet  The aim is it should not share its data to third parties.    GE sets up its own IoT center.    GE is in IoT mood.    GE can improve operational efficiency by studying data from its machines like situated India and Russia. This is just an example.  GE is Targetting for Predictive Maintenace Improves industrial productivity Based on criticality productivity will zoom if maintenance carried in-time.