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8 Ways to Optimize AWS Glue Jobs in a Nutshell

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  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

IoT application project need for BTech ECE students

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IOT Project IoT provides networking to connect people, things, applications, and data through the Internet to enable remote control, management, and interactive integrated services. IoT network scale, how large is it? Well, you have to think of this. The number of mobile devices exceed the number of people on Earth. In addition, predictions are made that there will be 50 billion 'things' connected to the Internet by 2020. So therefore, Internet of Things, this study is so important.  IoT Service Support. Some advanced IoT services will need to collect, analyze, and process segments of raw sensor information, raw sensor data, and we need to turn this into operational control information. Some sensor data types may have massive sizes, because the number of sensor IoT devices are so large.  #Introduction to Elecronic circuit analysis Also Read :   Project and Training on Io T So we need a platform that can collect and store all of this massive amount of