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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
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Overview Of Cloud Standards

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Cloud computing slowly becoming reality. So it has to address many concerns such as security, interoperability, portability, and governance at the earliest opportunity. This can be accelerated by compliance to guidelines and standards defined in consensus by the cloud providers.  Without addressing these concerns, users would be wary to tread this path in spite of its powerful economic model for business computing. Interoperability/integration Interoperability enables products/software components to work with or integrate with each other seamlessly, in order to achieve the desired result. Thus, it provides flexibility and the choice to use multiple products to achieve our needs. This is enabled by either integrating through standard interfaces or by means of a broker that converts one product interface to another. Cloud computing depends on compliance standards. Security Security involves the protection of information assets through various policies, procedures, a
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