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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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Top features in the design of data modelling (1 of 2)

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[Data modelling jobs career] The analogy with architecture is particularly appropriate because architects are designers and data modeling is also a design activity. In design, we do not expect to find a single correct answer, although we will certainly be able to identify many that are patently incorrect. Two data modelers (or architects) given the same set of requirements may produce quite different solutions. Data modeling is not just a simple process of "documenting requirements" though it is sometimes portrayed as such. Several factors contribute to the possibility of there being more than one workable model for most practical situations. First, we have a choice of what symbols or codes we use to represent real-world facts in the database. A person's age could be represented by Birth Date, Age at Date of Policy Issue, or even by a code corresponding to a range ("H" could mean "born between 1961 and 1970"). Second, there is usually more
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