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Showing posts with the label Kafka Performance

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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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How to Monitor Kafka-stream's Performance

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Kafka Streams API is a part of Kafka, it goes without saying that monitoring your application will require some monitoring of Kafka as well. Performance The consumer and producer performance is one of the fundamental performance concerns for a producer and consumer.   The Kafka data flow diagram What is lag For producers, we care mostly about how fast the producer is sending messages to the broker. Obviously, the higher the throughput, the better. For consumers, we’re also concerned with performance, or how fast we can read messages from a broker. we care about how much and how fast our producers can publish to a broker, and we simultaneously care about how quickly our consumers can read those messages from the broker. The difference between how fast the producers place records on the broker and when consumers read those messages is called consumer lag How to check consumer lag To check for consumer lag, Kafka provides a convenient command-line tool, kafka-consumer-groups.sh, found in
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