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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. Referring to the data dictionary and screenshots, its evident that the complete data lineage information is highly dispersed, spread across 29 lineage diagrams. where(outV().as('a')),

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

ML apps need to be developed through cycles of experimentation: due to the constant exposure to data, we don’t learn the behavior of ML apps through logical reasoning but through empirical observation. but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise. Versioning.

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Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg

AWS Big Data

Major market indexes, such as S&P 500, are subject to periodic inclusions and exclusions for reasons beyond the scope of this post (for an example, refer to CoStar Group, Invitation Homes Set to Join S&P 500; Others to Join S&P 100, S&P MidCap 400, and S&P SmallCap 600 ). Load the dataset into Amazon S3.

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Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes

AWS Big Data

For more information, refer to Retry Amazon S3 requests with EMRFS. To learn more about how to create an EMR cluster with Iceberg and use Amazon EMR Studio, refer to Use an Iceberg cluster with Spark and the Amazon EMR Studio Management Guide , respectively. We expire the old snapshots from the table and keep only the last two.

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Use Batch Processing Gateway to automate job management in multi-cluster Amazon EMR on EKS environments

AWS Big Data

For comprehensive instructions, refer to Running Spark jobs with the Spark operator. For official guidance, refer to Create a VPC. Refer to create-db-subnet-group for more details. Refer to create-db-subnet-group for more details. Refer to create-db-cluster for more details. SubnetId" | jq -c '.') mysql_aurora.3.06.1

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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

To learn more, refer to Exploring new ETL and ELT capabilities for Amazon Redshift from the AWS Glue Studio visual editor. or later supports change data capture as an experimental feature, which is only available for Copy-on-Write (CoW) tables. For instructions, refer to Set up IAM permissions for AWS Glue Studio.

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Amazon Managed Service for Apache Flink now supports Apache Flink version 1.19

AWS Big Data

In every Apache Flink release, there are exciting new experimental features. Refer to Using Apache Flink connectors to stay updated on any future changes regarding connector versions and compatibility. or later, refer to FlinkRuntimeException: “Not allowed configuration change(s) were detected”. SQL Apache Flink 1.19