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Manage concurrent write conflicts in Apache Iceberg on the AWS Glue Data Catalog

AWS Big Data

Metadata layer Contains metadata files that track table history, schema evolution, and snapshot information. In many operations (like OVERWRITE, MERGE, and DELETE), the query engine needs to know which files or rows are relevant, so it reads the current table snapshot. This is optional for operations like INSERT.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

Initially, data warehouses were the go-to solution for structured data and analytical workloads but were limited by proprietary storage formats and their inability to handle unstructured data. In practice, OTFs are used in a broad range of analytical workloads, from business intelligence to machine learning.

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RocksDB 101: Optimizing stateful streaming in Apache Spark with Amazon EMR and AWS Glue

AWS Big Data

When interacting with S3, RocksDB is designed to improve checkpointing efficiency; it does this through incremental updates and compaction to reduce the amount of data transferred to S3 during checkpoints, and by persisting fewer large state files compared to the many small files of the default state store, reducing S3 API calls and latency.

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How To Use Airbyte, dbt-teradata, Dagster, and Teradata Vantage™ for Seamless Data Integration

Teradata

Enter the host, user, and password, which are the same as those used by your Vantage instance (or ClearScape Analytics™ environment). The sample dbt project included converts raw data from an app database into a dimensional model, preparing customer and purchase data for analytics. In this example, we have used airbyte.

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Build Write-Audit-Publish pattern with Apache Iceberg branching and AWS Glue Data Quality

AWS Big Data

The importance of publishing only high-quality data cant be overstatedits the foundation for accurate analytics, reliable machine learning (ML) models, and sound decision-making. The metadata of an Iceberg table stores a history of snapshots. The data is visualized using matplotlib for interactive data analysis.

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Amazon Redshift out-of-the-box performance innovations for data lake queries

AWS Big Data

Data lakes are a powerful architecture to organize data for analytical processing, because they let builders use efficient analytical columnar formats like Apache Parquet , while letting them continue to modify the shape of their data as their applications evolve with open table formats like Apache Iceberg. improvement in performance.

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Move Beyond Excel, PowerPoint And Static Business Reporting with Powerful Interactive Dashboards

datapine

Soon businesses of all sizes will have so much amount of information that dashboard software will be the most invaluable resource a company can have. Visualizing the data and interacting on a single screen is no longer a luxury but a business necessity. That’s why we welcome you to the world of interactive dashboards.