AWS Big Data Blog

Category: AWS Glue

Automatically detect Personally Identifiable Information in Amazon Redshift using AWS Glue

With the exponential growth of data, companies are handling huge volumes and a wide variety of data including personally identifiable information (PII). PII is a legal term pertaining to information that can identify, contact, or locate a single person. Identifying and protecting sensitive data at scale has become increasingly complex, expensive, and time-consuming. Organizations have […]

How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

In our increasingly digital world, affordable access to high-speed broadband is a necessity to fully participate in our society, yet there are still millions of American households without internet access. HR&A Advisors—a multi-disciplinary consultancy with extensive work in the broadband and digital equity space is helping its state, county, and municipal clients deliver affordable internet […]

Prepare and load Amazon S3 data into Teradata using AWS Glue through its native connector for Teradata Vantage

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner. For […]

Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt focuses on the transform layer of extract, load, transform (ELT) or extract, transform, load (ETL) processes across data warehouses and databases through specific engine adapters to achieve extract and load functionality. It […]

Enhance query performance using AWS Glue Data Catalog column-level statistics

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum, resulting in improved query performance and potential cost savings. Data lakes are designed for storing vast amounts […]

Introducing Apache Hudi support with AWS Glue crawlers

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. Data engineers use Apache Hudi for streaming workloads as well as to create efficient incremental data pipelines. Hudi provides tables, transactions, efficient […]

Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. When running properly, it provides timely and trustworthy information. However, without vigilance, the varying data volumes, characteristics, and application behavior can cause data pipelines […]

Introducing AWS Glue serverless Spark UI for better monitoring and troubleshooting

Today, we are pleased to announce serverless Spark UI built into the AWS Glue console. You can now use Spark UI easily as it’s a built-in component of the AWS Glue console, enabling you to access it with a single click when examining the details of any given job run. There’s no infrastructure setup or teardown required. AWS Glue serverless Spark UI is a fully-managed serverless offering and generally starts up in a matter of seconds. Serverless Spark UI makes it significantly faster and easier to get jobs working in production because you have ready access to low level details for your job runs.

Architecture Diagram

Visualize Amazon DynamoDB insights in Amazon QuickSight using the Amazon Athena DynamoDB connector and AWS Glue

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data import and export tools. The scalability and flexible data schema of DynamoDB make it well-suited for a variety of use cases. These include internet-scale […]

Use generative AI with Amazon EMR, Amazon Bedrock, and English SDK for Apache Spark to unlock insights

In this era of big data, organizations worldwide are constantly searching for innovative ways to extract value and insights from their vast datasets. Apache Spark offers the scalability and speed needed to process large amounts of data efficiently. Amazon EMR is the industry-leading cloud big data solution for petabyte-scale data processing, interactive analytics, and machine […]