article thumbnail

Optimize data layout by bucketing with Amazon Athena and AWS Glue to accelerate downstream queries

AWS Big Data

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

article thumbnail

BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

Bayerische Motoren Werke AG (BMW) is a motor vehicle manufacturer headquartered in Germany with 149,475 employees worldwide and the profit before tax in the financial year 2022 was € 23.5 Data providers and consumers are the two fundamental users of a CDH dataset. The difference lies in when and where data transformation takes place.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Fabrics, Meshes & Stacks, oh my! Q&A with Sanjeev Mohan

Alation

He’s a true expert in the field, having worked at Oracle, Scient, BearingPoint, and Booz Allen Hamilton, and on data-focused projects with companies like LMVH, Major League Baseball, Toyota, American Express, Freddie Mac, and many, many others. I recently had the opportunity to connect with Mohan at Snowflake Summit 2022 in Las Vegas.

article thumbnail

Amazon EMR on EKS widens the performance gap: Run Apache Spark workloads 5.37 times faster and at 4.3 times lower cost

AWS Big Data

We have been continually improving the Spark performance in each Amazon EMR release to further shorten job runtime and optimize users’ spending on their Amazon EMR big data workloads. release in January 2022, the optimized Spark runtime was 3.5 times faster than our first release of 2022, Amazon EMR 6.5. As of the Amazon EMR 6.5

Testing 77
article thumbnail

Supercharge Your Data Lakehouse with Apache Iceberg in Cloudera Data Platform

Cloudera

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

article thumbnail

Why Data Lineage is Key to the LIBOR Transition

Octopai

As you may have heard, the existing London Interbank Offered Rate (LIBOR) will be retired on January 1st, 2022. Naturally, this will produce a massive growth in data management needs. In fact, the LIBOR transition program marks one of the largest data transformation obstacles ever seen in financial services.

article thumbnail

Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer.