Presto at Adobe: How Adobe Advertising uses Presto for Adhoc Query, Custom Reporting, and Internal Pipelines

Presto at Adobe: How Adobe Advertising uses Presto for Adhoc Query, Custom Reporting, and Internal Pipelines

Rajmani Arya, Varun Senthilnathan & Manoj Kumar Dhakad, Adobe Advertising: We are from the Product Engineering team in Adobe Advertising (https://business.adobe.com/in/product…. Adobe Advertising is a digital advertisement platform. We take care of accumulating all data, providing platform intelligence, building and maintaining machine leaning capabilities, building and maintaining internal pipelines that form derived data to be used by other teams. The volume of total incoming raw data ranges between 8 to 10 tb/ day spread across 7 regions. The total data in the system currently is about 7pb. This data is largely stored in Hive tables with a central metastore. We use Presto in three ways: 1. Data studio – an internal tool to enable data analysts, sales, marketing and other teams to do adhoc querying. This is also used by data engineers to do adhoc querying for engineering tasks. 2. Custom Reports – We create reports for customers to get performance insights on their campaigns. We have 100s of reports that are run on a daily basis. 3. Internal Pipelines – Presto is used to retrieve data to power 100s of pipelines run daily to generate derived data.

Ending DAG Distress: Building Self-Orchestrating Pipelines for Presto – Roy Hasson, Upsolver

Ending DAG Distress: Building Self-Orchestrating Pipelines for Presto – Roy Hasson, Upsolver

Ending DAG Distress: Building Self-Orchestrating Pipelines for Presto – Roy Hasson, Upsolver dbt and Airflow is a popular combination for creating and scheduling batch data modeling and transformation jobs that execute in a data warehouse like Snowflake. Presto users querying the data lake need a similar solution that is simple to use and makes it easy to ingest, model, transform and maintain datasets, without having to write or manage complex DAGs. In this session you will learn how Upsolver built a tool that allows engineers, developers and analysts to write data pipelines using SQL. Pipelines are automatically orchestrated, are data-aware and maintain a consistent data contract between each stage of the pipeline. You will also learn how to introduce the idea of data products into your company to enable more self-service for your Presto users.

Build & Query Secure S3 Data Lakes with Ahana Cloud and AWS Lake Formation

Build & Query Secure S3 Data Lakes with Ahana Cloud and AWS Lake Formation

AWS Lake Formation is a service that allows data platform users to set up a secure data lake in days. Creating a data lake with Presto and AWS Lake Formation is as simple as defining data sources and what data access and security policies you want to apply. In this talk, Wen will walk through the recently announced AWS Lake Formation and Ahana integration.

Authorizing Presto with AWS Lake Formation – Jalpreet Singh Nanda, Ahana & Roy Hasson, Amazon

Authorizing Presto with AWS Lake Formation – Jalpreet Singh Nanda, Ahana & Roy Hasson, Amazon

AWS Lake Formation is a service that allows data platform users to set up a secure data lake in days. Creating a data lake with Presto and Lake Formation is as simple as defining data sources and what data access and security policies you want to apply. At Ahana and Amazon, engineers are working on Presto and Lake Formation integration to support Authorization on Presto. This means that Presto clusters will be enforce data permissions on user queries against Lake Formation backed data lakes, which is a tightly integrated Lake Formation, AWS Glue, and Amazon S3 data lake stack. In this session we will present high level design, our leanings, future plans and demo how data platform users can use Lake Formation integration to support fine-grained data access controls on Presto.