AWS Big Data Blog

Amazon Redshift Engineering’s Advanced Table Design Playbook: Table Data Durability

Part 1: Preamble, Prerequisites, and Prioritization Part 2: Distribution Styles and Distribution Keys Part 3: Compound and Interleaved Sort Keys Part 4: Compression Encodings Part 5: Table Data Durability (Translated into Japanese) In the fifth and final installment of the Advanced Table Design Playbook, I’ll discuss how to use two simple table durability properties to […]

Amazon Redshift Engineering’s Advanced Table Design Playbook: Compression Encodings

Part 1: Preamble, Prerequisites, and Prioritization Part 2: Distribution Styles and Distribution Keys Part 3: Compound and Interleaved Sort Keys Part 4: Compression Encodings (Translated into Japanese) Part 5: Table Data Durability In part 4 of this blog series, I’ll be discussing when and when not to apply column encoding for compression, methods for determining ideal […]

Month in Review: November 2016

Another month of big data solutions on the Big Data Blog. Take a look at our summaries below and learn, comment, and share. Thank you for reading! Use Apache Flink on Amazon EMR It is even easier to run Flink on AWS as it is now natively supported in Amazon EMR 5.1.0. EMR supports running Flink-on-YARN so […]

Amazon Redshift Engineering’s Advanced Table Design Playbook: Compound and Interleaved Sort Keys

  Part 1: Preamble, Prerequisites, and Prioritization Part 2: Distribution Styles and Distribution Keys Part 3: Compound and Interleaved Sort Keys (Translated into Japanese) Part 4: Compression Encodings Part 5: Table Data Durability In this installment, I’ll cover different sort key options, when to use sort keys, and how to identify the most optimal sort key […]

Amazon Redshift Engineering’s Advanced Table Design Playbook: Distribution Styles and Distribution Keys

  Part 1: Preamble, Prerequisites, and Prioritization Part 2: Distribution Styles and Distribution Keys (Translated into Japanese) Part 3: Compound and Interleaved Sort Keys Part 4: Compression Encodings Part 5: Table Data Durability The first table and column properties we discuss in this blog series are table distribution styles (DISTSTYLE) and distribution keys (DISTKEY). This blog […]

Amazon Redshift Engineering’s Advanced Table Design Playbook: Preamble, Prerequisites, and Prioritization

  Part 1: Preamble, Prerequisites, and Prioritization (Translated into Japanese) Part 2: Distribution Styles and Distribution Keys Part 3: Compound and Interleaved Sort Keys Part 4: Compression Encodings Part 5: Table Data Durability Amazon Redshift is a fully managed, petabyte scale, massively parallel data warehouse that offers simple operations and high performance. AWS customers use Amazon […]

Implementing Authorization and Auditing using Apache Ranger on Amazon EMR

Updated 3/30/2022: Amazon EMR has announced official support of Apache Ranger (link). Open-source plugin support will not be maintained moving forward and compatibility with latest versions will not be tested. We recommend customers to move to the Amazon EMR support for Apache Ranger. Ranger Presto plugin support on EMR has been deprecated. Updated 12/03/2020: Support for […]

Analyzing Data in S3 using Amazon Athena

April 2024: This post was reviewed for accuracy. Amazon Athena is an interactive query service that makes it easy to analyze data directly from Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to set up or manage and you can start analyzing your data immediately. You don’t even need to […]

Introducing the Data Lake Solution on AWS

NOTE: The solution in this post is in the process of being updated. For the most current information, please visit the What is a data lake? page. This blog post has been translated into Japanese. Many of our customers choose to build their data lake on AWS. They find the flexible, pay-as-you-go, cloud model is […]