Amazon Web Services776 тыс
Опубликовано 24 апреля 2017, 17:29
Learn more about AWS at - amzn.to/2pt5V5R
Amazon Redshift Spectrum is a new feature that extends Amazon Redshift’s analytics capabilities beyond the data stored in your data warehouse to also query your data in Amazon S3. You can use Amazon Redshift and your existing business intelligence tools to run SQL queries against exabytes of data, and Redshift Spectrum applies sophisticated query optimization, scaling processing across thousands of nodes so results are fast – even with large data sets and complex queries.
In this session, we will show you how you can easily start querying your data stored in Amazon S3 with Redshift Spectrum. You can run Amazon Redshift queries on Amazon S3 data on its own, or you can run queries that join together data in S3 with data already in your Redshift data warehouse. We will highlight technical details of query execution and implementation of Redshift Spectrum. We will show a live demonstration, running a query over 1 exabyte of data. We will talk about supported queries, data formats, and strategies to save cost by compressing or transforming your data into a columnar format.
Amazon Redshift Spectrum is a new feature that extends Amazon Redshift’s analytics capabilities beyond the data stored in your data warehouse to also query your data in Amazon S3. You can use Amazon Redshift and your existing business intelligence tools to run SQL queries against exabytes of data, and Redshift Spectrum applies sophisticated query optimization, scaling processing across thousands of nodes so results are fast – even with large data sets and complex queries.
In this session, we will show you how you can easily start querying your data stored in Amazon S3 with Redshift Spectrum. You can run Amazon Redshift queries on Amazon S3 data on its own, or you can run queries that join together data in S3 with data already in your Redshift data warehouse. We will highlight technical details of query execution and implementation of Redshift Spectrum. We will show a live demonstration, running a query over 1 exabyte of data. We will talk about supported queries, data formats, and strategies to save cost by compressing or transforming your data into a columnar format.
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