Remove 2012 Remove Data Lake Remove Interactive Remove Testing
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Accelerate HiveQL with Oozie to Spark SQL migration on Amazon EMR

AWS Big Data

To configure AWS CLI interaction with AWS, refer to Quick setup. json ) to DynamoDB (for more information, refer to Write data to a table using the console or AWS CLI ): { "name": "step1.q", sample_data/us_current.csv s3://$s3_bucket_name/covid-19-testing-data/base/source_us_current/; Copy states_current.csv : aws s3 cp./sample_data/states_current.csv

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Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

AWS Big Data

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). enableHiveSupport().getOrCreate()

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

That resulted in server farms, collecting volumes of log data from customer interactions, data which was then aggregated and fed into machine learning algorithms which created data products as pre-computed results, which in turn made web apps smarter and enhanced e-commerce revenue. We keep feeding the monster data.

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Federate Amazon QuickSight access with open-source identity provider Keycloak

AWS Big Data

Test the application Let’s invoke the application you have created to seamlessly sign in to QuickSight using the following URL. Vamsi Bhadriraju is a Data Architect at AWS. He works closely with enterprise customers to build data lakes and analytical applications on the AWS Cloud.

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Run Spark SQL on Amazon Athena Spark

AWS Big Data

For interactive applications, Athena Spark allows you to spend less time waiting and be more productive, with application startup time in under a second. Running SQL on data lakes is fast, and Athena provides an optimized, Trino- and Presto-compatible API that includes a powerful optimizer.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Once upon a time, circa 2012-ish, data science conferences were replete with talks about an industry hellbent on loading amazing enormous Big Data into some kind of data lake, and applying all kinds of odd astrophysics-ish approaches…for eventual PROFIT! Or something. Nothing Spreads Like Fear”. No big deal.”.

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Q&A with Greg Rahn – The changing Data Warehouse market

Cloudera

And so I actually transitioned out of that group and into the Big Data Appliance group at Oracle, but soon realized that if that was what I wanted to keep doing, this up and coming company called Cloudera might be a better place to do it since these new technologies weren’t just a hobby at Cloudera. As you mentioned, Qlik is in there.