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Experiences with approximating queries in Microsoft’s production big-data clusters

The Morning Paper

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. VLDB’19. For the larger more production-like query analysed in §4.2.1,

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Expanding the Cloud: Introducing the AWS Asia Pacific (Mumbai) Region

All Things Distributed

AdiMap uses Amazon Kinesis to process real-time streaming online ad data and job feeds, and processes them for storage in petabyte-scale Amazon Redshift. Advanced problem solving that connects big data with machine learning. For more details, see the case studies at All AWS Customer Stories.

AWS 90
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Probabilistic Data Structures for Web Analytics and Data Mining

Highly Scalable

Let us start with a simple example that illustrates capabilities of probabilistic data structures: Let us have a data set that is simply a heap of ten million random integer values and we know that it contains not more than one million distinct values (there are many duplicates). what is the cardinality of the data set)?

Analytics 191
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Spot Instances - Increased Control - All Things Distributed

All Things Distributed

We have already seen customers successfully run HPC workloads, Hadoop-based jobs (as shown in the BackType case study), and testing simulations (as shown in the BrowserMob case study) on Spot. Driving down the cost of Big-Data analytics. Introducing the AWS South America (Sao Paulo) Region.

AWS 87
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Expanding the AWS Cloud: Introducing the AWS Canada (Central) Region

All Things Distributed

It adopted Amazon Redshift, Amazon EMR and AWS Lambda to power its data warehouse, big data, and data science applications, supporting the development of product features at a fraction of the cost of competing solutions. For more customer case studies, see All AWS Customer Stories. Rapid time to market.

AWS 155
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MapReduce Patterns, Algorithms, and Use Cases

Highly Scalable

Several practical case studies are also provided. Solution: Problem description is split in a set of specifications and specifications are stored as input data for Mappers. Case Study: Simulation of a Digital Communication System. Case Study: Breadth-First Search.

C++ 144
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Microsoft Engineering loves SQLBits

SQL Server According to Bob

Best practices on Building a Big Data Analytics Solution – Michael Rys. If you want to learn about Azure Data Lake, there is no one better. Maximise compute performance with Azure SQL Data Warehouse – More JRJ on Azure DW. Azure Cosmos DB: design patterns and case studies – Andrew Liu.