Matches in SemOpenAlex for { <https://semopenalex.org/work/W2286562392> ?p ?o ?g. }
Showing items 1 to 60 of
60
with 100 items per page.
- W2286562392 abstract "Summary form only given. Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation. Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the MapReduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which MapReduce is widely recognized to be a poor fit. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack." @default.
- W2286562392 created "2016-06-24" @default.
- W2286562392 creator A5051301731 @default.
- W2286562392 date "2015-12-01" @default.
- W2286562392 modified "2023-09-27" @default.
- W2286562392 title "Scale-out Beyond Map-Reduce" @default.
- W2286562392 doi "https://doi.org/10.1109/hipc.2015.59" @default.
- W2286562392 hasPublicationYear "2015" @default.
- W2286562392 type Work @default.
- W2286562392 sameAs 2286562392 @default.
- W2286562392 citedByCount "0" @default.
- W2286562392 crossrefType "proceedings-article" @default.
- W2286562392 hasAuthorship W2286562392A5051301731 @default.
- W2286562392 hasConcept C119857082 @default.
- W2286562392 hasConcept C124101348 @default.
- W2286562392 hasConcept C153083717 @default.
- W2286562392 hasConcept C165696696 @default.
- W2286562392 hasConcept C1668388 @default.
- W2286562392 hasConcept C199360897 @default.
- W2286562392 hasConcept C2522767166 @default.
- W2286562392 hasConcept C2781215313 @default.
- W2286562392 hasConcept C2781252014 @default.
- W2286562392 hasConcept C38652104 @default.
- W2286562392 hasConcept C41008148 @default.
- W2286562392 hasConcept C48044578 @default.
- W2286562392 hasConcept C75684735 @default.
- W2286562392 hasConcept C77088390 @default.
- W2286562392 hasConcept C79158427 @default.
- W2286562392 hasConceptScore W2286562392C119857082 @default.
- W2286562392 hasConceptScore W2286562392C124101348 @default.
- W2286562392 hasConceptScore W2286562392C153083717 @default.
- W2286562392 hasConceptScore W2286562392C165696696 @default.
- W2286562392 hasConceptScore W2286562392C1668388 @default.
- W2286562392 hasConceptScore W2286562392C199360897 @default.
- W2286562392 hasConceptScore W2286562392C2522767166 @default.
- W2286562392 hasConceptScore W2286562392C2781215313 @default.
- W2286562392 hasConceptScore W2286562392C2781252014 @default.
- W2286562392 hasConceptScore W2286562392C38652104 @default.
- W2286562392 hasConceptScore W2286562392C41008148 @default.
- W2286562392 hasConceptScore W2286562392C48044578 @default.
- W2286562392 hasConceptScore W2286562392C75684735 @default.
- W2286562392 hasConceptScore W2286562392C77088390 @default.
- W2286562392 hasConceptScore W2286562392C79158427 @default.
- W2286562392 hasLocation W22865623921 @default.
- W2286562392 hasOpenAccess W2286562392 @default.
- W2286562392 hasPrimaryLocation W22865623921 @default.
- W2286562392 hasRelatedWork W1863628336 @default.
- W2286562392 hasRelatedWork W2058081643 @default.
- W2286562392 hasRelatedWork W2281622660 @default.
- W2286562392 hasRelatedWork W2798903611 @default.
- W2286562392 hasRelatedWork W2808435801 @default.
- W2286562392 hasRelatedWork W2895312194 @default.
- W2286562392 hasRelatedWork W3007959775 @default.
- W2286562392 hasRelatedWork W3177887783 @default.
- W2286562392 hasRelatedWork W3185293612 @default.
- W2286562392 hasRelatedWork W3189969039 @default.
- W2286562392 isParatext "false" @default.
- W2286562392 isRetracted "false" @default.
- W2286562392 magId "2286562392" @default.
- W2286562392 workType "article" @default.