HotCDP '12Pub Date : 2012-04-10DOI: 10.1145/2169090.2169093
Malte Schwarzkopf, S. Hand
{"title":"A down-to-earth look at the cloud host OS","authors":"Malte Schwarzkopf, S. Hand","doi":"10.1145/2169090.2169093","DOIUrl":"https://doi.org/10.1145/2169090.2169093","url":null,"abstract":"Current cloud programming models have opened up new opportunities, but the platforms they run on are still rooted in the legacy of single machine-centric computing. This leads to inefficiency that both costs money and offends scientific sensibilities. In this position paper, we make a passionate and necessarily opinionated argument for a research agenda that challenges fundamental assumptions about operating systems and \"cloud\" application software. We present a set of ideas for possible directions, and hope to elicit fruitful discussion within the community.","PeriodicalId":183902,"journal":{"name":"HotCDP '12","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115650841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HotCDP '12Pub Date : 2012-04-10DOI: 10.1145/2169090.2169092
A. Rowstron, D. Narayanan, Austin Donnelly, G. O'Shea, Andrew Douglas
{"title":"Nobody ever got fired for using Hadoop on a cluster","authors":"A. Rowstron, D. Narayanan, Austin Donnelly, G. O'Shea, Andrew Douglas","doi":"10.1145/2169090.2169092","DOIUrl":"https://doi.org/10.1145/2169090.2169092","url":null,"abstract":"The norm for data analytics is now to run them on commodity clusters with MapReduce-like abstractions. One only needs to read the popular blogs to see the evidence of this. We believe that we could now say that \"nobody ever got fired for using Hadoop on a cluster\"!\u0000 We completely agree that Hadoop on a cluster is the right solution for jobs where the input data is multi-terabyte or larger. However, in this position paper we ask if this is the right path for general purpose data analytics? Evidence suggests that many MapReduce-like jobs process relatively small input data sets (less than 14 GB). Memory has reached a GB/$ ratio such that it is now technically and financially feasible to have servers with 100s GB of DRAM. We therefore ask, should we be scaling by using single machines with very large memories rather than clusters? We conjecture that, in terms of hardware and programmer time, this may be a better option for the majority of data processing jobs.","PeriodicalId":183902,"journal":{"name":"HotCDP '12","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131202124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HotCDP '12Pub Date : 2012-04-10DOI: 10.1145/2169090.2169094
Masoud Saeida Ardekani, M. Zawirski, P. Sutra, M. Shapiro
{"title":"The space complexity of transactional interactive reads","authors":"Masoud Saeida Ardekani, M. Zawirski, P. Sutra, M. Shapiro","doi":"10.1145/2169090.2169094","DOIUrl":"https://doi.org/10.1145/2169090.2169094","url":null,"abstract":"Transactional Web Applications need to perform fast interactive reads while ensuring reasonable isolation guarantees. This paper studies the problem of taking consistent snapshots for transactions with interactive reads. We introduce four levels of freshness, and solutions to guarantee them. We also explore trade-offs between the space complexity and the freshness levels.","PeriodicalId":183902,"journal":{"name":"HotCDP '12","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114289974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HotCDP '12Pub Date : 2012-04-10DOI: 10.1145/2169090.2169091
Nathan Backman, Rodrigo Fonseca, U. Çetintemel
{"title":"Managing parallelism for stream processing in the cloud","authors":"Nathan Backman, Rodrigo Fonseca, U. Çetintemel","doi":"10.1145/2169090.2169091","DOIUrl":"https://doi.org/10.1145/2169090.2169091","url":null,"abstract":"Stream processing applications run continuously and have varying load. Cloud infrastructures present an attractive option to meet these fluctuating computational demands. Coordinating such resources to meet end-to-end latency objectives efficiently is important in preventing the frivolous use of cloud resources. We present a framework that parallelizes and schedules workflows of stream operators, in real-time, to meet latency objectives. It supports data- and task-parallel processing of all workflow operators, by all computing nodes, while maintaining the ordering properties of sorted data streams. We show that a latency-oriented operator scheduling policy coupled with the diversification of computing node responsibilities encourages parallelism models that achieve end-to-end latency-minimization goals. We demonstrate the effectiveness of our framework with preliminary experimental results using a variety of real-world applications on heterogeneous clusters.","PeriodicalId":183902,"journal":{"name":"HotCDP '12","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115221352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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