The Experts below are selected from a list of 471 Experts worldwide ranked by ideXlab platform

Sandeep Tata - One of the best experts on this subject based on the ideXlab platform.

  • Clydesdale structured data processing on hadoop
    International Conference on Management of Data, 2012
    Co-Authors: Andrey Balmin, Tim Kaldewey, Sandeep Tata
    Abstract:

    There have been several recent proposals modifying Hadoop, radically changing the storage organization or query processing techniques to obtain good performance for structured data processing. We will showcase Clydesdale, a research prototype for structured data processing on Hadoop that can achieve dramatic performance improvements over existing solutions, without any changes to the underlying MapReduce implementation. Clydesdale achieves this through a novel synthesis of several techniques from the database literature and carefully adapting them to the Hadoop environment. On the star schema benchmark, we show that Clydesdale is on average 38x faster than Hive, the dominant approach for structured data processing on Hadoop today. To the best of our knowledge, Clydesdale is the fastest solution for processing workloads on structured data sets that fit a star schema on Hadoop. Attendees will be able to run queries on the data from the star schema benchmark on a remote Hadoop cluster with Clydesdale and Hive installed, and get a breakdown of the time taken to execute the query. Attendees will also be able to pose their own queries using ClyQL -- a novel embedded DSL in Scala that can be used to rapidly prototype star join queries. With this demonstration, we hope to convince the attendees that unlike previously thought, Hadoop can indeed efficiently support structured data processing.

  • Clydesdale structured data processing on mapreduce
    Extending Database Technology, 2012
    Co-Authors: Tim Kaldewey, Eugene J Shekita, Sandeep Tata
    Abstract:

    MapReduce has emerged as a promising architecture for large scale data analytics on commodity clusters. The rapid adoption of Hive, a SQL-like data processing language on Hadoop (an open source implementation of MapReduce), shows the increasing importance of processing structured data on MapReduce platforms. MapReduce offers several attractive properties such as the use of low-cost hardware, fault-tolerance, scalability, and elasticity. However, these advantages have required a substantial performance sacrifice.In this paper we introduce Clydesdale, a novel system for structured data processing on Hadoop -- a popular implementation of MapReduce. We show that Clydesdale provides more than an order of magnitude in performance improvements compared to existing approaches without requiring any changes to the underlying platform. Clydesdale is aimed at workloads where the data fits a star schema. It draws on column oriented storage, tailored join-plans, and multi-core execution strategies and carefully fits them into the constraints of a typical MapReduce platform. Using the star schema benchmark, we show that Clydesdale is on average 38x faster than Hive. This demonstrates that MapReduce in general, and Hadoop in particular, is a far more compelling platform for structured data processing than previous results suggest.

Goss, Peter L. - One of the best experts on this subject based on the ideXlab platform.

Tim Kaldewey - One of the best experts on this subject based on the ideXlab platform.

  • Clydesdale structured data processing on hadoop
    International Conference on Management of Data, 2012
    Co-Authors: Andrey Balmin, Tim Kaldewey, Sandeep Tata
    Abstract:

    There have been several recent proposals modifying Hadoop, radically changing the storage organization or query processing techniques to obtain good performance for structured data processing. We will showcase Clydesdale, a research prototype for structured data processing on Hadoop that can achieve dramatic performance improvements over existing solutions, without any changes to the underlying MapReduce implementation. Clydesdale achieves this through a novel synthesis of several techniques from the database literature and carefully adapting them to the Hadoop environment. On the star schema benchmark, we show that Clydesdale is on average 38x faster than Hive, the dominant approach for structured data processing on Hadoop today. To the best of our knowledge, Clydesdale is the fastest solution for processing workloads on structured data sets that fit a star schema on Hadoop. Attendees will be able to run queries on the data from the star schema benchmark on a remote Hadoop cluster with Clydesdale and Hive installed, and get a breakdown of the time taken to execute the query. Attendees will also be able to pose their own queries using ClyQL -- a novel embedded DSL in Scala that can be used to rapidly prototype star join queries. With this demonstration, we hope to convince the attendees that unlike previously thought, Hadoop can indeed efficiently support structured data processing.

  • Clydesdale structured data processing on mapreduce
    Extending Database Technology, 2012
    Co-Authors: Tim Kaldewey, Eugene J Shekita, Sandeep Tata
    Abstract:

    MapReduce has emerged as a promising architecture for large scale data analytics on commodity clusters. The rapid adoption of Hive, a SQL-like data processing language on Hadoop (an open source implementation of MapReduce), shows the increasing importance of processing structured data on MapReduce platforms. MapReduce offers several attractive properties such as the use of low-cost hardware, fault-tolerance, scalability, and elasticity. However, these advantages have required a substantial performance sacrifice.In this paper we introduce Clydesdale, a novel system for structured data processing on Hadoop -- a popular implementation of MapReduce. We show that Clydesdale provides more than an order of magnitude in performance improvements compared to existing approaches without requiring any changes to the underlying platform. Clydesdale is aimed at workloads where the data fits a star schema. It draws on column oriented storage, tailored join-plans, and multi-core execution strategies and carefully fits them into the constraints of a typical MapReduce platform. Using the star schema benchmark, we show that Clydesdale is on average 38x faster than Hive. This demonstrates that MapReduce in general, and Hadoop in particular, is a far more compelling platform for structured data processing than previous results suggest.

Fort Hays State University - One of the best experts on this subject based on the ideXlab platform.

  • Tiger Daily: December 1, 2016
    FHSU Scholars Repository, 2016
    Co-Authors: Fort Hays State University
    Abstract:

    ANNOUNCEMENTS · Reminder 2016 FHSU Student Academic Advising Evaluation · NEW - Faculty Scholarship Funding Bank Roll Over Option · 2016 Makerspace Holiday Ornament Competition EVENTS THIS WEEK/WEEKEND · Alumni Association Holiday Open House – TODAY, 10:00am to 5:00pm · Plymouth Schoolhouse Christmas Open House – TODAY, 2:30pm to 4:30pm · Honors Pedagogical Round Tables – TODAY, 3:00pm to 4:00pm · Clydesdale-Drawn Sleigh Ride with Santa – TODAY, 5:30pm to 9:30pm FUTURE EVENTS · FHSU vs. University of Colorado-Boulder Pregame Party & Discounted Game Tickets – Deadline TODAY SHARE WITH STUDENTS · Writing Center · The Library and U · Writing Circle – December 2, 4:00pm to 5:00pm · An Evening of Unity for FHSU Students – December 6, 6:00pm to 8:00p

  • Tiger Daily: November 29, 2016
    FHSU Scholars Repository, 2016
    Co-Authors: Fort Hays State University
    Abstract:

    ANNOUNCEMENTS · New Faculty Scholarship Funding Bank Roll Over Option · 2017–2018 Sabbatical Applications · New Employee Benefit Available – Colonial Life & Accident · Looking for the Perfect Tiger Gift EVENTS THIS WEEK/WEEKEND · Lunch and Learn @The Library – TODAY, 12:30pm to 1:00pm · University Holiday Party and Awards Ceremony – TODAY, 3:30pm · Annual Tree Lighting Ceremony – TODAY, 6:00pm · Voice Thread Mobile Workshop – TODAY, 6:00pm to 7:00pm · Retirement Reception for Larry Getty – TOMORROW, 2:30pm to 4:00pm · Retirement Reception for Collen Taylor – TOMORROW, 3:00pm to 4:00pm FUTURE EVENTS · Alumni Association Holiday Open House – December 1, 10:00am to 5:00pm · Plymouth Schoolhouse Christmas Open House – December 1, 2:30pm to 4:30pm · Clydesdale-Drawn Sleigh Ride with Santa – December 1, 5:30pm to 9:30pm SHARE WITH STUDENTS · Writing Cente

  • Tiger Daily: November 30, 2016
    FHSU Scholars Repository, 2016
    Co-Authors: Fort Hays State University
    Abstract:

    ANNOUNCEMENTS · Reminder 2016 FHSU Student Academic Advising Evaluation · NEW - Faculty Scholarship Funding Bank Roll Over Option · Calling for 2017 Alumni Awards Nominations · Spring Tuition Assistance · Last Day to Order Your Finals Care Packages · University Farm Fresh Pork EVENTS THIS WEEK/WEEKEND · Retirement Reception for Larry Getty – TODAY, 2:30pm to 4:00pm · Retirement Reception for Colleen Taylor – TODAY, 3:00pm to 4:00pm · Alumni Association Holiday Open House – TOMORROW, 10:00am to 5:00pm · Plymouth Schoolhouse Christmas Open House – TOMORROW, 2:30pm to 4:30pm · Honors Pedagogical Round Tables – TOMORROW, 3:00pm to 4:00pm · Clydesdale-Drawn Sleigh Ride with Santa – TOMORROW, 5:30pm to 9:30pm FUTURE EVENTS · FHSU vs. University of Colorado-Boulder Pregame Party & Discounted Game Tickets – Deadline December 1 SHARE WITH STUDENTS · Writing Circle – December 2, 4:00pm to 5:00p

Webb Robert - One of the best experts on this subject based on the ideXlab platform.