Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

Browse

Filters

2008 - 200912010 - 20151

Settings

Subject: search.filters.subject.batch

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Pig Squeal: Bridging Batch and Stream Processing Using Incremental Updates
    (2015) Lampton, James Holmes; Agrawala, Ashok; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    As developers shift from batch MapReduce to stream processing for better latency, they are faced with the dilemma of changing tools and maintaining multiple code bases. In this work we present a method for converting arbitrary chains of MapReduce jobs into pipelined, incremental processes to be executed in a stream processing framework. Pig Squeal is an enhancement of the Pig execution framework that runs lightly modified user scripts on Storm. The contributions of this work include: an analysis that tracks how information flows through MapReduce computations along with the influence of adding and deleting data from the input, a structure to generically handle these changes along with a description of the criteria to re-enable efficiencies using combiners, case studies for running word count and the more complex NationMind algorithms within Squeal, and a performance model which examines execution times of MapReduce algorithms after converted. A general solution to the conversion of analytics from batch to streaming impacts developers with expertise in batch systems by providing a means to use their expertise in a new environment. Imagine a medical researcher who develops a model for predicting emergency situations in a hospital on historical data (in a batch system). They could apply these techniques to quickly deploy these detectors on live patient feeds. It also significantly impacts organizations with large investments in batch codes by providing a tool for rapid prototyping and significantly lowering the costs of experimenting in these new environments.
  • Thumbnail Image
    Item
    SEQUENCE MODELING OF RAFT POLYMERIZATIONS WITH THE METHOD OF MOMENTS
    (2008-10-13) Zargar, Amin; Schork, Joseph; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Attempts to model the sequence structure of copolymers consisted of probabilistic functions that were incomplete and inaccurate. A novel technique to track sequence parameters is developed that determines not only copolymer composition, but sequence distribution as well. RAFT polymerizations are simulated with two independent and concurrent models to track MWD, conversion, copolymer composition, and sequence characteristics. Batch polymerizations are simulated with varying reactor conditions as a proof-of-concept to illustrate the power of the sequence model to track the composition of the polymer. Series of CSTR and PFR reactors with varying reactor conditions are then presented as applications to iteratively fine-tune copolymers with predetermined sequence and compositional structure.