Jennifer Ortiz

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In this demonstration, we will showcase Myria, our novel cloud service for big data management and analytics designed to improve productivity. Myria's goal is for users to simply upload their data and for the system to help them be self-sufficient data science experts on their data -- self-serve analytics. Using a web browser, Myria users can upload data,(More)
Public Clouds today provide a variety of services for data analysis such as Amazon Elastic MapReduce and Google BigQuery. Each service comes with a pricing model and service level agreement (SLA). Today's pricing models and SLAs are described at the level of compute resources (instance-hours or gigabytes processed). They are also different from one service(More)
In this paper, we present an overview of the Myria stack for big data management and analytics that we developed in the database group at the University of Washington and that we have been operating as a cloud service aimed at domain scientists around the UW campus. We highlight Myria’s key design choices and innovations and report on our experience with(More)
This paper presents the design and performance analysis of a scheduling technique for the provision of QoS over Broadband Wireless Access Networks (BWA). The proposed scheduling algorithm is based on the MAC protocol of the IEEE 802.16 standard and focuses on the uplink channel, which is the limiting factor of BWA networks and is critical in the delivery of(More)
We develop and evaluate an approach for generating Personalized Service Level Agreements (PSLAs) that separate cloud users from the details of compute resources behind a cloud database management service. PSLAs retain the possibility to trade-off performance for cost and do so in a manner specific to the user’s database.
We demonstrate PerfEnforce, a dynamic scaling engine for analytics services. PerfEnforce automatically scales a cluster of virtual machines in order to minimize costs while probabilistically meeting the query runtime guarantees offered by a performance-oriented service level agreement (SLA). The demonstration will show three families of dynamic scaling(More)
We present the motivation, design, implementation, and preliminary evaluation for a service that enables astronomers to study the growth history of galaxies by following their `merger trees' in large-scale astrophysical simulations. The service uses the Myria parallel data management system as back-end and the D3 data visualization library within its(More)
In this paper, we present PerfEnforce, a scaling engine designed to enable cloud providers to sell performance levels for data analytics cloud services. PerfEnforce scales a cluster of virtual machines (VMs) allocated to a user in a way that minimizes cost while probabilistically meeting the query runtime guarantees offered by a service level agreement(More)
1. PROBLEM AND MOTIVATION A variety of systems for data analytics are available as cloud services today, including Amazon Elastic MapReduce (EMR), Amazon Redshift, Azure’s HDInsight, and several others. While these services greatly facilitate access to compute resources and data analytics software, they remain hard for users to tune in terms of cost and(More)