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GREENWOOD / BLACK WALL STREET WILMINGTON 1898 LITTLE ROCK NINE TUSKEGEE STUDY ROSEWOOD 1923 THE TUSKEGEE AIRMEN SENECA VILLAGE BLACK TOWNS GREENWOOD / BLACK WALL STREET WILMINGTON 1898 LITTLE ROCK NINE TUSKEGEE STUDY ROSEWOOD 1923 THE TUSKEGEE AIRMEN SENECA VILLAGE BLACK TOWNS
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MY'STORY

The MOVE Fire

This is a personal recollection on the Move fire on May 13, 1985 Philadelphia police fired thousands of rounds at the MOVE house, city officials approved dropping an explosive device on the roof, the resulting fire was allowed to burn, 11 people—including five children—died, and 61 homes were destroyed. Philadelphia City Council later called it a “brutal attack carried out by the City of Philadelphia on its own citizens” and acknowledged that no individual faced criminal consequences for the bombing. One timeline correction worth preserving for the BHP record: the major previous MOVE-police confrontation was August 8, 1978, about seven years before the bombing, not a year or two earlier. Officer James Ramp was killed, other police and firefighters were wounded, nine MOVE members were later convicted, and television cameras recorded police beating Delbert Africa during his arrest. The 1985 MOVE Commission later specifically criticized city planners for failing to adequately use lessons from that 1978 confrontation. And that actually strengthens the point you’re making: 1985 did not happen without precedent or institutional memory. There had already been a deadly confrontation with MOVE, years of conflict, negotiations and police involvement before Osage Avenue.

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BLACK FACTS
The Truths They Never Taught You...

The Violence That Helped Spark the NAACP

In August 1908, a white mob attacked Springfield, Illinois’s Black community, destroying homes and businesses and lynching two Black men. National outrage over the violence helped spur the movement that created the NAACP the following year.

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Wikipedia

Distributed R

Distributed R
DeveloperHP
Stable release
1.2.0[1] / 22 October 2015; 10 years ago (22 October 2015)
Written inC++, R
Operating systemLinux
Typemachine learning algorithms
LicenseGNU General Public License
Websitewww.distributedr.org
Repository

Distributed R is an open source, high-performance platform for the R language. It splits tasks between multiple processing nodes to reduce execution time and analyze large data sets. Distributed R enhances R by adding distributed data structures, parallelism primitives to run functions on distributed data, a task scheduler, and multiple data loaders.[2] It is mostly used to implement distributed versions of machine learning tasks. Distributed R is written in C++ and R, and retains the familiar look and feel of R. As of February 2015, Hewlett-Packard (HP) provides enterprise support for Distributed R with proprietary additions such as a fast data loader from the Vertica database.[3]

History

[edit]

Distributed R was begun in 2011 by Indrajit Roy, Shivaram Venkataraman, Alvin AuYoung, and Robert S. Schreiber as a research project at HP Labs.[4] It was open sourced in 2014 under the GPLv2 license and is available at GitHub.

In February 2015, Distributed R reached its first stable version 1.0, along with enterprise support from HP.[5]

Components

[edit]

Distributed R is a platform to implement and execute distributed applications in R. The goal is to extend R for distributed computing, while retaining the simplicity and look-and-feel of R. Distributed R consists of the following components:

  • Distributed data structures: Distributed R extends R's common data structures such as array, data.frame, and list to store data across multiple nodes. The corresponding Distributed R data structures are darray, dframe, and dlist. Many of the common data structure operations in R, such as colSums, rowSums, nrow and others, are also available on distributed data structures.
  • Parallel loop: Programmers can use the parallel loop, called foreach, to manipulate distributed data structures and execute tasks in parallel. Programmers only specify the data structure and function to express applications, while the runtime schedules tasks and, if required, moves around data.
  • Distributed algorithms: Distributed versions of common machine learning and graph algorithms, such as clustering, classification, and regression.
  • Data loaders: Users can leverage Distributed R constructs to implement parallel connectors that load data from different sources. Distributed R already provides implementations to load data from files and databases to distributed data structures.

Integration with databases

[edit]

HP Vertica provides tight integration with their database and the open source Distributed R platform. HP Vertica 7.1 includes features that enable fast, parallel loading from the Vertica database to Distribute R. This parallel Vertica loader can be more than five times (5x) faster than using traditional ODBC based connectors. The Vertica database also supports deployment of machine learning models in the database. Distributed R users can call the distributed algorithms to create machine learning models, deploy them in the Vertica database, and use the model for in-database scoring and predictions. Architectural details of the Vertica database and Distributed R integration are described in the Sigmod 2015 paper.[6]

References

[edit]
  1. ^ "Release 1.2.0". 22 October 2015. Retrieved 20 July 2018.
  2. ^ Venkataraman, Shivaram; Bodzsar, Erik; Roy, Indrajit; AuYoung, Alvin; Schreiber, Robert S. (2013). "Presto: Distributed Machine Learning and Graph Processing with Sparse Matrices" (PDF). European Conference on Computer Systems (EuroSys). Archived from the original (PDF) on 2015-03-01.
  3. ^ Gagliordi, Natalie. "HP adds scale to open-source R in latest big data platform". ZDNet. Retrieved 17 February 2015.
  4. ^ Venkataraman, Shivaram; Roy, Indrajit; AuYoung, Alvin; Schreiber, Robert S. (2012). "Using R for Iterative and Incremental Processing". Workshop on Hot Topics in Cloud Computing (HotCloud).
  5. ^ "HP Delivers Predictive Analytics at Big Data Scale". hp.com. 17 February 2015. Retrieved 17 February 2015.
  6. ^ Prasad, Shreya; Fard, Arash; Gupta, Vishrut; Martinez, Jorge; LeFevre, Jeff; Xu, Vincent; Hsu, Meichun; Roy, Indrajit (2015). "Enabling predictive analytics in Vertica: Fast data transfer, distributed model creation and in-database prediction". ACM SIGMOD International Conference on Management of Data.
[edit]

Source: Wikipedia. Article content is retrieved live through the MediaWiki API.

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Wikipedia

Distributed R

Distributed R is an open source, high-performance platform for the R language. It splits tasks between multiple processing nodes to reduce execution time and analyze large data sets. Distributed R enhances R by adding distributed data structures, parallelism primitives to run functions on distributed data, a task scheduler, and multiple data loaders. It is mostly used to implement distributed versions of machine learning tasks. Distributed R is written in C++ and R, and retains the familiar look and feel of R. As of February 2015, Hewlett-Packard (HP) provides enterprise support for Distributed R with proprietary additions such as a fast data loader from the Vertica database.

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Wikipedia

Roa (fish)

Roa is a genus of butterflyfishes native to the Indian and Pacific oceans. The six species are widely distributed: R. australis near Australia, R. excelsa near Hawaii and nearby islands, R. jayakari near India, R. modesta near Japan and China, R. rumsfeldi in the Philippines, and R. haraguchiae near Japan and the Philippines.

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Wikipedia

R (programming language)

R is a programming language for statistical computing and data visualization. It has been widely adopted in the fields of data mining, bioinformatics, data analysis, and data science. The core R language is extended by a large number of software packages, which contain reusable code, documentation, and sample data. Some of the most popular R packages are in the tidyverse collection, which enhances functionality for visualizing, transforming, and modelling data, as well as improves the ease of programming (according to the authors and users). R is free and open-source software distributed under the GNU General Public License. The language is implemented primarily in C, Fortran, and R itself. Precompiled executables are available for the major operating systems (including Linux, MacOS, and Microsoft Windows). Its core is an interpreted language with a native command line interface. In addition, multiple third-party applications are available as graphical user interfaces; such applications include RStudio (an integrated development environment), Jupyter (a notebook interface), as well as Termux and Google Colab for mobile devices.

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Wikipedia

Distributed development

A distributed development project is a research and development (R&D) project that is done across multiple business worksites or locations. It is a form of R&D where the project members may not see each other face to face, but they are all working collaboratively toward the outcome of the project. Often this is done through email, the Internet and other forms of quick long-distance communication. Distributed development was largely pioneered by the open-source software community. It is different from outsourcing because all of the organizations are working together on an equal level, instead of one organization subcontracting the work to another. It is similar to a virtual team but with a research element.

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TOPIC OF THE DAY

Greenwood / Black Wall Street

Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.

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TRIVIA QUESTION OF THE DAY

Which heavyweight champion was known as the “Brown Bomber”?

Joe Louis.