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Big cdata News

I have some big news about our R package cdata. We have greatly improved the calling interface and Nina Zumel has just written the definitive introduction to cdata.

cdata is our general coordinatized data tool. It is what powers the deep learning performance graph (here demonstrated with R and Keras) that I announced a while ago.

KerasPlot

However, cdata is much more than that.

Continue reading Big cdata News

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Announcing rquery

We are excited to announce the rquery R package.

rquery is Win-Vector LLC‘s currently in development big data query tool for R.

rquery supplies set of operators inspired by Edgar F. Codd‘s relational algebra (updated to reflect lessons learned from working with R, SQL, and dplyr at big data scale in production).

Continue reading Announcing rquery

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Plotting Deep Learning Model Performance Trajectories

I am excited to share a new deep learning model performance trajectory graph.

Here is an example produced based on Keras in R using ggplot2:

Unknown Continue reading Plotting Deep Learning Model Performance Trajectories

Posted on Categories data science, Exciting Techniques, Pragmatic Data Science, Pragmatic Machine Learning, Programming, Statistics, TutorialsTags , , , ,

How to Greatly Speed Up Your Spark Queries

For some time we have been teaching R users "when working with wide tables on Spark or on databases: narrow to the columns you really want to work with early in your analysis."

The idea behind the advice is: working with fewer columns makes for quicker queries.


speed

photo: Jacques Henri Lartigue 1912

The issue arises because wide tables (200 to 1000 columns) are quite common in big-data analytics projects. Often these are "denormalized marts" that are used to drive many different projects. For any one project only a small subset of the columns may be relevant in a calculation.

Continue reading How to Greatly Speed Up Your Spark Queries

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Getting started with seplyr

A big “thank you!!!” to Microsoft for hosting our new introduction to seplyr. If you are working R and big data I think the seplyr package can be a valuable tool.


Safety
Continue reading Getting started with seplyr

Posted on Categories Coding, data science, Exciting Techniques, Pragmatic Data Science, Pragmatic Machine Learning, Statistics, TutorialsTags , , , , , , , , 1 Comment on Win-Vector LLC announces new “big data in R” tools

Win-Vector LLC announces new “big data in R” tools

Win-Vector LLC is proud to introduce two important new tool families (with documentation) in the 0.5.0 version of seplyr (also now available on CRAN):

  • partition_mutate_se() / partition_mutate_qt(): these are query planners/optimizers that work over dplyr::mutate() assignments. When using big-data systems through R (such as PostgreSQL or Apache Spark) these planners can make your code faster and sequence steps to avoid critical issues (the complementary problems of too long in-mutate dependence chains, of too many mutate steps, and incidental bugs; all explained in the linked tutorials).
  • if_else_device(): provides a dplyr::mutate() based simulation of per-row conditional blocks (including conditional assignment). This allows powerful imperative code (such as often seen in porting from SAS) to be directly and legibly translated into performant dplyr::mutate() data flow code that works on Spark (via Sparklyr) and databases.


Blacksmith working

Image by Jeff Kubina from Columbia, Maryland – [1], CC BY-SA 2.0, Link

Continue reading Win-Vector LLC announces new “big data in R” tools

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Vectorized Block ifelse in R

Win-Vector LLC has been working on porting some significant large scale production systems from SAS to R.

From this experience we want to share how to simulate, in R with Apache Spark (via Sparklyr), a nifty SAS feature: the vectorized “block if(){}else{}” structure. Continue reading Vectorized Block ifelse in R

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Arbitrary Data Transforms Using cdata

We have been writing a lot on higher-order data transforms lately:

Cdata

What I want to do now is "write a bit more, so I finally feel I have been concise."

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Posted on Categories Pragmatic Data Science, Pragmatic Machine Learning, Programming, Statistics, TutorialsTags , , , , , , ,

Data Wrangling at Scale

Just wrote a new R article: “Data Wrangling at Scale” (using Dirk Eddelbuettel’s tint template).

Fd

Please check it out.

Posted on Categories Coding, data science, Pragmatic Data Science, Programming, Statistics, TutorialsTags , , 1 Comment on Big Data Transforms

Big Data Transforms

As part of our consulting practice Win-Vector LLC has been helping a few clients stand-up advanced analytics and machine learning stacks using R and substantial data stores (such as relational database variants such as PostgreSQL or big data systems such as Spark).


IMG 6061 3

Often we come to a point where we or a partner realize: "the design would be a whole lot easier if we could phrase it in terms of higher order data operators."

Continue reading Big Data Transforms