![]() ![]() R-release (arm64): sparklyr_1.7.8.tgz, r-oldrel (arm64): sparklyr_1.7.8.tgz, r-release (x86_64): sparklyr_1.7.8.tgz, r-oldrel (x86_64): sparklyr_1.7.8.tgzĪdona, catalog, geospark, graphframes, rsparkling, shinyML, spark.sas7bdat, sparkavro, sparkbq, sparkhail, sparklyr.flint, sparklyr. The SparkR package contains the following man pages: AFTSurvivalRegressionModel-class alias ALSModel-class approxQuantile arrange as. Extend your toolbox by adding XGBoost, MLeap, H2O and Graphframes to your Spark plus R analysis. Gain access to Spark’s distributed Machine Learning libraries, Structure Streaming ,and ML Pipelines from R. R-devel: sparklyr_1.7.8.zip, r-release: sparklyr_1.7.8.zip, r-oldrel: sparklyr_1.7.8.zip R interface to Apache Spark Interact with Spark using familiar R interfaces, such as dplyr, broom, and DBI. Version:Īssertthat, base64enc, config (≥ 0.2), DBI (≥ 1.0.0), dbplyr (≥ 2.2.1), digest, dplyr (≥ 1.0.9), ellipsis (≥ 0.1.0), forge, generics, globals, glue, httr (≥ 1.2.1), jsonlite (≥ġ.4), methods, openssl (≥ 0.8), purrr, r2d3, rappdirs, rlang (≥ 0.1.4), rprojroot, rstudioapi (≥ 0.10), tibble, tidyr (≥ġ.2.0), tidyselect, uuid, vctrs, withr, xml2Īrrow (≥ 0.17.0), broom, diffobj, foreach, ggplot2, iterators, janeaustenr, Lahman, mlbench, nnet, nycflights13, R6, RCurl, reshape2, shiny (≥ 1.0.1), parsnip, testthat ![]() Spark's built-in machine learning algorithms. Provides a 'dplyr' compatible back-end, and provides an interface to Package supports connecting to local and remote Apache Spark clusters, ![]() You would probably need to use an upstream sparkr version thats similar to the CDH Spark youre using (1.x vs 2.x) and then just try to run a. R interface to Apache Spark, a fast and generalĮngine for big data processing, see. SparkR is also something you can try to get working. ![]()
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