{
 "paragraphs": [
  {
   "text": "%md\n\nThis tutorial is for how to use customize R runtime environment via conda in yarn mode.\nIn this approach, the R interpreter runs in yarn container instead of in the zeppelin server host. And remmeber this only works for IRKernel(`%r.ir`) but not for vanilla R(`%r.r`), so make sure you include the following python packages in your conda env.\n* python\n* jupyter\n* grpcio\n* protobuf\n* r-base\n* r-essentials\n* r-irkernel\n\n\n\n",
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   "dateUpdated": "2021-08-09 10:55:29.815",
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      "type": "HTML",
      "data": "<div class=\"markdown-body\">\n<p>This tutorial is for how to use customize R runtime environment via conda in yarn mode.<br />\nIn this approach, the R interpreter runs in yarn container instead of in the zeppelin server host. And remmeber this only works for IRKernel(<code>%r.ir</code>) but not for vanilla R(<code>%r.r</code>), so make sure you include the following python packages in your conda env.</p>\n<ul>\n<li>python</li>\n<li>jupyter</li>\n<li>grpcio</li>\n<li>protobuf</li>\n<li>r-base</li>\n<li>r-essentials</li>\n<li>r-irkernel</li>\n</ul>\n\n</div>"
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   "id": "paragraph_1616510705826_532544979",
   "dateCreated": "2021-06-19 21:58:16.909",
   "dateStarted": "2021-08-09 10:55:29.817",
   "dateFinished": "2021-08-09 10:55:29.825",
   "status": "FINISHED"
  },
  {
   "title": "Create R conda env",
   "text": "%sh\n\n# make sure you have miniconda, conda-pack and mamba installed.\n# install miniconda: https://docs.conda.io/en/latest/miniconda.html\n# install conda-pack: https://conda.github.io/conda-pack/\n# install mamba: https://github.com/mamba-org/mamba\n\necho \"name: r_env\nchannels:\n  - conda-forge\n  - defaults\ndependencies:\n  - python=3.7 \n  - jupyter\n  - grpcio\n  - protobuf\n  - r-base=3\n  - r-essentials\n  - r-evaluate\n  - r-base64enc\n  - r-knitr\n  - r-ggplot2\n  - r-irkernel\n  - r-shiny\n  - r-googlevis\" > r_env.yml\n    \nmamba env remove -n r_env\nmamba env create -f r_env.yml\n",
   "user": "anonymous",
   "dateUpdated": "2021-08-09 10:55:29.917",
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     {
      "type": "TEXT",
      "data": "\nRemove all packages in environment /mnt/disk1/jzhang/miniconda3/envs/r_env:\n\npkgs/main/noarch          \npkgs/main/linux-64        \npkgs/r/linux-64           \nconda-forge/noarch        \npkgs/r/noarch             \nconda-forge/linux-64      \nTransaction\n\n  Prefix: /mnt/disk1/jzhang/miniconda3/envs/r_env\n\n  Updating specs:\n\n   - python=3.7\n   - jupyter\n   - grpcio\n   - protobuf\n   - r-base=3\n   - r-essentials\n   - r-evaluate\n   - r-base64enc\n   - r-knitr\n   - r-ggplot2\n   - r-irkernel\n   - r-shiny\n   - r-googlevis\n\n\n  Package                               Version  Build                 Channel                    Size\n────────────────────────────────────────────────────────────────────────────────────────────────────────\n  Install:\n────────────────────────────────────────────────────────────────────────────────────────────────────────\n\n  + _libgcc_mutex                           0.1  conda_forge           conda-forge/linux-64     Cached\n  + _openmp_mutex                           4.5  1_gnu                 conda-forge/linux-64     Cached\n  + _r-mutex                              1.0.1  anacondar_1           conda-forge/noarch       Cached\n  + alsa-lib                              1.2.3  h516909a_0            conda-forge/linux-64     Cached\n  + argon2-cffi                          20.1.0  py37h5e8e339_2        conda-forge/linux-64     Cached\n  + async_generator                        1.10  py_0                  conda-forge/noarch       Cached\n  + attrs                                21.2.0  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + backcall                              0.2.0  pyh9f0ad1d_0          conda-forge/noarch       Cached\n  + backports                               1.0  py_2                  conda-forge/noarch       Cached\n  + backports.functools_lru_cache         1.6.4  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + binutils_impl_linux-64               2.36.1  h193b22a_2            conda-forge/linux-64     Cached\n  + binutils_linux-64                      2.36  hf3e587d_0            conda-forge/linux-64     Cached\n  + bleach                                4.0.0  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + bwidget                              1.9.14  ha770c72_0            conda-forge/linux-64     Cached\n  + bzip2                                 1.0.8  h7f98852_4            conda-forge/linux-64     Cached\n  + c-ares                               1.17.1  h7f98852_1            conda-forge/linux-64     Cached\n  + ca-certificates                   2021.5.30  ha878542_0            conda-forge/linux-64     Cached\n  + cairo                                1.16.0  h6cf1ce9_1008         conda-forge/linux-64     Cached\n  + certifi                           2021.5.30  py37h89c1867_0        conda-forge/linux-64     Cached\n  + cffi                                 1.14.6  py37hc58025e_0        conda-forge/linux-64     Cached\n  + curl                    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conda-forge/linux-64     Cached\n  + qt                                   5.12.9  hda022c4_4            conda-forge/linux-64     Cached\n  + qtconsole                             5.1.1  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + qtpy                                  1.9.0  py_0                  conda-forge/noarch       Cached\n  + r-askpass                               1.1  r36hcfec24a_2         conda-forge/linux-64     Cached\n  + r-assertthat                          0.2.1  r36h6115d3f_2         conda-forge/noarch       Cached\n  + r-backports                           1.2.1  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-base                                3.6.3  hbcea092_8            conda-forge/linux-64     Cached\n  + r-base64enc                           0.1_3  r36hcfec24a_1004      conda-forge/linux-64     Cached\n  + r-blob                                1.2.1  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-boot                      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Cached\n  + r-clipr                               0.7.1  r36h142f84f_0         conda-forge/noarch       Cached\n  + r-cluster                             2.1.2  r36h859d828_0         conda-forge/linux-64     Cached\n  + r-codetools                          0.2_18  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-colorspace                          2.0_1  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-commonmark                            1.7  r36hcfec24a_1002      conda-forge/linux-64     Cached\n  + r-cpp11                               0.2.7  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-crayon                              1.4.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-crul                                1.1.0  r36h785f33e_0         conda-forge/noarch       Cached\n  + r-curl                                4.3.1  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-data.table                         1.14.0  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-dbi                                 1.1.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-dbplyr                              2.1.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-desc                                1.3.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-diffobj                             0.3.4  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-digest                             0.6.27  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-dplyr                               1.0.6  r36h03ef668_1         conda-forge/linux-64     Cached\n  + r-dtplyr                              1.1.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-ellipsis                            0.3.2  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-essentials                            3.6  r36_2002              conda-forge/noarch       Cached\n  + r-evaluate                             0.14  r36h6115d3f_2         conda-forge/noarch       Cached\n  + r-fansi                               0.4.2  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-farver                              2.1.0  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-fastmap                             1.1.0  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-forcats                             0.5.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-foreach                             1.5.1  r36h142f84f_0         conda-forge/noarch       Cached\n  + r-foreign                            0.8_76  r36hcdcec82_1         conda-forge/linux-64     Cached\n  + r-formatr                               1.9  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-fs                                  1.5.0  r36h0357c0b_0         conda-forge/linux-64     Cached\n  + r-gargle                              1.1.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-generics                            0.1.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-ggplot2                             3.3.3  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-gistr                               0.9.0  r36h6115d3f_0         conda-forge/noarch       Cached\n  + r-glmnet                              4.1_1  r36h859d828_0         conda-forge/linux-64     Cached\n  + r-glue                                1.4.2  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-googledrive                         1.0.1  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-googlesheets4                       0.3.0  r36hc72bb7e_0         conda-forge/linux-64     Cached\n  + r-googlevis                          0.6.10  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-gower                               0.2.2  r36hcdcec82_0         conda-forge/linux-64     Cached\n  + r-gtable                              0.3.0  r36h6115d3f_3         conda-forge/noarch       Cached\n  + r-haven                               2.4.1  r36h2713e49_0         conda-forge/linux-64     Cached\n  + r-hexbin                             1.28.2  r36h859d828_0         conda-forge/linux-64     Cached\n  + r-highr                                 0.9  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-hms                                 1.1.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-htmltools                         0.5.1.1  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-htmlwidgets                         1.5.3  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-httpcode                            0.3.0  r36_1                 conda-forge/linux-64     Cached\n  + r-httpuv                              1.6.1  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-httr                                1.4.2  r36h6115d3f_0         conda-forge/noarch       Cached\n  + r-ids                                 1.0.1  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-ipred                              0.9_11  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-irdisplay                             1.0  r36hd8ed1ab_0         conda-forge/noarch       Cached\n  + r-irkernel                              1.2  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-isoband                             0.2.4  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-iterators                          1.0.13  r36h142f84f_0         conda-forge/noarch       Cached\n  + r-jquerylib                           0.1.4  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-jsonlite                            1.7.2  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-kernsmooth                        2.23_20  r36h742201e_0         conda-forge/linux-64     Cached\n  + r-knitr                                1.33  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-labeling                            0.4.2  r36h142f84f_0         conda-forge/noarch       Cached\n  + r-later                               1.2.0  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-lattice                           0.20_44  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-lava                                1.6.9  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-lazyeval                            0.2.2  r36hcfec24a_2         conda-forge/linux-64     Cached\n  + r-lifecycle                           1.0.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-lubridate                          1.7.10  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-magrittr                            2.0.1  r36hcfec24a_1         conda-forge/linux-64     Cached\n  + r-maps                                3.3.0  r36hcdcec82_1004      conda-forge/linux-64     Cached\n  + r-markdown                              1.1  r36hcfec24a_1         conda-forge/linux-64     Cached\n  + r-mass                               7.3_54  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-matrix                              1.3_3  r36he454529_0         conda-forge/linux-64     Cached\n  + r-mgcv                               1.8_35  r36he454529_0         conda-forge/linux-64     Cached\n  + r-mime                                 0.10  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-modelmetrics                      1.2.2.2  r36h0357c0b_1         conda-forge/linux-64     Cached\n  + r-modelr                              0.1.8  r36h6115d3f_0         conda-forge/noarch       Cached\n  + r-munsell                             0.5.0  r36h6115d3f_1003      conda-forge/noarch       Cached\n  + r-nlme                              3.1_152  r36h859d828_0         conda-forge/linux-64     Cached\n  + r-nnet                               7.3_16  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-numderiv                       2016.8_1.1  r36h6115d3f_3         conda-forge/noarch       Cached\n  + r-openssl                             1.4.4  r36he36bf35_0         conda-forge/linux-64     Cached\n  + r-pbdzmq                              0.3_5  r36h42bf92c_1         conda-forge/linux-64     Cached\n  + r-pillar                              1.6.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-pkgconfig                           2.0.3  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-pkgload                             1.2.1  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-plyr                                1.8.6  r36h0357c0b_1         conda-forge/linux-64     Cached\n  + r-praise                              1.0.0  r36h6115d3f_1004      conda-forge/noarch       Cached\n  + r-prettyunits                         1.1.1  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-proc                             1.17.0.1  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-processx                            3.5.2  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-prodlim                        2019.11.13  r36h0357c0b_1         conda-forge/linux-64     Cached\n  + r-progress                            1.2.2  r36h6115d3f_2         conda-forge/noarch       Cached\n  + r-promises                          1.2.0.1  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-pryr                                0.1.4  r36h0357c0b_1004      conda-forge/linux-64     Cached\n  + r-ps                                  1.6.0  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-purrr                               0.3.4  r36hcfec24a_1         conda-forge/linux-64     Cached\n  + r-quantmod                           0.4.18  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-r6                                  2.5.0  r36hc72bb7e_0         conda-forge/noarch      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r36h6115d3f_1003      conda-forge/noarch       Cached\n  + r-rematch2                            2.1.2  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-repr                                1.1.3  r36h785f33e_0         conda-forge/noarch       Cached\n  + r-reprex                              2.0.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-reshape2                            1.4.4  r36h0357c0b_1         conda-forge/linux-64     Cached\n  + r-rlang                              0.4.11  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-rmarkdown                             2.8  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-rpart                              4.1_15  r36hcfec24a_2         conda-forge/linux-64     Cached\n  + r-rprojroot                           2.0.2  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-rstudioapi                           0.13  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-rvest                               1.0.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-sass                                0.4.0  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-scales                              1.1.1  r36h6115d3f_0         conda-forge/noarch       Cached\n  + r-selectr                             0.4_2  r36h6115d3f_1         conda-forge/noarch       Cached\n  + r-shape                               1.4.6  r36ha770c72_0         conda-forge/noarch       Cached\n  + r-shiny                               1.6.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-sourcetools                         0.1.7  r36he1b5a44_1002      conda-forge/linux-64     Cached\n  + r-spatial                            7.3_14  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-squarem                            2021.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-stringi                             1.6.2  r36hcabe038_0         conda-forge/linux-64     Cached\n  + r-stringr                             1.4.0  r36h6115d3f_2         conda-forge/noarch       Cached\n  + r-survival                           3.2_11  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-sys                                   3.4  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-testthat                            3.0.2  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-tibble                              3.1.2  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-tidyr                               1.1.3  r36h03ef668_0         conda-forge/linux-64     Cached\n  + r-tidyselect                          1.1.1  r36hc72bb7e_0         conda-forge/linux-64     Cached\n  + r-tidyverse                           1.3.1  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-timedate                         3043.102  r36h6115d3f_1002      conda-forge/noarch       Cached\n  + r-tinytex                              0.31  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-triebeard                           0.3.0  r36he1b5a44_1003      conda-forge/linux-64     Cached\n  + r-ttr                                0.24.2  r36hcdcec82_0         conda-forge/linux-64     Cached\n  + r-urltools                            1.7.3  r36h0357c0b_2         conda-forge/linux-64     Cached\n  + r-utf8                                1.2.1  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-uuid                                0.1_4  r36hcdcec82_1         conda-forge/linux-64     Cached\n  + r-vctrs                               0.3.8  r36hcfec24a_1         conda-forge/linux-64     Cached\n  + r-viridislite                         0.4.0  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-waldo                               0.2.5  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-withr                               2.4.2  r36hc72bb7e_0         conda-forge/noarch       Cached\n  + r-xfun                                 0.23  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + r-xml2                                1.3.2  r36h0357c0b_1         conda-forge/linux-64     Cached\n  + r-xtable                              1.8_4  r36h6115d3f_3         conda-forge/noarch       Cached\n  + r-xts                                0.12.1  r36hcdcec82_0         conda-forge/linux-64     Cached\n  + r-yaml                                2.2.1  r36hcfec24a_1         conda-forge/linux-64     Cached\n  + r-zoo                                 1.8_9  r36hcfec24a_0         conda-forge/linux-64     Cached\n  + readline                                8.1  h46c0cb4_0            conda-forge/linux-64     Cached\n  + sed                                     4.8  he412f7d_0            conda-forge/linux-64     Cached\n  + send2trash                            1.7.1  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + setuptools                           49.6.0  py37h89c1867_3        conda-forge/linux-64     Cached\n  + six                                  1.16.0  pyh6c4a22f_0          conda-forge/noarch       Cached\n  + sqlite                               3.36.0  h9cd32fc_0            conda-forge/linux-64     Cached\n  + sysroot_linux-64                       2.12  he073ed8_14           conda-forge/noarch       Cached\n  + terminado                            0.10.1  py37h89c1867_0        conda-forge/linux-64     Cached\n  + testpath                              0.5.0  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + tk                                   8.6.10  h21135ba_1            conda-forge/linux-64     Cached\n  + tktable                                2.10  hb7b940f_3            conda-forge/linux-64     Cached\n  + tornado                                 6.1  py37h5e8e339_1        conda-forge/linux-64     Cached\n  + traitlets                             5.0.5  py_0                  conda-forge/noarch       Cached\n  + typing_extensions                  3.10.0.0  pyha770c72_0          conda-forge/noarch       Cached\n  + wcwidth                               0.2.5  pyh9f0ad1d_2          conda-forge/noarch       Cached\n  + webencodings                          0.5.1  py_1                  conda-forge/noarch       Cached\n  + wheel                                0.36.2  pyhd3deb0d_0          conda-forge/noarch       Cached\n  + widgetsnbextension                    3.5.1  py37h89c1867_4        conda-forge/linux-64     Cached\n  + xorg-kbproto                          1.0.7  h7f98852_1002         conda-forge/linux-64     Cached\n  + xorg-libice                          1.0.10  h7f98852_0            conda-forge/linux-64     Cached\n  + xorg-libsm                            1.2.3  hd9c2040_1000         conda-forge/linux-64     Cached\n  + xorg-libx11                           1.7.2  h7f98852_0            conda-forge/linux-64     Cached\n  + xorg-libxau                           1.0.9  h7f98852_0            conda-forge/linux-64     Cached\n  + xorg-libxdmcp                         1.1.3  h7f98852_0            conda-forge/linux-64     Cached\n  + xorg-libxext                          1.3.4  h7f98852_1            conda-forge/linux-64     Cached\n  + xorg-libxrender                      0.9.10  h7f98852_1003         conda-forge/linux-64     Cached\n  + xorg-renderproto                     0.11.1  h7f98852_1002         conda-forge/linux-64     Cached\n  + xorg-xextproto                        7.3.0  h7f98852_1002         conda-forge/linux-64     Cached\n  + xorg-xproto                          7.0.31  h7f98852_1007         conda-forge/linux-64     Cached\n  + xz                                    5.2.5  h516909a_1            conda-forge/linux-64     Cached\n  + zeromq                                4.3.4  h9c3ff4c_0            conda-forge/linux-64     Cached\n  + zipp                                  3.5.0  pyhd8ed1ab_0          conda-forge/noarch       Cached\n  + zlib                                 1.2.11  h516909a_1010         conda-forge/linux-64     Cached\n  + zstd                                  1.5.0  ha95c52a_0            conda-forge/linux-64     Cached\n\n  Summary:\n\n  Install: 358 packages\n\n  Total download: 0  B\n\n────────────────────────────────────────────────────────────────────────────────────────────────────────\n\n\n\nLooking for: ['python=3.7', 'jupyter', 'grpcio', 'protobuf', 'r-base=3', 'r-essentials', 'r-evaluate', 'r-base64enc', 'r-knitr', 'r-ggplot2', 'r-irkernel', 'r-shiny', 'r-googlevis']\n\n\nPreparing transaction: ...working... done\nVerifying transaction: ...working... done\nExecuting transaction: ...working... Enabling notebook extension jupyter-js-widgets/extension...\n      - Validating: \u001b[32mOK\u001b[0m\n\ndone\n#\n# To activate this environment, use\n#\n#     $ conda activate r_env\n#\n# To deactivate an active environment, use\n#\n#     $ conda deactivate\n\n"
     }
    ]
   },
   "apps": [],
   "runtimeInfos": {},
   "progressUpdateIntervalMs": 500,
   "jobName": "paragraph_1624111096910_1941489893",
   "id": "paragraph_1617163651950_276096757",
   "dateCreated": "2021-06-19 21:58:16.910",
   "dateStarted": "2021-08-09 10:55:29.920",
   "dateFinished": "2021-08-09 10:55:59.548",
   "status": "FINISHED"
  },
  {
   "title": "Create R conda tar",
   "text": "%sh\n\nrm -rf r_env.tar.gz\nconda pack -n r_env\n",
   "user": "anonymous",
   "dateUpdated": "2021-08-09 10:55:59.555",
   "progress": 0,
   "config": {
    "editorSetting": {
     "language": "sh",
     "editOnDblClick": false,
     "completionKey": "TAB",
     "completionSupport": false
    },
    "colWidth": 12.0,
    "editorMode": "ace/mode/sh",
    "fontSize": 9.0,
    "title": true,
    "results": {},
    "enabled": true
   },
   "settings": {
    "params": {},
    "forms": {}
   },
   "results": {
    "code": "SUCCESS",
    "msg": [
     {
      "type": "TEXT",
      "data": "Collecting packages...\nPacking environment at '/mnt/disk1/jzhang/miniconda3/envs/r_env' to 'r_env.tar.gz'\n\r[                                        ] | 0% Completed |  0.0s\r[                                        ] | 0% Completed |  0.1s\r[                                        ] | 0% Completed |  0.2s\r[                                        ] | 0% Completed |  0.3s\r[                                        ] | 0% Completed |  0.4s\r[                                        ] | 0% Completed |  0.5s\r[                                        ] | 0% Completed |  0.6s\r[                                        ] | 0% Completed |  0.7s\r[                                        ] | 0% Completed |  0.8s\r[                                        ] | 0% Completed |  0.9s\r[                                        ] | 1% Completed |  1.0s\r[                                        ] | 1% Completed |  1.1s\r[                                        ] | 1% Completed |  1.2s\r[    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   "dateFinished": "2021-08-09 10:57:09.103",
   "status": "FINISHED"
  },
  {
   "title": "Upload R conda tar to hdfs (Optional)",
   "text": "%sh\n\nhadoop fs -rmr /tmp/r_env.tar.gz\nhadoop fs -put r_env.tar.gz /tmp\n# The python conda tar should be publicly accessible by others, so need to change permission here.\nhadoop fs -chmod 644 /tmp/r_env.tar.gz\n",
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   "results": {
    "code": "SUCCESS",
    "msg": [
     {
      "type": "TEXT",
      "data": "rmr: DEPRECATED: Please use '-rm -r' instead.\n21/08/09 10:57:10 INFO fs.TrashPolicyDefault: Moved: 'hdfs://emr-header-1.cluster-46718:9000/tmp/r_env.tar.gz' to trash at: hdfs://emr-header-1.cluster-46718:9000/user/hadoop/.Trash/Current/tmp/r_env.tar.gz1628477830555\n"
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   "dateFinished": "2021-08-09 10:57:16.029",
   "status": "FINISHED"
  },
  {
   "title": "Configure R Interpreter",
   "text": "%r.conf\n\n# set zeppelin.interpreter.launcher to be yarn, so that R interpreter run in yarn container, \n# otherwise R interpreter run as local process in the zeppelin server host.\nzeppelin.interpreter.launcher yarn\n\n# zeppelin.yarn.dist.archives can be either local file or hdfs file\nzeppelin.yarn.dist.archives hdfs:///tmp/r_env.tar.gz#environment\n\nzeppelin.interpreter.conda.env.name environment\n\n",
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   "dateFinished": "2021-08-09 10:57:16.058",
   "status": "FINISHED"
  },
  {
   "title": "Base plotting",
   "text": "%r.ir\n\npairs(iris)\n",
   "user": "anonymous",
   "dateUpdated": "2021-08-09 10:57:16.155",
   "progress": 0,
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    "msg": [
     {
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bpd0x9u6SQg7HykAhRw9a2Zj6SmAmnah5HDF0muWp8Nom8XpPjSzu0a0BQT4gbg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\nj1VqEV+6xPK1ZV21w9UfHDmW5Yp8fOse1k2KkA3NP4sXy0Ws4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r/csf6mo/i7wXaViPS9RnYEx3a3+2vlvsao7Nh6yA+TLxLbcmx5sU0e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\ncO9SzMkna9HZxwnnVYVlu2ZkcxI2/5JiGkdSq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M4cS9cCrOKqNlFUU82zW8VGdnb2z1ik+o+zR3Nfy/MaItGjs2EY36ytZb0UkvcayxvV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\nl5b7fZI/tQekMZ/rIOinjX5gmDOKXha9QStKXdLTaG34BVo8m66sBdB4T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   "dateFinished": "2021-08-09 10:57:47.946",
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  },
  {
   "title": "Use ggplot2",
   "text": "%r.ir\n\nlibrary(ggplot2)\npres_rating <- data.frame(\n  rating = as.numeric(presidents),\n  year = as.numeric(floor(time(presidents))),\n  quarter = as.numeric(cycle(presidents))\n)\np <- ggplot(pres_rating, aes(x=year, y=quarter, fill=rating))\np + geom_raster()\n",
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   "dateUpdated": "2021-08-09 10:57:47.983",
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   "results": {
    "code": "SUCCESS",
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     {
      "type": "TEXT",
      "data": "\nAttaching package: ‘ggplot2’\n\n\nThe following object is masked from ‘package:SparkR’:\n\n    expr\n\n\n\n"
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     }
    ]
   },
   "apps": [],
   "runtimeInfos": {},
   "progressUpdateIntervalMs": 500,
   "jobName": "paragraph_1624111096911_1421779245",
   "id": "paragraph_1623916874799_812799753",
   "dateCreated": "2021-06-19 21:58:16.911",
   "dateStarted": "2021-08-09 10:57:47.986",
   "dateFinished": "2021-08-09 10:57:48.701",
   "status": "FINISHED"
  },
  {
   "title": "Use googleVis",
   "text": "%r.ir\n\nlibrary(googleVis)\ndf=data.frame(country=c(\"US\", \"GB\", \"BR\"), \n              val1=c(10,13,14), \n              val2=c(23,12,32))\nBar <- gvisBarChart(df)\nprint(Bar, tag = 'chart')\n",
   "user": "anonymous",
   "dateUpdated": "2021-08-09 10:57:48.786",
   "progress": 0,
   "config": {
    "editorSetting": {
     "language": "r",
     "editOnDblClick": false,
     "completionKey": "TAB",
     "completionSupport": true
    },
    "colWidth": 6.0,
    "editorMode": "ace/mode/r",
    "fontSize": 9.0,
    "title": true,
    "results": {},
    "enabled": true
   },
   "settings": {
    "params": {},
    "forms": {}
   },
   "results": {
    "code": "SUCCESS",
    "msg": [
     {
      "type": "TEXT",
      "data": "\nWelcome to googleVis version 0.6.10\n\nPlease read Google's Terms of Use\nbefore you start using the package:\nhttps://developers.google.com/terms/\n\nNote, the plot method of googleVis will by default use\nthe standard browser to display its output.\n\nSee the googleVis package vignettes for more details,\nor visit https://github.com/mages/googleVis.\n\nTo suppress this message use:\nsuppressPackageStartupMessages(library(googleVis))\n\n\n\n"
     },
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