【问题标题】:Error when connecting sparklyr to local将 sparklyr 连接到本地时出错
【发布时间】:2018-11-29 17:46:30
【问题描述】:

我正在尝试从本地环境运行 sparklyr 以复制生产环境。但是,我什至无法开始。我使用 spark_install() 成功安装了最新版本的 Spark,但是在尝试运行 spark_connect() 时,我收到了这个模糊且无用的错误。

> library(sparklyr)

> spark_installed_versions()
  spark hadoop                                                                 dir
1 2.3.1    2.7 C:\\Users\\...\\AppData\\Local/spark/spark-2.3.1-bin-hadoop2.7

> spark_connect(master = "local")
Error in if (is.na(a)) return(-1L) : argument is of length zero

这是我的会话信息的样子。

> sessionInfo()

R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] sparklyr_0.8.4.9003

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.17     dbplyr_1.2.1     compiler_3.5.0   pillar_1.2.3     later_0.7.3     
 [6] plyr_1.8.4       bindr_0.1.1      base64enc_0.1-3  tools_3.5.0      digest_0.6.15   
[11] jsonlite_1.5     tibble_1.4.2     nlme_3.1-137     lattice_0.20-35  pkgconfig_2.0.1 
[16] rlang_0.2.1      psych_1.8.4      shiny_1.1.0      DBI_1.0.0        rstudioapi_0.7  
[21] yaml_2.1.19      parallel_3.5.0   bindrcpp_0.2.2   stringr_1.3.1    dplyr_0.7.5     
[26] httr_1.3.1       rappdirs_0.3.1   rprojroot_1.3-2  grid_3.5.0       tidyselect_0.2.4
[31] glue_1.2.0       R6_2.2.2         foreign_0.8-70   reshape2_1.4.3   purrr_0.2.5     
[36] tidyr_0.8.1      magrittr_1.5     backports_1.1.2  promises_1.0.1   htmltools_0.3.6 
[41] assertthat_0.2.0 mnormt_1.5-5     mime_0.5         xtable_1.8-2     httpuv_1.4.3    
[46] config_0.3       stringi_1.1.7    lazyeval_0.2.1   broom_0.4.4   

【问题讨论】:

    标签: r sparklyr


    【解决方案1】:

    好吧,通过一些猜测,我能够解决我的问题。我必须手动指定“SPARK_HOME”环境。

    spark_installed_versions()[1, 3] %>% spark_home_set()
    

    【讨论】:

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