title: SparkR Cartesian joins causes error - trying to get date sequence
body: <p>Has anyone had success in doing a cartesian join between a sparkR DataFrame and a DataFrame converted from an R data.frame?</p>
  
  <p>I have a sparkR DataFrame (spark_df) that I pull in from an outside source - I apologize that I don't know how to provide a reproducible example of having data already in spark but not having previously converted from R.  I created a test R data frame with just one entry and converted it to a Spark data frame then try to join:</p>
  
  <p><code>test_df = data.frame(month_dates = '2015-11-01')
  t_dates = createDataFrame(sql, test_df)
  lpd = join(spark_df, t_dates)
  showDF(lpd)</code></p>
  
  <p>In reply, I get a slew of error messages ending in:</p>
  
  <pre><code>16/09/08 20:46:02 ERROR RBackendHandler: showString on 3363 failed
  Error in invokeJava(isStatic = FALSE, objId$id, methodName, ...) : 
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1643.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1643.0 (TID 17015, prod-mesos-s-6.aws.company.com): org.apache.spark.SparkException: R computation failed with
   7f5a022f3000-7f5a022f4000 rw-p 0182a000 ca:01 16926                      /usr/lib64/libicudata.so.54.1
  7f5a022f4000-7f5a0231a000 r-xp 00000000 ca:01 4839                       /usr/lib64/libtinfo.so.5.9
  7f5a0231a000-7f5a02519000 ---p 00026000 ca:01 4839                       /usr/lib64/libtinfo.so.5.9
  7f5a02519000-7f5a0251d000 r--p 00025000 ca:01 4839                       /usr/lib64/libtinfo.so.5.9
  7f5a0251d000-7f5a0251e000 rw-p 00029000 ca:01 4839                       /usr/lib64/libtinfo.so.5.9
  7f5a0251e000-7f5a02534000 r-xp 00000000 ca:01 11293                      /usr/lib64/libgcc_s-5.3.1-20160406.so.1
  7f5a02534000-7f5a02733000 ---p 00016000 ca:01 11293                      /usr/lib64/libgcc_s-5.3.1-20160
  </code></pre>
  
  <p>My end goal is a sequence of dates given a start date and end date so that I can fill in missing dates in t-dates.  I couldn't figure out a way to do sequences in SparkR which is why I was doing it in R and converting to SparkR DataFrame - if there is a better way to do this using SparkR that avoids data.frames altogether, that would be rad.  </p>
  
  <p>If anyone knows how to fix this issue, that would also be rad.  </p>
  
  <p>Session Info:</p>
  
  <pre><code>R version 3.3.0 (2016-05-03)
  Platform: x86_64-redhat-linux-gnu (64-bit)
  Running under: Fedora 22 (Twenty Two)    
  
  attached base packages:
  [1] stats     graphics  grDevices utils     datasets  methods   base     
  
  other attached packages:
  [1] SparkR_1.6.1    lubridate_1.5.6 zoo_1.7-12      dplyr_0.4.3    
  
  loaded via a namespace (and not attached):
   [1] lazyeval_0.2.0  magrittr_1.5    R6_2.1.2        assertthat_0.1 
   [5] parallel_3.3.0  tools_3.3.0     DBI_0.4-1       Rcpp_0.12.7    
   [9] stringi_1.1.1   grid_3.3.0      stringr_1.0.0   lattice_0.20-33
  </code></pre>