web service error "The script could not be parsed"

Hi,

I have a RM process that runs well on local, but the web service has error:

de.rapidanalytics.ejb.service.ServiceDataSourceException Error executing process /home/RM/0_main_recommender for service 0_main_recommender: The script could not be parsed.

Couldn't find similar error online. Could somebody help please? Thanks!

RM in XML:

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="6.4.000">
  <context>
    <input/>
    <output/>
    <macros>
      <macro>
        <key>TABLE_IN_KNOWN</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>TABLE_IN</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>PREDICTOR</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>LABEL</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>METRIC</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>GROUP</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>METADATA</key>
        <value>-1</value>
      </macro>
      <macro>
        <key>TABLE_OUT</key>
        <value>-1</value>
      </macro>
    </macros>
  </context>
  <operator activated="true" class="process" compatibility="6.4.000" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="r_scripting:execute_r" compatibility="6.4.000" expanded="true" height="60" name="Execute R" width="90" x="45" y="30">
        <parameter key="script" value="library(RODBC)&#10;library(readr)&#10;library(dplyr)&#10;&#10;&#10;# get metadata from different sources ####&#10;parse_metadata = function(table_in_known, table_in, col_predictor, col_label, col_metric, col_group, metadata, table_out){&#10;        &#10;        if(table_in_known != -1) { # read metadata from database&#10;                &#10;                &#10;                ch = odbcConnect('AnalyticsEngine')&#10;                &#10;                sql0 = paste0(&quot;&#10;                              SELECT * &#10;                              FROM [dbo].[aap_data_attribute_metadata]&#10;                              WHERE [table] = '&quot;, table_in_known, &quot;'&quot;)&#10;                &#10;                sql0 = paste0('&#10;                              SELECT * &#10;                              FROM [dbo].[aap_data_attribute_metadata]')&#10;                cat(sql0, '\n\n')&#10;                &#10;                metadata_fixed = sqlQuery(ch, sql0)&#10;                &#10;                table_in = table_in_known&#10;                &#10;        } else {&#10;                &#10;                if (metadata != -1){ &#10;                        &#10;                        &#10;                        &#10;                        &#10;                } else{ # what format of metadata? XML?&#10;                        &#10;                        metadata_fixed = data.frame(metadata)&#10;                        &#10;                }&#10;                &#10;                # save it to database&#10;                &#10;                &#10;        }&#10;        &#10;        &#10;        if(table_out == -1){&#10;                table_out = paste(table_in, format(Sys.time(), '%Y_%m_%d_%H_%M_%S'), sep = '_')&#10;        }&#10;        &#10;        &#10;        list(table_in, metadata_fixed, table_out)&#10;}&#10;&#10;&#10;&#10;&#10;decide_scenario = function(metadata){&#10;        &#10;        if ( ! 'label' %in% metadata$role){ # unsupervised&#10;                &#10;                scenario = c('outlier', 'clustering')        &#10;                &#10;        } else if ( sum(metadata$role == 'label') &gt; 1 ){&#10;                &#10;                stop('more than one label not allowed')&#10;                &#10;        } else { # supervised&#10;                &#10;                if (metadata[metadata$role == 'label', 'datatype']  %in% c('numeric', 'int')) {&#10;                        &#10;                        scenario = 'regression'&#10;                        &#10;                        #                         if(metadata[metadata$role == 'label', 'datatype']  == 'int' &amp; dat$){&#10;                        #                                 &#10;                        #                                 warning('are you sure the label is numeric, rather than classes?')&#10;                        #                         }&#10;                        &#10;                } else if (metadata[metadata$role == 'label', 'datatype']  %in% c('character', 'factor')) {&#10;                        &#10;                        scenario = 'classification'&#10;                } &#10;                &#10;        }&#10;        &#10;        if('datetime' %in% metadata$role){&#10;                scenario  = append(scenario, c('ts', 'aggregation'))&#10;        }&#10;        &#10;        scenario = append(scenario, 'feature_engineering') # this always work?&#10;        &#10;}&#10;&#10;rm_main = function(dat, in_rapidminer = T){&#10;        &#10;        # macro inputs from UI (default of macros is -1) ####&#10;        # either data source with known metadata&#10;        table_in_known = '%{TABLE_IN_KNOWN}'&#10;        &#10;        # or new data with metadata&#10;        table_in = '%{TABLE_IN}'&#10;        col_predictor = '%{PREDICTOR}'&#10;        col_label = '%{LABEL}'&#10;        col_metric = '%{METRIC}'&#10;        col_group = '%{GROUP}'&#10;        # or&#10;        metadata = '%{METADATA}' &#10;        # metadata (role and datatype) about the columns. If have this, `column_in` and `group` are ignored&#10;        &#10;        # # don't do this step now (high automation) ####&#10;        # # show user available algorithms based on metadata, and use chooses some of them        &#10;&#10;        &#10;        if(in_rapidminer == F){&#10;                table_in_known = 'HHS_CLM_ROLLING_36_MONTHS_Jul14_provider_daily'&#10;        }&#10;        &#10;        # now specify output table&#10;        table_out = '%{TABLE_OUT}'&#10;        &#10;&#10;        # parse and organize metadata from different sources ####&#10;        parsed = parse_metadata(table_in_known, table_in, col_predictor, col_label, col_metric, col_group, metadata, table_out)&#10;        &#10;        table_in = parsed[[1]]&#10;        metadata = parsed[[2]]&#10;        table_out = parsed[[3]]&#10;        &#10;                &#10;        scenario = decide_scenario(metadata)&#10;        &#10;        cat('scenario:', scenario, '\n')&#10;        cat('table_in:', table_in, '\n')&#10;        cat('table_out:', table_out, '\n')&#10;        &#10;}"/>
      </operator>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
    </process>
  </operator>
</process>