Using 3 GB RAM for Rapidminer

venkat

Hi All,

I am trying to process 143000 records and am using 3GB Ram for rapidminer.  It is taking two many days for process.  Input file size 337 MB only.

I integrated mysql with Rapidminer. I fed the data into mysql.


My XML is like this:

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="6.0.002">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="6.0.002" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="read_database" compatibility="6.0.002" expanded="true" height="60" name="Read Database" width="90" x="45" y="30">
        <parameter key="connection" value="mysql"/>
        <parameter key="query" value="SELECT `id`, `title`, `keywords`, `keyphrases`, `description`&#10;FROM `cat45`"/>
        <enumeration key="parameters"/>
      </operator>
      <operator activated="true" class="nominal_to_text" compatibility="6.0.002" expanded="true" height="76" name="Nominal to Text" width="90" x="45" y="165"/>
      <operator activated="true" class="text:process_document_from_data" compatibility="5.3.002" expanded="true" height="76" name="Process Documents from Data" width="90" x="179" y="390">
        <list key="specify_weights"/>
        <process expanded="true">
          <operator activated="true" class="text:transform_cases" compatibility="5.3.002" expanded="true" height="60" name="Transform Cases" width="90" x="112" y="165"/>
          <operator activated="true" class="text:filter_stopwords_english" compatibility="5.3.002" expanded="true" height="60" name="Filter Stopwords (English)" width="90" x="246" y="165"/>
          <operator activated="true" class="text:generate_n_grams_terms" compatibility="5.3.002" expanded="true" height="60" name="Generate n-Grams (Terms)" width="90" x="380" y="165"/>
          <connect from_port="document" to_op="Transform Cases" to_port="document"/>
          <connect from_op="Transform Cases" from_port="document" to_op="Filter Stopwords (English)" to_port="document"/>
          <connect from_op="Filter Stopwords (English)" from_port="document" to_op="Generate n-Grams (Terms)" to_port="document"/>
          <connect from_op="Generate n-Grams (Terms)" from_port="document" to_port="document 1"/>
          <portSpacing port="source_document" spacing="0"/>
          <portSpacing port="sink_document 1" spacing="0"/>
          <portSpacing port="sink_document 2" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="nominal_to_numerical" compatibility="6.0.002" expanded="true" height="94" name="Nominal to Numerical" width="90" x="380" y="345">
        <list key="comparison_groups"/>
      </operator>
      <operator activated="true" class="k_means" compatibility="6.0.002" expanded="true" height="76" name="Clustering" width="90" x="581" y="120">
        <parameter key="k" value="4"/>
        <parameter key="measure_types" value="MixedMeasures"/>
      </operator>
      <connect from_op="Read Database" from_port="output" to_op="Nominal to Text" to_port="example set input"/>
      <connect from_op="Nominal to Text" from_port="example set output" to_op="Process Documents from Data" to_port="example set"/>
      <connect from_op="Process Documents from Data" from_port="example set" to_op="Nominal to Numerical" to_port="example set input"/>
      <connect from_op="Nominal to Numerical" from_port="example set output" to_op="Clustering" to_port="example set"/>
      <connect from_op="Clustering" from_port="cluster model" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
  </operator>
</process>

Your help is very much appreciated.

Thanks in Advance,
Venkat

fras

Could you provicd the name of the operator where the process starts and never returns ?
Perhaps you may reduce the size of your select statement only using "title" ? If this works you
really need more RAM.
Why do you need operator "Nominal to Numerical" if TF-IDF delivers numerical values for all tokens found ?
And last but not least: Why you do not apply the "tokenize" operator inside "Prozess Documents" operator ?
You should start with tokenizing first and if this works you may add further operators like Generate-N-Grams and so on.