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Posted to commits@sdap.apache.org by le...@apache.org on 2017/10/27 22:34:57 UTC

[16/21] incubator-sdap-mudrod git commit: SDAP-1 Import all code under the SDAP SGA

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/SResult.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/SResult.java b/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/SResult.java
new file mode 100644
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+++ b/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/SResult.java
@@ -0,0 +1,183 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.ssearch.structure;
+
+import java.lang.reflect.Field;
+
+/**
+ * Data structure class for search result
+ */
+public class SResult {
+  public static final String rlist[] = { "term_score", "releaseDate_score", /*"versionNum_score",*/
+      "processingL_score", "allPop_score", "monthPop_score", "userPop_score"/*, "termAndv_score"*/ };
+  String shortName = null;
+  String longName = null;
+  String topic = null;
+  String description = null;
+  String relase_date = null;
+
+  public Double final_score = 0.0;
+  public Double term_score = 0.0;
+  public Double releaseDate_score = 0.0;
+  public Double versionNum_score = 0.0;
+  public Double processingL_score = 0.0;
+  public Double click_score = 0.0;
+  public Double allPop_score = 0.0;
+  public Double monthPop_score = 0.0;
+  public Double userPop_score = 0.0;
+  public Double termAndv_score = 0.0;
+  public Integer below = 0;
+
+  public Double Dataset_LongName_score = null;
+  public Double Dataset_Metadata_score = null;
+  public Double DatasetParameter_Term_score = null;
+  public Double DatasetSource_Source_LongName_score = null;
+  public Double DatasetSource_Sensor_LongName_score = null;
+
+  public String version = null;
+  public String processingLevel = null;
+  public String latency = null;
+  public String stopDateLong = null;
+  public String stopDateFormat = null;
+  public Double spatialR_Sat = null;
+  public Double spatialR_Grid = null;
+  public String temporalR = null;
+
+  public Double releaseDate = null;
+  public Double click = null;
+  public Double term = null;
+  public Double versionNum = null;
+  public Double processingL = null;
+  public Double allPop = null;
+  public Double monthPop = null;
+  public Double userPop = null;
+  public Double termAndv = null;
+
+  public Double Dataset_LongName = null;
+  public Double Dataset_Metadata = null;
+  public Double DatasetParameter_Term = null;
+  public Double DatasetSource_Source_LongName = null;
+  public Double DatasetSource_Sensor_LongName = null;
+
+  public Double prediction = 0.0;
+  public String label = null;
+
+  //add by quintinali
+  public String startDate;
+  public String endDate;
+  public String sensors;
+
+  /**
+   * @param shortName   short name of dataset
+   * @param longName    long name of dataset
+   * @param topic       topic of dataset
+   * @param description description of dataset
+   * @param date        release date of dataset
+   */
+  public SResult(String shortName, String longName, String topic, String description, String date) {
+    this.shortName = shortName;
+    this.longName = longName;
+    this.topic = topic;
+    this.description = description;
+    this.relase_date = date;
+  }
+
+  public SResult(SResult sr) {
+    for (int i = 0; i < rlist.length; i++) {
+      set(this, rlist[i], get(sr, rlist[i]));
+    }
+  }
+
+  /**
+   * Method of getting export header
+   *
+   * @param delimiter the delimiter used to separate strings
+   * @return header
+   */
+  public static String getHeader(String delimiter) {
+    String str = "";
+    for (int i = 0; i < rlist.length; i++) {
+      str += rlist[i] + delimiter;
+    }
+    str = str + "label" + "\n";
+    return "ShortName" + delimiter + "below" + delimiter + str;
+  }
+
+  /**
+   * Method of get a search results as string
+   *
+   * @param delimiter the delimiter used to separate strings
+   * @return search result as string
+   */
+  public String toString(String delimiter) {
+    String str = "";
+    for (int i = 0; i < rlist.length; i++) {
+      double score = get(this, rlist[i]);
+      str += score + delimiter;
+    }
+    str = str + label + "\n";
+    return shortName + delimiter + below + delimiter + str;
+  }
+
+  /**
+   * Generic setter method
+   *
+   * @param object     instance of SResult
+   * @param fieldName  field name that needs to be set on
+   * @param fieldValue field value that needs to be set to
+   * @return 1 means success, and 0 otherwise
+   */
+  public static boolean set(Object object, String fieldName, Object fieldValue) {
+    Class<?> clazz = object.getClass();
+    while (clazz != null) {
+      try {
+        Field field = clazz.getDeclaredField(fieldName);
+        field.setAccessible(true);
+        field.set(object, fieldValue);
+        return true;
+      } catch (NoSuchFieldException e) {
+        clazz = clazz.getSuperclass();
+      } catch (Exception e) {
+        throw new IllegalStateException(e);
+      }
+    }
+    return false;
+  }
+
+  /**
+   * Generic getter method
+   *
+   * @param object    instance of SResult
+   * @param fieldName field name of search result
+   * @param <V>       data type
+   * @return the value of the filed in the object
+   */
+  @SuppressWarnings("unchecked")
+  public static <V> V get(Object object, String fieldName) {
+    Class<?> clazz = object.getClass();
+    while (clazz != null) {
+      try {
+        Field field = clazz.getDeclaredField(fieldName);
+        field.setAccessible(true);
+        return (V) field.get(object);
+      } catch (NoSuchFieldException e) {
+        clazz = clazz.getSuperclass();
+      } catch (Exception e) {
+        throw new IllegalStateException(e);
+      }
+    }
+    return null;
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/package-info.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/package-info.java b/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/package-info.java
new file mode 100644
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--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/ssearch/structure/package-info.java
@@ -0,0 +1,17 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+/**
+ * This package includes data structure needed for ranking process
+ */
+package gov.nasa.jpl.mudrod.ssearch.structure;
\ No newline at end of file

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/ESTransportClient.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/ESTransportClient.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/ESTransportClient.java
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+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package gov.nasa.jpl.mudrod.utils;
+
+import org.elasticsearch.client.transport.TransportClient;
+import org.elasticsearch.common.settings.Settings;
+import org.elasticsearch.index.reindex.ReindexPlugin;
+import org.elasticsearch.percolator.PercolatorPlugin;
+import org.elasticsearch.plugins.Plugin;
+import org.elasticsearch.script.mustache.MustachePlugin;
+import org.elasticsearch.transport.Netty3Plugin;
+
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.Collections;
+
+/**
+ * A builder to create an instance of {@link TransportClient} This class
+ * pre-installs the {@link Netty3Plugin}, for the client. These plugins are all
+ * elasticsearch core modules required.
+ */
+@SuppressWarnings({ "unchecked", "varargs" })
+public class ESTransportClient extends TransportClient {
+
+  private static final Collection<Class<? extends Plugin>> PRE_INSTALLED_PLUGINS = Collections
+      .unmodifiableList(Arrays.asList(ReindexPlugin.class, PercolatorPlugin.class, MustachePlugin.class, Netty3Plugin.class));
+
+  @SafeVarargs
+  public ESTransportClient(Settings settings, Class<? extends Plugin>... plugins) {
+    this(settings, Arrays.asList(plugins));
+  }
+
+  public ESTransportClient(Settings settings, Collection<Class<? extends Plugin>> plugins) {
+    super(settings, Settings.EMPTY, addPlugins(plugins, PRE_INSTALLED_PLUGINS), null);
+
+  }
+
+  @Override
+  public void close() {
+    super.close();
+  }
+
+}
\ No newline at end of file

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/HttpRequest.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/HttpRequest.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/HttpRequest.java
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+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/HttpRequest.java
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+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.BufferedReader;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.net.HttpURLConnection;
+import java.net.URL;
+
+/**
+ * ClassName: HttpRequest
+ * Function: Http request tool.
+ */
+public class HttpRequest {
+
+  private static final Logger LOG = LoggerFactory.getLogger(HttpRequest.class);
+
+  public HttpRequest() {
+  }
+
+  public String getRequest(String requestUrl) {
+    String line = null;
+    try {
+      URL url = new URL(requestUrl);
+
+      HttpURLConnection connection = (HttpURLConnection) url.openConnection();
+      connection.setDoOutput(true);
+
+      connection.setConnectTimeout(5000);
+      connection.setReadTimeout(5000);
+      int code = connection.getResponseCode();
+      if (code != HttpURLConnection.HTTP_OK) {
+        line = "{\"exception\":\"Service failed\"}";
+        LOG.info(line);
+      } else {
+        InputStream content = connection.getInputStream();
+        BufferedReader in = new BufferedReader(new InputStreamReader(content));
+        line = in.readLine();
+      }
+    } catch (Exception e) {
+      line = "{\"exception\":\"No service was found\"}";
+      LOG.error(line);
+    }
+    return line;
+  }
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/LabeledRowMatrix.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/LabeledRowMatrix.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/LabeledRowMatrix.java
new file mode 100644
index 0000000..d1d144b
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+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/LabeledRowMatrix.java
@@ -0,0 +1,38 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import org.apache.spark.mllib.linalg.distributed.RowMatrix;
+
+import java.util.List;
+
+/**
+ * ClassName: LabeledRowMatrix
+ * Function: LabeledRowMatrix strut.
+ */
+public class LabeledRowMatrix {
+
+  // words: matrix row titles
+  public List<String> rowkeys;
+  // docs: matrix column titles
+  public List<String> colkeys;
+  // wordDocMatrix: a matrix in which each row is corresponding to a term and
+  // each column is a doc.
+  public RowMatrix rowMatrix;
+
+  public LabeledRowMatrix() {
+    // TODO Auto-generated constructor stub
+  }
+
+}
\ No newline at end of file

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/LinkageTriple.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/LinkageTriple.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/LinkageTriple.java
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+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/LinkageTriple.java
@@ -0,0 +1,192 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import gov.nasa.jpl.mudrod.driver.ESDriver;
+import org.elasticsearch.action.index.IndexRequest;
+import org.elasticsearch.action.search.SearchRequestBuilder;
+import org.elasticsearch.action.search.SearchResponse;
+import org.elasticsearch.action.update.UpdateRequest;
+import org.elasticsearch.common.unit.TimeValue;
+import org.elasticsearch.common.xcontent.XContentBuilder;
+import org.elasticsearch.index.query.QueryBuilders;
+import org.elasticsearch.search.SearchHit;
+import org.elasticsearch.search.aggregations.AggregationBuilders;
+import org.elasticsearch.search.aggregations.bucket.terms.Terms;
+import org.elasticsearch.search.sort.SortOrder;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.text.DecimalFormat;
+import java.util.List;
+import java.util.Map;
+
+import static org.elasticsearch.common.xcontent.XContentFactory.jsonBuilder;
+
+/**
+ * ClassName: LinkageTriple Function: Vocabulary linkage operations
+ */
+public class LinkageTriple implements Serializable {
+
+  /**
+   *
+   */
+  private static final long serialVersionUID = 1L;
+  // keyAId: ID of term A
+  public long keyAId;
+  // keyBId: ID of term B
+  public long keyBId;
+  // weight: The relationship between term A and Term B
+  public double weight;
+  // keyA: TermA
+  public String keyA;
+  // keyB: TermB
+  public String keyB;
+  // df: Format number
+  public static DecimalFormat df = new DecimalFormat("#.00");
+
+  public LinkageTriple() {
+    // TODO Auto-generated constructor stub
+  }
+
+  /**
+   * TODO Output linkage triples in string format.
+   *
+   * @see java.lang.Object#toString()
+   */
+  @Override
+  public String toString() {
+    return keyA + "," + keyB + ":" + weight;
+  }
+
+  public static void insertTriples(ESDriver es, List<LinkageTriple> triples, String index, String type) throws IOException {
+    LinkageTriple.insertTriples(es, triples, index, type, false, false);
+  }
+
+  public static void insertTriples(ESDriver es, List<LinkageTriple> triples, String index, String type, Boolean bTriple, boolean bSymmetry) throws IOException {
+    es.deleteType(index, type);
+    if (bTriple) {
+      LinkageTriple.addMapping(es, index, type);
+    }
+
+    if (triples == null) {
+      return;
+    }
+
+    es.createBulkProcessor();
+    int size = triples.size();
+    for (int i = 0; i < size; i++) {
+
+      XContentBuilder jsonBuilder = jsonBuilder().startObject();
+      if (bTriple) {
+
+        jsonBuilder.field("concept_A", triples.get(i).keyA);
+        jsonBuilder.field("concept_B", triples.get(i).keyB);
+
+      } else {
+        jsonBuilder.field("keywords", triples.get(i).keyA + "," + triples.get(i).keyB);
+      }
+
+      jsonBuilder.field("weight", Double.parseDouble(df.format(triples.get(i).weight)));
+      jsonBuilder.endObject();
+
+      IndexRequest ir = new IndexRequest(index, type).source(jsonBuilder);
+      es.getBulkProcessor().add(ir);
+
+      if (bTriple && bSymmetry) {
+        XContentBuilder symmetryJsonBuilder = jsonBuilder().startObject();
+        symmetryJsonBuilder.field("concept_A", triples.get(i).keyB);
+        symmetryJsonBuilder.field("concept_B", triples.get(i).keyA);
+
+        symmetryJsonBuilder.field("weight", Double.parseDouble(df.format(triples.get(i).weight)));
+
+        symmetryJsonBuilder.endObject();
+
+        IndexRequest symmetryir = new IndexRequest(index, type).source(symmetryJsonBuilder);
+        es.getBulkProcessor().add(symmetryir);
+      }
+    }
+    es.destroyBulkProcessor();
+  }
+
+  public static void addMapping(ESDriver es, String index, String type) {
+    XContentBuilder Mapping;
+    try {
+      Mapping = jsonBuilder().startObject().startObject(type).startObject("properties").startObject("concept_A").field("type", "string").field("index", "not_analyzed").endObject()
+          .startObject("concept_B").field("type", "string").field("index", "not_analyzed").endObject()
+
+          .endObject().endObject().endObject();
+
+      es.getClient().admin().indices().preparePutMapping(index).setType(type).setSource(Mapping).execute().actionGet();
+    } catch (IOException e) {
+      e.printStackTrace();
+    }
+  }
+
+  public static void standardTriples(ESDriver es, String index, String type) throws IOException {
+    es.createBulkProcessor();
+
+    SearchResponse sr = es.getClient().prepareSearch(index).setTypes(type).setQuery(QueryBuilders.matchAllQuery()).setSize(0)
+        .addAggregation(AggregationBuilders.terms("concepts").field("concept_A").size(0)).execute().actionGet();
+    Terms concepts = sr.getAggregations().get("concepts");
+
+    for (Terms.Bucket entry : concepts.getBuckets()) {
+      String concept = (String) entry.getKey();
+      double maxSim = LinkageTriple.getMaxSimilarity(es, index, type, concept);
+      if (maxSim == 1.0) {
+        continue;
+      }
+
+      SearchResponse scrollResp = es.getClient().prepareSearch(index).setTypes(type).setScroll(new TimeValue(60000)).setQuery(QueryBuilders.termQuery("concept_A", concept))
+          .addSort("weight", SortOrder.DESC).setSize(100).execute().actionGet();
+
+      while (true) {
+        for (SearchHit hit : scrollResp.getHits().getHits()) {
+          Map<String, Object> metadata = hit.getSource();
+          double sim = (double) metadata.get("weight");
+          double newSim = sim / maxSim;
+          UpdateRequest ur = es.generateUpdateRequest(index, type, hit.getId(), "weight", Double.parseDouble(df.format(newSim)));
+          es.getBulkProcessor().add(ur);
+        }
+
+        scrollResp = es.getClient().prepareSearchScroll(scrollResp.getScrollId()).setScroll(new TimeValue(600000)).execute().actionGet();
+        if (scrollResp.getHits().getHits().length == 0) {
+          break;
+        }
+      }
+    }
+
+    es.destroyBulkProcessor();
+  }
+
+  private static double getMaxSimilarity(ESDriver es, String index, String type, String concept) {
+
+    double maxSim = 1.0;
+    SearchRequestBuilder builder = es.getClient().prepareSearch(index).setTypes(type).setQuery(QueryBuilders.termQuery("concept_A", concept)).addSort("weight", SortOrder.DESC).setSize(1);
+
+    SearchResponse usrhis = builder.execute().actionGet();
+    SearchHit[] hits = usrhis.getHits().getHits();
+    if (hits.length == 1) {
+      SearchHit hit = hits[0];
+      Map<String, Object> result = hit.getSource();
+      maxSim = (double) result.get("weight");
+    }
+
+    if (maxSim == 0.0) {
+      maxSim = 1.0;
+    }
+
+    return maxSim;
+  }
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/MatrixUtil.java
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diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/MatrixUtil.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/MatrixUtil.java
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+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/MatrixUtil.java
@@ -0,0 +1,488 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import gov.nasa.jpl.mudrod.driver.SparkDriver;
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.api.java.Optional;
+import org.apache.spark.api.java.function.*;
+import org.apache.spark.mllib.feature.IDF;
+import org.apache.spark.mllib.feature.IDFModel;
+import org.apache.spark.mllib.linalg.*;
+import org.apache.spark.mllib.linalg.distributed.IndexedRow;
+import org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix;
+import org.apache.spark.mllib.linalg.distributed.RowMatrix;
+import scala.Tuple2;
+
+import java.io.BufferedWriter;
+import java.io.File;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Iterator;
+import java.util.List;
+import java.util.stream.Stream;
+
+/**
+ * Matrix utility tool
+ */
+public class MatrixUtil {
+
+  private MatrixUtil() {
+  }
+
+  /**
+   * buildSVDMatrix: Generate SVD matrix from TF-IDF matrix. Please make sure
+   * the TF-IDF matrix has been already built from the original documents.
+   *
+   * @param tfidfMatrix,
+   *          each row is a term and each column is a document name and each
+   *          cell is the TF-IDF value of the term in the corresponding
+   *          document.
+   * @param dimension
+   *          Column number of the SVD matrix
+   * @return RowMatrix, each row is a term and each column is a dimension in the
+   *         feature space, each cell is value of the term in the corresponding
+   *         dimension.
+   */
+  public static RowMatrix buildSVDMatrix(RowMatrix tfidfMatrix, int dimension) {
+    int matrixCol = (int) tfidfMatrix.numCols();
+    if (matrixCol < dimension) {
+      dimension = matrixCol;
+    }
+
+    SingularValueDecomposition<RowMatrix, Matrix> svd = tfidfMatrix.computeSVD(dimension, true, 1.0E-9d);
+    RowMatrix u = svd.U();
+    Vector s = svd.s();
+    return u.multiply(Matrices.diag(s));
+  }
+
+  /**
+   * buildSVDMatrix: Generate SVD matrix from Vector RDD.
+   *
+   * @param vecRDD
+   *          vectors of terms in feature space
+   * @param dimension
+   *          Column number of the SVD matrix
+   * @return RowMatrix, each row is a term and each column is a dimension in the
+   *         feature space, each cell is value of the term in the corresponding
+   *         dimension.
+   */
+  public static RowMatrix buildSVDMatrix(JavaRDD<Vector> vecRDD, int dimension) {
+    RowMatrix tfidfMatrix = new RowMatrix(vecRDD.rdd());
+    SingularValueDecomposition<RowMatrix, Matrix> svd = tfidfMatrix.computeSVD(dimension, true, 1.0E-9d);
+    RowMatrix u = svd.U();
+    Vector s = svd.s();
+    return u.multiply(Matrices.diag(s));
+  }
+
+  /**
+   * Create TF-IDF matrix from word-doc matrix.
+   *
+   * @param wordDocMatrix,
+   *          each row is a term, each column is a document name and each cell
+   *          is number of the term in the corresponding document.
+   * @return RowMatrix, each row is a term and each column is a document name
+   *         and each cell is the TF-IDF value of the term in the corresponding
+   *         document.
+   */
+  public static RowMatrix createTFIDFMatrix(RowMatrix wordDocMatrix) {
+    JavaRDD<Vector> newcountRDD = wordDocMatrix.rows().toJavaRDD();
+    IDFModel idfModel = new IDF().fit(newcountRDD);
+    JavaRDD<Vector> idf = idfModel.transform(newcountRDD);
+    return new RowMatrix(idf.rdd());
+  }
+
+  /**
+   * Create matrix from doc-terms JavaPairRDD.
+   *
+   * @param uniqueDocRDD
+   *          doc-terms JavaPairRDD, in which each key is a doc name, and value
+   *          is term list extracted from that doc
+   * @return LabeledRowMatrix {@link LabeledRowMatrix}
+   */
+  public static LabeledRowMatrix createWordDocMatrix(JavaPairRDD<String, List<String>> uniqueDocRDD) {
+    // Index documents with unique IDs
+    JavaPairRDD<List<String>, Long> corpus = uniqueDocRDD.values().zipWithIndex();
+    // cal word-doc numbers
+    JavaPairRDD<Tuple2<String, Long>, Double> worddocNumRDD = corpus.flatMapToPair(new PairFlatMapFunction<Tuple2<List<String>, Long>, Tuple2<String, Long>, Double>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Iterator<Tuple2<Tuple2<String, Long>, Double>> call(Tuple2<List<String>, Long> docwords) throws Exception {
+        List<Tuple2<Tuple2<String, Long>, Double>> pairs = new ArrayList<>();
+        List<String> words = docwords._1;
+        int n = words.size();
+        for (int i = 0; i < n; i++) {
+          Tuple2<String, Long> worddoc = new Tuple2<>(words.get(i), docwords._2);
+          pairs.add(new Tuple2<Tuple2<String, Long>, Double>(worddoc, 1.0));
+        }
+        return pairs.iterator();
+      }
+    }).reduceByKey(new Function2<Double, Double, Double>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Double call(Double first, Double second) throws Exception {
+        return first + second;
+      }
+    });
+    // cal word doc-numbers
+    JavaPairRDD<String, Tuple2<List<Long>, List<Double>>> wordDocnumRDD = worddocNumRDD
+        .mapToPair(new PairFunction<Tuple2<Tuple2<String, Long>, Double>, String, Tuple2<List<Long>, List<Double>>>() {
+          /**
+           *
+           */
+          private static final long serialVersionUID = 1L;
+
+          @Override
+          public Tuple2<String, Tuple2<List<Long>, List<Double>>> call(Tuple2<Tuple2<String, Long>, Double> worddocNum) throws Exception {
+            List<Long> docs = new ArrayList<>();
+            docs.add(worddocNum._1._2);
+            List<Double> nums = new ArrayList<>();
+            nums.add(worddocNum._2);
+            Tuple2<List<Long>, List<Double>> docmums = new Tuple2<>(docs, nums);
+            return new Tuple2<>(worddocNum._1._1, docmums);
+          }
+        });
+    // trans to vector
+    final int corporsize = (int) uniqueDocRDD.keys().count();
+    JavaPairRDD<String, Vector> wordVectorRDD = wordDocnumRDD.reduceByKey(new Function2<Tuple2<List<Long>, List<Double>>, Tuple2<List<Long>, List<Double>>, Tuple2<List<Long>, List<Double>>>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<List<Long>, List<Double>> call(Tuple2<List<Long>, List<Double>> arg0, Tuple2<List<Long>, List<Double>> arg1) throws Exception {
+        arg0._1.addAll(arg1._1);
+        arg0._2.addAll(arg1._2);
+        return new Tuple2<>(arg0._1, arg0._2);
+      }
+    }).mapToPair(new PairFunction<Tuple2<String, Tuple2<List<Long>, List<Double>>>, String, Vector>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<String, Vector> call(Tuple2<String, Tuple2<List<Long>, List<Double>>> arg0) throws Exception {
+        int docsize = arg0._2._1.size();
+        int[] intArray = new int[docsize];
+        double[] doubleArray = new double[docsize];
+        for (int i = 0; i < docsize; i++) {
+          intArray[i] = arg0._2._1.get(i).intValue();
+          doubleArray[i] = arg0._2._2.get(i).intValue();
+        }
+        Vector sv = Vectors.sparse(corporsize, intArray, doubleArray);
+        return new Tuple2<>(arg0._1, sv);
+      }
+    });
+
+    RowMatrix wordDocMatrix = new RowMatrix(wordVectorRDD.values().rdd());
+
+    LabeledRowMatrix labeledRowMatrix = new LabeledRowMatrix();
+    labeledRowMatrix.rowMatrix = wordDocMatrix;
+    labeledRowMatrix.rowkeys = wordVectorRDD.keys().collect();
+    labeledRowMatrix.colkeys = uniqueDocRDD.keys().collect();
+    return labeledRowMatrix;
+  }
+
+  public static LabeledRowMatrix createDocWordMatrix(JavaPairRDD<String, List<String>> uniqueDocRDD, JavaSparkContext sc) {
+    // Index word with unique IDs
+    JavaPairRDD<String, Long> wordIDRDD = uniqueDocRDD.values().flatMap(new FlatMapFunction<List<String>, String>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Iterator<String> call(List<String> arg0) throws Exception {
+        return arg0.iterator();
+      }
+    }).distinct().zipWithIndex();
+
+    //
+    JavaPairRDD<Tuple2<String, String>, Double> docwordNumRDD = uniqueDocRDD.flatMapToPair(new PairFlatMapFunction<Tuple2<String, List<String>>, Tuple2<String, String>, Double>() {
+
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Iterator<Tuple2<Tuple2<String, String>, Double>> call(Tuple2<String, List<String>> docwords) throws Exception {
+        List<Tuple2<Tuple2<String, String>, Double>> pairs = new ArrayList<>();
+        List<String> words = docwords._2;
+        int n = words.size();
+        for (int i = 0; i < n; i++) {
+          Tuple2<String, String> worddoc = new Tuple2<>(docwords._1, words.get(i));
+          pairs.add(new Tuple2<Tuple2<String, String>, Double>(worddoc, 1.0));
+        }
+        return pairs.iterator();
+      }
+    }).reduceByKey(new Function2<Double, Double, Double>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Double call(Double first, Double second) throws Exception {
+        return first + second;
+      }
+    });
+
+    //
+    JavaPairRDD<String, Tuple2<String, Double>> wordDocnumRDD = docwordNumRDD.mapToPair(new PairFunction<Tuple2<Tuple2<String, String>, Double>, String, Tuple2<String, Double>>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<String, Tuple2<String, Double>> call(Tuple2<Tuple2<String, String>, Double> arg0) throws Exception {
+
+        Tuple2<String, Double> wordmums = new Tuple2<>(arg0._1._1, arg0._2);
+        return new Tuple2<>(arg0._1._2, wordmums);
+      }
+    });
+
+    //
+
+    JavaPairRDD<String, Tuple2<Tuple2<String, Double>, Optional<Long>>> testRDD = wordDocnumRDD.leftOuterJoin(wordIDRDD);
+
+    int wordsize = (int) wordIDRDD.count();
+    JavaPairRDD<String, Vector> docVectorRDD = testRDD.mapToPair(new PairFunction<Tuple2<String, Tuple2<Tuple2<String, Double>, Optional<Long>>>, String, Tuple2<List<Long>, List<Double>>>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<String, Tuple2<List<Long>, List<Double>>> call(Tuple2<String, Tuple2<Tuple2<String, Double>, Optional<Long>>> arg0) throws Exception {
+        Optional<Long> oid = arg0._2._2;
+        Long wordId = (long) 0;
+        if (oid.isPresent()) {
+          wordId = oid.get();
+        }
+
+        List<Long> word = new ArrayList<>();
+        word.add(wordId);
+
+        List<Double> count = new ArrayList<>();
+        count.add(arg0._2._1._2);
+
+        Tuple2<List<Long>, List<Double>> wordcount = new Tuple2<>(word, count);
+
+        return new Tuple2<>(arg0._2._1._1, wordcount);
+      }
+
+    }).reduceByKey(new Function2<Tuple2<List<Long>, List<Double>>, Tuple2<List<Long>, List<Double>>, Tuple2<List<Long>, List<Double>>>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<List<Long>, List<Double>> call(Tuple2<List<Long>, List<Double>> arg0, Tuple2<List<Long>, List<Double>> arg1) throws Exception {
+        arg0._1.addAll(arg1._1);
+        arg0._2.addAll(arg1._2);
+        return new Tuple2<>(arg0._1, arg0._2);
+      }
+    }).mapToPair(new PairFunction<Tuple2<String, Tuple2<List<Long>, List<Double>>>, String, Vector>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<String, Vector> call(Tuple2<String, Tuple2<List<Long>, List<Double>>> arg0) throws Exception {
+        int docsize = arg0._2._1.size();
+        int[] intArray = new int[docsize];
+        double[] doubleArray = new double[docsize];
+        for (int i = 0; i < docsize; i++) {
+          intArray[i] = arg0._2._1.get(i).intValue();
+          doubleArray[i] = arg0._2._2.get(i).intValue();
+        }
+        Vector sv = Vectors.sparse(wordsize, intArray, doubleArray);
+        return new Tuple2<>(arg0._1, sv);
+      }
+    });
+
+    RowMatrix docwordMatrix = new RowMatrix(docVectorRDD.values().rdd());
+
+    LabeledRowMatrix labeledRowMatrix = new LabeledRowMatrix();
+    labeledRowMatrix.rowMatrix = docwordMatrix;
+    labeledRowMatrix.rowkeys = docVectorRDD.keys().collect();
+    labeledRowMatrix.colkeys = wordIDRDD.keys().collect();
+
+    return labeledRowMatrix;
+  }
+
+  /**
+   * loadVectorFromCSV: Load term vector from csv file.
+   *
+   * @param spark
+   *          spark instance
+   * @param csvFileName
+   *          csv matrix file
+   * @param skipNum
+   *          the numbers of rows which should be skipped Ignore the top skip
+   *          number rows of the csv file
+   * @return JavaPairRDD, each key is a term, and value is the vector of the
+   *         term in feature space.
+   */
+  public static JavaPairRDD<String, Vector> loadVectorFromCSV(SparkDriver spark, String csvFileName, int skipNum) {
+    // skip the first line (header), important!
+    JavaRDD<String> importRDD = spark.sc.textFile(csvFileName);
+    JavaPairRDD<String, Long> importIdRDD = importRDD.zipWithIndex().filter(new Function<Tuple2<String, Long>, Boolean>() {
+      /** */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Boolean call(Tuple2<String, Long> v1) throws Exception {
+        if (v1._2 > (skipNum - 1)) {
+          return true;
+        }
+        return false;
+      }
+    });
+
+    if (importIdRDD.count() == 0) {
+      return null;
+    }
+
+    return importIdRDD.mapToPair(new PairFunction<Tuple2<String, Long>, String, Vector>() {
+      /** */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<String, Vector> call(Tuple2<String, Long> t) throws Exception {
+        String[] fields = t._1.split(",");
+        String word = fields[0];
+        int fieldsize = fields.length;
+        int nStart = 1;
+        int nEnd = fieldsize - 1;
+        if (fieldsize < 2) {
+          nStart = 0;
+          nEnd = 0;
+        }
+        String[] numfields = Arrays.copyOfRange(fields, nStart, nEnd);
+
+        double[] nums = Stream.of(numfields).mapToDouble(Double::parseDouble).toArray();
+        Vector vec = Vectors.dense(nums);
+        return new Tuple2<>(word, vec);
+      }
+    });
+  }
+
+  /**
+   * Convert vectorRDD to indexed row matrix.
+   *
+   * @param vecs
+   *          Vector RDD
+   * @return IndexedRowMatrix
+   */
+  public static IndexedRowMatrix buildIndexRowMatrix(JavaRDD<Vector> vecs) {
+    JavaRDD<IndexedRow> indexrows = vecs.zipWithIndex().map(new Function<Tuple2<Vector, Long>, IndexedRow>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public IndexedRow call(Tuple2<Vector, Long> docId) {
+        return new IndexedRow(docId._2, docId._1);
+      }
+    });
+    return new IndexedRowMatrix(indexrows.rdd());
+  }
+
+  /**
+   * Transpose matrix
+   *
+   * @param indexedMatrix
+   *          spark indexed matrix
+   * @return rowmatrix, each row is corresponding to the column in the original
+   *         matrix and vice versa
+   */
+  public static RowMatrix transposeMatrix(IndexedRowMatrix indexedMatrix) {
+    return indexedMatrix.toCoordinateMatrix().transpose().toRowMatrix();
+  }
+
+  /**
+   * Output matrix to a CSV file.
+   *
+   * @param matrix
+   *          spark row matrix
+   * @param rowKeys
+   *          matrix row names
+   * @param colKeys
+   *          matrix coloum names
+   * @param fileName
+   *          csv file name
+   */
+  public static void exportToCSV(RowMatrix matrix, List<String> rowKeys, List<String> colKeys, String fileName) {
+
+    if (matrix.rows().isEmpty()) {
+      return;
+    }
+
+    int rownum = (int) matrix.numRows();
+    int colnum = (int) matrix.numCols();
+    List<Vector> rows = matrix.rows().toJavaRDD().collect();
+
+    File file = new File(fileName);
+    if (file.exists()) {
+      file.delete();
+    }
+    try {
+      file.createNewFile();
+      FileWriter fw = new FileWriter(file.getAbsoluteFile());
+      BufferedWriter bw = new BufferedWriter(fw);
+      String coltitle = " Num" + ",";
+      for (int j = 0; j < colnum; j++) {
+        coltitle += "\"" + colKeys.get(j) + "\",";
+      }
+      coltitle = coltitle.substring(0, coltitle.length() - 1);
+      bw.write(coltitle + "\n");
+
+      for (int i = 0; i < rownum; i++) {
+        double[] rowvlaue = rows.get(i).toArray();
+        String row = rowKeys.get(i) + ",";
+        for (int j = 0; j < colnum; j++) {
+          row += rowvlaue[j] + ",";
+        }
+        row = row.substring(0, row.length() - 1);
+        bw.write(row + "\n");
+      }
+
+      bw.close();
+
+    } catch (IOException e) {
+      e.printStackTrace();
+
+    }
+  }
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/RDDUtil.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/RDDUtil.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/RDDUtil.java
new file mode 100644
index 0000000..3fc45f4
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/RDDUtil.java
@@ -0,0 +1,53 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.function.FlatMapFunction;
+
+import java.util.Iterator;
+import java.util.List;
+
+/**
+ * ClassName: RDDUtil Function: Mudrod Spark RDD common methods
+ */
+public class RDDUtil {
+
+  public RDDUtil() {
+  }
+
+  /**
+   * getAllWordsInDoc: Extracted all unique terms from all docs.
+   *
+   * @param docwordRDD Pair RDD, each key is a doc, and value is term list extracted from
+   *                   that doc.
+   * @return unique term list
+   */
+  public static JavaRDD<String> getAllWordsInDoc(JavaPairRDD<String, List<String>> docwordRDD) {
+    JavaRDD<String> wordRDD = docwordRDD.values().flatMap(new FlatMapFunction<List<String>, String>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Iterator<String> call(List<String> list) {
+        return list.iterator();
+      }
+    }).distinct();
+
+    return wordRDD;
+  }
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/SVDUtil.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/SVDUtil.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/SVDUtil.java
new file mode 100644
index 0000000..1982996
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/SVDUtil.java
@@ -0,0 +1,118 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import gov.nasa.jpl.mudrod.discoveryengine.MudrodAbstract;
+import gov.nasa.jpl.mudrod.driver.ESDriver;
+import gov.nasa.jpl.mudrod.driver.SparkDriver;
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.mllib.linalg.distributed.CoordinateMatrix;
+import org.apache.spark.mllib.linalg.distributed.RowMatrix;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Properties;
+
+/**
+ * Singular value decomposition
+ */
+public class SVDUtil extends MudrodAbstract {
+
+  /**
+   *
+   */
+  private static final long serialVersionUID = 1L;
+  // wordRDD: terms extracted from all documents
+  JavaRDD<String> wordRDD;
+  // svdMatrix: svd matrix
+  private RowMatrix svdMatrix;
+  // simMatrix: similarity matrix
+  private CoordinateMatrix simMatrix;
+
+  /**
+   * Creates a new instance of SVDUtil.
+   *
+   * @param config the Mudrod configuration
+   * @param es     the Elasticsearch drive
+   * @param spark  the spark driver
+   */
+  public SVDUtil(Properties config, ESDriver es, SparkDriver spark) {
+    super(config, es, spark);
+  }
+
+  /**
+   * Build SVD matrix from docment-terms pairs.
+   *
+   * @param docwordRDD    JavaPairRDD, key is short name of data set and values are terms in
+   *                      the corresponding data set
+   * @param svdDimension: Dimension of matrix after singular value decomposition
+   * @return row matrix
+   */
+  public RowMatrix buildSVDMatrix(JavaPairRDD<String, List<String>> docwordRDD, int svdDimension) {
+
+    RowMatrix svdMatrix = null;
+    LabeledRowMatrix wordDocMatrix = MatrixUtil.createWordDocMatrix(docwordRDD);
+    RowMatrix ifIdfMatrix = MatrixUtil.createTFIDFMatrix(wordDocMatrix.rowMatrix);
+    svdMatrix = MatrixUtil.buildSVDMatrix(ifIdfMatrix, svdDimension);
+    this.svdMatrix = svdMatrix;
+    this.wordRDD = RDDUtil.getAllWordsInDoc(docwordRDD);
+    return svdMatrix;
+  }
+
+  /**
+   * Build svd matrix from CSV file.
+   *
+   * @param tfidfCSVfile  tf-idf matrix csv file
+   * @param svdDimension: Dimension of matrix after singular value decomposition
+   * @return row matrix
+   */
+  public RowMatrix buildSVDMatrix(String tfidfCSVfile, int svdDimension) {
+    RowMatrix svdMatrix = null;
+    JavaPairRDD<String, Vector> tfidfRDD = MatrixUtil.loadVectorFromCSV(spark, tfidfCSVfile, 2);
+    JavaRDD<Vector> vectorRDD = tfidfRDD.values();
+
+    svdMatrix = MatrixUtil.buildSVDMatrix(vectorRDD, svdDimension);
+    this.svdMatrix = svdMatrix;
+
+    this.wordRDD = tfidfRDD.keys();
+
+    return svdMatrix;
+  }
+
+  /**
+   * Calculate similarity
+   */
+  public void calSimilarity() {
+    CoordinateMatrix simMatrix = SimilarityUtil.calculateSimilarityFromMatrix(svdMatrix);
+    this.simMatrix = simMatrix;
+  }
+
+  /**
+   * Insert linkage triples to elasticsearch
+   *
+   * @param index index name
+   * @param type  linkage triple name
+   */
+  public void insertLinkageToES(String index, String type) {
+    List<LinkageTriple> triples = SimilarityUtil.matrixToTriples(wordRDD, simMatrix);
+    try {
+      LinkageTriple.insertTriples(es, triples, index, type);
+    } catch (IOException e) {
+      e.printStackTrace();
+    }
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/SimilarityUtil.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/SimilarityUtil.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/SimilarityUtil.java
new file mode 100644
index 0000000..8ae9770
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/SimilarityUtil.java
@@ -0,0 +1,277 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you
+ * may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.utils;
+
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.Optional;
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.mllib.linalg.distributed.CoordinateMatrix;
+import org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix;
+import org.apache.spark.mllib.linalg.distributed.MatrixEntry;
+import org.apache.spark.mllib.linalg.distributed.RowMatrix;
+import scala.Tuple2;
+
+import java.util.List;
+
+/**
+ * Similarity and distrance calculation utilities
+ */
+public class SimilarityUtil {
+
+  public static final int SIM_COSINE = 3;
+  public static final int SIM_HELLINGER = 2;
+  public static final int SIM_PEARSON = 1;
+  /**
+   * CalSimilarityFromMatrix: Calculate term similarity from matrix.
+   *
+   * @param svdMatrix. Each row is corresponding to a term, and each column is
+   *                   corresponding to a dimension of feature
+   * @return CoordinateMatrix, each row is corresponding to a term, and each
+   * column is also a term, the cell value is the similarity between the
+   * two terms
+   */
+  public static CoordinateMatrix calculateSimilarityFromMatrix(RowMatrix svdMatrix) {
+    JavaRDD<Vector> vecs = svdMatrix.rows().toJavaRDD();
+    return SimilarityUtil.calculateSimilarityFromVector(vecs);
+  }
+
+  /**
+   * CalSimilarityFromVector:Calculate term similarity from vector.
+   *
+   * @param vecs Each vector is corresponding to a term in the feature space.
+   * @return CoordinateMatrix, each row is corresponding to a term, and each
+   * column is also a term, the cell value is the similarity between the
+   * two terms
+   */
+  public static CoordinateMatrix calculateSimilarityFromVector(JavaRDD<Vector> vecs) {
+    IndexedRowMatrix indexedMatrix = MatrixUtil.buildIndexRowMatrix(vecs);
+    RowMatrix transposeMatrix = MatrixUtil.transposeMatrix(indexedMatrix);
+    return transposeMatrix.columnSimilarities();
+  }
+
+  /**
+   * Calculate term similarity from vector.
+   *
+   * @param importRDD the {@link org.apache.spark.api.java.JavaPairRDD}
+   *                  data structure containing the vectors.
+   * @param simType   the similarity calculation to execute e.g. 
+   * <ul>
+   * <li>{@link gov.nasa.jpl.mudrod.utils.SimilarityUtil#SIM_COSINE} - 3,</li>
+   * <li>{@link gov.nasa.jpl.mudrod.utils.SimilarityUtil#SIM_HELLINGER} - 2,</li>
+   * <li>{@link gov.nasa.jpl.mudrod.utils.SimilarityUtil#SIM_PEARSON} - 1</li>
+   * </ul>
+   * @return a new {@link org.apache.spark.api.java.JavaPairRDD}
+   */
+  public static JavaRDD<LinkageTriple> calculateSimilarityFromVector(JavaPairRDD<String, Vector> importRDD, int simType) {
+    JavaRDD<Tuple2<String, Vector>> importRDD1 = importRDD.map(f -> new Tuple2<String, Vector>(f._1, f._2));
+    JavaPairRDD<Tuple2<String, Vector>, Tuple2<String, Vector>> cartesianRDD = importRDD1.cartesian(importRDD1);
+
+    return cartesianRDD.map(new Function<Tuple2<Tuple2<String, Vector>, Tuple2<String, Vector>>, LinkageTriple>() {
+
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public LinkageTriple call(Tuple2<Tuple2<String, Vector>, Tuple2<String, Vector>> arg) {
+        String keyA = arg._1._1;
+        String keyB = arg._2._1;
+
+        if (keyA.equals(keyB)) {
+          return null;
+        }
+
+        Vector vecA = arg._1._2;
+        Vector vecB = arg._2._2;
+        Double weight = 0.0;
+
+        if (simType == SimilarityUtil.SIM_PEARSON) {
+          weight = SimilarityUtil.pearsonDistance(vecA, vecB);
+        } else if (simType == SimilarityUtil.SIM_HELLINGER) {
+          weight = SimilarityUtil.hellingerDistance(vecA, vecB);
+        }
+
+        LinkageTriple triple = new LinkageTriple();
+        triple.keyA = keyA;
+        triple.keyB = keyB;
+        triple.weight = weight;
+        return triple;
+      }
+    }).filter(new Function<LinkageTriple, Boolean>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Boolean call(LinkageTriple arg0) throws Exception {
+        if (arg0 == null) {
+          return false;
+        }
+        return true;
+      }
+    });
+  }
+
+  /**
+   * MatrixtoTriples:Convert term similarity matrix to linkage triple list.
+   *
+   * @param keys      each key is a term
+   * @param simMatirx term similarity matrix, in which each row and column is a term and
+   *                  the cell value is the similarity between the two terms
+   * @return linkage triple list
+   */
+  public static List<LinkageTriple> matrixToTriples(JavaRDD<String> keys, CoordinateMatrix simMatirx) {
+    if (simMatirx.numCols() != keys.count()) {
+      return null;
+    }
+
+    // index words
+    JavaPairRDD<Long, String> keyIdRDD = JavaPairRDD.fromJavaRDD(keys.zipWithIndex().map(new Function<Tuple2<String, Long>, Tuple2<Long, String>>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<Long, String> call(Tuple2<String, Long> docId) {
+        return docId.swap();
+      }
+    }));
+
+    JavaPairRDD<Long, LinkageTriple> entriesRowRDD = simMatirx.entries().toJavaRDD().mapToPair(new PairFunction<MatrixEntry, Long, LinkageTriple>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<Long, LinkageTriple> call(MatrixEntry t) throws Exception {
+        LinkageTriple triple = new LinkageTriple();
+        triple.keyAId = t.i();
+        triple.keyBId = t.j();
+        triple.weight = t.value();
+        return new Tuple2<>(triple.keyAId, triple);
+      }
+    });
+
+    JavaPairRDD<Long, LinkageTriple> entriesColRDD = entriesRowRDD.leftOuterJoin(keyIdRDD).values().mapToPair(new PairFunction<Tuple2<LinkageTriple, Optional<String>>, Long, LinkageTriple>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public Tuple2<Long, LinkageTriple> call(Tuple2<LinkageTriple, Optional<String>> t) throws Exception {
+        LinkageTriple triple = t._1;
+        Optional<String> stra = t._2;
+        if (stra.isPresent()) {
+          triple.keyA = stra.get();
+        }
+        return new Tuple2<>(triple.keyBId, triple);
+      }
+    });
+
+    JavaRDD<LinkageTriple> tripleRDD = entriesColRDD.leftOuterJoin(keyIdRDD).values().map(new Function<Tuple2<LinkageTriple, Optional<String>>, LinkageTriple>() {
+      /**
+       *
+       */
+      private static final long serialVersionUID = 1L;
+
+      @Override
+      public LinkageTriple call(Tuple2<LinkageTriple, Optional<String>> t) throws Exception {
+        LinkageTriple triple = t._1;
+        Optional<String> strb = t._2;
+        if (strb.isPresent()) {
+          triple.keyB = strb.get();
+        }
+        return triple;
+      }
+    });
+    return tripleRDD.collect();
+  }
+
+  /**
+   * Calculate similarity (Hellinger Distance) between vectors
+   *
+   * @param vecA initial vector from which to calculate a similarity
+   * @param vecB second vector involved in similarity calculation
+   * @return similarity between two vectors
+   */
+  public static double hellingerDistance(Vector vecA, Vector vecB) {
+    double[] arrA = vecA.toArray();
+    double[] arrB = vecB.toArray();
+
+    double sim = 0.0;
+
+    int arrsize = arrA.length;
+    for (int i = 0; i < arrsize; i++) {
+      double a = arrA[i];
+      double b = arrB[i];
+      double sqrtDiff = Math.sqrt(a) - Math.sqrt(b);
+      sim += sqrtDiff * sqrtDiff;
+    }
+
+    sim = sim / Math.sqrt(2);
+
+    return sim;
+  }
+
+  /**
+   * Calculate similarity (Pearson Distance) between vectors
+   *
+   * @param vecA initial vector from which to calculate a similarity
+   * @param vecB second vector involved in similarity calculation
+   * @return similarity between two vectors
+   */
+  public static double pearsonDistance(Vector vecA, Vector vecB) {
+    double[] arrA = vecA.toArray();
+    double[] arrB = vecB.toArray();
+
+    int viewA = 0;
+    int viewB = 0;
+    int viewAB = 0;
+
+    int arrsize = arrA.length;
+    for (int i = 0; i < arrsize; i++) {
+      if (arrA[i] > 0) {
+        viewA++;
+      }
+
+      if (arrB[i] > 0) {
+        viewB++;
+      }
+
+      if (arrB[i] > 0 && arrA[i] > 0) {
+        viewAB++;
+      }
+    }
+    return viewAB / (Math.sqrt(viewA) * Math.sqrt(viewB));
+  }
+
+  /**
+   * calculate similarity between vectors
+   *
+   * @param vecA initial vector from which to calculate a similarity
+   * @param vecB second vector involved in similarity calculation
+   * @return similarity between two vectors
+   */
+  public static double cosineDistance(Vector vecA, Vector vecB) {
+    return 1;
+  }
+}
\ No newline at end of file

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/utils/package-info.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/utils/package-info.java b/core/src/main/java/gov/nasa/jpl/mudrod/utils/package-info.java
new file mode 100644
index 0000000..3fcd95e
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/utils/package-info.java
@@ -0,0 +1,18 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+/**
+ * This package includes utilities classes for calculating similarity and
+ * parsing HTTP request
+ */
+package gov.nasa.jpl.mudrod.utils;
\ No newline at end of file

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/package-info.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/package-info.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/package-info.java
new file mode 100644
index 0000000..f4a8b86
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/package-info.java
@@ -0,0 +1,18 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+/**
+ * This package includes web log pre-processing, processing, and data structure
+ * classes.
+ */
+package gov.nasa.jpl.mudrod.weblog;
\ No newline at end of file

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/KGreedyPartitionSolver.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/KGreedyPartitionSolver.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/KGreedyPartitionSolver.java
new file mode 100644
index 0000000..4397873
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/KGreedyPartitionSolver.java
@@ -0,0 +1,142 @@
+package gov.nasa.jpl.mudrod.weblog.partition;
+
+import java.util.*;
+
+public class KGreedyPartitionSolver implements ThePartitionProblemSolver {
+
+  public boolean bsorted = false;
+
+  public KGreedyPartitionSolver() {
+    // default constructor
+  }
+
+  public KGreedyPartitionSolver(boolean bsorted) {
+    this.bsorted = true;
+  }
+
+  @Override
+  public Map<String, Integer> solve(Map<String, Double> labelNums, int k) {
+    List<Double> lista = null;
+    List<String> months = null;
+
+    if (!this.bsorted) {
+      LinkedHashMap sortedMap = this.sortMapByValue(labelNums);
+      lista = new ArrayList(sortedMap.values());
+      months = new ArrayList(sortedMap.keySet());
+    } else {
+      lista = new ArrayList(labelNums.values());
+      months = new ArrayList(labelNums.keySet());
+    }
+
+    List<List<Double>> parts = new ArrayList<>();
+    List<List<String>> splitMonths = new ArrayList<>();
+
+    for (int i = 0; i < k; i++) {
+      List<Double> part = new ArrayList();
+      parts.add(part);
+
+      List<String> monthList = new ArrayList();
+      splitMonths.add(monthList);
+    }
+
+    int j = 0;
+    for (Double lista1 : lista) {
+
+      Double minimalSum = -1.0;
+      int position = 0;
+      for (int i = 0; i < parts.size(); i++) {
+        List<Double> part = parts.get(i);
+        if (minimalSum == -1) {
+          minimalSum = Suma(part);
+          position = i;
+        } else if (Suma(part) < minimalSum) {
+          minimalSum = Suma(part);
+          position = i;
+        }
+      }
+
+      List<Double> part = parts.get(position);
+      part.add(lista1);
+      parts.set(position, part);
+
+      List<String> month = splitMonths.get(position);
+      month.add(months.get(j));
+      splitMonths.set(position, month);
+      j++;
+    }
+
+    /*  for(int i=0; i<splitMonths.size(); i++){
+        System.out.println("group:" + i);
+        printStrList(splitMonths.get(i));
+      }
+      
+      for(int i=0; i<parts.size(); i++){
+        print(parts.get(i));
+      }*/
+
+    Map<String, Integer> LabelGroups = new HashMap<String, Integer>();
+    for (int i = 0; i < splitMonths.size(); i++) {
+      List<String> list = splitMonths.get(i);
+      for (int m = 0; m < list.size(); m++) {
+        LabelGroups.put(list.get(m), i);
+      }
+    }
+
+    return LabelGroups;
+  }
+
+  public LinkedHashMap<String, Double> sortMapByValue(Map passedMap) {
+    List mapKeys = new ArrayList(passedMap.keySet());
+    List mapValues = new ArrayList(passedMap.values());
+    Collections.sort(mapValues, Collections.reverseOrder());
+    Collections.sort(mapKeys, Collections.reverseOrder());
+
+    LinkedHashMap sortedMap = new LinkedHashMap();
+
+    Iterator valueIt = mapValues.iterator();
+    while (valueIt.hasNext()) {
+      Object val = valueIt.next();
+      Iterator keyIt = mapKeys.iterator();
+
+      while (keyIt.hasNext()) {
+        Object key = keyIt.next();
+        String comp1 = passedMap.get(key).toString();
+        String comp2 = val.toString();
+
+        if (comp1.equals(comp2)) {
+          passedMap.remove(key);
+          mapKeys.remove(key);
+          sortedMap.put((String) key, (Double) val);
+          break;
+        }
+
+      }
+
+    }
+    return sortedMap;
+  }
+
+  private Double Suma(List<Double> part) {
+    Double ret = 0.0;
+    for (int i = 0; i < part.size(); i++) {
+      ret += part.get(i);
+    }
+    return ret;
+  }
+
+  private void print(List<Double> list) {
+    /*for (int i = 0; i < list.size(); i++) {
+        System.out.print(list.get(i)+",");
+    }*/
+    System.out.print("sum is:" + Suma(list));
+    System.out.println();
+  }
+
+  private void printStrList(List<String> list) {
+    for (int i = 0; i < list.size(); i++) {
+      System.out.print(list.get(i) + ",");
+    }
+    System.out.println();
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/ThePartitionProblemSolver.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/ThePartitionProblemSolver.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/ThePartitionProblemSolver.java
new file mode 100644
index 0000000..11aaed3
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/ThePartitionProblemSolver.java
@@ -0,0 +1,8 @@
+package gov.nasa.jpl.mudrod.weblog.partition;
+
+import java.util.Map;
+
+public interface ThePartitionProblemSolver {
+
+  public Map<String, Integer> solve(Map<String, Double> labelNums, int k);
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/logPartitioner.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/logPartitioner.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/logPartitioner.java
new file mode 100644
index 0000000..4c299dd
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/partition/logPartitioner.java
@@ -0,0 +1,33 @@
+package gov.nasa.jpl.mudrod.weblog.partition;
+
+import org.apache.spark.Partitioner;
+
+import java.util.Map;
+
+public class logPartitioner extends Partitioner {
+
+  int num;
+  Map<String, Integer> UserGroups;
+
+  public logPartitioner(int num) {
+    this.num = num;
+  }
+
+  public logPartitioner(Map<String, Integer> UserGroups, int num) {
+    this.UserGroups = UserGroups;
+    this.num = num;
+  }
+
+  @Override
+  public int getPartition(Object arg0) {
+    // TODO Auto-generated method stub
+    String user = (String) arg0;
+    return UserGroups.get(user);
+  }
+
+  @Override
+  public int numPartitions() {
+    // TODO Auto-generated method stub
+    return num;
+  }
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/ClickStreamGenerator.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/ClickStreamGenerator.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/ClickStreamGenerator.java
new file mode 100644
index 0000000..34323df
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/ClickStreamGenerator.java
@@ -0,0 +1,74 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.weblog.pre;
+
+import gov.nasa.jpl.mudrod.discoveryengine.DiscoveryStepAbstract;
+import gov.nasa.jpl.mudrod.driver.ESDriver;
+import gov.nasa.jpl.mudrod.driver.SparkDriver;
+import gov.nasa.jpl.mudrod.utils.LabeledRowMatrix;
+import gov.nasa.jpl.mudrod.utils.MatrixUtil;
+import gov.nasa.jpl.mudrod.weblog.structure.ClickStream;
+import gov.nasa.jpl.mudrod.weblog.structure.SessionExtractor;
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.List;
+import java.util.Properties;
+
+/**
+ * Supports ability to extract click stream data based on session processing results
+ */
+public class ClickStreamGenerator extends DiscoveryStepAbstract {
+
+  /**
+   *
+   */
+  private static final long serialVersionUID = 1L;
+  private static final Logger LOG = LoggerFactory.getLogger(ClickStreamGenerator.class);
+
+  public ClickStreamGenerator(Properties props, ESDriver es, SparkDriver spark) {
+    super(props, es, spark);
+  }
+
+  @Override
+  public Object execute() {
+    LOG.info("Starting ClickStreamGenerator...");
+    startTime = System.currentTimeMillis();
+
+    String clickstremMatrixFile = props.getProperty("clickstreamMatrix");
+    try {
+      SessionExtractor extractor = new SessionExtractor();
+      JavaRDD<ClickStream> clickstreamRDD = extractor.extractClickStreamFromES(this.props, this.es, this.spark);
+      int weight = Integer.parseInt(props.getProperty("downloadWeight"));
+      JavaPairRDD<String, List<String>> metaddataQueryRDD = extractor.bulidDataQueryRDD(clickstreamRDD, weight);
+      LabeledRowMatrix wordDocMatrix = MatrixUtil.createWordDocMatrix(metaddataQueryRDD);
+
+      MatrixUtil.exportToCSV(wordDocMatrix.rowMatrix, wordDocMatrix.rowkeys, wordDocMatrix.colkeys, clickstremMatrixFile);
+    } catch (Exception e) {
+      LOG.error("Encountered error within ClickStreamGenerator: {}", e);
+    }
+
+    endTime = System.currentTimeMillis();
+    LOG.info("ClickStreamGenerator complete. Time elapsed {} seconds.", (endTime - startTime) / 1000);
+    return null;
+  }
+
+  @Override
+  public Object execute(Object o) {
+    return null;
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/CrawlerDetection.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/CrawlerDetection.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/CrawlerDetection.java
new file mode 100644
index 0000000..80bf33b
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/CrawlerDetection.java
@@ -0,0 +1,252 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.weblog.pre;
+
+import gov.nasa.jpl.mudrod.discoveryengine.DiscoveryStepAbstract;
+import gov.nasa.jpl.mudrod.driver.ESDriver;
+import gov.nasa.jpl.mudrod.driver.SparkDriver;
+import gov.nasa.jpl.mudrod.main.MudrodConstants;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.api.java.function.Function2;
+import org.elasticsearch.action.index.IndexRequest;
+import org.elasticsearch.action.search.SearchResponse;
+import org.elasticsearch.common.unit.TimeValue;
+import org.elasticsearch.index.query.BoolQueryBuilder;
+import org.elasticsearch.index.query.QueryBuilders;
+import org.elasticsearch.search.SearchHit;
+import org.elasticsearch.search.aggregations.AggregationBuilder;
+import org.elasticsearch.search.aggregations.AggregationBuilders;
+import org.elasticsearch.search.aggregations.bucket.histogram.DateHistogramInterval;
+import org.elasticsearch.search.aggregations.bucket.histogram.Histogram;
+import org.elasticsearch.search.aggregations.bucket.histogram.Histogram.Order;
+import org.elasticsearch.search.aggregations.bucket.terms.Terms;
+import org.joda.time.DateTime;
+import org.joda.time.Seconds;
+import org.joda.time.format.DateTimeFormatter;
+import org.joda.time.format.ISODateTimeFormat;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.IOException;
+import java.util.*;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+/**
+ * An {@link DiscoveryStepAbstract}
+ * implementation which detects a known list of Web crawlers which may may be
+ * present within, and pollute various logs acting as input to Mudrod.
+ */
+public class CrawlerDetection extends LogAbstract {
+  /**
+   *
+   */
+  private static final long serialVersionUID = 1L;
+  private static final Logger LOG = LoggerFactory.getLogger(CrawlerDetection.class);
+
+  public static final String CRAWLER = "crawler";
+  public static final String GOOGLE_BOT = "googlebot";
+  public static final String BING_BOT = "bingbot";
+  public static final String YAHOO_BOT = "slurp";
+  public static final String YACY_BOT = "yacybot";
+  public static final String ROGER_BOT = "rogerbot";
+  public static final String YANDEX_BOT = "yandexbot";
+
+  public static final String NO_AGENT_BOT = "-";
+  public static final String PERL_BOT = "libwww-perl/";
+  public static final String APACHE_HHTP = "apache-httpclient/";
+  public static final String JAVA_CLIENT = "java/";
+  public static final String CURL = "curl/";
+
+  /**
+   * Paramterized constructor to instantiate a configured instance of
+   * {@link CrawlerDetection}
+   *
+   * @param props populated {@link java.util.Properties} object
+   * @param es    {@link ESDriver} object to use in
+   *              crawler detection preprocessing.
+   * @param spark {@link SparkDriver} object to use in
+   *              crawler detection preprocessing.
+   */
+  public CrawlerDetection(Properties props, ESDriver es, SparkDriver spark) {
+    super(props, es, spark);
+  }
+
+  public CrawlerDetection() {
+    super(null, null, null);
+  }
+
+  @Override
+  public Object execute() {
+    LOG.info("Starting Crawler detection {}.", httpType);
+    startTime = System.currentTimeMillis();
+    try {
+      checkByRate();
+    } catch (InterruptedException | IOException e) {
+      LOG.error("Encountered an error whilst detecting Web crawlers.", e);
+    }
+    endTime = System.currentTimeMillis();
+    es.refreshIndex();
+    LOG.info("Crawler detection complete. Time elapsed {} seconds", (endTime - startTime) / 1000);
+    return null;
+  }
+
+  /**
+   * Check known crawler through crawler agent name list
+   *
+   * @param agent name of a log line
+   * @return 1 if the log is initiated by crawler, 0 otherwise
+   */
+  public boolean checkKnownCrawler(String agent) {
+    agent = agent.toLowerCase();
+    if (agent.contains(CRAWLER) || agent.contains(GOOGLE_BOT) || agent.contains(BING_BOT) || agent.contains(APACHE_HHTP) || agent.contains(PERL_BOT) || agent.contains(YAHOO_BOT) || agent
+        .contains(YANDEX_BOT) || agent.contains(NO_AGENT_BOT) || agent.contains(PERL_BOT) || agent.contains(APACHE_HHTP) || agent.contains(JAVA_CLIENT) || agent.contains(CURL)) {
+      return true;
+    } else {
+      return false;
+    }
+  }
+
+  public void checkByRate() throws InterruptedException, IOException {
+    String processingType = props.getProperty(MudrodConstants.PROCESS_TYPE);
+    if (processingType.equals("sequential")) {
+      checkByRateInSequential();
+    } else if (processingType.equals("parallel")) {
+      checkByRateInParallel();
+    }
+  }
+
+  /**
+   * Check crawler by request sending rate, which is read from configruation
+   * file
+   *
+   * @throws InterruptedException InterruptedException
+   * @throws IOException          IOException
+   */
+  public void checkByRateInSequential() throws InterruptedException, IOException {
+    es.createBulkProcessor();
+
+    int rate = Integer.parseInt(props.getProperty("sendingrate"));
+
+    Terms users = this.getUserTerms(this.httpType);
+    LOG.info("Original User count: {}", Integer.toString(users.getBuckets().size()));
+
+    int userCount = 0;
+    for (Terms.Bucket entry : users.getBuckets()) {
+      String user = entry.getKey().toString();
+      int count = checkByRate(es, user);
+      userCount += count;
+    }
+    es.destroyBulkProcessor();
+    LOG.info("User count: {}", Integer.toString(userCount));
+  }
+
+  void checkByRateInParallel() throws InterruptedException, IOException {
+
+    JavaRDD<String> userRDD = getUserRDD(this.httpType);
+    LOG.info("Original User count: {}", userRDD.count());
+
+    int userCount = 0;
+    userCount = userRDD.mapPartitions((FlatMapFunction<Iterator<String>, Integer>) iterator -> {
+      ESDriver tmpES = new ESDriver(props);
+      tmpES.createBulkProcessor();
+      List<Integer> realUserNums = new ArrayList<>();
+      while (iterator.hasNext()) {
+        String s = iterator.next();
+        Integer realUser = checkByRate(tmpES, s);
+        realUserNums.add(realUser);
+      }
+      tmpES.destroyBulkProcessor();
+      tmpES.close();
+      return realUserNums.iterator();
+    }).reduce((Function2<Integer, Integer, Integer>) (a, b) -> a + b);
+
+    LOG.info("User count: {}", Integer.toString(userCount));
+  }
+
+  private int checkByRate(ESDriver es, String user) {
+
+    int rate = Integer.parseInt(props.getProperty("sendingrate"));
+    Pattern pattern = Pattern.compile("get (.*?) http/*");
+    Matcher matcher;
+
+    BoolQueryBuilder filterSearch = new BoolQueryBuilder();
+    filterSearch.must(QueryBuilders.termQuery("IP", user));
+
+    AggregationBuilder aggregation = AggregationBuilders.dateHistogram("by_minute").field("Time").dateHistogramInterval(DateHistogramInterval.MINUTE).order(Order.COUNT_DESC);
+    SearchResponse checkRobot = es.getClient().prepareSearch(logIndex).setTypes(httpType, ftpType).setQuery(filterSearch).setSize(0).addAggregation(aggregation).execute().actionGet();
+
+    Histogram agg = checkRobot.getAggregations().get("by_minute");
+
+    List<? extends Histogram.Bucket> botList = agg.getBuckets();
+    long maxCount = botList.get(0).getDocCount();
+    if (maxCount >= rate) {
+      return 0;
+    } else {
+      DateTime dt1 = null;
+      int toLast = 0;
+      SearchResponse scrollResp = es.getClient().prepareSearch(logIndex).setTypes(httpType, ftpType).setScroll(new TimeValue(60000)).setQuery(filterSearch).setSize(100).execute().actionGet();
+      while (true) {
+        for (SearchHit hit : scrollResp.getHits().getHits()) {
+          Map<String, Object> result = hit.getSource();
+          String logtype = (String) result.get("LogType");
+          if (logtype.equals("PO.DAAC")) {
+            String request = (String) result.get("Request");
+            matcher = pattern.matcher(request.trim().toLowerCase());
+            boolean find = false;
+            while (matcher.find()) {
+              request = matcher.group(1);
+              result.put("RequestUrl", "http://podaac.jpl.nasa.gov" + request);
+              find = true;
+            }
+            if (!find) {
+              result.put("RequestUrl", request);
+            }
+          } else {
+            result.put("RequestUrl", result.get("Request"));
+          }
+
+          DateTimeFormatter fmt = ISODateTimeFormat.dateTime();
+          DateTime dt2 = fmt.parseDateTime((String) result.get("Time"));
+
+          if (dt1 == null) {
+            toLast = 0;
+          } else {
+            toLast = Math.abs(Seconds.secondsBetween(dt1, dt2).getSeconds());
+          }
+          result.put("ToLast", toLast);
+          IndexRequest ir = new IndexRequest(logIndex, cleanupType).source(result);
+
+          es.getBulkProcessor().add(ir);
+          dt1 = dt2;
+        }
+
+        scrollResp = es.getClient().prepareSearchScroll(scrollResp.getScrollId()).setScroll(new TimeValue(600000)).execute().actionGet();
+        if (scrollResp.getHits().getHits().length == 0) {
+          break;
+        }
+      }
+
+    }
+
+    return 1;
+  }
+
+  @Override
+  public Object execute(Object o) {
+    return null;
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/incubator-sdap-mudrod/blob/7b76fa16/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/HistoryGenerator.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/HistoryGenerator.java b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/HistoryGenerator.java
new file mode 100644
index 0000000..d5dc102
--- /dev/null
+++ b/core/src/main/java/gov/nasa/jpl/mudrod/weblog/pre/HistoryGenerator.java
@@ -0,0 +1,139 @@
+/*
+ * Licensed under the Apache License, Version 2.0 (the "License"); you 
+ * may not use this file except in compliance with the License. 
+ * You may obtain a copy of the License at
+ * 
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package gov.nasa.jpl.mudrod.weblog.pre;
+
+import gov.nasa.jpl.mudrod.driver.ESDriver;
+import gov.nasa.jpl.mudrod.driver.SparkDriver;
+import gov.nasa.jpl.mudrod.main.MudrodConstants;
+import org.elasticsearch.action.search.SearchRequestBuilder;
+import org.elasticsearch.action.search.SearchResponse;
+import org.elasticsearch.index.query.QueryBuilders;
+import org.elasticsearch.search.aggregations.AggregationBuilders;
+import org.elasticsearch.search.aggregations.bucket.terms.Terms;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.io.BufferedWriter;
+import java.io.File;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.util.*;
+
+/**
+ * Supports ability to generate search history (queries) for each individual
+ * user (IP)
+ */
+public class HistoryGenerator extends LogAbstract {
+  private static final long serialVersionUID = 1L;
+  private static final Logger LOG = LoggerFactory.getLogger(HistoryGenerator.class);
+
+  public HistoryGenerator(Properties props, ESDriver es, SparkDriver spark) {
+    super(props, es, spark);
+  }
+
+  @Override
+  public Object execute() {
+    LOG.info("Starting HistoryGenerator...");
+    startTime = System.currentTimeMillis();
+
+    generateBinaryMatrix();
+
+    endTime = System.currentTimeMillis();
+    LOG.info("HistoryGenerator complete. Time elapsed {} seconds", (endTime - startTime) / 1000);
+    return null;
+  }
+
+  /**
+   * Method to generate a binary user*query matrix (stored in temporary .csv
+   * file)
+   */
+  public void generateBinaryMatrix() {
+    try {
+
+      System.out.println(props.getProperty("userHistoryMatrix"));
+      File file = new File(props.getProperty("userHistoryMatrix"));
+      if (file.exists()) {
+        file.delete();
+      }
+
+      file.createNewFile();
+
+      FileWriter fw = new FileWriter(file.getAbsoluteFile());
+      BufferedWriter bw = new BufferedWriter(fw);
+      bw.write("Num" + ",");
+
+      // step 1: write first row of csv
+      List<String> logIndexList = es.getIndexListWithPrefix(props.getProperty(MudrodConstants.LOG_INDEX));
+
+      String[] logIndices = logIndexList.toArray(new String[0]);
+      String[] statictypeArray = new String[] { this.sessionStats };
+      int docCount = es.getDocCount(logIndices, statictypeArray);
+
+      SearchResponse sr = es.getClient().prepareSearch(logIndices).setTypes(statictypeArray).setQuery(QueryBuilders.matchAllQuery()).setSize(0)
+          .addAggregation(AggregationBuilders.terms("IPs").field("IP").size(docCount)).execute().actionGet();
+      Terms ips = sr.getAggregations().get("IPs");
+      List<String> ipList = new ArrayList<>();
+      for (Terms.Bucket entry : ips.getBuckets()) {
+        if (entry.getDocCount() > Integer.parseInt(props.getProperty(MudrodConstants.MINI_USER_HISTORY))) { // filter
+          // out
+          // less
+          // active users/ips
+          ipList.add(entry.getKey().toString());
+        }
+      }
+      bw.write(String.join(",", ipList) + "\n");
+
+      // step 2: step the rest rows of csv
+      SearchRequestBuilder sr2Builder = es.getClient().prepareSearch(logIndices).setTypes(statictypeArray).setQuery(QueryBuilders.matchAllQuery()).setSize(0)
+          .addAggregation(AggregationBuilders.terms("KeywordAgg").field("keywords").size(docCount).subAggregation(AggregationBuilders.terms("IPAgg").field("IP").size(docCount)));
+
+      SearchResponse sr2 = sr2Builder.execute().actionGet();
+      Terms keywords = sr2.getAggregations().get("KeywordAgg");
+
+      for (Terms.Bucket keyword : keywords.getBuckets()) {
+
+        Map<String, Integer> ipMap = new HashMap<>();
+        Terms ipAgg = keyword.getAggregations().get("IPAgg");
+
+        int distinctUser = ipAgg.getBuckets().size();
+        if (distinctUser > Integer.parseInt(props.getProperty(MudrodConstants.MINI_USER_HISTORY))) {
+          bw.write(keyword.getKey() + ",");
+          for (Terms.Bucket IP : ipAgg.getBuckets()) {
+
+            ipMap.put(IP.getKey().toString(), 1);
+          }
+          for (int i = 0; i < ipList.size(); i++) {
+            if (ipMap.containsKey(ipList.get(i))) {
+              bw.write(ipMap.get(ipList.get(i)) + ",");
+            } else {
+              bw.write("0,");
+            }
+          }
+          bw.write("\n");
+        }
+      }
+
+      bw.close();
+    } catch (IOException e) {
+      e.printStackTrace();
+    }
+
+  }
+
+  @Override
+  public Object execute(Object o) {
+    return null;
+  }
+
+}