Example usage for org.apache.mahout.math.random Sampler interface-usage

Introduction

In this page you can find the example usage for org.apache.mahout.math.random Sampler interface-usage.

Usage

From source file com.mapr.synth.distributions.ChineseRestaurant.java

/**
 * Generates samples from a generalized Chinese restaurant process (or Pittman-Yor process).
 * <p/>
 * The number of values drawn exactly once will asymptotically be equal to the discount parameter
 * as the total number of draws T increases without bound.  The number of unique values sampled will
 * increase as O(alpha * log T) if discount = 0 or O(alpha * T^discount) for discount > 0.

From source file com.mapr.synth.distributions.LongTail.java

/**
 * Samples from a set of things based on a long-tailed distribution.  This converts
 * the ChineseRestaurant distribution from a distribution over integers into a distribution
 * over more plausible looking things like words.
 */
public abstract class LongTail<T> implements Sampler<T> {

From source file com.mapr.synth.distributions.TermGenerator.java

/**
 * Generate words at random from a specialized vocabulary.  Every term generator's
 * frequency distribution has a common basis, but each will diverge after initialization.
 *
 * Thread safe for sampling
 */

From source file com.mapr.synth.LogGenerator.java

/**
 * Generates kind of realistic log lines consisting of a user id (a cookie), an IP address and a query.
 */
public class LogGenerator implements Sampler<LogLine> {
    private PriorityQueue<LogLine> eventBuffer = Queues.newPriorityQueue();
    private PriorityQueue<User> users = Queues.newPriorityQueue();

From source file com.mapr.synth.samplers.FieldSampler.java

@JsonTypeInfo(use = JsonTypeInfo.Id.NAME, include = JsonTypeInfo.As.PROPERTY, property = "class")
@JsonSubTypes({ @JsonSubTypes.Type(value = AddressSampler.class, name = "address"),
        @JsonSubTypes.Type(value = DateSampler.class, name = "date"),
        @JsonSubTypes.Type(value = ArrivalSampler.class, name = "event"),
        @JsonSubTypes.Type(value = ForeignKeySampler.class, name = "foreign-key"),
        @JsonSubTypes.Type(value = IdSampler.class, name = "id"),

From source file com.mapr.synth.samplers.SchemaSampler.java

/**
 * Samples from a specified schema to generate reasonably interesting data.
 */
public class SchemaSampler implements Sampler<JsonNode> {
    private final JsonNodeFactory nodeFactory = JsonNodeFactory.withExactBigDecimals(false);

From source file org.apache.drill.synth.ChineseRestaurant.java

/**
 *
 * Generates samples from a generalized Chinese restaurant process (or Pittman-Yor process).
 *
 * The number of values drawn exactly once will asymptotically be equal to the discount parameter
 * as the total number of draws T increases without bound.  The number of unique values sampled will

From source file org.apache.drill.synth.LogGenerator.java

/**
 * Generates kind of realistic log lines consisting of a user id (a cookie), an IP address and a query.
 */
public class LogGenerator implements Sampler<LogLine> {
    private LongTail<InetAddress> ipGenerator = new LongTail<InetAddress>(1, 0.5) {
        Random gen = new Random();

From source file org.apache.drill.synth.LongTail.java

/**
 * Samples from a set of things based on a long-tailed distribution.  This converts
 * the ChineseRestaurant distribution from a distribution over integers into a distribution
 * over more plausible looking things like words.
 */
public abstract class LongTail<T> implements Sampler<T> {

From source file org.apache.drill.synth.sampler.ChineseRestaurant.java

/**
 * Generates samples from a generalized Chinese restaurant process (or Pittman-Yor process).
 * <p/>
 * The number of values drawn exactly once will asymptotically be equal to the discount parameter
 * as the total number of draws T increases without bound.  The number of unique values sampled will
 * increase as O(alpha * log T) if discount = 0 or O(alpha * T^discount) for discount > 0.

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