1 /* 2 * Copyright 2017, OpenCensus Authors 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 17 package io.opencensus.trace.samplers; 18 19 import io.opencensus.trace.Sampler; 20 import io.opencensus.trace.Span; 21 22 /** 23 * Static class to access a set of pre-defined {@link Sampler Samplers}. 24 * 25 * @since 0.5 26 */ 27 public final class Samplers { 28 private static final Sampler ALWAYS_SAMPLE = new AlwaysSampleSampler(); 29 private static final Sampler NEVER_SAMPLE = new NeverSampleSampler(); 30 31 // No instance of this class. 32 private Samplers() {} 33 34 /** 35 * Returns a {@link Sampler} that always makes a "yes" decision on {@link Span} sampling. 36 * 37 * @return a {@code Sampler} that always makes a "yes" decision on {@code Span} sampling. 38 * @since 0.5 39 */ 40 public static Sampler alwaysSample() { 41 return ALWAYS_SAMPLE; 42 } 43 44 /** 45 * Returns a {@link Sampler} that always makes a "no" decision on {@link Span} sampling. 46 * 47 * @return a {@code Sampler} that always makes a "no" decision on {@code Span} sampling. 48 * @since 0.5 49 */ 50 public static Sampler neverSample() { 51 return NEVER_SAMPLE; 52 } 53 54 /** 55 * Returns a {@link Sampler} that makes a "yes" decision with a given probability. 56 * 57 * @param probability The desired probability of sampling. Must be within [0.0, 1.0]. 58 * @return a {@code Sampler} that makes a "yes" decision with a given probability. 59 * @throws IllegalArgumentException if {@code probability} is out of range 60 * @since 0.5 61 */ 62 public static Sampler probabilitySampler(double probability) { 63 return ProbabilitySampler.create(probability); 64 } 65 } 66
