| /** |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you 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 org.apache.apex.malhar.lib.testbench; |
| |
| import java.util.HashMap; |
| import java.util.Map; |
| |
| import javax.validation.constraints.Min; |
| |
| import org.slf4j.Logger; |
| import org.slf4j.LoggerFactory; |
| |
| import com.datatorrent.api.Context.OperatorContext; |
| import com.datatorrent.api.DefaultInputPort; |
| import com.datatorrent.api.DefaultOutputPort; |
| import com.datatorrent.common.util.BaseOperator; |
| |
| /** |
| * This operator expects incoming tuples to be of type HashMap<String, Integer>. |
| * These values are throughput per window from upstream operators. |
| * At the end of the application window, the total and average throughput are emitted. |
| * <p> |
| * Benchmarks: This node has been benchmarked at over 5 million tuples/second in local/inline mode<br> |
| * <b>Tuple Schema</b> |
| * Each input tuple is HashMap<String, Integer><br> |
| * Output tuple is a HashMap<String, Integer>, where strings are throughputs, averages etc<br> |
| * <b>Port Interface</b><br> |
| * <b>count</b>: Output port for emitting the results<br> |
| * <b>data</b>: Input port for receiving the incoming tuple<br> |
| * <br> |
| * <b>Properties</b>: |
| * rolling_window_count: Number of windows to average over |
| * <br> |
| * Compile time checks are:<br> |
| * none |
| * <br> |
| * <b>Benchmarks</b>: Blast as many tuples as possible in inline mode<br> |
| * Benchmarked at over 17 million tuples/second in local/in-line mode<br> |
| * </p> |
| * @displayName Throughput Counter |
| * @category Test Bench |
| * @tags count |
| * @since 0.3.2 |
| */ |
| public class ThroughputCounter<K, V extends Number> extends BaseOperator |
| { |
| private static Logger log = LoggerFactory.getLogger(ThroughputCounter.class); |
| |
| /** |
| * The input port which receives throughput information from upstream operators. |
| */ |
| public final transient DefaultInputPort<HashMap<K, V>> data = new DefaultInputPort<HashMap<K, V>>() |
| { |
| @Override |
| public void process(HashMap<K, V> tuple) |
| { |
| for (Map.Entry<K, V> e: tuple.entrySet()) { |
| tuple_count += e.getValue().longValue(); |
| } |
| } |
| }; |
| |
| /** |
| * The output port which emits throughput statistics. |
| */ |
| public final transient DefaultOutputPort<HashMap<String,Number>> count = new DefaultOutputPort<HashMap<String, Number>>(); |
| |
| public static final String OPORT_COUNT_TUPLE_AVERAGE = "avg"; |
| public static final String OPORT_COUNT_TUPLE_COUNT = "count"; |
| public static final String OPORT_COUNT_TUPLE_TIME = "window_time"; |
| public static final String OPORT_COUNT_TUPLE_TUPLES_PERSEC = "tuples_per_sec"; |
| public static final String OPORT_COUNT_TUPLE_WINDOWID = "window_id"; |
| |
| private long windowStartTime = 0; |
| @Min(1) |
| private int rolling_window_count = 1; |
| long[] tuple_numbers = null; |
| long[] time_numbers = null; |
| int tuple_index = 0; |
| int count_denominator = 1; |
| long count_windowid = 0; |
| long tuple_count = 1; // so that the first begin window starts the count down |
| boolean didemit = false; |
| |
| |
| @Min(1) |
| public int getRollingWindowCount() |
| { |
| return rolling_window_count; |
| } |
| |
| public void setRollingWindowCount(int i) |
| { |
| rolling_window_count = i; |
| } |
| |
| @Override |
| public void setup(OperatorContext context) |
| { |
| windowStartTime = System.currentTimeMillis(); |
| log.debug(String.format("\nTupleCounter: set window to %d", rolling_window_count)); |
| if (rolling_window_count != 1) { // Initialized the tuple_numbers |
| tuple_numbers = new long[rolling_window_count]; |
| time_numbers = new long[rolling_window_count]; |
| for (int i = tuple_numbers.length; i > 0; i--) { |
| tuple_numbers[i - 1] = 0; |
| time_numbers[i - 1] = 0; |
| } |
| tuple_index = 0; |
| } |
| } |
| |
| @Override |
| public void beginWindow(long windowId) |
| { |
| if (tuple_count != 0) { // Do not restart time if no tuples were sent |
| windowStartTime = System.currentTimeMillis(); |
| if (didemit) { |
| tuple_count = 0; |
| } |
| } |
| } |
| |
| /** |
| * convenient method for not sending more than configured number of windows. |
| */ |
| @Override |
| public void endWindow() |
| { |
| if (tuple_count == 0) { |
| return; |
| } |
| |
| long elapsedTime = System.currentTimeMillis() - windowStartTime; |
| if (elapsedTime == 0) { |
| didemit = false; |
| return; |
| } |
| |
| long average; |
| long tuples_per_sec = (tuple_count * 1000) / elapsedTime; // * 1000 as elapsedTime is in millis |
| if (rolling_window_count == 1) { |
| average = tuples_per_sec; |
| } else { // use tuple_numbers |
| long slots; |
| if (count_denominator == rolling_window_count) { |
| tuple_numbers[tuple_index] = tuple_count; |
| time_numbers[tuple_index] = elapsedTime; |
| slots = rolling_window_count; |
| tuple_index++; |
| if (tuple_index == rolling_window_count) { |
| tuple_index = 0; |
| } |
| } else { |
| tuple_numbers[count_denominator - 1] = tuple_count; |
| time_numbers[count_denominator - 1] = elapsedTime; |
| slots = count_denominator; |
| count_denominator++; |
| } |
| long time_slot = 0; |
| long numtuples = 0; |
| for (int i = 0; i < slots; i++) { |
| numtuples += tuple_numbers[i]; |
| time_slot += time_numbers[i]; |
| } |
| average = (numtuples * 1000) / time_slot; |
| } |
| HashMap<String, Number> tuples = new HashMap<String, Number>(); |
| tuples.put(OPORT_COUNT_TUPLE_AVERAGE, new Long(average)); |
| tuples.put(OPORT_COUNT_TUPLE_COUNT, new Long(tuple_count)); |
| tuples.put(OPORT_COUNT_TUPLE_TIME, new Long(elapsedTime)); |
| tuples.put(OPORT_COUNT_TUPLE_TUPLES_PERSEC, new Long(tuples_per_sec)); |
| tuples.put(OPORT_COUNT_TUPLE_WINDOWID, new Long(count_windowid++)); |
| count.emit(tuples); |
| didemit = true; |
| } |
| } |