[GitHub] [kafka] wcarlson5 commented on a diff in pull request #12161: DRAFT: KAFKA-13873 Add ability to Pause / Resume KafkaStreams Topologies

[GitBox <gi...@apache.org>]

wcarlson5 commented on code in PR #12161:
URL: https://github.com/apache/kafka/pull/12161#discussion_r872731431


##########
streams/src/main/java/org/apache/kafka/streams/processor/internals/StoreChangelogReader.java:
##########
@@ -463,7 +463,10 @@ public void restore(final Map<TaskId, Task> tasks) {
                 final TaskId taskId = changelogs.get(partition).stateManager.taskId();
                 try {
                     if (restoreChangelog(changelogs.get(partition))) {
-                        tasks.get(taskId).clearTaskTimeout();
+                        final Task task = tasks.get(taskId);
+                        if (task != null) {

Review Comment:
   Why are we getting null here when we were not before?



##########
streams/src/main/java/org/apache/kafka/streams/processor/internals/Tasks.java:
##########
@@ -273,6 +273,12 @@ Collection<Task> allTasks() {
         return readOnlyTasks;
     }
 
+    Collection<Task> notPausedTasks() {
+        return Collections.unmodifiableCollection(readOnlyActiveTasks.stream().filter(t ->

Review Comment:
   nit: Can we align each call on its own line for readability?



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,897 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.purgeLocalStreamsState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.startApplicationAndWaitUntilRunning;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForCompletion;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForStandbyCompletion;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.hamcrest.core.IsEqual.equalTo;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.io.File;
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import java.util.concurrent.atomic.AtomicInteger;
+import java.util.concurrent.atomic.AtomicLong;
+import org.apache.kafka.clients.admin.Admin;
+import org.apache.kafka.clients.consumer.Consumer;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.clients.consumer.KafkaConsumer;
+import org.apache.kafka.clients.producer.KafkaProducer;
+import org.apache.kafka.clients.producer.ProducerConfig;
+import org.apache.kafka.clients.producer.ProducerRecord;
+import org.apache.kafka.common.TopicPartition;
+import org.apache.kafka.common.serialization.IntegerDeserializer;
+import org.apache.kafka.common.serialization.IntegerSerializer;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.common.utils.MockTime;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.Topology;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils.TrackingStateRestoreListener;
+import org.apache.kafka.streams.kstream.Consumed;
+import org.apache.kafka.streams.kstream.KStream;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.StateRestoreListener;
+import org.apache.kafka.streams.processor.TaskId;
+import org.apache.kafka.streams.processor.api.Processor;
+import org.apache.kafka.streams.processor.api.ProcessorContext;
+import org.apache.kafka.streams.processor.api.Record;
+import org.apache.kafka.streams.processor.internals.StateDirectory;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueBytesStoreSupplier;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.StoreBuilder;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.streams.state.internals.InMemoryKeyValueStore;
+import org.apache.kafka.streams.state.internals.KeyValueStoreBuilder;
+import org.apache.kafka.streams.state.internals.OffsetCheckpoint;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));

Review Comment:
   nit: line length



##########
streams/src/main/java/org/apache/kafka/streams/processor/internals/StreamThread.java:
##########
@@ -897,7 +897,8 @@ private void initializeAndRestorePhase() {
         }
         // we can always let changelog reader try restoring in order to initialize the changelogs;
         // if there's no active restoring or standby updating it would not try to fetch any data
-        changelogReader.restore(taskManager.tasks());
+        // After KAFKA-13873, we only restore the not paused tasks.
+        changelogReader.restore(taskManager.notPausedTasks());

Review Comment:
   when a paused task is resumed will restore be called if necessary?



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldAllowForTopologiesToStartPaused() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);

Review Comment:
   nit: clean up?



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldAllowForTopologiesToStartPaused() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.pause(); // This pause processing.
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify no output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreamsWithNamedTopologies() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.deleteTopicsAndWait(NEW_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+        CLUSTER.createTopic(NEW_STREAM, 2, 1);
+
+        // Create KafkaStream / NamedTopologyBuilders
+        final KafkaStreamsNamedTopologyWrapper streams = new KafkaStreamsNamedTopologyWrapper(props());

Review Comment:
   I don't see where this gets cleaned up...



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));

Review Comment:
   you can probably just call close()



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));

Review Comment:
   Maybe you can wait the max poll interval?



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldAllowForTopologiesToStartPaused() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.pause(); // This pause processing.
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify no output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreamsWithNamedTopologies() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.deleteTopicsAndWait(NEW_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+        CLUSTER.createTopic(NEW_STREAM, 2, 1);
+
+        // Create KafkaStream / NamedTopologyBuilders
+        final KafkaStreamsNamedTopologyWrapper streams = new KafkaStreamsNamedTopologyWrapper(props());
+        final NamedTopologyBuilder builder1 = streams.newNamedTopologyBuilder("topology1");
+        builder1.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+
+        final NamedTopologyBuilder builder2 = streams.newNamedTopologyBuilder("topology2");
+        builder2.stream(NEW_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_2);
+
+        // Start KafkaStream
+        streams.start(asList(builder1.build(), builder2.build()));
+        waitForApplicationState(singletonList(streams), State.RUNNING, STARTUP_TIMEOUT);
+
+        // Write data for topology1
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy1
+        // JNH: Pause topology1
+        streams.pauseNamedTopology("topology1");
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        // JNH: Assert the topology1 is paused and topology2 is not paused
+        assertTrue(streams.isNamedTopologyPaused("topology1"));
+
+        // Write more data for topology 1 and topology 2
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = streams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output for topology1 somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Verify that topology 2 is not paused and has processed data.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+
+
+        // Resume KafkaStreams/topology
+        // JNH: resume topology 1; assert that it is running.
+        streams.resumeNamedTopology("topology1");
+        assertFalse(streams.isNamedTopologyPaused("topoology1"));
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+
+        // JNH: Assert any final notes.
+    }
+
+    @Test
+    public void shouldPauseAndResumeAllKafkaStreamsWithNamedTopologies() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.deleteTopicsAndWait(NEW_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+        CLUSTER.createTopic(NEW_STREAM, 2, 1);
+
+        // Create KafkaStream / NamedTopologyBuilders
+        final KafkaStreamsNamedTopologyWrapper streams = new KafkaStreamsNamedTopologyWrapper(props());
+        final NamedTopologyBuilder builder1 = streams.newNamedTopologyBuilder("topology1");
+        builder1.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+
+        final NamedTopologyBuilder builder2 = streams.newNamedTopologyBuilder("topology2");
+        builder2.stream(NEW_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_2);
+
+        // Start KafkaStream
+        streams.start(asList(builder1.build(), builder2.build()));
+        waitForApplicationState(singletonList(streams), State.RUNNING, STARTUP_TIMEOUT);
+
+        // Write data for topology1
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy1
+        // JNH: Pause topology1
+        streams.pause();
+        //streams.pauseNamedTopology("topology1");
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        // JNH: Assert the topology1 is paused and topology2 is not paused
+        assertTrue(streams.isPaused());
+        assertTrue(streams.isNamedTopologyPaused("topology1"));
+        assertTrue(streams.isNamedTopologyPaused("topology2"));
+
+
+        // Write more data for topology 1 and topology 2
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = streams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output for topology1 somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Verify that topology 2 is paused and has processed data.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Verify that topology 2 is not paused and has processed data.
+        //assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+
+
+        // Resume KafkaStreams/topology
+        // JNH: resume topology 1; assert that it is running.
+        streams.resumeNamedTopology("topology1");
+        assertFalse(streams.isNamedTopologyPaused("topoology1"));
+        assertFalse(streams.isPaused()); // Are all paused?  No.
+        assertTrue(streams.isNamedTopologyPaused("topology2"));  // Still paused
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));

Review Comment:
   topology2 as well



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldAllowForTopologiesToStartPaused() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.pause(); // This pause processing.
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify no output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreamsWithNamedTopologies() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.deleteTopicsAndWait(NEW_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+        CLUSTER.createTopic(NEW_STREAM, 2, 1);
+
+        // Create KafkaStream / NamedTopologyBuilders
+        final KafkaStreamsNamedTopologyWrapper streams = new KafkaStreamsNamedTopologyWrapper(props());
+        final NamedTopologyBuilder builder1 = streams.newNamedTopologyBuilder("topology1");
+        builder1.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+
+        final NamedTopologyBuilder builder2 = streams.newNamedTopologyBuilder("topology2");
+        builder2.stream(NEW_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_2);
+
+        // Start KafkaStream
+        streams.start(asList(builder1.build(), builder2.build()));
+        waitForApplicationState(singletonList(streams), State.RUNNING, STARTUP_TIMEOUT);
+
+        // Write data for topology1
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy1
+        // JNH: Pause topology1
+        streams.pauseNamedTopology("topology1");
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        // JNH: Assert the topology1 is paused and topology2 is not paused
+        assertTrue(streams.isNamedTopologyPaused("topology1"));

Review Comment:
   Make sure the other topology is not paused?



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldAllowForTopologiesToStartPaused() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.pause(); // This pause processing.
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify no output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreamsWithNamedTopologies() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.deleteTopicsAndWait(NEW_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+        CLUSTER.createTopic(NEW_STREAM, 2, 1);
+
+        // Create KafkaStream / NamedTopologyBuilders
+        final KafkaStreamsNamedTopologyWrapper streams = new KafkaStreamsNamedTopologyWrapper(props());
+        final NamedTopologyBuilder builder1 = streams.newNamedTopologyBuilder("topology1");
+        builder1.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+
+        final NamedTopologyBuilder builder2 = streams.newNamedTopologyBuilder("topology2");
+        builder2.stream(NEW_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_2);
+
+        // Start KafkaStream
+        streams.start(asList(builder1.build(), builder2.build()));
+        waitForApplicationState(singletonList(streams), State.RUNNING, STARTUP_TIMEOUT);
+
+        // Write data for topology1
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy1
+        // JNH: Pause topology1
+        streams.pauseNamedTopology("topology1");
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        // JNH: Assert the topology1 is paused and topology2 is not paused
+        assertTrue(streams.isNamedTopologyPaused("topology1"));
+
+        // Write more data for topology 1 and topology 2
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = streams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output for topology1 somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Verify that topology 2 is not paused and has processed data.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+
+
+        // Resume KafkaStreams/topology
+        // JNH: resume topology 1; assert that it is running.
+        streams.resumeNamedTopology("topology1");
+        assertFalse(streams.isNamedTopologyPaused("topoology1"));
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+
+        // JNH: Assert any final notes.
+    }
+
+    @Test
+    public void shouldPauseAndResumeAllKafkaStreamsWithNamedTopologies() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.deleteTopicsAndWait(NEW_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+        CLUSTER.createTopic(NEW_STREAM, 2, 1);
+
+        // Create KafkaStream / NamedTopologyBuilders
+        final KafkaStreamsNamedTopologyWrapper streams = new KafkaStreamsNamedTopologyWrapper(props());
+        final NamedTopologyBuilder builder1 = streams.newNamedTopologyBuilder("topology1");
+        builder1.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+
+        final NamedTopologyBuilder builder2 = streams.newNamedTopologyBuilder("topology2");
+        builder2.stream(NEW_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_2);
+
+        // Start KafkaStream
+        streams.start(asList(builder1.build(), builder2.build()));
+        waitForApplicationState(singletonList(streams), State.RUNNING, STARTUP_TIMEOUT);
+
+        // Write data for topology1
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy1
+        // JNH: Pause topology1
+        streams.pause();
+        //streams.pauseNamedTopology("topology1");
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        // JNH: Assert the topology1 is paused and topology2 is not paused
+        assertTrue(streams.isPaused());
+        assertTrue(streams.isNamedTopologyPaused("topology1"));
+        assertTrue(streams.isNamedTopologyPaused("topology2"));
+
+
+        // Write more data for topology 1 and topology 2
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+        produceToInputTopics(NEW_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = streams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output for topology1 somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Verify that topology 2 is paused and has processed data.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_2, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Verify that topology 2 is not paused and has processed data.

Review Comment:
   clean up



##########
streams/src/test/java/org/apache/kafka/streams/integration/PauseResumeIntegrationTest.java:
##########
@@ -0,0 +1,501 @@
+/*
+ * 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.kafka.streams.integration;
+
+import static java.util.Arrays.asList;
+import static java.util.Collections.singletonList;
+import static org.apache.kafka.streams.KeyValue.pair;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.safeUniqueTestName;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitForApplicationState;
+import static org.apache.kafka.streams.integration.utils.IntegrationTestUtils.waitUntilMinKeyValueRecordsReceived;
+import static org.hamcrest.MatcherAssert.assertThat;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
+
+import java.time.Duration;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.List;
+import java.util.Map;
+import java.util.Properties;
+import java.util.concurrent.CountDownLatch;
+import java.util.concurrent.TimeUnit;
+import org.apache.kafka.clients.consumer.ConsumerConfig;
+import org.apache.kafka.common.serialization.LongDeserializer;
+import org.apache.kafka.common.serialization.LongSerializer;
+import org.apache.kafka.common.serialization.Serdes;
+import org.apache.kafka.common.serialization.StringDeserializer;
+import org.apache.kafka.common.serialization.StringSerializer;
+import org.apache.kafka.common.utils.Bytes;
+import org.apache.kafka.streams.KafkaStreams;
+import org.apache.kafka.streams.KafkaStreams.State;
+import org.apache.kafka.streams.KeyValue;
+import org.apache.kafka.streams.LagInfo;
+import org.apache.kafka.streams.StreamsBuilder;
+import org.apache.kafka.streams.StreamsConfig;
+import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
+import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
+import org.apache.kafka.streams.kstream.Materialized;
+import org.apache.kafka.streams.processor.internals.namedtopology.KafkaStreamsNamedTopologyWrapper;
+import org.apache.kafka.streams.processor.internals.namedtopology.NamedTopologyBuilder;
+import org.apache.kafka.streams.state.KeyValueStore;
+import org.apache.kafka.streams.state.Stores;
+import org.apache.kafka.test.IntegrationTest;
+import org.apache.kafka.test.TestUtils;
+import org.hamcrest.CoreMatchers;
+import org.junit.After;
+import org.junit.AfterClass;
+import org.junit.Before;
+import org.junit.BeforeClass;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+import org.junit.rules.TestName;
+
+@Category({IntegrationTest.class})
+public class PauseResumeIntegrationTest {
+    private static final Duration STARTUP_TIMEOUT = Duration.ofSeconds(45);
+    private static final int NUM_BROKERS = 1;
+
+    public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(NUM_BROKERS);
+    private static Properties producerConfig;
+    private static Properties consumerConfig;
+
+    private static final Materialized<Object, Long, KeyValueStore<Bytes, byte[]>> IN_MEMORY_STORE = Materialized.as(Stores.inMemoryKeyValueStore("store"));
+
+
+    // existing topic that is pre-filled but cleared between tests
+    private static final String EXISTING_STREAM = "existing-stream";
+    private static final String NEW_STREAM = "new-stream";
+
+    private static final String INPUT_STREAM_1 = "input-stream-1";
+    private static final String INPUT_STREAM_2 = "input-stream-2";
+    private static final String INPUT_STREAM_3 = "input-stream-3";
+
+    private static final String OUTPUT_STREAM_1 = "output-stream-1";
+    private static final String OUTPUT_STREAM_2 = "output-stream-2";
+    private static final String OUTPUT_STREAM_3 = "output-stream-3";
+
+    private static final List<KeyValue<String, Long>> STANDARD_INPUT_DATA =
+        asList(pair("A", 100L), pair("B", 200L), pair("A", 300L), pair("C", 400L), pair("C", -50L));
+    // JNH: Why are there 5 outputs unlike in NamedTopologyIT?
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+        asList(pair("B", 1L), pair("A", 2L), pair("C", 2L));
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("A", 1L), pair("B", 1L), pair("A", 2L), pair("C", 1L), pair("C", 2L));
+    private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA2 =
+        asList(pair("B", 2L), pair("A", 4L), pair("C", 4L));
+    // output of count operation with caching
+    // private static final List<KeyValue<String, Long>> COUNT_OUTPUT_DATA =
+    //    asList(pair("B", 1L), pair("A", 2L), pair("C", 2L)); // output of count operation with caching
+
+    @BeforeClass
+    public static void startCluster() throws Exception {
+        CLUSTER.start();
+
+        CLUSTER.createTopic(INPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(INPUT_STREAM_3, 2, 1);
+
+        producerConfig = TestUtils.producerConfig(CLUSTER.bootstrapServers(), StringSerializer.class, LongSerializer.class);
+        consumerConfig = TestUtils.consumerConfig(CLUSTER.bootstrapServers(), StringDeserializer.class, LongDeserializer.class);
+
+        CLUSTER.createTopic(OUTPUT_STREAM_1, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_2, 2, 1);
+        CLUSTER.createTopic(OUTPUT_STREAM_3, 2, 1);
+    }
+
+    @AfterClass
+    public static void closeCluster() {
+        CLUSTER.stop();
+    }
+
+    @Rule
+    public final TestName testName = new TestName();
+    private String appId;
+    private KafkaStreams kafkaStreams;
+
+    @Before
+    public void createTopics() throws InterruptedException {
+        appId = safeUniqueTestName(PauseResumeIntegrationTest.class, testName);
+
+        final Properties adminConfig = new Properties();
+        adminConfig.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+    }
+
+    private Properties props() {
+        final Properties streamsConfiguration = new Properties();
+        streamsConfiguration.put(StreamsConfig.APPLICATION_ID_CONFIG, appId);
+        streamsConfiguration.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, CLUSTER.bootstrapServers());
+        //streamsConfiguration.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
+        streamsConfiguration.put(StreamsConfig.STATE_DIR_CONFIG, TestUtils.tempDirectory(appId).getPath());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
+        streamsConfiguration.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.Long().getClass());
+        streamsConfiguration.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 1000L);
+        streamsConfiguration.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
+        return streamsConfiguration;
+    }
+
+    @After
+    public void shutdown() {
+        if (kafkaStreams != null) {
+            kafkaStreams.close(Duration.ofSeconds(30));
+        }
+    }
+
+    private static void produceToInputTopics(final String topic, final Collection<KeyValue<String, Long>> records) {
+        IntegrationTestUtils.produceKeyValuesSynchronously(
+            topic,
+            records,
+            producerConfig,
+            CLUSTER.time
+        );
+    }
+
+
+    @Test
+    public void shouldPauseAndResumeKafkaStreams() throws Exception {
+
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();
+
+        // Use statelistener to verify transition to paused transition?
+        // Read status as Paused?
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write more data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify that consumer read new data -- AKA, there is no lag.
+        final Map<String, Map<Integer, LagInfo>> lagMap = kafkaStreams.allLocalStorePartitionLags();
+        final Long maxLag = lagMap.values().stream().flatMap(m -> m.values().stream()).map(LagInfo::offsetLag).max(Long::compare).get();
+        assertEquals(0, (long) maxLag);
+
+        // Verify no output somehow? (Hard to prove negative)
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Resume KafkaStreams/topology
+        kafkaStreams.resume();
+        assertFalse(kafkaStreams.isPaused());
+
+        // Verify that the input written during the pause is processed.
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 3), CoreMatchers.equalTo(COUNT_OUTPUT_DATA2));
+    }
+
+    @Test
+    public void shouldAllowForTopologiesToStartPaused() throws Exception {
+        CLUSTER.deleteTopicsAndWait(EXISTING_STREAM);
+        CLUSTER.createTopic(EXISTING_STREAM, 2, 1);
+
+        // Create KafkaStream
+        final StreamsBuilder builder = new StreamsBuilder();
+        //builder.stream(EXISTING_STREAM).groupBy((k, v) -> k).count(IN_MEMORY_STORE).toStream().to(OUTPUT_STREAM_1);
+        builder.stream(EXISTING_STREAM).groupByKey().count().toStream().to(OUTPUT_STREAM_1);
+        final Properties props = props();
+        props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION_CONFIG, StreamsConfig.OPTIMIZE);
+
+        kafkaStreams = new KafkaStreams(builder.build(props), props);
+
+        // Shows pattern for blocking on state change.
+        final CountDownLatch startupLatch = new CountDownLatch(1);
+        kafkaStreams.setStateListener((newState, oldState) -> {
+            if (newState == State.RUNNING && oldState == State.REBALANCING) {
+                startupLatch.countDown();
+            }
+        });
+
+        // Start KafkaStream
+        kafkaStreams.pause(); // This pause processing.
+        kafkaStreams.start();
+        assertTrue(startupLatch.await(30, TimeUnit.SECONDS));
+
+        assertTrue(kafkaStreams.isPaused());
+
+        // Write data
+        produceToInputTopics(EXISTING_STREAM, STANDARD_INPUT_DATA);
+
+        // Verify no output
+        assertThat(waitUntilMinKeyValueRecordsReceived(consumerConfig, OUTPUT_STREAM_1, 0), CoreMatchers.equalTo(Collections.emptyList()));
+
+        // Pause KafkaStreams/topplogy
+        kafkaStreams.pause();

Review Comment:
   do we need to pause twice?



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