Add travis build step and fix javadoc formatting

.travis.yml

@@ -1,9 +1,21 @@
 language: java
-git:
-  depth: 3
 jdk:
   - oraclejdk8
-env:
-  - HADOOP_VERSION=2.7.6
-  - HADOOP_VERSION=2.8.4
-script: "./gradlew test --stacktrace --info -Ddyno.hadoop.bin.version=${HADOOP_VERSION}"
+git:
+  depth: 3
+install: true
+
+jobs:
+  include:
+    - stage: test
+      name: "Build"
+      script: "./gradlew build -x test"
+    - stage: test
+      script: "./gradlew test --stacktrace --info -Ddyno.hadoop.bin.version=${HADOOP_VERSION}"
+      env: HADOOP_VERSION=2.7.6
+    - stage: test
+      script: "./gradlew test --stacktrace --info -Ddyno.hadoop.bin.version=${HADOOP_VERSION}"
+      env: HADOOP_VERSION=2.8.4
+
+stages:
+  - test

dynamometer-workload/src/main/java/com/linkedin/dynamometer/workloadgenerator/TimedInputFormat.java

@@ -20,11 +20,11 @@
 
 /**
  * An {@link InputFormat} which is time-based. Starts at some timestamp (specified by the
- * {@value WorkloadDriver#START_TIMESTAMP_MS configuration) and runs for a time specified by the
+ * {@value WorkloadDriver#START_TIMESTAMP_MS} configuration) and runs for a time specified by the
  * {@value DURATION_KEY} configuration. Spawns {@value NUM_MAPPERS_KEY} mappers. Both {@value DURATION_KEY}
  * and {@value NUM_MAPPERS_KEY} are required.
  *
- * <p/>The values returned as the key by this InputFormat are just a sequential counter.
+ * <p>The values returned as the key by this InputFormat are just a sequential counter.
  */
 public class TimedInputFormat extends InputFormat<LongWritable, NullWritable> {
 
@@ -48,14 +48,14 @@ public List<InputSplit> getSplits(JobContext job) {
   public RecordReader<LongWritable, NullWritable> createRecordReader(InputSplit split, TaskAttemptContext context) {
     return new TimedRecordReader();
   }
-  
+
   public static List<String> getConfigDescriptions() {
     return Lists.newArrayList(
         NUM_MAPPERS_KEY + " (required): Number of mappers to launch.",
         DURATION_KEY + " (required): Number of minutes to induce workload for."
     );
   }
-  
+
   public static boolean verifyConfigurations(Configuration conf) {
     return conf.getInt(NUM_MAPPERS_KEY, -1) != -1
         && conf.getTimeDuration(DURATION_KEY, -1, TimeUnit.MILLISECONDS) != -1;

dynamometer-workload/src/main/java/com/linkedin/dynamometer/workloadgenerator/audit/AuditLogHiveTableParser.java

@@ -21,14 +21,14 @@
  * Where relativeTimestampMs represents the time elapsed between the start of
  * the audit log and the occurrence of the audit event. Assuming your audit
  * logs are available in Hive, this can be generated with a query looking like:
- * <pre>
+ * <pre>{@code
  *   INSERT OVERWRITE DIRECTORY '${outputPath}'
  *   SELECT (timestamp - ${startTimestamp} AS relativeTimestamp, ugi, cmd, src, dst, ip
  *   FROM '${auditLogTableLocation}'
  *   WHERE timestamp >= ${startTimestamp} AND timestamp < ${endTimestamp}
  *   DISTRIBUTE BY src
  *   SORT BY relativeTimestamp ASC;
- * </pre>
+ * }</pre>
  * Note that the sorting step is important; events in each distinct file must be in
  * time-ascending order.
  */

dynamometer-workload/src/main/java/com/linkedin/dynamometer/workloadgenerator/audit/UserCommandKey.java

@@ -13,7 +13,7 @@
 import org.apache.hadoop.io.WritableComparable;
 
 /**
- * UserCommandKey is a {@link Writable} used as a composite key combining the user id and
+ * UserCommandKey is a {@link WritableComparable} used as a composite key combining the user id and
  * type of a replayed command. It is used as the output key for AuditReplayMapper and the
  * keys for AuditReplayReducer.
  */