svn merge -c 1558948 FIXES: MAPREDUCE-5672. Provide optional RollingFileAppender for container log4j (syslog). Contributed by Gera Shegalov
git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/branches/branch-2@1558957 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Jason Darrell Lowe
parent
e6d2096a18
commit
0fa22b8120
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@ -129,6 +129,9 @@ Release 2.4.0 - UNRELEASED
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MAPREDUCE-5724. JobHistoryServer does not start if HDFS is not running.
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(tucu)
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MAPREDUCE-5672. Provide optional RollingFileAppender for container log4j
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(syslog) (Gera Shegalov via jlowe)
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Release 2.3.0 - UNRELEASED
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INCOMPATIBLE CHANGES
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@ -149,8 +149,10 @@ public class MapReduceChildJVM {
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private static void setupLog4jProperties(Task task,
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Vector<String> vargs,
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long logSize) {
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String logLevel = getChildLogLevel(task.conf, task.isMapTask());
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MRApps.addLog4jSystemProperties(logLevel, logSize, vargs);
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String logLevel = getChildLogLevel(task.conf, task.isMapTask());
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int numBackups = task.conf.getInt(MRJobConfig.TASK_LOG_BACKUPS,
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MRJobConfig.DEFAULT_TASK_LOG_BACKUPS);
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MRApps.addLog4jSystemProperties(logLevel, logSize, numBackups, vargs);
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}
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public static List<String> getVMCommand(
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@ -61,6 +61,7 @@ import org.apache.hadoop.yarn.exceptions.YarnRuntimeException;
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import org.apache.hadoop.yarn.util.ApplicationClassLoader;
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import org.apache.hadoop.yarn.util.Apps;
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import org.apache.hadoop.yarn.util.ConverterUtils;
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import org.apache.log4j.RollingFileAppender;
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/**
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* Helper class for MR applications
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@ -490,15 +491,23 @@ public class MRApps extends Apps {
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* Add the JVM system properties necessary to configure {@link ContainerLogAppender}.
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* @param logLevel the desired log level (eg INFO/WARN/DEBUG)
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* @param logSize See {@link ContainerLogAppender#setTotalLogFileSize(long)}
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* @param numBackups See {@link RollingFileAppender#setMaxBackupIndex(int)}
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* @param vargs the argument list to append to
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*/
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public static void addLog4jSystemProperties(
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String logLevel, long logSize, List<String> vargs) {
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String logLevel, long logSize, int numBackups, List<String> vargs) {
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vargs.add("-Dlog4j.configuration=container-log4j.properties");
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vargs.add("-D" + YarnConfiguration.YARN_APP_CONTAINER_LOG_DIR + "=" +
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ApplicationConstants.LOG_DIR_EXPANSION_VAR);
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vargs.add(
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"-D" + YarnConfiguration.YARN_APP_CONTAINER_LOG_SIZE + "=" + logSize);
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vargs.add("-Dhadoop.root.logger=" + logLevel + ",CLA");
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if (logSize > 0L && numBackups > 0) {
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// log should be rolled
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vargs.add("-D" + YarnConfiguration.YARN_APP_CONTAINER_LOG_BACKUPS + "="
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+ numBackups);
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vargs.add("-Dhadoop.root.logger=" + logLevel + ",CRLA");
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} else {
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vargs.add("-Dhadoop.root.logger=" + logLevel + ",CLA");
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}
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}
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}
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@ -407,6 +407,10 @@ public interface MRJobConfig {
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MR_AM_PREFIX+"log.level";
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public static final String DEFAULT_MR_AM_LOG_LEVEL = "INFO";
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public static final String MR_AM_LOG_BACKUPS =
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MR_AM_PREFIX + "container.log.backups";
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public static final int DEFAULT_MR_AM_LOG_BACKUPS = 0; // don't roll
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/**The number of splits when reporting progress in MR*/
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public static final String MR_AM_NUM_PROGRESS_SPLITS =
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MR_AM_PREFIX+"num-progress-splits";
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@ -681,7 +685,11 @@ public interface MRJobConfig {
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+ "$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*";
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public static final String WORKFLOW_ID = "mapreduce.workflow.id";
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public static final String TASK_LOG_BACKUPS =
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MR_PREFIX + "task.container.log.backups";
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public static final int DEFAULT_TASK_LOG_BACKUPS = 0; // don't roll
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public static final String WORKFLOW_NAME = "mapreduce.workflow.name";
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public static final String WORKFLOW_NODE_NAME =
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@ -815,6 +815,31 @@
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</description>
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</property>
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<property>
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<name>yarn.app.mapreduce.task.container.log.backups</name>
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<value>0</value>
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<description>Number of backup files for task logs when using
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ContainerRollingLogAppender (CRLA). See
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org.apache.log4j.RollingFileAppender.maxBackupIndex. By default,
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ContainerLogAppender (CLA) is used, and container logs are not rolled. CRLA
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is enabled for tasks when both mapreduce.task.userlog.limit.kb and
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yarn.app.mapreduce.task.container.log.backups are greater than zero.
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</description>
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</property>
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<property>
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<name>yarn.app.mapreduce.am.container.log.backups</name>
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<value>0</value>
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<description>Number of backup files for the ApplicationMaster logs when using
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ContainerRollingLogAppender (CRLA). See
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org.apache.log4j.RollingFileAppender.maxBackupIndex. By default,
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ContainerLogAppender (CLA) is used, and container logs are not rolled. CRLA
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is enabled for the ApplicationMaster when both
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mapreduce.task.userlog.limit.kb and
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yarn.app.mapreduce.am.container.log.backups are greater than zero.
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</description>
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</property>
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<property>
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<name>mapreduce.job.userlog.retain.hours</name>
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<value>24</value>
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@ -392,7 +392,9 @@ public class YARNRunner implements ClientProtocol {
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long logSize = TaskLog.getTaskLogLength(new JobConf(conf));
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String logLevel = jobConf.get(
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MRJobConfig.MR_AM_LOG_LEVEL, MRJobConfig.DEFAULT_MR_AM_LOG_LEVEL);
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MRApps.addLog4jSystemProperties(logLevel, logSize, vargs);
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int numBackups = jobConf.getInt(MRJobConfig.MR_AM_LOG_BACKUPS,
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MRJobConfig.DEFAULT_MR_AM_LOG_BACKUPS);
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MRApps.addLog4jSystemProperties(logLevel, logSize, numBackups, vargs);
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// Check for Java Lib Path usage in MAP and REDUCE configs
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warnForJavaLibPath(conf.get(MRJobConfig.MAP_JAVA_OPTS,""), "map",
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@ -23,10 +23,12 @@ import java.io.File;
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import java.io.FileInputStream;
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import java.io.FileNotFoundException;
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import java.io.FileOutputStream;
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import java.io.InputStreamReader;
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import java.io.IOException;
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import java.io.StringReader;
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import java.net.URI;
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import java.security.PrivilegedExceptionAction;
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import java.util.EnumSet;
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import java.util.HashMap;
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import java.util.Map;
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import java.util.jar.JarOutputStream;
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@ -53,6 +55,8 @@ import org.apache.hadoop.io.IOUtils;
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import org.apache.hadoop.io.LongWritable;
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import org.apache.hadoop.io.NullWritable;
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import org.apache.hadoop.io.Text;
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import org.apache.hadoop.mapred.JobConf;
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import org.apache.hadoop.mapred.TaskLog;
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import org.apache.hadoop.mapreduce.Counters;
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import org.apache.hadoop.mapreduce.Job;
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import org.apache.hadoop.mapreduce.JobCounter;
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@ -65,17 +69,22 @@ import org.apache.hadoop.mapreduce.TaskCompletionEvent;
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import org.apache.hadoop.mapreduce.TaskID;
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import org.apache.hadoop.mapreduce.TaskReport;
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import org.apache.hadoop.mapreduce.TaskType;
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import org.apache.hadoop.mapreduce.TypeConverter;
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import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
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import org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter;
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import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
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import org.apache.hadoop.mapreduce.lib.output.NullOutputFormat;
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import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
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import org.apache.hadoop.mapreduce.v2.api.records.JobId;
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import org.apache.hadoop.security.UserGroupInformation;
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import org.apache.hadoop.security.token.Token;
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import org.apache.hadoop.security.token.TokenIdentifier;
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import org.apache.hadoop.util.JarFinder;
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import org.apache.hadoop.util.Shell;
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import org.apache.hadoop.yarn.api.records.ApplicationId;
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import org.apache.hadoop.yarn.conf.YarnConfiguration;
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import org.apache.hadoop.yarn.server.resourcemanager.rmapp.RMAppState;
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import org.apache.log4j.Level;
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import org.junit.AfterClass;
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import org.junit.Assert;
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import org.junit.BeforeClass;
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@ -84,6 +93,9 @@ import org.junit.Test;
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public class TestMRJobs {
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private static final Log LOG = LogFactory.getLog(TestMRJobs.class);
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private static final EnumSet<RMAppState> TERMINAL_RM_APP_STATES =
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EnumSet.of(RMAppState.FINISHED, RMAppState.FAILED, RMAppState.KILLED);
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private static final int NUM_NODE_MGRS = 3;
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protected static MiniMRYarnCluster mrCluster;
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protected static MiniDFSCluster dfsCluster;
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@ -122,7 +134,8 @@ public class TestMRJobs {
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}
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if (mrCluster == null) {
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mrCluster = new MiniMRYarnCluster(TestMRJobs.class.getName(), 3);
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mrCluster = new MiniMRYarnCluster(TestMRJobs.class.getName(),
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NUM_NODE_MGRS);
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Configuration conf = new Configuration();
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conf.set("fs.defaultFS", remoteFs.getUri().toString()); // use HDFS
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conf.set(MRJobConfig.MR_AM_STAGING_DIR, "/apps_staging_dir");
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@ -416,6 +429,115 @@ public class TestMRJobs {
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// TODO later: add explicit "isUber()" checks of some sort
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}
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@Test(timeout = 120000)
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public void testContainerRollingLog() throws IOException,
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InterruptedException, ClassNotFoundException {
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if (!(new File(MiniMRYarnCluster.APPJAR)).exists()) {
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LOG.info("MRAppJar " + MiniMRYarnCluster.APPJAR
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+ " not found. Not running test.");
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return;
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}
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final SleepJob sleepJob = new SleepJob();
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final JobConf sleepConf = new JobConf(mrCluster.getConfig());
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sleepConf.set(MRJobConfig.MAP_LOG_LEVEL, Level.ALL.toString());
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sleepConf.set(MRJobConfig.MR_AM_LOG_LEVEL, Level.ALL.toString());
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sleepConf.setLong(MRJobConfig.TASK_USERLOG_LIMIT, 1);
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sleepConf.setInt(MRJobConfig.TASK_LOG_BACKUPS, 3);
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sleepConf.setInt(MRJobConfig.MR_AM_LOG_BACKUPS, 7);
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sleepJob.setConf(sleepConf);
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final Job job = sleepJob.createJob(1, 0, 1L, 100, 0L, 0);
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job.setJarByClass(SleepJob.class);
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job.addFileToClassPath(APP_JAR); // The AppMaster jar itself.
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job.waitForCompletion(true);
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final JobId jobId = TypeConverter.toYarn(job.getJobID());
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final ApplicationId appID = jobId.getAppId();
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int pollElapsed = 0;
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while (true) {
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Thread.sleep(1000);
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pollElapsed += 1000;
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if (TERMINAL_RM_APP_STATES.contains(
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mrCluster.getResourceManager().getRMContext().getRMApps().get(appID)
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.getState())) {
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break;
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}
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if (pollElapsed >= 60000) {
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LOG.warn("application did not reach terminal state within 60 seconds");
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break;
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}
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}
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Assert.assertEquals(RMAppState.FINISHED, mrCluster.getResourceManager()
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.getRMContext().getRMApps().get(appID).getState());
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// Job finished, verify logs
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//
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final String appIdStr = appID.toString();
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final String appIdSuffix = appIdStr.substring("application_".length(),
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appIdStr.length());
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final String containerGlob = "container_" + appIdSuffix + "_*_*";
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final String syslogGlob = appIdStr
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+ Path.SEPARATOR + containerGlob
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+ Path.SEPARATOR + TaskLog.LogName.SYSLOG;
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int numAppMasters = 0;
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int numMapTasks = 0;
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for (int i = 0; i < NUM_NODE_MGRS; i++) {
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final Configuration nmConf = mrCluster.getNodeManager(i).getConfig();
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for (String logDir :
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nmConf.getTrimmedStrings(YarnConfiguration.NM_LOG_DIRS)) {
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final Path absSyslogGlob =
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new Path(logDir + Path.SEPARATOR + syslogGlob);
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LOG.info("Checking for glob: " + absSyslogGlob);
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final FileStatus[] syslogs = localFs.globStatus(absSyslogGlob);
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for (FileStatus slog : syslogs) {
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// check all syslogs for the container
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//
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final FileStatus[] sysSiblings = localFs.globStatus(new Path(
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slog.getPath().getParent(), TaskLog.LogName.SYSLOG + "*"));
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boolean foundAppMaster = false;
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floop:
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for (FileStatus f : sysSiblings) {
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final BufferedReader reader = new BufferedReader(
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new InputStreamReader(localFs.open(f.getPath())));
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String line;
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try {
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while ((line = reader.readLine()) != null) {
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if (line.contains(MRJobConfig.APPLICATION_MASTER_CLASS)) {
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foundAppMaster = true;
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break floop;
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}
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}
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} finally {
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reader.close();
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}
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}
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if (foundAppMaster) {
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numAppMasters++;
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} else {
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numMapTasks++;
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}
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Assert.assertSame("Number of sylog* files",
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foundAppMaster
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? sleepConf.getInt(MRJobConfig.MR_AM_LOG_BACKUPS, 0) + 1
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: sleepConf.getInt(MRJobConfig.TASK_LOG_BACKUPS, 0) + 1,
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sysSiblings.length);
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}
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}
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}
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// Make sure we checked non-empty set
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//
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Assert.assertEquals("No AppMaster log found!", 1, numAppMasters);
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if (sleepConf.getBoolean(MRJobConfig.JOB_UBERTASK_ENABLE, false)) {
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Assert.assertEquals("MapTask log with uber found!", 0, numMapTasks);
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} else {
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Assert.assertEquals("No MapTask log found!", 1, numMapTasks);
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}
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}
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public static class DistributedCacheChecker extends
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Mapper<LongWritable, Text, NullWritable, NullWritable> {
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@ -928,6 +928,9 @@ public class YarnConfiguration extends Configuration {
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public static final String YARN_APP_CONTAINER_LOG_SIZE =
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YARN_PREFIX + "app.container.log.filesize";
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public static final String YARN_APP_CONTAINER_LOG_BACKUPS =
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YARN_PREFIX + "app.container.log.backups";
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////////////////////////////////
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// Other Configs
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////////////////////////////////
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@ -0,0 +1,65 @@
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/**
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.hadoop.yarn;
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import org.apache.hadoop.classification.InterfaceAudience.Public;
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import org.apache.hadoop.classification.InterfaceStability.Unstable;
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import org.apache.log4j.RollingFileAppender;
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import java.io.File;
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import java.io.Flushable;
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/**
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* A simple log4j-appender for container's logs.
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*
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*/
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@Public
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@Unstable
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public class ContainerRollingLogAppender extends RollingFileAppender
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implements Flushable {
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private String containerLogDir;
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@Override
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public void activateOptions() {
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synchronized (this) {
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setFile(new File(this.containerLogDir, "syslog").toString());
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setAppend(true);
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super.activateOptions();
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}
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}
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@Override
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public void flush() {
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if (qw != null) {
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qw.flush();
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}
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}
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/**
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* Getter/Setter methods for log4j.
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*/
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public String getContainerLogDir() {
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return this.containerLogDir;
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}
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public void setContainerLogDir(String containerLogDir) {
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this.containerLogDir = containerLogDir;
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}
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}
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@ -35,6 +35,13 @@ log4j.appender.CLA.totalLogFileSize=${yarn.app.container.log.filesize}
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log4j.appender.CLA.layout=org.apache.log4j.PatternLayout
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log4j.appender.CLA.layout.ConversionPattern=%d{ISO8601} %p [%t] %c: %m%n
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log4j.appender.CRLA=org.apache.hadoop.yarn.ContainerRollingLogAppender
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log4j.appender.CRLA.containerLogDir=${yarn.app.container.log.dir}
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log4j.appender.CRLA.maximumFileSize=${yarn.app.container.log.filesize}
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log4j.appender.CRLA.maxBackupIndex=${yarn.app.container.log.backups}
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log4j.appender.CRLA.layout=org.apache.log4j.PatternLayout
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log4j.appender.CRLA.layout.ConversionPattern=%d{ISO8601} %p [%t] %c: %m%n
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#
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# Event Counter Appender
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# Sends counts of logging messages at different severity levels to Hadoop Metrics.
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