Merge pull request #102174 from dagiro/ts_yarn3

ts_yarn3

Author: v-albemi

articles/hdinsight/hdinsight-hadoop-access-yarn-app-logs-linux.md

@@ -5,9 +5,9 @@ author: hrasheed-msft
 ms.author: hrasheed
 ms.reviewer: jasonh
 ms.service: hdinsight
-ms.custom: hdinsightactive
 ms.topic: conceptual
-ms.date: 11/15/2019
+ms.custom: hdinsightactive
+ms.date: 01/23/2020
 ---
 
 # Access Apache Hadoop YARN application logs on Linux-based HDInsight
@@ -22,7 +22,7 @@ Each application may consist of multiple *application attempts*. If an applicati
 
 To scale your cluster to support greater processing throughput, you can use [Autoscale](hdinsight-autoscale-clusters.md) or [Scale your clusters manually using a few different languages](hdinsight-scaling-best-practices.md#utilities-to-scale-clusters).
 
-## <a name="YARNTimelineServer"></a>YARN Timeline Server
+## YARN Timeline Server
 
 The [Apache Hadoop YARN Timeline Server](https://hadoop.apache.org/docs/r2.7.3/hadoop-yarn/hadoop-yarn-site/TimelineServer.html) provides generic information on completed applications
 
@@ -33,36 +33,123 @@ YARN Timeline Server includes the following type of data:
 * Information on attempts made to complete the application
 * The containers used by any given application attempt
 
-## <a name="YARNAppsAndLogs"></a>YARN applications and logs
+## YARN applications and logs
 
 YARN supports multiple programming models ([Apache Hadoop MapReduce](https://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html)  being one of them) by decoupling resource management from application scheduling/monitoring. YARN uses a global *ResourceManager* (RM), per-worker-node *NodeManagers* (NMs), and per-application *ApplicationMasters* (AMs). The per-application AM negotiates resources (CPU, memory, disk, network) for running your application with the RM. The RM works with NMs to grant these resources, which are granted as *containers*. The AM is responsible for tracking the progress of the containers assigned to it by the RM. An application may require many containers depending on the nature of the application.
 
 Each application may consist of multiple *application attempts*. If an application fails, it may be retried as a new attempt. Each attempt runs in a container. In a sense, a container provides the context for basic unit of work performed by a YARN application. All work that is done within the context of a container is performed on the single worker node on which the container was allocated. See [Apache Hadoop YARN Concepts](https://hadoop.apache.org/docs/r2.7.4/hadoop-yarn/hadoop-yarn-site/WritingYarnApplications.html) for further reference.
 
 Application logs (and the associated container logs) are critical in debugging problematic Hadoop applications. YARN provides a nice framework for collecting, aggregating, and storing application logs with the [Log Aggregation](https://hortonworks.com/blog/simplifying-user-logs-management-and-access-in-yarn/) feature. The Log Aggregation feature makes accessing application logs more deterministic. It aggregates logs across all containers on a worker node and stores them as one aggregated log file per worker node. The log is stored on the default file system after an application finishes. Your application may use hundreds or thousands of containers, but logs for all containers run on a single worker node are always aggregated to a single file. So there's only 1 log per worker node used by your application. Log Aggregation is enabled by default on HDInsight clusters version 3.0 and above. Aggregated logs are located in default storage for the cluster. The following path is the HDFS path to the logs:
 
-    /app-logs/<user>/logs/<applicationId>
+```
+/app-logs/<user>/logs/<applicationId>
+```
 
 In the path, `user` is the name of the user who started the application. The `applicationId` is the unique identifier assigned to an application by the YARN RM.
 
 The aggregated logs aren't directly readable, as they're written in a [TFile](https://issues.apache.org/jira/secure/attachment/12396286/TFile%20Specification%2020081217.pdf), [binary format](https://issues.apache.org/jira/browse/HADOOP-3315) indexed by container. Use the YARN ResourceManager logs or CLI tools to view these logs as plain text for applications or containers of interest.
 
+## Yarn logs in an ESP cluster
+
+Two configurations must be added to the custom `mapred-site` in Ambari.
+
+1. From a web browser, navigate to `https://CLUSTERNAME.azurehdinsight.net`, where `CLUSTERNAME` is the name of your cluster.
+
+1. From the Ambari UI, navigate to **MapReduce2** > **Configs** > **Advanced** > **Custom mapred-site**.
+
+1. Add *one* of the following sets of properties:
+
+    **Set 1**
+
+    ```
+    mapred.acls.enabled=true
+    mapreduce.job.acl-view-job=*
+    ```
+
+    **Set 2**
+
+    ```
+    mapreduce.job.acl-view-job=<user1>,<user2>,<user3>
+    ```
+
+1. Save changes and restart all affected services.
+
 ## YARN CLI tools
 
-To use the YARN CLI tools, you must first connect to the HDInsight cluster using SSH. For information, see [Use SSH with HDInsight](hdinsight-hadoop-linux-use-ssh-unix.md).
+1. Use [ssh command](./hdinsight-hadoop-linux-use-ssh-unix.md) to connect to your cluster. Edit the command below by replacing CLUSTERNAME with the name of your cluster, and then enter the command:
+
+    ```cmd
+    ssh [email protected]
+    ```
+
+1. List all the application ids of the currently running Yarn applications with the following command:
+
+    ```bash
+    yarn top
+    ```
 
-You can view these logs as plain text by running one of the following commands:
+    Note the application id from the `APPLICATIONID` column whose logs are to be downloaded.
 
+    ```output
+    YARN top - 18:00:07, up 19d, 0:14, 0 active users, queue(s): root
+    NodeManager(s): 4 total, 4 active, 0 unhealthy, 0 decommissioned, 0 lost, 0 rebooted
+    Queue(s) Applications: 2 running, 10 submitted, 0 pending, 8 completed, 0 killed, 0 failed
+    Queue(s) Mem(GB): 97 available, 3 allocated, 0 pending, 0 reserved
+    Queue(s) VCores: 58 available, 2 allocated, 0 pending, 0 reserved
+    Queue(s) Containers: 2 allocated, 0 pending, 0 reserved
+    
+                      APPLICATIONID USER             TYPE      QUEUE   #CONT  #RCONT  VCORES RVCORES     MEM    RMEM  VCORESECS    MEMSECS %PROGR       TIME NAME
+     application_1490377567345_0007 hive            spark  thriftsvr       1       0       1       0      1G      0G    1628407    2442611  10.00   18:20:20 Thrift JDBC/ODBC Server
+     application_1490377567345_0006 hive            spark  thriftsvr       1       0       1       0      1G      0G    1628430    2442645  10.00   18:20:20 Thrift JDBC/ODBC Server
+    ```
+
+1. You can view these logs as plain text by running one of the following commands:
+
+    ```bash
     yarn logs -applicationId <applicationId> -appOwner <user-who-started-the-application>
     yarn logs -applicationId <applicationId> -appOwner <user-who-started-the-application> -containerId <containerId> -nodeAddress <worker-node-address>
+    ```
+
+    Specify the &lt;applicationId>, &lt;user-who-started-the-application>, &lt;containerId>, and &lt;worker-node-address> information when running these commands.
+
+### Other sample commands
+
+1. Download Yarn containers logs for all application masters with the command below. This will create the log file named `amlogs.txt` in text format.
+
+    ```bash
+    yarn logs -applicationId <application_id> -am ALL > amlogs.txt
+    ```
+
+1. Download Yarn container logs for only the latest application master with the following command:
 
-Specify the &lt;applicationId>, &lt;user-who-started-the-application>, &lt;containerId>, and &lt;worker-node-address> information when running these commands.
+    ```bash
+    yarn logs -applicationId <application_id> -am -1 > latestamlogs.txt
+    ```
+
+1. Download YARN container logs for first two application masters with the following command:
+
+    ```bash
+    yarn logs -applicationId <application_id> -am 1,2 > first2amlogs.txt
+    ```
+
+1. Download all Yarn container logs with the following command:
+
+    ```bash
+    yarn logs -applicationId <application_id> > logs.txt
+    ```
+
+1. Download yarn container log for a particular container with the following command:
+
+    ```bash
+    yarn logs -applicationId <application_id> -containerId <container_id> > containerlogs.txt
+    ```
 
 ## YARN ResourceManager UI
 
 The YARN ResourceManager UI runs on the cluster headnode. It's accessed through the Ambari web UI. Use the following steps to view the YARN logs:
 
 1. In your web browser, navigate to `https://CLUSTERNAME.azurehdinsight.net`. Replace CLUSTERNAME with the name of your HDInsight cluster.
+
 2. From the list of services on the left, select **YARN**.
 
     ![Apache Ambari Yarn service selected](./media/hdinsight-hadoop-access-yarn-app-logs-linux/yarn-service-selected.png)