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Posted to issues@spark.apache.org by "Faisal (JIRA)" <ji...@apache.org> on 2016/06/16 20:11:05 UTC

[jira] [Created] (SPARK-15999) Wrong/Missing information for Spark UI/REST port

Faisal created SPARK-15999:
------------------------------

             Summary: Wrong/Missing information for Spark UI/REST port
                 Key: SPARK-15999
                 URL: https://issues.apache.org/jira/browse/SPARK-15999
             Project: Spark
          Issue Type: Bug
          Components: Documentation, Streaming
    Affects Versions: 1.5.0
         Environment: CDH5.5.2, Spark 1.5.0
            Reporter: Faisal
            Priority: Minor


*Spark Monitoring documentation*

https://spark.apache.org/docs/1.5.0/monitoring.html

{quote}
You can access this interface by simply opening http://<driver-node>:4040 in a web browser. If multiple SparkContexts are running on the same host, they will bind to successive ports beginning with 4040 (4041, 4042, etc).
{quote}
This statement is very confusing and doesn't apply at all in spark streaming jobs(unless i am missing something)

Same is the case with REST API calls.
{quote}
REST API
In addition to viewing the metrics in the UI, they are also available as JSON. This gives developers an easy way to create new visualizations and monitoring tools for Spark. The JSON is available for both running applications, and in the history server. The endpoints are mounted at /api/v1. Eg., for the history server, they would typically be accessible at http://<server-url>:18080/api/v1, and for a running application, at http://localhost:4040/api/v1.
{quote}

I am running spark streaming job in CDH-5.5.2 Spark version 1.5.0
and nowhere on driver node, executor node for running/live application i am able to call rest service.
My spark streaming jobs running in yarn cluster mode
--master yarn-cluster

However for historyServer
i am able to call REST service and can pull up json messages
using the URL
http://historyServer:18088/api/v1/applications
{code}
[ {
  "id" : "application_1463099418950_11465",
  "name" : "PySparkShell",
  "attempts" : [ {
    "startTime" : "2016-06-15T15:28:32.460GMT",
    "endTime" : "2016-06-15T19:01:39.100GMT",
    "sparkUser" : "abc",
    "completed" : true
  } ]
}, {
  "id" : "application_1463099418950_11635",
  "name" : "DataProcessor-ETL.ETIME",
  "attempts" : [ {
    "attemptId" : "1",
    "startTime" : "2016-06-15T18:56:04.413GMT",
    "endTime" : "2016-06-15T18:58:00.022GMT",
    "sparkUser" : "abc",
    "completed" : true
  } ]
}, 
{code}





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