[
https://issues.apache.org/jira/browse/SPARK-26101?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Maziyar PANAHI updated SPARK-26101:
-----------------------------------
Description:
Hello,
I am using *Spark 2.3.0.cloudera3* on Cloudera cluster. When I start my Spark
session (Zeppelin, Shell, or spark-submit) my real username is being
impersonated successfully. That allows YARN to use the right queue based on the
username, also HDFS knows the permissions.
Example (running Spark by user `panahi`):
```
18/11/17 13:55:47 INFO spark.SecurityManager: Changing view acls to: *panahi*
18/11/17 13:55:47 INFO spark.SecurityManager: Changing modify acls to: *panahi*
18/11/17 13:55:47 INFO spark.SecurityManager: Changing view acls groups to:
18/11/17 13:55:47 INFO spark.SecurityManager: Changing modify acls groups to:
18/11/17 13:55:47 INFO spark.SecurityManager: SecurityManager: authentication
disabled; ui acls disabled; users with view permissions: Set(mpanahi); groups
with view permissions: Set();
users with modify permissions: Set(*panahi*); groups with modify permissions:
Set()
...
18/11/17 13:55:52 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: root.multivac
start time: 1542459353040
final status: UNDEFINED
tracking URL:
[http://hadoop-master-1:8088/proxy/application_1542456252041_0006/]
user: *panahi*
```
However, when I use Spark RDD Pipe() it is being executed as `yarn` user. This
makes it impossible to use a `c/c++` application that needs read/write access
to HDFS because the user `yarn` does not have permissions on the user's
directory.
How to produce this issue:
```
val test = sc.parallelize(Seq("test user")).repartition(1)
val piped = test.pipe(Seq("whoami"))
val c = piped.collect()
*result:*
test: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[26] at repartition at
<console>:37 piped: org.apache.spark.rdd.RDD[String] = PipedRDD[27] at pipe at
<console>:37 c: Array[String] = Array(*yarn*)
```
I believe since Spark is the key actor to invoke this execution inside YARN
cluster, Spark needs to respect the actual/current username. Or maybe there is
another config for impersonation between Spark and YARN in this situation, but
I haven't found any.
Many thanks.
was:
Hello,
I am using `Spark 2.3.0.cloudera3` on Cloudera cluster. When I start my Spark
session (Zeppelin, Shell, or spark-submit) my real username is being
impersonated successfully. That allows YARN to use the right queue based on the
username, also HDFS knows the permissions.
Example (running Spark by user `panahi`):
```
18/11/17 13:55:47 INFO spark.SecurityManager: Changing view acls to: *panahi*
18/11/17 13:55:47 INFO spark.SecurityManager: Changing modify acls to: *panahi*
18/11/17 13:55:47 INFO spark.SecurityManager: Changing view acls groups to:
18/11/17 13:55:47 INFO spark.SecurityManager: Changing modify acls groups to:
18/11/17 13:55:47 INFO spark.SecurityManager: SecurityManager: authentication
disabled; ui acls disabled; users with view permissions: Set(mpanahi); groups
with view permissions: Set();
users with modify permissions: Set(*panahi*); groups with modify permissions:
Set()
...
18/11/17 13:55:52 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: root.multivac
start time: 1542459353040
final status: UNDEFINED
tracking URL: http://hadoop-master-1:8088/proxy/application_1542456252041_0006/
user: *panahi*
```
However, when I use Spark RDD Pipe() it is being executed as `yarn` user. This
makes it impossible to use a `c/c++` application that needs read/write access
to HDFS because the user `yarn` does not have permissions on the user's
directory.
How to produce this issue:
```scala
val test = sc.parallelize(Seq("test user")).repartition(1)
val piped = test.pipe(Seq("whoami"))
val c = piped.collect()
*result:*
test: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[26] at repartition at
<console>:37 piped: org.apache.spark.rdd.RDD[String] = PipedRDD[27] at pipe at
<console>:37 c: Array[String] = Array(*yarn*)
```
I believe since Spark is the key actor to invoke this execution inside YARN
cluster, Spark needs to respect the actual/current username. Or maybe there is
another config for impersonation between Spark and YARN in this situation, but
I haven't found any.
Many thanks.
> Spark Pipe() executes the external app by yarn user not the real user
> ---------------------------------------------------------------------
>
> Key: SPARK-26101
> URL: https://issues.apache.org/jira/browse/SPARK-26101
> Project: Spark
> Issue Type: Bug
> Components: YARN
> Affects Versions: 2.3.0
> Reporter: Maziyar PANAHI
> Priority: Major
>
> Hello,
>
> I am using *Spark 2.3.0.cloudera3* on Cloudera cluster. When I start my Spark
> session (Zeppelin, Shell, or spark-submit) my real username is being
> impersonated successfully. That allows YARN to use the right queue based on
> the username, also HDFS knows the permissions.
> Example (running Spark by user `panahi`):
> ```
> 18/11/17 13:55:47 INFO spark.SecurityManager: Changing view acls to: *panahi*
> 18/11/17 13:55:47 INFO spark.SecurityManager: Changing modify acls to:
> *panahi*
> 18/11/17 13:55:47 INFO spark.SecurityManager: Changing view acls groups to:
> 18/11/17 13:55:47 INFO spark.SecurityManager: Changing modify acls groups to:
> 18/11/17 13:55:47 INFO spark.SecurityManager: SecurityManager: authentication
> disabled; ui acls disabled; users with view permissions: Set(mpanahi); groups
> with view permissions: Set();
> users with modify permissions: Set(*panahi*); groups with modify permissions:
> Set()
> ...
> 18/11/17 13:55:52 INFO yarn.Client:
> client token: N/A
> diagnostics: N/A
> ApplicationMaster host: N/A
> ApplicationMaster RPC port: -1
> queue: root.multivac
> start time: 1542459353040
> final status: UNDEFINED
> tracking URL:
> [http://hadoop-master-1:8088/proxy/application_1542456252041_0006/]
> user: *panahi*
> ```
> However, when I use Spark RDD Pipe() it is being executed as `yarn` user.
> This makes it impossible to use a `c/c++` application that needs read/write
> access to HDFS because the user `yarn` does not have permissions on the
> user's directory.
> How to produce this issue:
> ```
> val test = sc.parallelize(Seq("test user")).repartition(1)
> val piped = test.pipe(Seq("whoami"))
> val c = piped.collect()
> *result:*
> test: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[26] at repartition
> at <console>:37 piped: org.apache.spark.rdd.RDD[String] = PipedRDD[27] at
> pipe at <console>:37 c: Array[String] = Array(*yarn*)
> ```
> I believe since Spark is the key actor to invoke this execution inside YARN
> cluster, Spark needs to respect the actual/current username. Or maybe there
> is another config for impersonation between Spark and YARN in this situation,
> but I haven't found any.
>
> Many thanks.
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