4dabba8f76
### What changes were proposed in this pull request?
In a secure Yarn cluster, even though HBase or Kafka, or Hive services are not used in the user application, yarn client unnecessarily trying to generate Delegations token from these services. This will add additional delays while submitting spark application in a yarn cluster
Also during HBase delegation token generation step in the application submit stage, HBaseDelegationTokenProvider prints a full Exception Stack trace and it causes a noisy warning.
Apart from printing exception stack trace, Application submission taking more time as it retries connection to HBase master multiple times before it gives up. So, if HBase is not used in the user Applications, it is better to suggest User disable HBase Delegation Token generation.
This PR aims to avoid printing full Exception Stack by just printing just Exception name and also add a suggestion message to disable `Delegation Token generation` if service is not used in the Spark Application.
eg: `If HBase is not used, set spark.security.credentials.hbase.enabled to false`
### Why are the changes needed?
To avoid printing full Exception stack trace in WARN log
#### Before the fix
----------------
```
spark-shell --master yarn
.......
.......
21/06/12 14:29:41 WARN security.HBaseDelegationTokenProvider: Failed to get token from service hbase
java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.security.HBaseDelegationTokenProvider.obtainDelegationTokensWithHBaseConn(HBaseDelegationT
okenProvider.scala:93)
at org.apache.spark.deploy.security.HBaseDelegationTokenProvider.obtainDelegationTokens(HBaseDelegationTokenProvider.
scala:60)
at org.apache.spark.deploy.security.HadoopDelegationTokenManager$$anonfun$6.apply(HadoopDelegationTokenManager.scala:
166)
at org.apache.spark.deploy.security.HadoopDelegationTokenManager$$anonfun$6.apply(HadoopDelegationTokenManager.scala:
164)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at scala.collection.MapLike$DefaultValuesIterable.foreach(MapLike.scala:206)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
at org.apache.spark.deploy.security.HadoopDelegationTokenManager.obtainDelegationTokens(HadoopDelegationTokenManager.
scala:164)
```
#### After the fix
------------
```
spark-shell --master yarn
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
21/06/13 02:10:02 WARN security.HBaseDelegationTokenProvider: Failed to get token from service hbase due to java.lang.reflect.InvocationTargetException Retrying to fetch HBase security token with hbase connection parameter.
21/06/13 02:10:40 WARN security.HBaseDelegationTokenProvider: Failed to get token from service hbase java.lang.reflect.InvocationTargetException. If HBase is not used, set spark.security.credentials.hbase.enabled to false
21/06/13 02:10:47 WARN cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request executors before the AM has registered!
```
### Does this PR introduce _any_ user-facing change?
Yes, in the log, it avoids printing full Exception stack trace.
Instread prints this.
**WARN security.HBaseDelegationTokenProvider: Failed to get token from service hbase java.lang.reflect.InvocationTargetException. If HBase is not used, set spark.security.credentials.hbase.enabled to false**
### How was this patch tested?
Tested manually as it can be verified only in a secure cluster
Closes #32894 from vinodkc/br_fix_Hbase_DT_Exception_stack_printing.
Authored-by: Vinod KC <vinod.kc.in@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
|
||
|---|---|---|
| .. | ||
| catalyst | ||
| core | ||
| hive | ||
| hive-thriftserver | ||
| create-docs.sh | ||
| gen-sql-api-docs.py | ||
| gen-sql-config-docs.py | ||
| gen-sql-functions-docs.py | ||
| mkdocs.yml | ||
| README.md | ||
Spark SQL
This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.
Spark SQL is broken up into four subprojects:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
- Hive Support (sql/hive) - Includes extensions that allow users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow users to run queries that include Hive UDFs, UDAFs, and UDTFs.
- HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.
Running ./sql/create-docs.sh generates SQL documentation for built-in functions under sql/site, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.