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cornel creanga commented on SPARK-39804: ---------------------------------------- Spark will only load the default file when no custom configuration was declared (it check to see if log4j2 is using the org.apache.logging.log4j.core.config.DefaultConfiguration) If you need an example how to declare a configuration programmatically you can take a look on my git repo [here|[http://example.com|https://github.com/cornelcreanga/spark-playground/blob/master/examples/src/main/scala/com/creanga/playground/spark/example/logging/CustomConfigurationFactory.java]]. > Override Spark Core_2.12 (v3.3.0) logging configuration > ------------------------------------------------------- > > Key: SPARK-39804 > URL: https://issues.apache.org/jira/browse/SPARK-39804 > Project: Spark > Issue Type: Question > Components: Spark Core > Affects Versions: 3.3.0 > Reporter: Jitin Dominic > Priority: Major > > I'm using Grails 2.5.4 and trying to use _SparkSession_ instance for > generating a Parquet output. Recently, upgraded the spark core and it's > related dependencies to their latest version(v3.3.0). > > During the SparkSession builder() initialization, I notice that some extra > logs are getting displayed: > > {noformat} > Using Spark's default log4j profile: > org/apache/spark/log4j2-defaults.properties > 22/07/13 11:58:54 WARN Utils: Your hostname, XY resolves to a loopback > address: 127.0.1.1; using 1XX.1XX.0.1XX instead (on interface wlo1) > 22/07/13 11:58:54 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to > another address > 22/07/13 11:58:54 INFO SparkContext: Running Spark version 3.3.0 > 22/07/13 11:58:54 WARN NativeCodeLoader: Unable to load native-hadoop library > for your platform... using builtin-java classes where applicable > 22/07/13 11:58:54 INFO ResourceUtils: > ============================================================== > 22/07/13 11:58:54 INFO ResourceUtils: No custom resources configured for > spark.driver. > 22/07/13 11:58:54 INFO ResourceUtils: > ============================================================== > 22/07/13 11:58:54 INFO SparkContext: Submitted application: ABCDE > 22/07/13 11:58:54 INFO ResourceProfile: Default ResourceProfile created, > executor resources: Map(cores -> name: cores, amount: 1, script: , vendor: , > memory -> name: memory, amount: 1024, script: , vendor: , offHeap -> name: > offHeap, amount: 0, script: , vendor: ), task resources: Map(cpus -> name: > cpus, amount: 1.0) > 22/07/13 11:58:54 INFO ResourceProfile: Limiting resource is cpu > 22/07/13 11:58:54 INFO ResourceProfileManager: Added ResourceProfile id: 0 > 22/07/13 11:58:54 INFO SecurityManager: Changing view acls to: xy > 22/07/13 11:58:54 INFO SecurityManager: Changing modify acls to: xy > 22/07/13 11:58:54 INFO SecurityManager: Changing view acls groups to: > 22/07/13 11:58:54 INFO SecurityManager: Changing modify acls groups to: > 22/07/13 11:58:54 INFO SecurityManager: SecurityManager: authentication > disabled; ui acls disabled; users with view permissions: Set(xy); groups > with view permissions: Set(); users with modify permissions: Set(xy); groups > with modify permissions: Set() > 22/07/13 11:58:54 INFO Utils: Successfully started service 'sparkDriver' on > port 39483. > 22/07/13 11:58:54 INFO SparkEnv: Registering MapOutputTracker > 22/07/13 11:58:54 INFO SparkEnv: Registering BlockManagerMaster > 22/07/13 11:58:54 INFO BlockManagerMasterEndpoint: Using > org.apache.spark.storage.DefaultTopologyMapper for getting topology > information > 22/07/13 11:58:54 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint > up > 22/07/13 11:58:54 INFO SparkEnv: Registering BlockManagerMasterHeartbeat > 22/07/13 11:58:55 INFO DiskBlockManager: Created local directory at > /tmp/blockmgr-cf39a58e-e5bc-4a26-b92a-d945a0deb8e7 > 22/07/13 11:58:55 INFO MemoryStore: MemoryStore started with capacity 2004.6 > MiB > 22/07/13 11:58:55 INFO SparkEnv: Registering OutputCommitCoordinator > 22/07/13 11:58:55 INFO Utils: Successfully started service 'SparkUI' on port > 4040. > 22/07/13 11:58:55 INFO Executor: Starting executor ID driver on host > 1XX.1XX.0.1XX > 22/07/13 11:58:55 INFO Executor: Starting executor with user classpath > (userClassPathFirst = false): '' > 22/07/13 11:58:55 INFO Utils: Successfully started service > 'org.apache.spark.network.netty.NettyBlockTransferService' on port 33993. > 22/07/13 11:58:55 INFO NettyBlockTransferService: Server created on > 192.168.0.135:33993 > 22/07/13 11:58:55 INFO BlockManager: Using > org.apache.spark.storage.RandomBlockReplicationPolicy for block replication > policy > 22/07/13 11:58:55 INFO BlockManagerMaster: Registering BlockManager > BlockManagerId(driver, 192.168.0.135, 33993, None) > 22/07/13 11:58:55 INFO BlockManagerMasterEndpoint: Registering block manager > 192.168.0.135:33993 with 2004.6 MiB RAM, BlockManagerId(driver, > 192.168.0.135, 33993, None) > 22/07/13 11:58:55 INFO BlockManagerMaster: Registered BlockManager > BlockManagerId(driver, 192.168.0.135, 33993, None) > 22/07/13 11:58:55 INFO BlockManager: Initialized BlockManager: > BlockManagerId(driver, 192.168.0.135, 33993, None){noformat} > > Before initializing the SparkSession instance using the builder() method, > I've configured the logger level programmatically by: > {code:java} > Configurator.setLevel("org", Level.ERROR) > Configurator.setLevel("org.apache.spark", Level.ERROR) > Configurator.setLevel("akka", Level.ERROR) > Configurator.setLevel("scala", Level.ERROR) > Configurator.setLevel("java", Level.ERROR) > Configurator.setLevel("org.slf4j", Level.ERROR) > Configurator.setLevel("com", Level.ERROR) > Configurator.setLevel("javax", Level.ERROR) > Configurator.setLevel("jakarta", Level.ERROR) > Configurator.setLevel("io", Level.ERROR) > Configurator.setLevel("net", Level.ERROR) > {code} > I notice that it's picking the default _log4j2.properties_ file of Spark. Is > there a way I can override the logging configuration programatically or > disable this default logging so that these extra logs don't appear ? -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org