[SPARK-47671][Core] Enable structured logging in log4j2.properties.template and update docs

conf/log4j2.properties.pattern-layout-template

@@ -0,0 +1,69 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# Set everything to be logged to the console
+rootLogger.level = info
+rootLogger.appenderRef.stdout.ref = console
+
+# In the pattern layout configuration below, we specify an explicit `%ex` conversion
+# pattern for logging Throwables. If this was omitted, then (by default) Log4J would
+# implicitly add an `%xEx` conversion pattern which logs stacktraces with additional
+# class packaging information. That extra information can sometimes add a substantial
+# performance overhead, so we disable it in our default logging config.
+# For more information, see SPARK-39361.
+appender.console.type = Console
+appender.console.name = console
+appender.console.target = SYSTEM_ERR
+appender.console.layout.type = PatternLayout
+appender.console.layout.pattern = %d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n%ex
+
+# Set the default spark-shell/spark-sql log level to WARN. When running the
+# spark-shell/spark-sql, the log level for these classes is used to overwrite
+# the root logger's log level, so that the user can have different defaults
+# for the shell and regular Spark apps.
+logger.repl.name = org.apache.spark.repl.Main
+logger.repl.level = warn
+
+logger.thriftserver.name = org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver
+logger.thriftserver.level = warn
+
+# Settings to quiet third party logs that are too verbose
+logger.jetty1.name = org.sparkproject.jetty
+logger.jetty1.level = warn
+logger.jetty2.name = org.sparkproject.jetty.util.component.AbstractLifeCycle
+logger.jetty2.level = error
+logger.replexprTyper.name = org.apache.spark.repl.SparkIMain$exprTyper
+logger.replexprTyper.level = info
+logger.replSparkILoopInterpreter.name = org.apache.spark.repl.SparkILoop$SparkILoopInterpreter
+logger.replSparkILoopInterpreter.level = info
+logger.parquet1.name = org.apache.parquet
+logger.parquet1.level = error
+logger.parquet2.name = parquet
+logger.parquet2.level = error
+
+# SPARK-9183: Settings to avoid annoying messages when looking up nonexistent UDFs in SparkSQL with Hive support
+logger.RetryingHMSHandler.name = org.apache.hadoop.hive.metastore.RetryingHMSHandler
+logger.RetryingHMSHandler.level = fatal
+logger.FunctionRegistry.name = org.apache.hadoop.hive.ql.exec.FunctionRegistry
+logger.FunctionRegistry.level = error
+
+# For deploying Spark ThriftServer
+# SPARK-34128: Suppress undesirable TTransportException warnings involved in THRIFT-4805
+appender.console.filter.1.type = RegexFilter
+appender.console.filter.1.regex = .*Thrift error occurred during processing of message.*
+appender.console.filter.1.onMatch = deny
+appender.console.filter.1.onMismatch = neutral

conf/log4j2.properties.template

@@ -19,17 +19,11 @@
 rootLogger.level = info
 rootLogger.appenderRef.stdout.ref = console
 
-# In the pattern layout configuration below, we specify an explicit `%ex` conversion
-# pattern for logging Throwables. If this was omitted, then (by default) Log4J would
-# implicitly add an `%xEx` conversion pattern which logs stacktraces with additional
-# class packaging information. That extra information can sometimes add a substantial
-# performance overhead, so we disable it in our default logging config.
-# For more information, see SPARK-39361.
 appender.console.type = Console
 appender.console.name = console
 appender.console.target = SYSTEM_ERR
-appender.console.layout.type = PatternLayout
-appender.console.layout.pattern = %d{yy/MM/dd HH:mm:ss} %p %c{1}: %m%n%ex
+appender.console.layout.type = JsonTemplateLayout
+appender.console.layout.eventTemplateUri = classpath:org/apache/spark/SparkLayout.json
 
 # Set the default spark-shell/spark-sql log level to WARN. When running the
 # spark-shell/spark-sql, the log level for these classes is used to overwrite

docs/configuration.md

@@ -3670,14 +3670,17 @@ Note: When running Spark on YARN in `cluster` mode, environment variables need t
 # Configuring Logging
 
 Spark uses [log4j](http://logging.apache.org/log4j/) for logging. You can configure it by adding a
-`log4j2.properties` file in the `conf` directory. One way to start is to copy the existing
-`log4j2.properties.template` located there.
+`log4j2.properties` file in the `conf` directory. One way to start is to copy the existing templates `log4j2.properties.template` or `log4j2.properties.pattern-layout-template` located there.
 
-By default, Spark adds 1 record to the MDC (Mapped Diagnostic Context): `mdc.taskName`, which shows something
-like `task 1.0 in stage 0.0`. You can add `%X{mdc.taskName}` to your patternLayout in
-order to print it in the logs.
+## Structured Logging
+Starting from version 4.0.0, Spark has adopted the [JSON Template Layout](https://logging.apache.org/log4j/2.x/manual/json-template-layout.html) for logging, which outputs logs in JSON format. This format facilitates querying logs using Spark SQL with the JSON data source. Additionally, the logs include all Mapped Diagnostic Context (MDC) information for search and debugging purposes.
+
+To implement structured logging, start with the `log4j2.properties.template` file.
+
+## Plain Text Logging
+If you prefer plain text logging, you can use the `log4j2.properties.pattern-layout-template` file as a starting point. This is the default configuration used by Spark before the 4.0.0 release. This configuration uses the [PatternLayout](https://logging.apache.org/log4j/2.x/manual/layouts.html#PatternLayout) to log all the logs in plain text. MDC information is not included by default. In order to print it in the logs, you can update the patternLayout in the file. For example, you can add `%X{mdc.taskName}` to print the task name in the logs.
 Moreover, you can use `spark.sparkContext.setLocalProperty(s"mdc.$name", "value")` to add user specific data into MDC.
-The key in MDC will be the string of "mdc.$name".
+The key in MDC will be the string of `mdc.$name`.
 
 # Overriding configuration directory