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[SPARK-47671][CORE] Enable structured logging in log4j2.properties.te…
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…mplate and update docs

### What changes were proposed in this pull request?

- Rename the current log4j2.properties.template as log4j2.properties.pattern-layout-template
- Enable structured logging in log4j2.properties.template
- Update `configuration.md` on how to configure logging

### Why are the changes needed?

Providing a structured logging template and document how to configure loggings in Spark 4.0.0

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Manual test

### Was this patch authored or co-authored using generative AI tooling?

No

Closes #46349 from gengliangwang/logTemplate.

Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
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gengliangwang authored and dongjoon-hyun committed May 3, 2024
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69 changes: 69 additions & 0 deletions conf/log4j2.properties.pattern-layout-template
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#
# 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
10 changes: 2 additions & 8 deletions conf/log4j2.properties.template
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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
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15 changes: 9 additions & 6 deletions docs/configuration.md
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Expand Up @@ -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

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