Output Spark application id in the logs with Log4j - json

Question

I have a custom Log4j file for the Spark application. I would like to output Spark app id along with other attributes like message and date so the JSON string structure would look like this:
{"name":,"time":,"date":,"level":,"thread":,"message":,"app_id":}
Now, this structure looks like this:
{"name":,"time":,"date":,"level":,"thread":,"message":}
How can I define such layout for the Spark driver logs?
My log4j file looks like this:
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE log4j:configuration SYSTEM "log4j.dtd">
<log4j:configuration xmlns:log4j='http://jakarta.apache.org/log4j/'>
<appender name="Json" class="org.apache.log4j.ConsoleAppender">
<layout class="org.apache.hadoop.log.Log4Json">
<param name="ConversionLayout" value=""/>
</layout>
</appender>
<root>
<level value="INFO"/>
<appender-ref ref="Json"/>
</root>
</log4j:configuration>

Answer 1

I doubt that org.apache.hadoop.log.Log4Json can be adjusted for this purpose. According to its javadoc and source code it might be rather cumbersome.
Although it looks like you are using Log4j 1x, its API is quite flexible and we can easily define our own layout by extending org.apache.log4j.Layout.
We'll need a case class that will be transformed into JSON according to the target structure:
case class LoggedMessage(name: String,
appId: String,
thread: String,
time: Long,
level: String,
message: String)
And Layout might be extended as follows. To access the value of "app_id", we'll use Log4j's Mapped Diagnostic Context
import org.apache.log4j.Layout
import org.apache.log4j.spi.LoggingEvent
import org.json4s.DefaultFormats
import org.json4s.native.Serialization.write
class JsonLoggingLayout extends Layout {
// required by the API
override def ignoresThrowable(): Boolean = false
// required by the API
override def activateOptions(): Unit = { /* nothing */ }
override def format(event: LoggingEvent): String = {
// we are using json4s for JSON serialization
implicit val formats = DefaultFormats
// retrieve app_id from Mapped Diagnostic Context
val appId = event.getMDC("app_id") match {
case null => "[no_app]" // logged messages outside our app
case defined: AnyRef => defined.toString
}
val message = LoggedMessage("TODO",
appId,
Thread.currentThread().getName,
event.getTimeStamp,
event.getLevel.toString,
event.getMessage.toString)
write(message) + "\n"
}
}
Finally, when the Spark session is created, we put the app_id value into MDC:
import org.apache.log4j.{Logger, MDC}
// create Spark session
MDC.put("app_id", session.sparkContext.applicationId)
logger.info("-------- this is info --------")
logger.warn("-------- THIS IS A WARNING --------")
logger.error("-------- !!! ERROR !!! --------")
This produces following logs:
{"name":"TODO","appId":"local-1550247707920","thread":"main","time":1550247708149,"level":"INFO","message":"-------- this is info --------"}
{"name":"TODO","appId":"local-1550247707920","thread":"main","time":1550247708150,"level":"WARN","message":"-------- THIS IS A WARNING --------"}
{"name":"TODO","appId":"local-1550247707920","thread":"main","time":1550247708150,"level":"ERROR","message":"-------- !!! ERROR !!! --------"}
And, of course, do not forget to refer the implementation in log4j config xml:
<appender name="Json" class="org.apache.log4j.ConsoleAppender">
<layout class="stackoverflow.q54706582.JsonLoggingLayout" />
</appender>