This page describes an older version of the product. The latest stable version is 16.4.

Spark Logging for InsightEdge


Spark uses log4j to make logging calls. For information about the log4j logging framework, refer to the log4j Overview online documentation.

Configuration

Log4j configures the logging during initialization, using a logging configuration file that is read at startup. This logging configuration file is in the standard java.util.Properties format.

InsightEdge log4j Default Configuration

The default Spark logger configuration file is located under the following directory:

<XAP_HOME>/insightedge/conf/spark_log4j.properties

Configuration File Properties

Console Appender

The Console Appender writes log messages to the console.

RollingFileAppender

The RollingFileAppender writes log messages to log files. The Spark log files are:

  • Written to /logs.
  • Rolled based on file size (up to 2GB)

Log File Name Format

The format of the log file name is:

{yyyy-MM-dd~HH.mm}-gigaspaces-{role}.log

The role is either spark-master or spark-worker. For example:

2017-09-17~17.44-gigaspaces-spark-master.log

Spark Log Message Format

In log4j, the log message format is configured in the *.layout.ConversionPattern property. In InsightEdge, the Spark log message format is configured to match the XAP format. Therefore, the ConversionPattern is:

    log4j.appender.console.layout.ConversionPattern=%d{yyyy-MM-dd HH:mm:ss,SSS} %p [%c] - %m%n
    log4j.appender.file.layout.ConversionPattern=%d{yyyy-MM-dd HH:mm:ss,SSS} %p [%c] - %m%n

Overriding the Default Configuration

Spark_log4j.properties can either be modified to suit the requirements of your environment, or deleted if you prefer to use the Spark default log4j configuration.