Spark Log Overview

Log Description

Log paths:

Executor run log: ${BIGDATA_DATA_HOME}/hadoop/data${i}/nm/containerlogs/application_${appid}/container_{$contid}

The logs of running tasks are stored in the preceding path. After the running is complete, the system determines whether to aggregate the logs to an HDFS directory based on the YARN configuration. For details, see YARN Common Configuration Parameters.
Other logs: /var/log/Bigdata/spark2x

Log archiving rule:

When tasks are submitted in yarn-client or yarn-cluster mode, executor log files are stored each time when the size of the log files reaches 50 MB. A maximum of 10 log files can be reserved without being compressed.
The JobHistory2x log file is backed up each time when the size of the log file reaches 100 MB. A maximum of 100 log files can be reserved without being compressed.
The JDBCServer2x log file is backed up each time when the size of the log file reaches 100 MB. A maximum of 100 log files can be reserved without being compressed.
The IndexServer2x log file is backed up each time when the size of the log file reaches 100 MB. A maximum of 100 log files can be reserved without being compressed.
The JDBCServer2x audit log file is backed up each time when the size of the log file reaches 20 MB by default. A maximum of 20 log files can be reserved without being compressed.
The log file size and the number of compressed files to be reserved can be configured on FusionInsight Manager.

**Table 1** Spark2x log list
Log Type	Name	Description
SparkResource2x logs	spark.log	Spark2x service initialization log
	prestart.log	Prestart script log
	cleanup.log	Cleanup log file for instance installation and uninstallation
	spark-availability-check.log	Spark2x service health check log
	spark-service-check.log	Spark2x service check log
JDBCServer2x logs	JDBCServer-start.log	JDBCServer2x startup log
	JDBCServer-stop.log	JDBCServer2x stop log
	JDBCServer.log	JDBCServer2x run log on the server
	jdbc-state-check.log	JDBCServer2x health check log
	jdbcserver-omm-pid**-gc.log..current	IJDBCServer2x process GC log
	spark-omm-org.apache.spark.sql.hive.thriftserver.HiveThriftProxyServer2-**.out	JDBCServer2x process startup log. If the process stops, the jstack information is printed.
JobHistory2x logs	jobHistory-start.log	JobHistory2x startup log
	jobHistory-stop.log	JobHistory2x stop log
	JobHistory.log	JobHistory2x running process log
	jobhistory-omm-pid**-gc.log..current	JobHistory2x process GC log
	spark-omm-org.apache.spark.deploy.history.HistoryServer-**.out	JobHistory2x process startup log. If the process stops, the jstack information is printed.
IndexServer2x logs	IndexServer-start.log	IndexServer2x startup log
	IndexServer-stop.log	IndexServer2x stop log
	IndexServer.log	IndexServer2x run log on the server
	indexserver-state-check.log	IndexServer2x health check log
	indexserver-omm-pid**-gc.log..current	IndexServer2x process GC log
	spark-omm-org.apache.spark.sql.hive.thriftserver.IndexServerProxy-**.out	IndexServer2x process startup log. If the process stops, the jstack information is printed.
Audit Log	jdbcserver-audit.log ranger-audit.log	JDBCServer2x audit log

Log levels

Table 2 describes the log levels supported by Spark2x. The priorities of log levels are ERROR, WARN, INFO, and DEBUG in descending order. Logs whose levels are higher than or equal to the specified level are printed. The number of printed logs decreases as the specified log level increases.

**Table 2** Log levels
Level	Description
ERROR	Error information about the current event processing
WARN	Exception information about the current event processing
INFO	Logs of this level record normal running status information about the system and events.
DEBUG	Logs of this level record the system information and system debugging information.

To modify log levels, perform the following operations:

By default, the service does not need to be restarted after the Spark2x log levels are configured.

Log in to FusionInsight Manager.
Choose Cluster > Services > Spark2x and click Configurations.
Select All Configurations.
On the menu bar on the left, select the log menu of the target role.
Select a desired log level.
Click Save. Then, click OK.

Log Format

**Table 3** Log Format
Type	Format	Example
Run log	<yyyy-MM-dd HH:mm:ss,SSS>\|<Log level>\|<Name of the thread that generates the log>\|<Message in the log>\|<Location where the log event occurs>	2014-09-22 11:16:23,980 INFO DAGScheduler: Final stage: Stage 0(reduce at SparkPi.scala:35)