Logs

Event log

Event log is a special log format in Spark. Logs are written by a driver and read by a special service called Spark History Server (SHS). SHS launches alongside the master and the workers when a SPYT cluster is started. SHS uses the log to draw a UI similar to Spark UI.

The difference between them is that Spark UI is available on the driver only while a job is running, whereas SHS is always up and can read the logs of completed jobs.
Logs are written to a dynamic table in discovery-path. SHS can delete them automatically.

Enabling

Set spark.eventLog.enabled to true on starting a job:

$ spark-submit-yt ... --conf spark.eventLog.enabled=true

Configuring

For a detailed description of SHS settings, please see the Spark documentation. You can pass any settings from this description in to spark-launch-yt ... --params '{spark_conf={"spark.param"=value;...}}'.

By default, the spark.history.fs.cleaner.enabled is set to true. The other parameters' default values are as per the Spark documentation. If the parameters are set to their defaults, SHS deletes all logs older than one week. You can change this age limit using the setting: spark.history.fs.cleaner.maxAge (spark-launch-yt ... --params '{spark_conf={"spark.history.fs.cleaner.maxAge"="14d";...}}').

Worker logs

When you start a cluster, you can configure worker logs to upload to YTsaurus tables. Logs will be written to {cluster_path}/logs/worker_log with a separate table created for each date. To enable sending of logs when starting a cluster, you must use one of these options:

  • --enable-worker-log-transfer: Enables log forwarding.
  • --enable-worker-log-json-mode: Enables json mode for the logs. Table data are displayed in a more convenient format and broken down into component parts. If the option is disabled, logs are written to a single column called messages.
  • --worker-log-update-interval ... : Sets the frequency of log upload; the default value is 10 minutes (10m), the minimum value is 1 minute.
  • --worker-log-table-ttl ... : Sets the table age limit; the default is 7 days (7d).

You can view logs on SHS: the executors tab of any application contains [HS]-prefixed links for every worker. A log page referenced by these links is generated from the YTsaurus tables; therefore, it is available even if a worker no longer is. A log persists until the relevant table is deleted:

spark-launch-yt ... \
  --enable-worker-log-transfer \
  --enable-worker-log-json-mode \
  --worker-log-update-interval 30m \
  --worker-log-table-ttl 30d
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