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diff --git a/docs/configuration.md b/docs/configuration.md index 71fafa5734..b84104cc7e 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -784,6 +784,45 @@ Apart from these, the following properties are also available, and may be useful higher memory usage in Spark. </td> </tr> +<tr> + <td><code>spark.executor.logs.rolling.strategy</code></td> + <td>(none)</td> + <td> + Set the strategy of rolling of executor logs. By default it is disabled. It can + be set to "time" (time-based rolling) or "size" (size-based rolling). For "time", + use <code>spark.executor.logs.rolling.time.interval</code> to set the rolling interval. + For "size", use <code>spark.executor.logs.rolling.size.maxBytes</code> to set + the maximum file size for rolling. + </td> +</tr> +<tr> + <td><code>spark.executor.logs.rolling.time.interval</code></td> + <td>daily</td> + <td> + Set the time interval by which the executor logs will be rolled over. + Rolling is disabled by default. Valid values are `daily`, `hourly`, `minutely` or + any interval in seconds. See <code>spark.executor.logs.rolling.maxRetainedFiles</code> + for automatic cleaning of old logs. + </td> +</tr> +<tr> + <td><code>spark.executor.logs.rolling.size.maxBytes</code></td> + <td>(none)</td> + <td> + Set the max size of the file by which the executor logs will be rolled over. + Rolling is disabled by default. Value is set in terms of bytes. + See <code>spark.executor.logs.rolling.maxRetainedFiles</code> + for automatic cleaning of old logs. + </td> +</tr> +<tr> + <td><code>spark.executor.logs.rolling.maxRetainedFiles</code></td> + <td>(none)</td> + <td> + Sets the number of latest rolling log files that are going to be retained by the system. + Older log files will be deleted. Disabled by default. + </td> +</tr> </table> #### Cluster Managers |