Mist creates and orchestrates Apache Spark contexts automatically. Every job is run in a context. In fact context describes a named Spark context and Mist settings for this Spark context.
Contexts may be created using mist-cli or http-api.
Also, there is special
default context. It may be configured only using mist-configuration file.
It’s goal to setup default values for all context, so for creating a new context it isn’t required to define values for all its fields.
|sparkConf||empty||settings for a [spark](https://spark.apache.org/docs/latest/configuration.html)|
|maxJobs||1||amount of jobs executed in parallel|
|maxConnFailures||5||allowed amount of worker crushes before context will be switched into `broken` state (it fails all incoming requests until context settings is updated).|
|runOptions||""||additional command line arguments for building spark-submit command to start worker, e.x: pass `--jars`|
|streamingDuration||1s||spark streaming duration|
|precreated||false||if true starts worker immediately, if false await first job start requests before starting worker *NOTE*: works only with `shared` workerMode|
|downtime||false||idle-timeout for `shared` worker|