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example_config.json
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example_config.json
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{
"kernel_python_credentials" : {
"username": "",
"password": "",
"url": "http://lighter.spark:8080/lighter/api",
"auth": "None"
},
"kernel_scala_credentials" : {
"username": "",
"password": "",
"url": "http://lighter.spark:8080/lighter/api",
"auth": "None"
},
"kernel_r_credentials": {
"username": "",
"password": "",
"url": "http://lighter.spark:8080/lighter/api"
},
"logging_config": {
"version": 1,
"formatters": {
"magicsFormatter": {
"format": "%(asctime)s\t%(levelname)s\t%(message)s",
"datefmt": ""
}
},
"handlers": {
"magicsHandler": {
"class": "hdijupyterutils.filehandler.MagicsFileHandler",
"formatter": "magicsFormatter",
"home_path": "~/.sparkmagic"
}
},
"loggers": {
"magicsLogger": {
"handlers": ["magicsHandler"],
"level": "DEBUG",
"propagate": 0
}
}
},
"authenticators": {
"Kerberos": "sparkmagic.auth.kerberos.Kerberos",
"None": "sparkmagic.auth.customauth.Authenticator",
"Basic_Access": "sparkmagic.auth.basic.Basic"
},
"wait_for_idle_timeout_seconds": 15,
"livy_session_startup_timeout_seconds": 600,
"fatal_error_suggestion": "The code failed because of a fatal error:\n\t{}.\n\nSome things to try:\na) Make sure Spark has enough available resources for Jupyter to create a Spark context.\nb) Contact your Jupyter administrator to make sure the Spark magics library is configured correctly.\nc) Restart the kernel.",
"ignore_ssl_errors": false,
"session_configs": {
"driverMemory": "1000M",
"executorCores": 2
},
"use_auto_viz": true,
"coerce_dataframe": true,
"max_results_sql": 2500,
"pyspark_dataframe_encoding": "utf-8",
"heartbeat_refresh_seconds": 30,
"livy_server_heartbeat_timeout_seconds": 0,
"heartbeat_retry_seconds": 10,
"server_extension_default_kernel_name": "pysparkkernel",
"custom_headers": {
"X-Compatibility-Mode": "sparkmagic"
},
"retry_policy": "configurable",
"retry_seconds_to_sleep_list": [0.2, 0.5, 1, 3, 5],
"configurable_retry_policy_max_retries": 8
}