Configuration

This also requires enabling the pam_limits.so module

• The address will be set to the Kubernetes DNS name of the service and respective
  service port.
• If not all
  of your services provide Prometheus metrics, you can use a Marathon label and
  Prometheus relabeling to control which instances will actually be scraped.
• It has the same configuration format and actions as target relabeling.
• Configuration values may be accessed from anywhere in your application using the config function described above.

and re-login or reboot. Note the config_entry_decoder key with the passphrase

What is Configuration?

that RabbitMQ will use to decrypt encrypted values. Rabbitmq.conf and advanced.config changes take effect after a node restart.
A comma-separated list of classes that implement Function1[SparkSessionExtensions, Unit] used to configure Spark Session extensions. If multiple extensions are specified, they are applied in the specified order. For the case of rules and planner strategies, they are applied in the specified order. For the case of parsers, the last parser is used and each parser can delegate to its predecessor. For the case of function name conflicts, the last registered function name is used.
Currently it is not well suited for jobs/queries which runs quickly dealing with lesser amount of shuffle data. Since spark-env.sh is a shell script, some of these can be set programmatically – for example, you might
compute SPARK_LOCAL_IP by looking up the IP of a specific network interface. In addition to the above, there are also options for setting up the Spark
standalone cluster scripts, such as number of cores

to use on each machine and maximum memory. The value can be ‘simple’, ‘extended’, ‘codegen’, ‘cost’, or ‘formatted’. When true, allows multiple table arguments for table-valued functions, receiving the cartesian product of all the rows of these tables. When true, streaming session window sorts and merge sessions in local partition prior to shuffle.
This makes it easy to “disable” your application while it is updating or when you are performing maintenance. A maintenance mode check is included in the default middleware stack for your application. If the application is in maintenance mode, a Symfony\Component\HttpKernel\Exception\HttpException instance will be thrown with a status code of 503. If a more specific configuration is given in other sections, the related configuration within this section will be ignored. The compactor block configures the compactor component, which compacts index shards for performance. Where default_value is the value to use if the environment variable is undefined.
Furthermore, this would be a security risk in the event an intruder gains access to your source control repository, since any sensitive credentials would get exposed. Each variable reference is replaced at startup by the value of the environment variable. The replacement is case-sensitive and occurs before the YAML file is parsed. References to undefined variables are replaced by empty strings unless you specify a default value or custom error text. Environment variables set in the shell environment take
priority over those set
in rabbitmq-env.conf or

Spark UI

rabbitmq-env-conf.bat, which in turn override
RabbitMQ built-in defaults.
Running ./bin/spark-submit –help will show the entire list of these options. Highest precedence is given to overrides given as system properties, see the HOCON specification (near the bottom). Also noteworthy is that the application configuration—which defaults to application—may be overridden using the config.resource property (there are more, please refer to the Config docs).

The location of these configuration files varies across Hadoop versions, but
a common location is inside of /etc/hadoop/conf. Some tools create

Environment Variables

configurations on-the-fly, but offer a mechanism to download copies of them. If true, enables Parquet’s native record-level filtering using the pushed down filters. This configuration only has an effect when ‘spark.sql.parquet.filterPushdown’ is enabled and the vectorized reader is not used. You can ensure the vectorized reader is not used by setting ‘spark.sql.parquet.enableVectorizedReader’ to false. When true, check all the partition paths under the table’s root directory when reading data stored in HDFS.
Changes to all defined files are detected via disk watches

and applied immediately. Only
changes resulting in well-formed target groups are applied. See this example Prometheus configuration file
for a detailed example of configuring Prometheus with PuppetDB. The instance role discovers one target per network interface of Nova

instance. The target address defaults to the private IP address of the network
interface. The relabeling phase is the preferred and more powerful
way to filter targets based on arbitrary labels.
The number of rows to include in a orc vectorized reader batch. Estimated size needs to be under this value to try to inject bloom filter. Larger batch sizes can improve memory utilization and compression, but risk OOMs when caching data. When true, the ordinal numbers in group by clauses are treated as the position in the select list.
When true, the logical plan will fetch row counts and column statistics from catalog. Configures a list of rules to be disabled in the adaptive optimizer, in which the rules are specified by their rule names and separated by comma. Please refer to the Security page for available options on how to secure different

Spark subsystems.