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Credentials and configuration settings are located in multiple places, such as the system or user environment variables, local AWS configuration files, or explicitly declared on the command line as a parameter. Certain locations take precedence over others. The AWS CLI credentials and configuration settings take precedence in the following order:
This guide explains the configuration methods for Keycloak and how to start and apply the preferred configuration. It includes configuration guidelines for optimizing Keycloak for faster startup and low memory footprint.
If --db-url=cliValue had not been used, the applied value would be KC_DB_URL=envVarValue. If the value were not applied by either the command line or an environment variable, db-url=confFileValue would be used. However, if this value had been set in a user defined configuration file, that value would take precedence over the conf/keycloak.conf file. If none of the previous values were applied, the value kc.db-url=confFileValue would be used due to the lowest priority among the available configuration sources.
At the end of each configuration guide, look for the Relevantoptions heading, which defines the applicable configurationformats. For all configuration options, see All configuration. Choose the configuration source and format that applies to your use case.
By default, the server always fetches configuration options from the conf/keycloak.conf file. For a new installation, this file holds only commented settings as an idea of what you want to set when running in production.
In most cases, the available configuration options should suffice to configure the server.However, for a specific behavior or capability that is missing in the Keycloak configuration, you can use properties from the underlying Quarkus framework.
If possible, avoid using properties directly from Quarkus, because they are unsupported by Keycloak. If your need is essential, consider opening an enhancement request first. This approach helps us improve the configuration of Keycloak to fit your needs.
Note that some Quarkus properties are already mapped in the Keycloak configuration, such as quarkus.http.port and similar essential properties. If the property is used by Keycloak, defining that property key in quarkus.properties has no effect. The Keycloak configuration value takes precedence over the Quarkus property value.
Without further configuration, this command will not start Keycloak and show you an error instead. This response is done on purpose, because Keycloak follows a secure by default principle. Production mode expects a hostname to be set up and an HTTPS/TLS setup to be available when started.
By default, example configuration options for the production mode are commented out in the default conf/keycloak.conf file. These options give you an idea about the main configuration to consider when running Keycloak in production.
This command shows build options that you enter. Keycloak distinguishes between build options, that are usable when running the build command, and configuration options, that are usable when starting up the server.
For a non-optimized startup of Keycloak, this distinction has no effect. However, if you run a build before the startup, only a subset of options is available to the build command. The restriction is due to the build options getting persisted into an optimized Keycloak image. For example, configuration for credentials such as db-password (which is a configuration option) must not get persisted for security reasons.
You can achieve most optimizations to startup and runtime behavior by using the build command. Also, by using the keycloak.conf file as a configuration source, you avoid some steps at startup that would otherwise require command line parameters, such as initializing the CLI itself. As a result, the server starts up even faster.
While numbers without units are generally interpreted as bytes, a few are interpreted as KiB or MiB.See documentation of individual configuration properties. Specifying units is desirable wherepossible.
The Spark shell and spark-submittool support two ways to load configurations dynamically. The first is command line options,such as --master, as shown above. spark-submit can accept any Spark property using the --conf/-cflag, but uses special flags for properties that play a part in launching the Spark application.Running ./bin/spark-submit --help will show the entire list of these options.
Any values specified as flags or in the properties file will be passed on to the applicationand merged with those specified through SparkConf. Properties set directly on the SparkConftake highest precedence, then flags passed to spark-submit or spark-shell, then optionsin the spark-defaults.conf file. A few configuration keys have been renamed since earlierversions of Spark; in such cases, the older key names are still accepted, but take lowerprecedence than any instance of the newer key.
Server configurations are set in Spark Connect server, for example, when you start the Spark Connect server with ./sbin/start-connect-server.sh.They are typically set via the config file and command-lineoptions with --conf/-c.
The initial number of shuffle partitions before coalescing. If not set, it equals to spark.sql.shuffle.partitions. This configuration only has an effect when 'spark.sql.adaptive.enabled' and 'spark.sql.adaptive.coalescePartitions.enabled' are both true.
The ratio of the number of two buckets being coalesced should be less than or equal to this value for bucket coalescing to be applied. This configuration only has an effect when 'spark.sql.bucketing.coalesceBucketsInJoin.enabled' is set to true.
If the configuration property is set to true, java.time.Instant and java.time.LocalDate classes of Java 8 API are used as external types for Catalyst's TimestampType and DateType. If it is set to false, java.sql.Timestamp and java.sql.Date are used for the same purpose.
When PRETTY, the error message consists of textual representation of error class, message and query context. The MINIMAL and STANDARD formats are pretty JSON formats where STANDARD includes an additional JSON field message. This configuration property influences on error messages of Thrift Server and SQL CLI while running queries.
Whether to ignore corrupt files. If true, the Spark jobs will continue to run when encountering corrupted files and the contents that have been read will still be returned. This configuration is effective only when using file-based sources such as Parquet, JSON and ORC.
Whether to ignore missing files. If true, the Spark jobs will continue to run when encountering missing files and the contents that have been read will still be returned. This configuration is effective only when using file-based sources such as Parquet, JSON and ORC.
The suggested (not guaranteed) maximum number of split file partitions. If it is set, Spark will rescale each partition to make the number of partitions is close to this value if the initial number of partitions exceeds this value. This configuration is effective only when using file-based sources such as Parquet, JSON and ORC.
The suggested (not guaranteed) minimum number of split file partitions. If not set, the default value is spark.sql.leafNodeDefaultParallelism. This configuration is effective only when using file-based sources such as Parquet, JSON and ORC.
When true, also tries to merge possibly different but compatible Parquet schemas in different Parquet data files. This configuration is only effective when "spark.sql.hive.convertMetastoreParquet" is true.
When true, check all the partition paths under the table's root directory when reading data stored in HDFS. This configuration will be deprecated in the future releases and replaced by spark.files.ignoreMissingFiles.
Configures a list of rules to be disabled in the optimizer, in which the rules are specified by their rule names and separated by comma. It is not guaranteed that all the rules in this configuration will eventually be excluded, as some rules are necessary for correctness. The optimizer will log the rules that have indeed been excluded.
When enabled, Parquet timestamp columns with annotation isAdjustedToUTC = false are inferred as TIMESTAMP_NTZ type during schema inference. Otherwise, all the Parquet timestamp columns are inferred as TIMESTAMP_LTZ types. Note that Spark writes the output schema into Parquet's footer metadata on file writing and leverages it on file reading. Thus this configuration only affects the schema inference on Parquet files which are not written by Spark.
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.
Regex to decide which keys in a Spark SQL command's options map contain sensitive information. The values of options whose names that match this regex will be redacted in the explain output. This redaction is applied on top of the global redaction configuration defined by spark.redaction.regex.
The default number of partitions to use when shuffling data for joins or aggregations. Note: For structured streaming, this configuration cannot be changed between query restarts from the same checkpoint location.
When true, decide whether to do bucketed scan on input tables based on query plan automatically. Do not use bucketed scan if 1. query does not have operators to utilize bucketing (e.g. join, group-by, etc), or 2. there's an exchange operator between these operators and table scan. Note when 'spark.sql.sources.bucketing.enabled' is set to false, this configuration does not take any effect.
The maximum number of paths allowed for listing files at driver side. If the number of detected paths exceeds this value during partition discovery, it tries to list the files with another Spark distributed job. This configuration is effective only when using file-based sources such as Parquet, JSON and ORC.
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