Spark. 1. 4. 1  . Spark provides three locations to configure the system. Spark Spark. Spark. Conf object. Java system properties. Environment. variables can be used to set per machine. IP address, through. Logging can. be configured through log. Spark. Spark properties control most application settings and are. These. SparkSpark. ConfSpari. Context. Spark. Confpassed. Spark Configuration. Spark properties control most application parameters and can be set by using a SparkConf. The maximum delay caused by retrying is 15. Netty is a NIO client server framework which enables quick and easy development of network applications such as protocol servers and clients. It greatly simplifies. Socketsessionthriftboostserialization. using namespace apachethrift. Thriftuser Python fastbinary protocol deserialization. in the 98th percentile of deserialization of a thrift object in python using. 3 5 20 28 ms delay. Jitter DelayNote that I made it using SVN though. THRIFT1772 Serialization does not check types of. THRIFT1772 Serialization does not check types of embedded structures. Facebook Thrift Download as Word. delay between data being written and becoming available to read. and all message and field headers are written using the. Parameters Test serialization c. http has a serialization delay of 4. 75. Storm should support rolling upgradedowngrade of storm. thrift and defaulting the serialization delegate to thrift serialization. files using thrift 0. Spark. Context.  Spark. Conf allows. you to configure. Spark. Conf url set. URL. and application name, as well as arbitrary key value pairs. For example, we could initialize an application with two threads as. Note that we run with local2, meaning two threads which. Spark. Conf. set. Masterlocal2. App. NameCounting. Sheep. setspark. Spark. Contextconf. Note that we can have more than 1 thread in local mode, and in. Spark Streaming, we may actually require one to prevent. Properties that specify some time duration should be configured. The following format is accepted 2. Properties that specify a byte size should be configured with a. The following format is accepted 1b bytes. Dynamically Loading Spark Properties. In some cases, you may want to avoid hard coding certain. Spark. Conf. For instance, if youd like to run the same application with. Spark allows you. Spark. Contextnew. Spark. Conf. Then, you can supply configuration values at runtime. binspark submit name My app master local4 conf spark. Java. Options XX Print. GCDetails XX Print. GCTime. Stamps my. App. jar. The Spark shell and spark submit tool. The first are. command line options, such as  master. Spark property using the  conf flag. Spark application. Running . binspark submit. For example spark. Log. enabled true. Kryo. Serializer. Any values specified as flags or in the properties file will be. Spark. Conf. Properties set directly on the Spark. Conf take. highest precedence, then flags passed. A few configuration keys have been renamed since earlier versions. Spark in such cases, the older key names are still accepted. Viewing Spark Properties. The application web UI at http 4. Spark properties in the Environment tab. This is a useful place. Note that only values explicitly specified. Spark. Conf. or the command line will appear. For all other configuration. Available Properties. Most of the properties that control internal settings have. Some of the most common options to set. Application Properties. The name of your application. This will appear in the UI and in log. Number of cores to use for the driver process, only in cluster. Result. Size. Limit of total size of serialized results of all partitions for. Spark action e. g. Should be at least 1. M, or 0 for. unlimited. Jobs will be aborted if the total size is above this. Having a high limit may cause out of memory errors in driver. JVM. Setting a proper limit can protect the driver from. Amount of memory to use for the driver process, i. Spark. Context is initialized. Note In client mode, this config must. Spark. Conf directly. JVM has already started at. Instead, please set this through. Amount of memory to use per executor process, in the same format as. JVM memory strings e. Listeners. A comma separated list of classes that. Spark. Listener. when initializing Spark. Context, instances of these classes will be. Sparks listener bus. If a class has a. Spark. Conf, that. If no valid constructor can be found, the. Spark. Context creation will fail with an exception. Directory to use for scratch space in Spark, including map output. RDDs that get stored on disk. This should be on a fast. It can also be a comma separated list of. NOTE In Spark 1. SPARKLOCALDIRS Standalone. Mesos or LOCALDIRS YARN environment variables set by the. Logs the effective Spark. Conf as INFO when a Spark. Context is. The cluster manager to connect to. See the list. Apart from these, the following properties are also available, and. Runtime Environment. Class. Path. Extra classpath entries to append to the classpath of the. Note In client mode, this config must. Spark. Conf directly. JVM has already started at. Instead, please set this through. Java. Options. A string of extra JVM options to pass to the driver. For instance. GC settings or other logging.  Note In client mode, this config must. Spark. Conf directly. JVM has already started at. Instead, please set this through. Library. Path. Set a special library path to use when launching the driver. JVM.  Note In client mode, this config must. Spark. Conf directly. JVM has already started at. Instead, please set this through. Class. Path. First. Experimental Whether to give user added jars precedence over. Sparks own jars when loading classes in the the driver. This. feature can be used to mitigate conflicts between Sparks. It is currently an experimental. This is used in cluster mode only. Class. Path. Extra classpath entries to append to the classpath of executors. This exists primarily for backwards compatibility with older. Spark. Users typically should not need to set this. Java. Options. A string of extra JVM options to pass to executors. For instance. GC settings or other logging. Note that it is illegal to set Spark. Spark properties. Spark. Conf object or the spark defaults. Heap size settings can be. Library. Path. Set a special library path to use when launching executor. Retained. Files. Sets the number of latest rolling log files that are going to be. Older log files will be deleted. Disabled. spark. executor. Size. Set the max size of the file by which the executor logs will be. Rolling is disabled by default. See spark. executor. Retained. Files for. Set the strategy of rolling of executor logs. By default it is. It can be set to time time based rolling or size. For time, usespark. For size. use spark. Bytes to. set the maximum file size for rolling. Set the time interval by which the executor logs will be rolled. Rolling is disabled by default. Valid values are daily. Seespark. executor. Retained. Files for. Class. Path. First. Experimental Same functionality as spark. Class. Path. First. Env. Environment. Variable. Name. Add the environment variable specified. Environment. Variable. Name to. the Executor process. The user can specify multiple of these to set. Enable profiling in Python worker, the profile result will show up. It also can be dumped into disk by. If some of the profile results had been. By default the pyspark. Basic. Profiler. Spark. Context constructor. The directory which is used to dump the profile result before. The results will be dumped as separated file for. RDD. They can be loaded by ptats. Stats. If this is. Amount of memory to use per python worker process during. JVM memory strings. If the memory used during aggregation goes above this amount, it. Reuse Python worker or not. If yes, it will use a fixed number of. Python workers, does not need to fork a Python process for every. It will be very useful if there is large broadcast, then the. JVM to Python. worker for every task. Shuffle Behavior. Size. In. Flight. Maximum size of map outputs to fetch simultaneously from each. Since each output requires us to create a buffer to. Transfer. Service. Implementation to use for transferring shuffle and cached blocks. There are two implementations. Netty based block transfer is intended to be simpler but equally. Whether to compress map output files. Generally a good idea. Compression will usespark. Files. If set to true, consolidates intermediate files created during a.