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package.scala
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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.internal
import java.util.Locale
import java.util.concurrent.TimeUnit
import org.apache.spark.launcher.SparkLauncher
import org.apache.spark.metrics.GarbageCollectionMetrics
import org.apache.spark.network.shuffle.Constants
import org.apache.spark.network.util.ByteUnit
import org.apache.spark.scheduler.{EventLoggingListener, SchedulingMode}
import org.apache.spark.shuffle.sort.io.LocalDiskShuffleDataIO
import org.apache.spark.storage.{DefaultTopologyMapper, RandomBlockReplicationPolicy}
import org.apache.spark.unsafe.array.ByteArrayMethods
import org.apache.spark.util.Utils
import org.apache.spark.util.collection.unsafe.sort.UnsafeSorterSpillReader.MAX_BUFFER_SIZE_BYTES
package object config {
private[spark] val SPARK_DRIVER_PREFIX = "spark.driver"
private[spark] val SPARK_EXECUTOR_PREFIX = "spark.executor"
private[spark] val SPARK_TASK_PREFIX = "spark.task"
private[spark] val LISTENER_BUS_EVENT_QUEUE_PREFIX = "spark.scheduler.listenerbus.eventqueue"
private[spark] val RESOURCES_DISCOVERY_PLUGIN =
ConfigBuilder("spark.resources.discoveryPlugin")
.doc("Comma-separated list of class names implementing" +
"org.apache.spark.api.resource.ResourceDiscoveryPlugin to load into the application." +
"This is for advanced users to replace the resource discovery class with a " +
"custom implementation. Spark will try each class specified until one of them " +
"returns the resource information for that resource. It tries the discovery " +
"script last if none of the plugins return information for that resource.")
.version("3.0.0")
.stringConf
.toSequence
.createWithDefault(Nil)
private[spark] val DRIVER_RESOURCES_FILE =
ConfigBuilder("spark.driver.resourcesFile")
.internal()
.doc("Path to a file containing the resources allocated to the driver. " +
"The file should be formatted as a JSON array of ResourceAllocation objects. " +
"Only used internally in standalone mode.")
.version("3.0.0")
.stringConf
.createOptional
private[spark] val DRIVER_CLASS_PATH =
ConfigBuilder(SparkLauncher.DRIVER_EXTRA_CLASSPATH)
.version("1.0.0")
.stringConf
.createOptional
private[spark] val DRIVER_JAVA_OPTIONS =
ConfigBuilder(SparkLauncher.DRIVER_EXTRA_JAVA_OPTIONS)
.withPrepended(SparkLauncher.DRIVER_DEFAULT_JAVA_OPTIONS)
.version("1.0.0")
.stringConf
.createOptional
private[spark] val DRIVER_LIBRARY_PATH =
ConfigBuilder(SparkLauncher.DRIVER_EXTRA_LIBRARY_PATH)
.version("1.0.0")
.stringConf
.createOptional
private[spark] val DRIVER_USER_CLASS_PATH_FIRST =
ConfigBuilder("spark.driver.userClassPathFirst")
.version("1.3.0")
.booleanConf
.createWithDefault(false)
private[spark] val DRIVER_CORES = ConfigBuilder("spark.driver.cores")
.doc("Number of cores to use for the driver process, only in cluster mode.")
.version("1.3.0")
.intConf
.createWithDefault(1)
private[spark] val DRIVER_MEMORY = ConfigBuilder(SparkLauncher.DRIVER_MEMORY)
.doc("Amount of memory to use for the driver process, in MiB unless otherwise specified.")
.version("1.1.1")
.bytesConf(ByteUnit.MiB)
.createWithDefaultString("1g")
private[spark] val DRIVER_MEMORY_OVERHEAD = ConfigBuilder("spark.driver.memoryOverhead")
.doc("The amount of non-heap memory to be allocated per driver in cluster mode, " +
"in MiB unless otherwise specified.")
.version("2.3.0")
.bytesConf(ByteUnit.MiB)
.createOptional
private[spark] val DRIVER_LOG_DFS_DIR =
ConfigBuilder("spark.driver.log.dfsDir").version("3.0.0").stringConf.createOptional
private[spark] val DRIVER_LOG_LAYOUT =
ConfigBuilder("spark.driver.log.layout")
.version("3.0.0")
.stringConf
.createOptional
private[spark] val DRIVER_LOG_PERSISTTODFS =
ConfigBuilder("spark.driver.log.persistToDfs.enabled")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val DRIVER_LOG_ALLOW_EC =
ConfigBuilder("spark.driver.log.allowErasureCoding")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_ENABLED = ConfigBuilder("spark.eventLog.enabled")
.version("1.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_DIR = ConfigBuilder("spark.eventLog.dir")
.version("1.0.0")
.stringConf
.createWithDefault(EventLoggingListener.DEFAULT_LOG_DIR)
private[spark] val EVENT_LOG_COMPRESS =
ConfigBuilder("spark.eventLog.compress")
.version("1.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_BLOCK_UPDATES =
ConfigBuilder("spark.eventLog.logBlockUpdates.enabled")
.version("2.3.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_ALLOW_EC =
ConfigBuilder("spark.eventLog.erasureCoding.enabled")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_TESTING =
ConfigBuilder("spark.eventLog.testing")
.internal()
.version("1.0.1")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_OUTPUT_BUFFER_SIZE = ConfigBuilder("spark.eventLog.buffer.kb")
.doc("Buffer size to use when writing to output streams, in KiB unless otherwise specified.")
.version("1.0.0")
.bytesConf(ByteUnit.KiB)
.createWithDefaultString("100k")
private[spark] val EVENT_LOG_STAGE_EXECUTOR_METRICS =
ConfigBuilder("spark.eventLog.logStageExecutorMetrics")
.doc("Whether to write per-stage peaks of executor metrics (for each executor) " +
"to the event log.")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_GC_METRICS_YOUNG_GENERATION_GARBAGE_COLLECTORS =
ConfigBuilder("spark.eventLog.gcMetrics.youngGenerationGarbageCollectors")
.doc("Names of supported young generation garbage collector. A name usually is " +
" the return of GarbageCollectorMXBean.getName. The built-in young generation garbage " +
s"collectors are ${GarbageCollectionMetrics.YOUNG_GENERATION_BUILTIN_GARBAGE_COLLECTORS}")
.version("3.0.0")
.stringConf
.toSequence
.createWithDefault(GarbageCollectionMetrics.YOUNG_GENERATION_BUILTIN_GARBAGE_COLLECTORS)
private[spark] val EVENT_LOG_GC_METRICS_OLD_GENERATION_GARBAGE_COLLECTORS =
ConfigBuilder("spark.eventLog.gcMetrics.oldGenerationGarbageCollectors")
.doc("Names of supported old generation garbage collector. A name usually is " +
"the return of GarbageCollectorMXBean.getName. The built-in old generation garbage " +
s"collectors are ${GarbageCollectionMetrics.OLD_GENERATION_BUILTIN_GARBAGE_COLLECTORS}")
.version("3.0.0")
.stringConf
.toSequence
.createWithDefault(GarbageCollectionMetrics.OLD_GENERATION_BUILTIN_GARBAGE_COLLECTORS)
private[spark] val EVENT_LOG_OVERWRITE =
ConfigBuilder("spark.eventLog.overwrite")
.version("1.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_CALLSITE_LONG_FORM =
ConfigBuilder("spark.eventLog.longForm.enabled")
.version("2.4.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_ENABLE_ROLLING =
ConfigBuilder("spark.eventLog.rolling.enabled")
.doc("Whether rolling over event log files is enabled. If set to true, it cuts down " +
"each event log file to the configured size.")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EVENT_LOG_ROLLING_MAX_FILE_SIZE =
ConfigBuilder("spark.eventLog.rolling.maxFileSize")
.doc(s"When ${EVENT_LOG_ENABLE_ROLLING.key}=true, specifies the max size of event log file" +
" to be rolled over.")
.version("3.0.0")
.bytesConf(ByteUnit.BYTE)
.checkValue(_ >= ByteUnit.MiB.toBytes(10), "Max file size of event log should be " +
"configured to be at least 10 MiB.")
.createWithDefaultString("128m")
private[spark] val EXECUTOR_ID =
ConfigBuilder("spark.executor.id").version("1.2.0").stringConf.createOptional
private[spark] val EXECUTOR_CLASS_PATH =
ConfigBuilder(SparkLauncher.EXECUTOR_EXTRA_CLASSPATH)
.version("1.0.0")
.stringConf
.createOptional
private[spark] val EXECUTOR_HEARTBEAT_DROP_ZERO_ACCUMULATOR_UPDATES =
ConfigBuilder("spark.executor.heartbeat.dropZeroAccumulatorUpdates")
.internal()
.version("3.0.0")
.booleanConf
.createWithDefault(true)
private[spark] val EXECUTOR_HEARTBEAT_INTERVAL =
ConfigBuilder("spark.executor.heartbeatInterval")
.version("1.1.0")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefaultString("10s")
private[spark] val EXECUTOR_HEARTBEAT_MAX_FAILURES =
ConfigBuilder("spark.executor.heartbeat.maxFailures")
.internal()
.version("1.6.2")
.intConf
.createWithDefault(60)
private[spark] val EXECUTOR_PROCESS_TREE_METRICS_ENABLED =
ConfigBuilder("spark.executor.processTreeMetrics.enabled")
.doc("Whether to collect process tree metrics (from the /proc filesystem) when collecting " +
"executor metrics.")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val EXECUTOR_METRICS_POLLING_INTERVAL =
ConfigBuilder("spark.executor.metrics.pollingInterval")
.doc("How often to collect executor metrics (in milliseconds). " +
"If 0, the polling is done on executor heartbeats. " +
"If positive, the polling is done at this interval.")
.version("3.0.0")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefaultString("0")
private[spark] val EXECUTOR_JAVA_OPTIONS =
ConfigBuilder(SparkLauncher.EXECUTOR_EXTRA_JAVA_OPTIONS)
.withPrepended(SparkLauncher.EXECUTOR_DEFAULT_JAVA_OPTIONS)
.version("1.0.0")
.stringConf
.createOptional
private[spark] val EXECUTOR_LIBRARY_PATH =
ConfigBuilder(SparkLauncher.EXECUTOR_EXTRA_LIBRARY_PATH)
.version("1.0.0")
.stringConf
.createOptional
private[spark] val EXECUTOR_USER_CLASS_PATH_FIRST =
ConfigBuilder("spark.executor.userClassPathFirst")
.version("1.3.0")
.booleanConf
.createWithDefault(false)
private[spark] val EXECUTOR_CORES = ConfigBuilder(SparkLauncher.EXECUTOR_CORES)
.version("1.0.0")
.intConf
.createWithDefault(1)
private[spark] val EXECUTOR_MEMORY = ConfigBuilder(SparkLauncher.EXECUTOR_MEMORY)
.doc("Amount of memory to use per executor process, in MiB unless otherwise specified.")
.version("0.7.0")
.bytesConf(ByteUnit.MiB)
.createWithDefaultString("1g")
private[spark] val EXECUTOR_MEMORY_OVERHEAD = ConfigBuilder("spark.executor.memoryOverhead")
.doc("The amount of non-heap memory to be allocated per executor in cluster mode, " +
"in MiB unless otherwise specified.")
.version("2.3.0")
.bytesConf(ByteUnit.MiB)
.createOptional
private[spark] val CORES_MAX = ConfigBuilder("spark.cores.max")
.doc("When running on a standalone deploy cluster or a Mesos cluster in coarse-grained " +
"sharing mode, the maximum amount of CPU cores to request for the application from across " +
"the cluster (not from each machine). If not set, the default will be " +
"`spark.deploy.defaultCores` on Spark's standalone cluster manager, or infinite " +
"(all available cores) on Mesos.")
.version("0.6.0")
.intConf
.createOptional
private[spark] val MEMORY_OFFHEAP_ENABLED = ConfigBuilder("spark.memory.offHeap.enabled")
.doc("If true, Spark will attempt to use off-heap memory for certain operations. " +
"If off-heap memory use is enabled, then spark.memory.offHeap.size must be positive.")
.version("1.6.0")
.withAlternative("spark.unsafe.offHeap")
.booleanConf
.createWithDefault(false)
private[spark] val MEMORY_OFFHEAP_SIZE = ConfigBuilder("spark.memory.offHeap.size")
.doc("The absolute amount of memory which can be used for off-heap allocation, " +
" in bytes unless otherwise specified. " +
"This setting has no impact on heap memory usage, so if your executors' total memory " +
"consumption must fit within some hard limit then be sure to shrink your JVM heap size " +
"accordingly. This must be set to a positive value when spark.memory.offHeap.enabled=true.")
.version("1.6.0")
.bytesConf(ByteUnit.BYTE)
.checkValue(_ >= 0, "The off-heap memory size must not be negative")
.createWithDefault(0)
private[spark] val MEMORY_STORAGE_FRACTION = ConfigBuilder("spark.memory.storageFraction")
.doc("Amount of storage memory immune to eviction, expressed as a fraction of the " +
"size of the region set aside by spark.memory.fraction. The higher this is, the " +
"less working memory may be available to execution and tasks may spill to disk more " +
"often. Leaving this at the default value is recommended. ")
.version("1.6.0")
.doubleConf
.checkValue(v => v >= 0.0 && v < 1.0, "Storage fraction must be in [0,1)")
.createWithDefault(0.5)
private[spark] val MEMORY_FRACTION = ConfigBuilder("spark.memory.fraction")
.doc("Fraction of (heap space - 300MB) used for execution and storage. The " +
"lower this is, the more frequently spills and cached data eviction occur. " +
"The purpose of this config is to set aside memory for internal metadata, " +
"user data structures, and imprecise size estimation in the case of sparse, " +
"unusually large records. Leaving this at the default value is recommended. ")
.version("1.6.0")
.doubleConf
.createWithDefault(0.6)
private[spark] val STORAGE_SAFETY_FRACTION = ConfigBuilder("spark.storage.safetyFraction")
.version("1.1.0")
.doubleConf
.createWithDefault(0.9)
private[spark] val STORAGE_UNROLL_MEMORY_THRESHOLD =
ConfigBuilder("spark.storage.unrollMemoryThreshold")
.doc("Initial memory to request before unrolling any block")
.version("1.1.0")
.longConf
.createWithDefault(1024 * 1024)
private[spark] val STORAGE_REPLICATION_PROACTIVE =
ConfigBuilder("spark.storage.replication.proactive")
.doc("Enables proactive block replication for RDD blocks. " +
"Cached RDD block replicas lost due to executor failures are replenished " +
"if there are any existing available replicas. This tries to " +
"get the replication level of the block to the initial number")
.version("2.2.0")
.booleanConf
.createWithDefault(false)
private[spark] val STORAGE_MEMORY_MAP_THRESHOLD =
ConfigBuilder("spark.storage.memoryMapThreshold")
.doc("Size in bytes of a block above which Spark memory maps when " +
"reading a block from disk. " +
"This prevents Spark from memory mapping very small blocks. " +
"In general, memory mapping has high overhead for blocks close to or below " +
"the page size of the operating system.")
.version("0.9.2")
.bytesConf(ByteUnit.BYTE)
.createWithDefaultString("2m")
private[spark] val STORAGE_REPLICATION_POLICY =
ConfigBuilder("spark.storage.replication.policy")
.version("2.1.0")
.stringConf
.createWithDefaultString(classOf[RandomBlockReplicationPolicy].getName)
private[spark] val STORAGE_REPLICATION_TOPOLOGY_MAPPER =
ConfigBuilder("spark.storage.replication.topologyMapper")
.version("2.1.0")
.stringConf
.createWithDefaultString(classOf[DefaultTopologyMapper].getName)
private[spark] val STORAGE_CACHED_PEERS_TTL = ConfigBuilder("spark.storage.cachedPeersTtl")
.version("1.1.1")
.intConf
.createWithDefault(60 * 1000)
private[spark] val STORAGE_MAX_REPLICATION_FAILURE =
ConfigBuilder("spark.storage.maxReplicationFailures")
.version("1.1.1")
.intConf
.createWithDefault(1)
private[spark] val STORAGE_DECOMMISSION_ENABLED =
ConfigBuilder("spark.storage.decommission.enabled")
.doc("Whether to decommission the block manager when decommissioning executor")
.version("3.1.0")
.booleanConf
.createWithDefault(false)
private[spark] val STORAGE_DECOMMISSION_MAX_REPLICATION_FAILURE_PER_BLOCK =
ConfigBuilder("spark.storage.decommission.maxReplicationFailuresPerBlock")
.internal()
.doc("Maximum number of failures which can be handled for the replication of " +
"one RDD block when block manager is decommissioning and trying to move its " +
"existing blocks.")
.version("3.1.0")
.intConf
.createWithDefault(3)
private[spark] val STORAGE_DECOMMISSION_REPLICATION_REATTEMPT_INTERVAL =
ConfigBuilder("spark.storage.decommission.replicationReattemptInterval")
.internal()
.doc("The interval of time between consecutive cache block replication reattempts " +
"happening on each decommissioning executor (due to storage decommissioning).")
.version("3.1.0")
.timeConf(TimeUnit.MILLISECONDS)
.checkValue(_ > 0, "Time interval between two consecutive attempts of " +
"cache block replication should be positive.")
.createWithDefaultString("30s")
private[spark] val STORAGE_REPLICATION_TOPOLOGY_FILE =
ConfigBuilder("spark.storage.replication.topologyFile")
.version("2.1.0")
.stringConf
.createOptional
private[spark] val STORAGE_EXCEPTION_PIN_LEAK =
ConfigBuilder("spark.storage.exceptionOnPinLeak")
.version("1.6.2")
.booleanConf
.createWithDefault(false)
private[spark] val STORAGE_BLOCKMANAGER_TIMEOUTINTERVAL =
ConfigBuilder("spark.storage.blockManagerTimeoutIntervalMs")
.version("0.7.3")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefaultString("60s")
private[spark] val STORAGE_BLOCKMANAGER_SLAVE_TIMEOUT =
ConfigBuilder("spark.storage.blockManagerSlaveTimeoutMs")
.version("0.7.0")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefaultString(Network.NETWORK_TIMEOUT.defaultValueString)
private[spark] val STORAGE_CLEANUP_FILES_AFTER_EXECUTOR_EXIT =
ConfigBuilder("spark.storage.cleanupFilesAfterExecutorExit")
.doc("Whether or not cleanup the files not served by the external shuffle service " +
"on executor exits.")
.version("2.4.0")
.booleanConf
.createWithDefault(true)
private[spark] val DISKSTORE_SUB_DIRECTORIES =
ConfigBuilder("spark.diskStore.subDirectories")
.doc("Number of subdirectories inside each path listed in spark.local.dir for " +
"hashing Block files into.")
.version("0.6.0")
.intConf
.checkValue(_ > 0, "The number of subdirectories must be positive.")
.createWithDefault(64)
private[spark] val BLOCK_FAILURES_BEFORE_LOCATION_REFRESH =
ConfigBuilder("spark.block.failures.beforeLocationRefresh")
.doc("Max number of failures before this block manager refreshes " +
"the block locations from the driver.")
.version("2.0.0")
.intConf
.createWithDefault(5)
private[spark] val IS_PYTHON_APP =
ConfigBuilder("spark.yarn.isPython")
.internal()
.version("1.5.0")
.booleanConf
.createWithDefault(false)
private[spark] val CPUS_PER_TASK =
ConfigBuilder("spark.task.cpus").version("0.5.0").intConf.createWithDefault(1)
private[spark] val DYN_ALLOCATION_ENABLED =
ConfigBuilder("spark.dynamicAllocation.enabled")
.version("1.2.0")
.booleanConf
.createWithDefault(false)
private[spark] val DYN_ALLOCATION_TESTING =
ConfigBuilder("spark.dynamicAllocation.testing")
.version("1.2.0")
.booleanConf
.createWithDefault(false)
private[spark] val DYN_ALLOCATION_MIN_EXECUTORS =
ConfigBuilder("spark.dynamicAllocation.minExecutors")
.version("1.2.0")
.intConf
.createWithDefault(0)
private[spark] val DYN_ALLOCATION_INITIAL_EXECUTORS =
ConfigBuilder("spark.dynamicAllocation.initialExecutors")
.version("1.3.0")
.fallbackConf(DYN_ALLOCATION_MIN_EXECUTORS)
private[spark] val DYN_ALLOCATION_MAX_EXECUTORS =
ConfigBuilder("spark.dynamicAllocation.maxExecutors")
.version("1.2.0")
.intConf
.createWithDefault(Int.MaxValue)
private[spark] val DYN_ALLOCATION_EXECUTOR_ALLOCATION_RATIO =
ConfigBuilder("spark.dynamicAllocation.executorAllocationRatio")
.version("2.4.0")
.doubleConf
.createWithDefault(1.0)
private[spark] val DYN_ALLOCATION_CACHED_EXECUTOR_IDLE_TIMEOUT =
ConfigBuilder("spark.dynamicAllocation.cachedExecutorIdleTimeout")
.version("1.4.0")
.timeConf(TimeUnit.SECONDS)
.checkValue(_ >= 0L, "Timeout must be >= 0.")
.createWithDefault(Integer.MAX_VALUE)
private[spark] val DYN_ALLOCATION_EXECUTOR_IDLE_TIMEOUT =
ConfigBuilder("spark.dynamicAllocation.executorIdleTimeout")
.version("1.2.0")
.timeConf(TimeUnit.SECONDS)
.checkValue(_ >= 0L, "Timeout must be >= 0.")
.createWithDefault(60)
private[spark] val DYN_ALLOCATION_SHUFFLE_TRACKING_ENABLED =
ConfigBuilder("spark.dynamicAllocation.shuffleTracking.enabled")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val DYN_ALLOCATION_SHUFFLE_TRACKING_TIMEOUT =
ConfigBuilder("spark.dynamicAllocation.shuffleTracking.timeout")
.version("3.0.0")
.timeConf(TimeUnit.MILLISECONDS)
.checkValue(_ >= 0L, "Timeout must be >= 0.")
.createWithDefault(Long.MaxValue)
private[spark] val DYN_ALLOCATION_SCHEDULER_BACKLOG_TIMEOUT =
ConfigBuilder("spark.dynamicAllocation.schedulerBacklogTimeout")
.version("1.2.0")
.timeConf(TimeUnit.SECONDS).createWithDefault(1)
private[spark] val DYN_ALLOCATION_SUSTAINED_SCHEDULER_BACKLOG_TIMEOUT =
ConfigBuilder("spark.dynamicAllocation.sustainedSchedulerBacklogTimeout")
.version("1.2.0")
.fallbackConf(DYN_ALLOCATION_SCHEDULER_BACKLOG_TIMEOUT)
private[spark] val LEGACY_LOCALITY_WAIT_RESET =
ConfigBuilder("spark.locality.wait.legacyResetOnTaskLaunch")
.doc("Whether to use the legacy behavior of locality wait, which resets the delay timer " +
"anytime a task is scheduled. See Delay Scheduling section of TaskSchedulerImpl's class " +
"documentation for more details.")
.internal()
.version("3.1.0")
.booleanConf
.createWithDefault(false)
private[spark] val LOCALITY_WAIT = ConfigBuilder("spark.locality.wait")
.version("0.5.0")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefaultString("3s")
private[spark] val SHUFFLE_SERVICE_ENABLED =
ConfigBuilder("spark.shuffle.service.enabled")
.version("1.2.0")
.booleanConf
.createWithDefault(false)
private[spark] val SHUFFLE_SERVICE_FETCH_RDD_ENABLED =
ConfigBuilder(Constants.SHUFFLE_SERVICE_FETCH_RDD_ENABLED)
.doc("Whether to use the ExternalShuffleService for fetching disk persisted RDD blocks. " +
"In case of dynamic allocation if this feature is enabled executors having only disk " +
"persisted blocks are considered idle after " +
"'spark.dynamicAllocation.executorIdleTimeout' and will be released accordingly.")
.version("3.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val SHUFFLE_SERVICE_DB_ENABLED =
ConfigBuilder("spark.shuffle.service.db.enabled")
.doc("Whether to use db in ExternalShuffleService. Note that this only affects " +
"standalone mode.")
.version("3.0.0")
.booleanConf
.createWithDefault(true)
private[spark] val SHUFFLE_SERVICE_PORT =
ConfigBuilder("spark.shuffle.service.port").version("1.2.0").intConf.createWithDefault(7337)
private[spark] val KEYTAB = ConfigBuilder("spark.kerberos.keytab")
.doc("Location of user's keytab.")
.version("3.0.0")
.stringConf.createOptional
private[spark] val PRINCIPAL = ConfigBuilder("spark.kerberos.principal")
.doc("Name of the Kerberos principal.")
.version("3.0.0")
.stringConf
.createOptional
private[spark] val KERBEROS_RELOGIN_PERIOD = ConfigBuilder("spark.kerberos.relogin.period")
.version("3.0.0")
.timeConf(TimeUnit.SECONDS)
.createWithDefaultString("1m")
private[spark] val KERBEROS_RENEWAL_CREDENTIALS =
ConfigBuilder("spark.kerberos.renewal.credentials")
.doc(
"Which credentials to use when renewing delegation tokens for executors. Can be either " +
"'keytab', the default, which requires a keytab to be provided, or 'ccache', which uses " +
"the local credentials cache.")
.version("3.0.0")
.stringConf
.checkValues(Set("keytab", "ccache"))
.createWithDefault("keytab")
private[spark] val KERBEROS_FILESYSTEMS_TO_ACCESS =
ConfigBuilder("spark.kerberos.access.hadoopFileSystems")
.doc("Extra Hadoop filesystem URLs for which to request delegation tokens. The filesystem " +
"that hosts fs.defaultFS does not need to be listed here.")
.version("3.0.0")
.stringConf
.toSequence
.createWithDefault(Nil)
private[spark] val EXECUTOR_INSTANCES = ConfigBuilder("spark.executor.instances")
.version("1.0.0")
.intConf
.createOptional
private[spark] val PY_FILES = ConfigBuilder("spark.yarn.dist.pyFiles")
.internal()
.version("2.2.1")
.stringConf
.toSequence
.createWithDefault(Nil)
private[spark] val TASK_MAX_DIRECT_RESULT_SIZE =
ConfigBuilder("spark.task.maxDirectResultSize")
.version("2.0.0")
.bytesConf(ByteUnit.BYTE)
.createWithDefault(1L << 20)
private[spark] val TASK_MAX_FAILURES =
ConfigBuilder("spark.task.maxFailures")
.version("0.8.0")
.intConf
.createWithDefault(4)
private[spark] val TASK_REAPER_ENABLED =
ConfigBuilder("spark.task.reaper.enabled")
.version("2.0.3")
.booleanConf
.createWithDefault(false)
private[spark] val TASK_REAPER_KILL_TIMEOUT =
ConfigBuilder("spark.task.reaper.killTimeout")
.version("2.0.3")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefault(-1)
private[spark] val TASK_REAPER_POLLING_INTERVAL =
ConfigBuilder("spark.task.reaper.pollingInterval")
.version("2.0.3")
.timeConf(TimeUnit.MILLISECONDS)
.createWithDefaultString("10s")
private[spark] val TASK_REAPER_THREAD_DUMP =
ConfigBuilder("spark.task.reaper.threadDump")
.version("2.0.3")
.booleanConf
.createWithDefault(true)
// Blacklist confs
private[spark] val BLACKLIST_ENABLED =
ConfigBuilder("spark.blacklist.enabled")
.version("2.1.0")
.booleanConf
.createOptional
private[spark] val MAX_TASK_ATTEMPTS_PER_EXECUTOR =
ConfigBuilder("spark.blacklist.task.maxTaskAttemptsPerExecutor")
.version("2.1.0")
.intConf
.createWithDefault(1)
private[spark] val MAX_TASK_ATTEMPTS_PER_NODE =
ConfigBuilder("spark.blacklist.task.maxTaskAttemptsPerNode")
.version("2.1.0")
.intConf
.createWithDefault(2)
private[spark] val MAX_FAILURES_PER_EXEC =
ConfigBuilder("spark.blacklist.application.maxFailedTasksPerExecutor")
.version("2.2.0")
.intConf
.createWithDefault(2)
private[spark] val MAX_FAILURES_PER_EXEC_STAGE =
ConfigBuilder("spark.blacklist.stage.maxFailedTasksPerExecutor")
.version("2.1.0")
.intConf
.createWithDefault(2)
private[spark] val MAX_FAILED_EXEC_PER_NODE =
ConfigBuilder("spark.blacklist.application.maxFailedExecutorsPerNode")
.version("2.2.0")
.intConf
.createWithDefault(2)
private[spark] val MAX_FAILED_EXEC_PER_NODE_STAGE =
ConfigBuilder("spark.blacklist.stage.maxFailedExecutorsPerNode")
.version("2.1.0")
.intConf
.createWithDefault(2)
private[spark] val BLACKLIST_TIMEOUT_CONF =
ConfigBuilder("spark.blacklist.timeout")
.version("2.1.0")
.timeConf(TimeUnit.MILLISECONDS)
.createOptional
private[spark] val BLACKLIST_KILL_ENABLED =
ConfigBuilder("spark.blacklist.killBlacklistedExecutors")
.version("2.2.0")
.booleanConf
.createWithDefault(false)
private[spark] val BLACKLIST_LEGACY_TIMEOUT_CONF =
ConfigBuilder("spark.scheduler.executorTaskBlacklistTime")
.internal()
.version("1.0.0")
.timeConf(TimeUnit.MILLISECONDS)
.createOptional
private[spark] val BLACKLIST_FETCH_FAILURE_ENABLED =
ConfigBuilder("spark.blacklist.application.fetchFailure.enabled")
.version("2.3.0")
.booleanConf
.createWithDefault(false)
// End blacklist confs
private[spark] val UNREGISTER_OUTPUT_ON_HOST_ON_FETCH_FAILURE =
ConfigBuilder("spark.files.fetchFailure.unRegisterOutputOnHost")
.doc("Whether to un-register all the outputs on the host in condition that we receive " +
" a FetchFailure. This is set default to false, which means, we only un-register the " +
" outputs related to the exact executor(instead of the host) on a FetchFailure.")
.version("2.3.0")
.booleanConf
.createWithDefault(false)
private[spark] val LISTENER_BUS_EVENT_QUEUE_CAPACITY =
ConfigBuilder("spark.scheduler.listenerbus.eventqueue.capacity")
.doc("The default capacity for event queues. Spark will try to initialize " +
"an event queue using capacity specified by `spark.scheduler.listenerbus" +
".eventqueue.queueName.capacity` first. If it's not configured, Spark will " +
"use the default capacity specified by this config.")
.version("2.3.0")
.intConf
.checkValue(_ > 0, "The capacity of listener bus event queue must be positive")
.createWithDefault(10000)
private[spark] val LISTENER_BUS_METRICS_MAX_LISTENER_CLASSES_TIMED =
ConfigBuilder("spark.scheduler.listenerbus.metrics.maxListenerClassesTimed")
.internal()
.version("2.3.0")
.intConf
.createWithDefault(128)
private[spark] val LISTENER_BUS_LOG_SLOW_EVENT_ENABLED =
ConfigBuilder("spark.scheduler.listenerbus.logSlowEvent")
.internal()
.doc("When enabled, log the event that takes too much time to process. This helps us " +
"discover the event types that cause performance bottlenecks. The time threshold is " +
"controlled by spark.scheduler.listenerbus.logSlowEvent.threshold.")
.version("3.0.0")
.booleanConf
.createWithDefault(true)
private[spark] val LISTENER_BUS_LOG_SLOW_EVENT_TIME_THRESHOLD =
ConfigBuilder("spark.scheduler.listenerbus.logSlowEvent.threshold")
.internal()
.doc("The time threshold of whether a event is considered to be taking too much time to " +
s"process. Log the event if ${LISTENER_BUS_LOG_SLOW_EVENT_ENABLED.key} is true.")
.version("3.0.0")
.timeConf(TimeUnit.NANOSECONDS)
.createWithDefaultString("1s")
// This property sets the root namespace for metrics reporting
private[spark] val METRICS_NAMESPACE = ConfigBuilder("spark.metrics.namespace")
.version("2.1.0")
.stringConf
.createOptional
private[spark] val METRICS_CONF = ConfigBuilder("spark.metrics.conf")
.version("0.8.0")
.stringConf
.createOptional
private[spark] val METRICS_EXECUTORMETRICS_SOURCE_ENABLED =
ConfigBuilder("spark.metrics.executorMetricsSource.enabled")
.doc("Whether to register the ExecutorMetrics source with the metrics system.")
.version("3.0.0")
.booleanConf
.createWithDefault(true)
private[spark] val METRICS_STATIC_SOURCES_ENABLED =
ConfigBuilder("spark.metrics.staticSources.enabled")
.doc("Whether to register static sources with the metrics system.")
.version("3.0.0")
.booleanConf
.createWithDefault(true)
private[spark] val PYSPARK_DRIVER_PYTHON = ConfigBuilder("spark.pyspark.driver.python")
.version("2.1.0")
.stringConf
.createOptional
private[spark] val PYSPARK_PYTHON = ConfigBuilder("spark.pyspark.python")
.version("2.1.0")
.stringConf
.createOptional
// To limit how many applications are shown in the History Server summary ui
private[spark] val HISTORY_UI_MAX_APPS =
ConfigBuilder("spark.history.ui.maxApplications")
.version("2.0.1")
.intConf
.createWithDefault(Integer.MAX_VALUE)
private[spark] val IO_ENCRYPTION_ENABLED = ConfigBuilder("spark.io.encryption.enabled")
.version("2.1.0")
.booleanConf
.createWithDefault(false)
private[spark] val IO_ENCRYPTION_KEYGEN_ALGORITHM =
ConfigBuilder("spark.io.encryption.keygen.algorithm")
.version("2.1.0")
.stringConf
.createWithDefault("HmacSHA1")
private[spark] val IO_ENCRYPTION_KEY_SIZE_BITS = ConfigBuilder("spark.io.encryption.keySizeBits")
.version("2.1.0")
.intConf
.checkValues(Set(128, 192, 256))
.createWithDefault(128)
private[spark] val IO_CRYPTO_CIPHER_TRANSFORMATION =
ConfigBuilder("spark.io.crypto.cipher.transformation")
.internal()
.version("2.1.0")
.stringConf
.createWithDefaultString("AES/CTR/NoPadding")
private[spark] val DRIVER_HOST_ADDRESS = ConfigBuilder("spark.driver.host")
.doc("Address of driver endpoints.")
.version("0.7.0")
.stringConf
.createWithDefault(Utils.localCanonicalHostName())
private[spark] val DRIVER_PORT = ConfigBuilder("spark.driver.port")
.doc("Port of driver endpoints.")
.version("0.7.0")
.intConf
.createWithDefault(0)
private[spark] val DRIVER_SUPERVISE = ConfigBuilder("spark.driver.supervise")
.doc("If true, restarts the driver automatically if it fails with a non-zero exit status. " +
"Only has effect in Spark standalone mode or Mesos cluster deploy mode.")
.version("1.3.0")
.booleanConf
.createWithDefault(false)
private[spark] val DRIVER_BIND_ADDRESS = ConfigBuilder("spark.driver.bindAddress")
.doc("Address where to bind network listen sockets on the driver.")
.version("2.1.0")
.fallbackConf(DRIVER_HOST_ADDRESS)
private[spark] val BLOCK_MANAGER_PORT = ConfigBuilder("spark.blockManager.port")
.doc("Port to use for the block manager when a more specific setting is not provided.")
.version("1.1.0")
.intConf
.createWithDefault(0)
private[spark] val DRIVER_BLOCK_MANAGER_PORT = ConfigBuilder("spark.driver.blockManager.port")
.doc("Port to use for the block manager on the driver.")
.version("2.1.0")
.fallbackConf(BLOCK_MANAGER_PORT)
private[spark] val IGNORE_CORRUPT_FILES = ConfigBuilder("spark.files.ignoreCorruptFiles")
.doc("Whether to ignore corrupt files. If true, the Spark jobs will continue to run when " +
"encountering corrupted or non-existing files and contents that have been read will still " +
"be returned.")
.version("2.1.0")
.booleanConf
.createWithDefault(false)
private[spark] val IGNORE_MISSING_FILES = ConfigBuilder("spark.files.ignoreMissingFiles")
.doc("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.")
.version("2.4.0")
.booleanConf
.createWithDefault(false)
private[spark] val APP_CALLER_CONTEXT = ConfigBuilder("spark.log.callerContext")
.version("2.2.0")
.stringConf
.createOptional
private[spark] val FILES_MAX_PARTITION_BYTES = ConfigBuilder("spark.files.maxPartitionBytes")
.doc("The maximum number of bytes to pack into a single partition when reading files.")
.version("2.1.0")
.bytesConf(ByteUnit.BYTE)
.createWithDefault(128 * 1024 * 1024)
private[spark] val FILES_OPEN_COST_IN_BYTES = ConfigBuilder("spark.files.openCostInBytes")
.doc("The estimated cost to open a file, measured by the number of bytes could be scanned in" +
" the same time. This is used when putting multiple files into a partition. It's better to" +
" over estimate, then the partitions with small files will be faster than partitions with" +
" bigger files.")
.version("2.1.0")
.bytesConf(ByteUnit.BYTE)
.createWithDefault(4 * 1024 * 1024)
private[spark] val HADOOP_RDD_IGNORE_EMPTY_SPLITS =
ConfigBuilder("spark.hadoopRDD.ignoreEmptySplits")
.internal()
.doc("When true, HadoopRDD/NewHadoopRDD will not create partitions for empty input splits.")
.version("2.3.0")
.booleanConf
.createWithDefault(false)
private[spark] val SECRET_REDACTION_PATTERN =
ConfigBuilder("spark.redaction.regex")
.doc("Regex to decide which Spark configuration properties and environment variables in " +
"driver and executor environments contain sensitive information. When this regex matches " +
"a property key or value, the value is redacted from the environment UI and various logs " +
"like YARN and event logs.")
.version("2.1.2")
.regexConf
.createWithDefault("(?i)secret|password|token".r)
private[spark] val STRING_REDACTION_PATTERN =
ConfigBuilder("spark.redaction.string.regex")
.doc("Regex to decide which parts of strings produced by Spark contain sensitive " +
"information. When this regex matches a string part, that string part is replaced by a " +
"dummy value. This is currently used to redact the output of SQL explain commands.")
.version("2.2.0")
.regexConf
.createOptional
private[spark] val AUTH_SECRET =
ConfigBuilder("spark.authenticate.secret")
.version("1.0.0")
.stringConf
.createOptional
private[spark] val AUTH_SECRET_BIT_LENGTH =
ConfigBuilder("spark.authenticate.secretBitLength")
.version("1.6.0")
.intConf
.createWithDefault(256)
private[spark] val NETWORK_AUTH_ENABLED =
ConfigBuilder("spark.authenticate")
.version("1.0.0")
.booleanConf
.createWithDefault(false)
private[spark] val SASL_ENCRYPTION_ENABLED =
ConfigBuilder("spark.authenticate.enableSaslEncryption")
.version("1.4.0")
.booleanConf